WorldWideScience

Sample records for cancer risk prediction

  1. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  2. Korean risk assessment model for breast cancer risk prediction.

    Science.gov (United States)

    Park, Boyoung; Ma, Seung Hyun; Shin, Aesun; Chang, Myung-Chul; Choi, Ji-Yeob; Kim, Sungwan; Han, Wonshik; Noh, Dong-Young; Ahn, Sei-Hyun; Kang, Daehee; Yoo, Keun-Young; Park, Sue K

    2013-01-01

    We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk. Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail's equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort. The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (pKorean women, especially urban women.

  3. Applying a new mammographic imaging marker to predict breast cancer risk

    Science.gov (United States)

    Aghaei, Faranak; Danala, Gopichandh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

    2018-02-01

    Identifying and developing new mammographic imaging markers to assist prediction of breast cancer risk has been attracting extensive research interest recently. Although mammographic density is considered an important breast cancer risk, its discriminatory power is lower for predicting short-term breast cancer risk, which is a prerequisite to establish a more effective personalized breast cancer screening paradigm. In this study, we presented a new interactive computer-aided detection (CAD) scheme to generate a new quantitative mammographic imaging marker based on the bilateral mammographic tissue density asymmetry to predict risk of cancer detection in the next subsequent mammography screening. An image database involving 1,397 women was retrospectively assembled and tested. Each woman had two digital mammography screenings namely, the "current" and "prior" screenings with a time interval from 365 to 600 days. All "prior" images were originally interpreted negative. In "current" screenings, these cases were divided into 3 groups, which include 402 positive, 643 negative, and 352 biopsy-proved benign cases, respectively. There is no significant difference of BIRADS based mammographic density ratings between 3 case groups (p cancer detection in the "current" screening. Study demonstrated that this new imaging marker had potential to yield significantly higher discriminatory power to predict short-term breast cancer risk.

  4. Relationship of Predicted Risk of Developing Invasive Breast Cancer, as Assessed with Three Models, and Breast Cancer Mortality among Breast Cancer Patients.

    Directory of Open Access Journals (Sweden)

    Mark E Sherman

    Full Text Available Breast cancer risk prediction models are used to plan clinical trials and counsel women; however, relationships of predicted risks of breast cancer incidence and prognosis after breast cancer diagnosis are unknown.Using largely pre-diagnostic information from the Breast Cancer Surveillance Consortium (BCSC for 37,939 invasive breast cancers (1996-2007, we estimated 5-year breast cancer risk (<1%; 1-1.66%; ≥1.67% with three models: BCSC 1-year risk model (BCSC-1; adapted to 5-year predictions; Breast Cancer Risk Assessment Tool (BCRAT; and BCSC 5-year risk model (BCSC-5. Breast cancer-specific mortality post-diagnosis (range: 1-13 years; median: 5.4-5.6 years was related to predicted risk of developing breast cancer using unadjusted Cox proportional hazards models, and in age-stratified (35-44; 45-54; 55-69; 70-89 years models adjusted for continuous age, BCSC registry, calendar period, income, mode of presentation, stage and treatment. Mean age at diagnosis was 60 years.Of 6,021 deaths, 2,993 (49.7% were ascribed to breast cancer. In unadjusted case-only analyses, predicted breast cancer risk ≥1.67% versus <1.0% was associated with lower risk of breast cancer death; BCSC-1: hazard ratio (HR = 0.82 (95% CI = 0.75-0.90; BCRAT: HR = 0.72 (95% CI = 0.65-0.81 and BCSC-5: HR = 0.84 (95% CI = 0.75-0.94. Age-stratified, adjusted models showed similar, although mostly non-significant HRs. Among women ages 55-69 years, HRs approximated 1.0. Generally, higher predicted risk was inversely related to percentages of cancers with unfavorable prognostic characteristics, especially among women 35-44 years.Among cases assessed with three models, higher predicted risk of developing breast cancer was not associated with greater risk of breast cancer death; thus, these models would have limited utility in planning studies to evaluate breast cancer mortality reduction strategies. Further, when offering women counseling, it may be useful to note that high

  5. A utility/cost analysis of breast cancer risk prediction algorithms

    Science.gov (United States)

    Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

    2016-03-01

    Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening.

  6. Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening.

    Science.gov (United States)

    Autier, Philippe; Boniol, Mathieu; Smans, Michel; Sullivan, Richard; Boyle, Peter

    2016-01-01

    The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. The observed and predicted RR of breast cancer death were 0.72 (0.56-0.94) and 0.98 (0.77-1.24) in the HIP trial, and 0.79 (0.78-1.01) and 0.90 (0.80-1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62-0.87), while the predicted RR was 0.89 (0.75-1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70-0.97) if extra cancers were excluded. In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.

  7. Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer.

    Science.gov (United States)

    Yu, Ami; Woo, Sang Myung; Joo, Jungnam; Yang, Hye-Ryung; Lee, Woo Jin; Park, Sang-Jae; Nam, Byung-Ho

    2016-01-01

    There is no reliable screening tool to identify people with high risk of developing pancreatic cancer even though pancreatic cancer represents the fifth-leading cause of cancer-related death in Korea. The goal of this study was to develop an individualized risk prediction model that can be used to screen for asymptomatic pancreatic cancer in Korean men and women. Gender-specific risk prediction models for pancreatic cancer were developed using the Cox proportional hazards model based on an 8-year follow-up of a cohort study of 1,289,933 men and 557,701 women in Korea who had biennial examinations in 1996-1997. The performance of the models was evaluated with respect to their discrimination and calibration ability based on the C-statistic and Hosmer-Lemeshow type χ2 statistic. A total of 1,634 (0.13%) men and 561 (0.10%) women were newly diagnosed with pancreatic cancer. Age, height, BMI, fasting glucose, urine glucose, smoking, and age at smoking initiation were included in the risk prediction model for men. Height, BMI, fasting glucose, urine glucose, smoking, and drinking habit were included in the risk prediction model for women. Smoking was the most significant risk factor for developing pancreatic cancer in both men and women. The risk prediction model exhibited good discrimination and calibration ability, and in external validation it had excellent prediction ability. Gender-specific risk prediction models for pancreatic cancer were developed and validated for the first time. The prediction models will be a useful tool for detecting high-risk individuals who may benefit from increased surveillance for pancreatic cancer.

  8. Updating risk prediction tools: a case study in prostate cancer.

    Science.gov (United States)

    Ankerst, Donna P; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J; Feng, Ziding; Sanda, Martin G; Partin, Alan W; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M

    2012-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically, the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [-2]proPSA measured on an external case-control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer.

    Science.gov (United States)

    Loeb, Stacy; Shin, Sanghyuk S; Broyles, Dennis L; Wei, John T; Sanda, Martin; Klee, George; Partin, Alan W; Sokoll, Lori; Chan, Daniel W; Bangma, Chris H; van Schaik, Ron H N; Slawin, Kevin M; Marks, Leonard S; Catalona, William J

    2017-07-01

    To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram. Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis. Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

  10. Predicted cancer risks induced by computed tomography examinations during childhood, by a quantitative risk assessment approach.

    Science.gov (United States)

    Journy, Neige; Ancelet, Sophie; Rehel, Jean-Luc; Mezzarobba, Myriam; Aubert, Bernard; Laurier, Dominique; Bernier, Marie-Odile

    2014-03-01

    The potential adverse effects associated with exposure to ionizing radiation from computed tomography (CT) in pediatrics must be characterized in relation to their expected clinical benefits. Additional epidemiological data are, however, still awaited for providing a lifelong overview of potential cancer risks. This paper gives predictions of potential lifetime risks of cancer incidence that would be induced by CT examinations during childhood in French routine practices in pediatrics. Organ doses were estimated from standard radiological protocols in 15 hospitals. Excess risks of leukemia, brain/central nervous system, breast and thyroid cancers were predicted from dose-response models estimated in the Japanese atomic bomb survivors' dataset and studies of medical exposures. Uncertainty in predictions was quantified using Monte Carlo simulations. This approach predicts that 100,000 skull/brain scans in 5-year-old children would result in eight (90 % uncertainty interval (UI) 1-55) brain/CNS cancers and four (90 % UI 1-14) cases of leukemia and that 100,000 chest scans would lead to 31 (90 % UI 9-101) thyroid cancers, 55 (90 % UI 20-158) breast cancers, and one (90 % UI risks without exposure). Compared to background risks, radiation-induced risks would be low for individuals throughout life, but relative risks would be highest in the first decades of life. Heterogeneity in the radiological protocols across the hospitals implies that 5-10 % of CT examinations would be related to risks 1.4-3.6 times higher than those for the median doses. Overall excess relative risks in exposed populations would be 1-10 % depending on the site of cancer and the duration of follow-up. The results emphasize the potential risks of cancer specifically from standard CT examinations in pediatrics and underline the necessity of optimization of radiological protocols.

  11. Quantitative prediction of oral cancer risk in patients with oral leukoplakia.

    Science.gov (United States)

    Liu, Yao; Li, Yicheng; Fu, Yue; Liu, Tong; Liu, Xiaoyong; Zhang, Xinyan; Fu, Jie; Guan, Xiaobing; Chen, Tong; Chen, Xiaoxin; Sun, Zheng

    2017-07-11

    Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.

  12. Development of a Breast Cancer Risk Prediction Model for Women in Nigeria.

    Science.gov (United States)

    Wang, Shengfeng; Ogundiran, Temidayo O; Ademola, Adeyinka; Oluwasola, Olayiwola A; Adeoye, Adewunmi O; Sofoluwe, Adenike; Morhason-Bello, Imran; Odedina, Stella O; Agwai, Imaria; Adebamowo, Clement; Obajimi, Millicent; Ojengbede, Oladosu; Olopade, Olufunmilayo I; Huo, Dezheng

    2018-04-20

    Risk prediction models have been widely used to identify women at higher risk of breast cancer. We aim to develop a model for absolute breast cancer risk prediction for Nigerian women. A total of 1,811 breast cancer cases and 2,225 controls from the Nigerian Breast Cancer Study (NBCS, 1998~2015) were included. Subjects were randomly divided into the training and validation sets. Incorporating local incidence rates, multivariable logistic regressions were used to develop the model. The NBCS model included age, age at menarche, parity, duration of breast feeding, family history of breast cancer, height, body mass index, benign breast diseases and alcohol consumption. The model developed in the training set performed well in the validation set. The discriminating accuracy of the NBCS model (area under ROC curve [AUC]=0.703, 95% confidence interval [CI]: 0.687-0.719) was better than the Black Women's Health Study (BWHS) model (AUC=0.605, 95% CI: 0.586-0.624), Gail model for White population (AUC=0.551, 95% CI: 0.531-0.571), and Gail model for Black population (AUC=0.545, 95% CI: 0.525-0.565). Compared to the BWHS, two Gail models, the net reclassification improvement of the NBCS model were 8.26%, 13.45% and 14.19%, respectively. We have developed a breast cancer risk prediction model specific to women in Nigeria, which provides a promising and indispensable tool to identify women in need of breast cancer early detection in SSA populations. Our model is the first breast cancer risk prediction model in Africa. It can be used to identify women at high-risk for breast cancer screening. Copyright ©2018, American Association for Cancer Research.

  13. Comparative Risk Predictions of Second Cancers After Carbon-Ion Therapy Versus Proton Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Eley, John G., E-mail: jeley@som.umaryland.edu [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); University of Texas Graduate School of Biomedical Sciences, Houston, Texas (United States); Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland (United States); Friedrich, Thomas [GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt (Germany); Homann, Kenneth L.; Howell, Rebecca M. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); University of Texas Graduate School of Biomedical Sciences, Houston, Texas (United States); Scholz, Michael; Durante, Marco [GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt (Germany); Newhauser, Wayne D. [Department of Physics and Astronomy, Louisiana State University and Agricultural and Mechanical College, Baton Rouge, Louisiana (United States); Mary Bird Perkins Cancer Center, Baton Rouge, Louisiana (United States)

    2016-05-01

    Purpose: This work proposes a theoretical framework that enables comparative risk predictions for second cancer incidence after particle beam therapy for different ion species for individual patients, accounting for differences in relative biological effectiveness (RBE) for the competing processes of tumor initiation and cell inactivation. Our working hypothesis was that use of carbon-ion therapy instead of proton therapy would show a difference in the predicted risk of second cancer incidence in the breast for a sample of Hodgkin lymphoma (HL) patients. Methods and Materials: We generated biologic treatment plans and calculated relative predicted risks of second cancer in the breast by using two proposed methods: a full model derived from the linear quadratic model and a simpler linear-no-threshold model. Results: For our reference calculation, we found the predicted risk of breast cancer incidence for carbon-ion plans-to-proton plan ratio, , to be 0.75 ± 0.07 but not significantly smaller than 1 (P=.180). Conclusions: Our findings suggest that second cancer risks are, on average, comparable between proton therapy and carbon-ion therapy.

  14. Extensions of the Rosner-Colditz breast cancer prediction model to include older women and type-specific predicted risk.

    Science.gov (United States)

    Glynn, Robert J; Colditz, Graham A; Tamimi, Rulla M; Chen, Wendy Y; Hankinson, Susan E; Willett, Walter W; Rosner, Bernard

    2017-08-01

    A breast cancer risk prediction rule previously developed by Rosner and Colditz has reasonable predictive ability. We developed a re-fitted version of this model, based on more than twice as many cases now including women up to age 85, and further extended it to a model that distinguished risk factor prediction of tumors with different estrogen/progesterone receptor status. We compared the calibration and discriminatory ability of the original, the re-fitted, and the type-specific models. Evaluation used data from the Nurses' Health Study during the period 1980-2008, when 4384 incident invasive breast cancers occurred over 1.5 million person-years. Model development used two-thirds of study subjects and validation used one-third. Predicted risks in the validation sample from the original and re-fitted models were highly correlated (ρ = 0.93), but several parameters, notably those related to use of menopausal hormone therapy and age, had different estimates. The re-fitted model was well-calibrated and had an overall C-statistic of 0.65. The extended, type-specific model identified several risk factors with varying associations with occurrence of tumors of different receptor status. However, this extended model relative to the prediction of any breast cancer did not meaningfully reclassify women who developed breast cancer to higher risk categories, nor women remaining cancer free to lower risk categories. The re-fitted Rosner-Colditz model has applicability to risk prediction in women up to age 85, and its discrimination is not improved by consideration of varying associations across tumor subtypes.

  15. Risk prediction model for colorectal cancer: National Health Insurance Corporation study, Korea.

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    Shin, Aesun; Joo, Jungnam; Yang, Hye-Ryung; Bak, Jeongin; Park, Yunjin; Kim, Jeongseon; Oh, Jae Hwan; Nam, Byung-Ho

    2014-01-01

    Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30-80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics. Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women. Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer.

  16. Lung cancer in never smokers Epidemiology and risk prediction models

    Science.gov (United States)

    McCarthy, William J.; Meza, Rafael; Jeon, Jihyoun; Moolgavkar, Suresh

    2012-01-01

    In this chapter we review the epidemiology of lung cancer incidence and mortality among never smokers/ nonsmokers and describe the never smoker lung cancer risk models used by CISNET modelers. Our review focuses on those influences likely to have measurable population impact on never smoker risk, such as secondhand smoke, even though the individual-level impact may be small. Occupational exposures may also contribute importantly to the population attributable risk of lung cancer. We examine the following risk factors in this chapter: age, environmental tobacco smoke, cooking fumes, ionizing radiation including radon gas, inherited genetic susceptibility, selected occupational exposures, preexisting lung disease, and oncogenic viruses. We also compare the prevalence of never smokers between the three CISNET smoking scenarios and present the corresponding lung cancer mortality estimates among never smokers as predicted by a typical CISNET model. PMID:22882894

  17. Risk prediction model for colorectal cancer: National Health Insurance Corporation study, Korea.

    Directory of Open Access Journals (Sweden)

    Aesun Shin

    Full Text Available PURPOSE: Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. METHODS: Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30-80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics. RESULTS: Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women. CONCLUSIONS: Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer.

  18. Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study.

    Directory of Open Access Journals (Sweden)

    Kevin Ten Haaf

    2017-04-01

    Full Text Available Selection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years. Nine previously established risk models were assessed for their ability to identify those most likely to develop or die from lung cancer. All models considered age and various aspects of smoking exposure (smoking status, smoking duration, cigarettes per day, pack-years smoked, time since smoking cessation as risk predictors. In addition, some models considered factors such as gender, race, ethnicity, education, body mass index, chronic obstructive pulmonary disease, emphysema, personal history of cancer, personal history of pneumonia, and family history of lung cancer.Retrospective analyses were performed on 53,452 National Lung Screening Trial (NLST participants (1,925 lung cancer cases and 884 lung cancer deaths and 80,672 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO ever-smoking participants (1,463 lung cancer cases and 915 lung cancer deaths. Six-year lung cancer incidence and mortality risk predictions were assessed for (1 calibration (graphically by comparing the agreement between the predicted and the observed risks, (2 discrimination (area under the receiver operating characteristic curve [AUC] between individuals with and without lung cancer (death, and (3 clinical usefulness (net benefit in decision curve analysis by identifying risk thresholds at which applying risk-based eligibility would improve lung cancer screening efficacy. To further assess performance, risk model sensitivities and specificities in the PLCO were compared to those based on the NLST eligibility criteria. Calibration was satisfactory, but discrimination ranged widely (AUCs from 0.61 to 0.81. The models outperformed the NLST eligibility criteria over a substantial range of risk thresholds in decision curve analysis, with a higher sensitivity for all models and a

  19. Clinical utility of polymorphisms in one-carbon metabolism for breast cancer risk prediction

    Directory of Open Access Journals (Sweden)

    Shaik Mohammad Naushad

    2011-01-01

    Full Text Available This study addresses the issues in translating the laboratory derived data obtained during discovery phase of research to a clinical setting using a breast cancer model. Laboratory-based risk assessment indi-cated that a family history of breast cancer, reduced folate carrier 1 (RFC1 G80A, thymidylate synthase (TYMS 5’-UTR 28bp tandem repeat, methylene tetrahydrofolate reductase (MTHFR C677T and catecholamine-O-methyl transferase (COMT genetic polymorphisms in one-carbon metabolic pathway increase the risk for breast cancer. Glutamate carboxypeptidase II (GCPII C1561T and cytosolic serine hydroxymethyl transferase (cSHMT C1420T polymorphisms were found to decrease breast cancer risk. In order to test the clinical validity of this information in the risk prediction of breast cancer, data was stratified based on number of protective alleles into four categories and in each category sensitivity and 1-specificity values were obtained based on the distribution of number of risk alleles in cases and controls. Receiver operating characteristic (ROC curves were plotted and the area under ROC curve (C was used as a measure of discriminatory ability between cases and controls. In subjects without any protective allele, aberrations in one-carbon metabolism showed perfect prediction (C=0.93 while the predictability was lost in subjects with one protective allele (C=0.60. However, predictability increased steadily with increasing number of protective alleles (C=0.63 for 2 protective alleles and C=0.71 for 3 protective alleles. The cut-off point for discrimination was >4 alleles in all predictable combinations. Models of this kind can serve as valuable tools in translational re-search, especially in identifying high-risk individuals and reducing the disease risk either by life style modification or by medical intervention.

  20. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  1. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  7. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

    DEFF Research Database (Denmark)

    Winkler Wille, Mathilde M.; van Riel, Sarah J.; Saghir, Zaigham

    2015-01-01

    Objectives: Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. Methods: From...... the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were...... used to evaluate risk discrimination. Results: AUCs of 0.826–0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer...

  12. Predictive accuracy of the PanCan lung cancer risk prediction model - external validation based on CT from the Danish Lung Cancer Screening Trial

    International Nuclear Information System (INIS)

    Winkler Wille, Mathilde M.; Dirksen, Asger; Riel, Sarah J. van; Jacobs, Colin; Scholten, Ernst T.; Ginneken, Bram van; Saghir, Zaigham; Pedersen, Jesper Holst; Hohwue Thomsen, Laura; Skovgaard, Lene T.

    2015-01-01

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were used to evaluate risk discrimination. AUCs of 0.826-0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer; in fact opposing effects of sex were observed in the two cohorts. Thus, female sex appeared to lower the risk (p = 0.047 and p = 0.040) in the DLCST. High risk discrimination was validated in the DLCST cohort, mainly determined by nodule size. Age and family history of lung cancer were significant predictors and could be included in the parsimonious model. Sex appears to be a less useful predictor. (orig.)

  13. Predictive accuracy of the PanCan lung cancer risk prediction model - external validation based on CT from the Danish Lung Cancer Screening Trial

    Energy Technology Data Exchange (ETDEWEB)

    Winkler Wille, Mathilde M.; Dirksen, Asger [Gentofte Hospital, Department of Respiratory Medicine, Hellerup (Denmark); Riel, Sarah J. van; Jacobs, Colin; Scholten, Ernst T.; Ginneken, Bram van [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Saghir, Zaigham [Herlev Hospital, Department of Respiratory Medicine, Herlev (Denmark); Pedersen, Jesper Holst [Copenhagen University Hospital, Department of Thoracic Surgery, Rigshospitalet, Koebenhavn Oe (Denmark); Hohwue Thomsen, Laura [Hvidovre Hospital, Department of Respiratory Medicine, Hvidovre (Denmark); Skovgaard, Lene T. [University of Copenhagen, Department of Biostatistics, Koebenhavn Oe (Denmark)

    2015-10-15

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were used to evaluate risk discrimination. AUCs of 0.826-0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer; in fact opposing effects of sex were observed in the two cohorts. Thus, female sex appeared to lower the risk (p = 0.047 and p = 0.040) in the DLCST. High risk discrimination was validated in the DLCST cohort, mainly determined by nodule size. Age and family history of lung cancer were significant predictors and could be included in the parsimonious model. Sex appears to be a less useful predictor. (orig.)

  14. Evaluation of Polygenic Risk Scores for Breast and Ovarian Cancer Risk Prediction in BRCA1 and BRCA2 Mutation Carriers

    DEFF Research Database (Denmark)

    Kuchenbaecker, Karoline B; McGuffog, Lesley; Barrowdale, Daniel

    2017-01-01

    Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic ...... risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management....

  15. Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry.

    Science.gov (United States)

    Wen, Wanqing; Shu, Xiao-Ou; Guo, Xingyi; Cai, Qiuyin; Long, Jirong; Bolla, Manjeet K; Michailidou, Kyriaki; Dennis, Joe; Wang, Qin; Gao, Yu-Tang; Zheng, Ying; Dunning, Alison M; García-Closas, Montserrat; Brennan, Paul; Chen, Shou-Tung; Choi, Ji-Yeob; Hartman, Mikael; Ito, Hidemi; Lophatananon, Artitaya; Matsuo, Keitaro; Miao, Hui; Muir, Kenneth; Sangrajrang, Suleeporn; Shen, Chen-Yang; Teo, Soo H; Tseng, Chiu-Chen; Wu, Anna H; Yip, Cheng Har; Simard, Jacques; Pharoah, Paul D P; Hall, Per; Kang, Daehee; Xiang, Yongbing; Easton, Douglas F; Zheng, Wei

    2016-12-08

    Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry. We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk. We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively. Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.

  16. Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies.

    Science.gov (United States)

    Van Neste, Leander; Partin, Alan W; Stewart, Grant D; Epstein, Jonathan I; Harrison, David J; Van Criekinge, Wim

    2016-09-01

    Prostate cancer (PCa) diagnosis is challenging because efforts for effective, timely treatment of men with significant cancer typically result in over-diagnosis and repeat biopsies. The presence or absence of epigenetic aberrations, more specifically DNA-methylation of GSTP1, RASSF1, and APC in histopathologically negative prostate core biopsies has resulted in an increased negative predictive value (NPV) of ∼90% and thus could lead to a reduction of unnecessary repeat biopsies. Here, it is investigated whether, in methylation-positive men, DNA-methylation intensities could help to identify those men harboring high-grade (Gleason score ≥7) PCa, resulting in an improved positive predictive value. Two cohorts, consisting of men with histopathologically negative index biopsies, followed by a positive or negative repeat biopsy, were combined. EpiScore, a methylation intensity algorithm was developed in methylation-positive men, using area under the curve of the receiver operating characteristic as metric for performance. Next, a risk score was developed combining EpiScore with traditional clinical risk factors to further improve the identification of high-grade (Gleason Score ≥7) cancer. Compared to other risk factors, detection of DNA-methylation in histopathologically negative biopsies was the most significant and important predictor of high-grade cancer, resulting in a NPV of 96%. In methylation-positive men, EpiScore was significantly higher for those with high-grade cancer detected upon repeat biopsy, compared to those with either no or low-grade cancer. The risk score resulted in further improvement of patient risk stratification and was a significantly better predictor compared to currently used metrics as PSA and the prostate cancer prevention trial (PCPT) risk calculator (RC). A decision curve analysis indicated strong clinical utility for the risk score as decision-making tool for repeat biopsy. Low DNA-methylation levels in PCa-negative biopsies led

  17. External validation of models predicting the individual risk of metachronous peritoneal carcinomatosis from colon and rectal cancer.

    Science.gov (United States)

    Segelman, J; Akre, O; Gustafsson, U O; Bottai, M; Martling, A

    2016-04-01

    To externally validate previously published predictive models of the risk of developing metachronous peritoneal carcinomatosis (PC) after resection of nonmetastatic colon or rectal cancer and to update the predictive model for colon cancer by adding new prognostic predictors. Data from all patients with Stage I-III colorectal cancer identified from a population-based database in Stockholm between 2008 and 2010 were used. We assessed the concordance between the predicted and observed probabilities of PC and utilized proportional-hazard regression to update the predictive model for colon cancer. When applied to the new validation dataset (n = 2011), the colon and rectal cancer risk-score models predicted metachronous PC with a concordance index of 79% and 67%, respectively. After adding the subclasses of pT3 and pT4 stage and mucinous tumour to the colon cancer model, the concordance index increased to 82%. In validation of external and recent cohorts, the predictive accuracy was strong in colon cancer and moderate in rectal cancer patients. The model can be used to identify high-risk patients for planned second-look laparoscopy/laparotomy for possible subsequent cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

  18. A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

    Science.gov (United States)

    Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

    2012-04-01

    A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the

  19. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

    NARCIS (Netherlands)

    Petersen, Japke F.; Stuiver, Martijn M.; Timmermans, Adriana J.; Chen, Amy; Zhang, Hongzhen; O'Neill, James P.; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T.; Koch, Wayne; van den Brekel, Michiel W. M.

    2017-01-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442

  20. Prediction of prostate cancer in unscreened men: external validation of a risk calculator.

    Science.gov (United States)

    van Vugt, Heidi A; Roobol, Monique J; Kranse, Ries; Määttänen, Liisa; Finne, Patrik; Hugosson, Jonas; Bangma, Chris H; Schröder, Fritz H; Steyerberg, Ewout W

    2011-04-01

    Prediction models need external validation to assess their value beyond the setting where the model was derived from. To assess the external validity of the European Randomized study of Screening for Prostate Cancer (ERSPC) risk calculator (www.prostatecancer-riskcalculator.com) for the probability of having a positive prostate biopsy (P(posb)). The ERSPC risk calculator was based on data of the initial screening round of the ERSPC section Rotterdam and validated in 1825 and 531 men biopsied at the initial screening round in the Finnish and Swedish sections of the ERSPC respectively. P(posb) was calculated using serum prostate specific antigen (PSA), outcome of digital rectal examination (DRE), transrectal ultrasound and ultrasound assessed prostate volume. The external validity was assessed for the presence of cancer at biopsy by calibration (agreement between observed and predicted outcomes), discrimination (separation of those with and without cancer), and decision curves (for clinical usefulness). Prostate cancer was detected in 469 men (26%) of the Finnish cohort and in 124 men (23%) of the Swedish cohort. Systematic miscalibration was present in both cohorts (mean predicted probability 34% versus 26% observed, and 29% versus 23% observed, both pscreened men, but overestimated the risk of a positive biopsy. Further research is necessary to assess the performance and applicability of the ERSPC risk calculator when a clinical setting is considered rather than a screening setting. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Colorectal Cancer Risk Assessment Tool

    Science.gov (United States)

    ... 11/12/2014 Risk Calculator About the Tool Colorectal Cancer Risk Factors Download SAS and Gauss Code Page ... Rectal Cancer: Prevention, Genetics, Causes Tests to Detect Colorectal Cancer and Polyps Cancer Risk Prediction Resources Update November ...

  2. Risk stratification and prediction of cancer of focal thyroid fluorodeoxyglucose uptake during cancer evaluation

    International Nuclear Information System (INIS)

    Kim, Bo-Hyun; Na, Min-A.; Kim, In-Joo; Kim, Seong-Jang; Kim, Yong-Ki

    2010-01-01

    Focal thyroid incidentaloma by F-18 2-deoxy-2-F18-fluoro-D-glucose (FDG) positron emission tomography (PET) has been reported 1-4% of cancer patients and normal healthy population, with a risk of cancer ranging 14-50%. The aim of this study was to investigate the prevalence of thyroid incidentaloma in F-18 FDG PET/CT and risk of cancer, usefulness of visual and SUV max and SUV mean differentiating malignant nodules and to define the predictable variables. A total 159 patients with focal thyroid FDG incidentaloma during cancer evaluation with non-thyroid cancer were enrolled. After F-18 PET/CT, we analyzed the image visually and obtained semiquantitative indices. The incidence of focal FDG thyroid incidentaloma is 1.36% and cancer risk is 23.3%. The incidence of focal thyroid FDG uptake was significantly higher in women (2.88 vs. 0.31%; X 2 =136.4, p max (malignant: median 4.53, range 2.1-12.0; benign: median 3.08, range 1.6-35, p=0.0093). However, SUV mean have no statistical differences (malignant: median 2.17, range 1.77-3.19; benign: median 2.05, range 1.15-5.77, p=0.0541). In ROC analyses, the optimal visual grades were >grade 3, and the optimal semiquantitative indices were 4.46 for SUV max , 2.03 for SUV mean . The visual grade was superior to other variables for the differentiation malignant from benign thyroid incidentalomas. The size and visual grade was the potent predictor by logistic regression analysis. Focal thyroid FDG incidentalomas in non-thyroid cancer patients during evaluation have a high risk of malignancy. The size and visual grade are potential predictors for malignant thyroid incidentaloma. (author)

  3. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

    Science.gov (United States)

    Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

    2018-05-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

  4. Update on breast cancer risk prediction and prevention.

    Science.gov (United States)

    Sestak, Ivana; Cuzick, Jack

    2015-02-01

    Breast cancer is the most common cancer in women worldwide. This review will focus on current prevention strategies for women at high risk. The identification of women who are at high risk of developing breast cancer is key to breast cancer prevention. Recent findings have shown that the inclusion of breast density and a panel of low-penetrance genetic polymorphisms can improve risk estimation compared with previous models. Preventive therapy with aromatase inhibitors has produced large reductions in breast cancer incidence in postmenopausal women. Tamoxifen confers long-term protection and is the only proven preventive treatment for premenopausal women. Several other agents, including metformin, bisphosphonates, aspirin and statins, have been found to be effective in nonrandomized settings. There are many options for the prevention of oestrogen-positive breast cancer, in postmenopausal women who can be given a selective oestrogen receptor modulator or an aromatase inhibitor. It still remains unclear how to prevent oestrogen-negative breast cancer, which occurs more often in premenopausal women. Identification of women at high risk of the disease is crucial, and the inclusion of breast density and a panel of genetic polymorphisms, which individually have low penetrance, can improve risk assessment.

  5. Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Hollingsworth, Alan B.; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qiu, Yuchen; Liu, Hong; Zheng, Bin

    2018-02-01

    In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally preserving projection (LPP) based feature combination and regeneration algorithm to predict short-term breast cancer risk. A dataset involving negative mammograms acquired from 500 women was assembled. This dataset was divided into two age-matched classes of 250 high risk cases in which cancer was detected in the next subsequent mammography screening and 250 low risk cases, which remained negative. First, a computer-aided image processing scheme was applied to segment fibro-glandular tissue depicted on mammograms and initially compute 44 features related to the bilateral asymmetry of mammographic tissue density distribution between left and right breasts. Next, a multi-feature fusion based machine learning classifier was built to predict the risk of cancer detection in the next mammography screening. A leave-one-case-out (LOCO) cross-validation method was applied to train and test the machine learning classifier embedded with a LLP algorithm, which generated a new operational vector with 4 features using a maximal variance approach in each LOCO process. Results showed a 9.7% increase in risk prediction accuracy when using this LPP-embedded machine learning approach. An increased trend of adjusted odds ratios was also detected in which odds ratios increased from 1.0 to 11.2. This study demonstrated that applying the LPP algorithm effectively reduced feature dimensionality, and yielded higher and potentially more robust performance in predicting short-term breast cancer risk.

  6. An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study

    OpenAIRE

    Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

    2017-01-01

    Background No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Methods Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; th...

  7. Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent.

    Directory of Open Access Journals (Sweden)

    Yan Guo

    2016-08-01

    Full Text Available Observational epidemiological studies have shown that high body mass index (BMI is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors.We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC (cases  =  46,325, controls  =  42,482. We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10. The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31-0.62, p  =  9.91 × 10-8 and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46-0.71, p  =  1.88 × 10-8. This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60-0.84, p   =   1.64 × 10-7. Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs in association with breast cancer risk at p < 0.05; for 16 of them, the

  8. Predicting risk of cancer during HIV infection

    DEFF Research Database (Denmark)

    Borges, Álvaro H; Silverberg, Michael J; Wentworth, Deborah

    2013-01-01

    To investigate the relationship between inflammatory [interleukin-6 (IL-6) and C-reactive protein (CRP)] and coagulation (D-dimer) biomarkers and cancer risk during HIV infection.......To investigate the relationship between inflammatory [interleukin-6 (IL-6) and C-reactive protein (CRP)] and coagulation (D-dimer) biomarkers and cancer risk during HIV infection....

  9. Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening.

    Science.gov (United States)

    Katki, Hormuzd A; Kovalchik, Stephanie A; Petito, Lucia C; Cheung, Li C; Jacobs, Eric; Jemal, Ahmedin; Berg, Christine D; Chaturvedi, Anil K

    2018-05-15

    Lung cancer screening guidelines recommend using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations. The performance of each model in selecting ever-smokers for screening is unknown. To compare the U.S. screening populations selected by 9 lung cancer risk models (the Bach model; the Spitz model; the Liverpool Lung Project [LLP] model; the LLP Incidence Risk Model [LLPi]; the Hoggart model; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 [PLCOM2012]; the Pittsburgh Predictor; the Lung Cancer Risk Assessment Tool [LCRAT]; and the Lung Cancer Death Risk Assessment Tool [LCDRAT]) and to examine their predictive performance in 2 cohorts. Population-based prospective studies. United States. Models selected U.S. screening populations by using data from the National Health Interview Survey from 2010 to 2012. Model performance was evaluated using data from 337 388 ever-smokers in the National Institutes of Health-AARP Diet and Health Study and 72 338 ever-smokers in the CPS-II (Cancer Prevention Study II) Nutrition Survey cohort. Model calibration (ratio of model-predicted to observed cases [expected-observed ratio]) and discrimination (area under the curve [AUC]). At a 5-year risk threshold of 2.0%, the models chose U.S. screening populations ranging from 7.6 million to 26 million ever-smokers. These disagreements occurred because, in both validation cohorts, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) were well-calibrated (expected-observed ratio range, 0.92 to 1.12) and had higher AUCs (range, 0.75 to 0.79) than 5 models that generally overestimated risk (expected-observed ratio range, 0.83 to 3.69) and had lower AUCs (range, 0.62 to 0.75). The 4 best-performing models also had the highest sensitivity at a fixed specificity (and vice versa) and similar discrimination at a fixed risk threshold. These models showed better agreement on size of the

  10. Development of a risk prediction model for lung cancer: The Japan Public Health Center-based Prospective Study.

    Science.gov (United States)

    Charvat, Hadrien; Sasazuki, Shizuka; Shimazu, Taichi; Budhathoki, Sanjeev; Inoue, Manami; Iwasaki, Motoki; Sawada, Norie; Yamaji, Taiki; Tsugane, Shoichiro

    2018-03-01

    Although the impact of tobacco consumption on the occurrence of lung cancer is well-established, risk estimation could be improved by risk prediction models that consider various smoking habits, such as quantity, duration, and time since quitting. We constructed a risk prediction model using a population of 59 161 individuals from the Japan Public Health Center (JPHC) Study Cohort II. A parametric survival model was used to assess the impact of age, gender, and smoking-related factors (cumulative smoking intensity measured in pack-years, age at initiation, and time since cessation). Ten-year cumulative probability of lung cancer occurrence estimates were calculated with consideration of the competing risk of death from other causes. Finally, the model was externally validated using 47 501 individuals from JPHC Study Cohort I. A total of 1210 cases of lung cancer occurred during 986 408 person-years of follow-up. We found a dose-dependent effect of tobacco consumption with hazard ratios for current smokers ranging from 3.78 (2.00-7.16) for cumulative consumption ≤15 pack-years to 15.80 (9.67-25.79) for >75 pack-years. Risk decreased with time since cessation. Ten-year cumulative probability of lung cancer occurrence estimates ranged from 0.04% to 11.14% in men and 0.07% to 6.55% in women. The model showed good predictive performance regarding discrimination (cross-validated c-index = 0.793) and calibration (cross-validated χ 2 = 6.60; P-value = .58). The model still showed good discrimination in the external validation population (c-index = 0.772). In conclusion, we developed a prediction model to estimate the probability of developing lung cancer based on age, gender, and tobacco consumption. This model appears useful in encouraging high-risk individuals to quit smoking and undergo increased surveillance. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  11. A 2-stage ovarian cancer screening strategy using the Risk of Ovarian Cancer Algorithm (ROCA) identifies early-stage incident cancers and demonstrates high positive predictive value.

    Science.gov (United States)

    Lu, Karen H; Skates, Steven; Hernandez, Mary A; Bedi, Deepak; Bevers, Therese; Leeds, Leroy; Moore, Richard; Granai, Cornelius; Harris, Steven; Newland, William; Adeyinka, Olasunkanmi; Geffen, Jeremy; Deavers, Michael T; Sun, Charlotte C; Horick, Nora; Fritsche, Herbert; Bast, Robert C

    2013-10-01

    A 2-stage ovarian cancer screening strategy was evaluated that incorporates change of carbohydrate antigen 125 (CA125) levels over time and age to estimate risk of ovarian cancer. Women with high-risk scores were referred for transvaginal ultrasound (TVS). A single-arm, prospective study of postmenopausal women was conducted. Participants underwent an annual CA125 blood test. Based on the Risk of Ovarian Cancer Algorithm (ROCA) result, women were triaged to next annual CA125 test (low risk), repeat CA125 test in 3 months (intermediate risk), or TVS and referral to a gynecologic oncologist (high risk). A total of 4051 women participated over 11 years. The average annual rate of referral to a CA125 test in 3 months was 5.8%, and the average annual referral rate to TVS and review by a gynecologic oncologist was 0.9%. Ten women underwent surgery on the basis of TVS, with 4 invasive ovarian cancers (1 with stage IA disease, 2 with stage IC disease, and 1 with stage IIB disease), 2 ovarian tumors of low malignant potential (both stage IA), 1 endometrial cancer (stage I), and 3 benign ovarian tumors, providing a positive predictive value of 40% (95% confidence interval = 12.2%, 73.8%) for detecting invasive ovarian cancer. The specificity was 99.9% (95% confidence interval = 99.7%, 100%). All 4 women with invasive ovarian cancer were enrolled in the study for at least 3 years with low-risk annual CA125 test values prior to rising CA125 levels. ROCA followed by TVS demonstrated excellent specificity and positive predictive value in a population of US women at average risk for ovarian cancer. Copyright © 2013 American Cancer Society.

  12. Prediction of Breast and Prostate Cancer Risks in Male BRCA1 and BRCA2 Mutation Carriers Using Polygenic Risk Scores.

    Science.gov (United States)

    Lecarpentier, Julie; Silvestri, Valentina; Kuchenbaecker, Karoline B; Barrowdale, Daniel; Dennis, Joe; McGuffog, Lesley; Soucy, Penny; Leslie, Goska; Rizzolo, Piera; Navazio, Anna Sara; Valentini, Virginia; Zelli, Veronica; Lee, Andrew; Amin Al Olama, Ali; Tyrer, Jonathan P; Southey, Melissa; John, Esther M; Conner, Thomas A; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Steele, Linda; Ding, Yuan Chun; Neuhausen, Susan L; Hansen, Thomas V O; Osorio, Ana; Weitzel, Jeffrey N; Toss, Angela; Medici, Veronica; Cortesi, Laura; Zanna, Ines; Palli, Domenico; Radice, Paolo; Manoukian, Siranoush; Peissel, Bernard; Azzollini, Jacopo; Viel, Alessandra; Cini, Giulia; Damante, Giuseppe; Tommasi, Stefania; Peterlongo, Paolo; Fostira, Florentia; Hamann, Ute; Evans, D Gareth; Henderson, Alex; Brewer, Carole; Eccles, Diana; Cook, Jackie; Ong, Kai-Ren; Walker, Lisa; Side, Lucy E; Porteous, Mary E; Davidson, Rosemarie; Hodgson, Shirley; Frost, Debra; Adlard, Julian; Izatt, Louise; Eeles, Ros; Ellis, Steve; Tischkowitz, Marc; Godwin, Andrew K; Meindl, Alfons; Gehrig, Andrea; Dworniczak, Bernd; Sutter, Christian; Engel, Christoph; Niederacher, Dieter; Steinemann, Doris; Hahnen, Eric; Hauke, Jan; Rhiem, Kerstin; Kast, Karin; Arnold, Norbert; Ditsch, Nina; Wang-Gohrke, Shan; Wappenschmidt, Barbara; Wand, Dorothea; Lasset, Christine; Stoppa-Lyonnet, Dominique; Belotti, Muriel; Damiola, Francesca; Barjhoux, Laure; Mazoyer, Sylvie; Van Heetvelde, Mattias; Poppe, Bruce; De Leeneer, Kim; Claes, Kathleen B M; de la Hoya, Miguel; Garcia-Barberan, Vanesa; Caldes, Trinidad; Perez Segura, Pedro; Kiiski, Johanna I; Aittomäki, Kristiina; Khan, Sofia; Nevanlinna, Heli; van Asperen, Christi J; Vaszko, Tibor; Kasler, Miklos; Olah, Edith; Balmaña, Judith; Gutiérrez-Enríquez, Sara; Diez, Orland; Teulé, Alex; Izquierdo, Angel; Darder, Esther; Brunet, Joan; Del Valle, Jesús; Feliubadalo, Lidia; Pujana, Miquel Angel; Lazaro, Conxi; Arason, Adalgeir; Agnarsson, Bjarni A; Johannsson, Oskar Th; Barkardottir, Rosa B; Alducci, Elisa; Tognazzo, Silvia; Montagna, Marco; Teixeira, Manuel R; Pinto, Pedro; Spurdle, Amanda B; Holland, Helene; Lee, Jong Won; Lee, Min Hyuk; Lee, Jihyoun; Kim, Sung-Won; Kang, Eunyoung; Kim, Zisun; Sharma, Priyanka; Rebbeck, Timothy R; Vijai, Joseph; Robson, Mark; Lincoln, Anne; Musinsky, Jacob; Gaddam, Pragna; Tan, Yen Y; Berger, Andreas; Singer, Christian F; Loud, Jennifer T; Greene, Mark H; Mulligan, Anna Marie; Glendon, Gord; Andrulis, Irene L; Toland, Amanda Ewart; Senter, Leigha; Bojesen, Anders; Nielsen, Henriette Roed; Skytte, Anne-Bine; Sunde, Lone; Jensen, Uffe Birk; Pedersen, Inge Sokilde; Krogh, Lotte; Kruse, Torben A; Caligo, Maria A; Yoon, Sook-Yee; Teo, Soo-Hwang; von Wachenfeldt, Anna; Huo, Dezheng; Nielsen, Sarah M; Olopade, Olufunmilayo I; Nathanson, Katherine L; Domchek, Susan M; Lorenchick, Christa; Jankowitz, Rachel C; Campbell, Ian; James, Paul; Mitchell, Gillian; Orr, Nick; Park, Sue Kyung; Thomassen, Mads; Offit, Kenneth; Couch, Fergus J; Simard, Jacques; Easton, Douglas F; Chenevix-Trench, Georgia; Schmutzler, Rita K; Antoniou, Antonis C; Ottini, Laura

    2017-07-10

    Purpose BRCA1/2 mutations increase the risk of breast and prostate cancer in men. Common genetic variants modify cancer risks for female carriers of BRCA1/2 mutations. We investigated-for the first time to our knowledge-associations of common genetic variants with breast and prostate cancer risks for male carriers of BRCA1/ 2 mutations and implications for cancer risk prediction. Materials and Methods We genotyped 1,802 male carriers of BRCA1/2 mutations from the Consortium of Investigators of Modifiers of BRCA1/2 by using the custom Illumina OncoArray. We investigated the combined effects of established breast and prostate cancer susceptibility variants on cancer risks for male carriers of BRCA1/2 mutations by constructing weighted polygenic risk scores (PRSs) using published effect estimates as weights. Results In male carriers of BRCA1/2 mutations, PRS that was based on 88 female breast cancer susceptibility variants was associated with breast cancer risk (odds ratio per standard deviation of PRS, 1.36; 95% CI, 1.19 to 1.56; P = 8.6 × 10 -6 ). Similarly, PRS that was based on 103 prostate cancer susceptibility variants was associated with prostate cancer risk (odds ratio per SD of PRS, 1.56; 95% CI, 1.35 to 1.81; P = 3.2 × 10 -9 ). Large differences in absolute cancer risks were observed at the extremes of the PRS distribution. For example, prostate cancer risk by age 80 years at the 5th and 95th percentiles of the PRS varies from 7% to 26% for carriers of BRCA1 mutations and from 19% to 61% for carriers of BRCA2 mutations, respectively. Conclusion PRSs may provide informative cancer risk stratification for male carriers of BRCA1/2 mutations that might enable these men and their physicians to make informed decisions on the type and timing of breast and prostate cancer risk management.

  13. Clinical audit in gynecological cancer surgery: development of a risk scoring system to predict adverse events.

    Science.gov (United States)

    Kondalsamy-Chennakesavan, Srinivas; Bouman, Chantal; De Jong, Suzanne; Sanday, Karen; Nicklin, Jim; Land, Russell; Obermair, Andreas

    2009-12-01

    Advanced gynecological surgery undertaken in a specialized gynecologic oncology unit may be associated with significant perioperative morbidity. Validated risk prediction models are available for general surgical specialties but currently not for gynecological cancer surgery. The objective of this study was to evaluate risk factors for adverse events (AEs) of patients treated for suspected or proven gynecological cancer and to develop a clinical risk score (RS) to predict such AEs. AEs were prospectively recorded and matched with demographical, clinical and histopathological data on 369 patients who had an abdominal or laparoscopic procedure for proven or suspected gynecological cancer at a tertiary gynecological cancer center. Stepwise multiple logistic regression was used to determine the best predictors of AEs. For the risk score (RS), the coefficients from the model were scaled using a factor of 2 and rounded to the nearest integer to derive the risk points. Sum of all the risk points form the RS. Ninety-five patients (25.8%) had at least one AE. Twenty-nine (7.9%) and 77 (20.9%) patients experienced intra- and postoperative AEs respectively with 11 patients (3.0%) experiencing both. The independent predictors for any AE were complexity of the surgical procedure, elevated SGOT (serum glutamic oxaloacetic transaminase, > or /=35 U/L), higher ASA scores and overweight. The risk score can vary from 0 to 14. The risk for developing any AE is described by the formula 100 / (1 + e((3.697 - (RS /2)))). RS allows for quantification of the risk for AEs. Risk factors are generally not modifiable with the possible exception of obesity.

  14. Thyroid Cancer Risk Assessment Tool

    Science.gov (United States)

    The R package thyroid implements a risk prediction model developed by NCI researchers to calculate the absolute risk of developing a second primary thyroid cancer (SPTC) in individuals who were diagnosed with a cancer during their childhood.

  15. The more from East-Asian, the better: risk prediction of colorectal cancer risk by GWAS-identified SNPs among Japanese.

    Science.gov (United States)

    Abe, Makiko; Ito, Hidemi; Oze, Isao; Nomura, Masatoshi; Ogawa, Yoshihiro; Matsuo, Keitaro

    2017-12-01

    Little is known about the difference of genetic predisposition for CRC between ethnicities; however, many genetic traits common to colorectal cancer have been identified. This study investigated whether more SNPs identified in GWAS in East Asian population could improve the risk prediction of Japanese and explored possible application of genetic risk groups as an instrument of the risk communication. 558 Patients histologically verified colorectal cancer and 1116 first-visit outpatients were included for derivation study, and 547 cases and 547 controls were for replication study. Among each population, we evaluated prediction models for the risk of CRC that combined the genetic risk group based on SNPs from GWASs in European-population and a similarly developed model adding SNPs from GWASs in East Asian-population. We examined whether adding East Asian-specific SNPs would improve the discrimination. Six SNPs (rs6983267, rs4779584, rs4444235, rs9929218, rs10936599, rs16969681) from 23 SNPs by European-based GWAS and five SNPs (rs704017, rs11196172, rs10774214, rs647161, rs2423279) among ten SNPs by Asian-based GWAS were selected in CRC risk prediction model. Compared with a 6-SNP-based model, an 11-SNP model including Asian GWAS-SNPs showed improved discrimination capacity in Receiver operator characteristic analysis. A model with 11 SNPs resulted in statistically significant improvement in both derivation (P = 0.0039) and replication studies (P = 0.0018) compared with six SNP model. We estimated cumulative risk of CRC by using genetic risk group based on 11 SNPs and found that the cumulative risk at age 80 is approximately 13% in the high-risk group while 6% in the low-risk group. We constructed a more efficient CRC risk prediction model with 11 SNPs including newly identified East Asian-based GWAS SNPs (rs704017, rs11196172, rs10774214, rs647161, rs2423279). Risk grouping based on 11 SNPs depicted lifetime difference of CRC risk. This might be useful for

  16. A predictive tool to estimate the risk of axillary metastases in breast cancer patients with negative axillary ultrasound

    DEFF Research Database (Denmark)

    Meretoja, T J; Heikkilä, P S; Mansfield, A S

    2014-01-01

    of this study was to evaluate the risk factors for axillary metastases in breast cancer patients with negative preoperative axillary ultrasound. METHODS: A total of 1,395 consecutive patients with invasive breast cancer and SNB formed the original patient series. A univariate analysis was conducted to assess...... risk factors for axillary metastases. Binary logistic regression analysis was conducted to form a predictive model based on the risk factors. The predictive model was first validated internally in a patient series of 566 further patients and then externally in a patient series of 2,463 patients from......BACKGROUND: Sentinel node biopsy (SNB) is the "gold standard" in axillary staging in clinically node-negative breast cancer patients. However, axillary treatment is undergoing a paradigm shift and studies are being conducted on whether SNB may be omitted in low-risk patients. The purpose...

  17. Predictive Risk of Radiation Induced Cerebral Necrosis in Pediatric Brain Cancer Patients after VMAT Versus Proton Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Freund, Derek; Zhang, Rui, E-mail: rzhang@marybird.com [Department of Radiation Oncology, Mary Bird Perkins Cancer Center, 4950 Essen Ln., Baton Rouge, LA 70809 (United States); Department of Physics and Astronomy, Louisiana State University, Nicholson Hall, Tower Dr., Baton Rouge, LA 70810 (United States); Sanders, Mary [Department of Radiation Oncology, Mary Bird Perkins Cancer Center, 4950 Essen Ln., Baton Rouge, LA 70809 (United States); Newhauser, Wayne [Department of Radiation Oncology, Mary Bird Perkins Cancer Center, 4950 Essen Ln., Baton Rouge, LA 70809 (United States); Department of Physics and Astronomy, Louisiana State University, Nicholson Hall, Tower Dr., Baton Rouge, LA 70810 (United States)

    2015-04-13

    Cancer of the brain and central nervous system (CNS) is the second most common of all pediatric cancers. Treatment of many of these cancers includes radiation therapy of which radiation induced cerebral necrosis (RICN) can be a severe and potentially devastating side effect. Risk factors for RICN include brain volume irradiated, the dose given per fraction and total dose. Thirteen pediatric patients were selected for this study to determine the difference in predicted risk of RICN when treating with volumetric modulated arc therapy (VMAT) compared to passively scattered proton therapy (PSPT) and intensity modulated proton therapy (IMPT). Plans were compared on the basis of dosimetric endpoints in the planned treatment volume (PTV) and brain and a radiobiological endpoint of RICN calculated using the Lyman-Kutcher-Burman probit model. Uncertainty tests were performed to determine if the predicted risk of necrosis was sensitive to positional errors, proton range errors and selection of risk models. Both PSPT and IMPT plans resulted in a significant increase in the maximum dose to the brain, a significant reduction in the total brain volume irradiated to low doses, and a significant lower predicted risk of necrosis compared with the VMAT plans. The findings of this study were upheld by the uncertainty analysis.

  18. Predictive Risk of Radiation Induced Cerebral Necrosis in Pediatric Brain Cancer Patients after VMAT Versus Proton Therapy

    Directory of Open Access Journals (Sweden)

    Derek Freund

    2015-04-01

    Full Text Available Cancer of the brain and central nervous system (CNS is the second most common of all pediatric cancers. Treatment of many of these cancers includes radiation therapy of which radiation induced cerebral necrosis (RICN can be a severe and potentially devastating side effect. Risk factors for RICN include brain volume irradiated, the dose given per fraction and total dose. Thirteen pediatric patients were selected for this study to determine the difference in predicted risk of RICN when treating with volumetric modulated arc therapy (VMAT compared to passively scattered proton therapy (PSPT and intensity modulated proton therapy (IMPT. Plans were compared on the basis of dosimetric endpoints in the planned treatment volume (PTV and brain and a radiobiological endpoint of RICN calculated using the Lyman-Kutcher-Burman probit model. Uncertainty tests were performed to determine if the predicted risk of necrosis was sensitive to positional errors, proton range errors and selection of risk models. Both PSPT and IMPT plans resulted in a significant increase in the maximum dose to the brain, a significant reduction in the total brain volume irradiated to low doses, and a significant lower predicted risk of necrosis compared with the VMAT plans. The findings of this study were upheld by the uncertainty analysis.

  19. Predicting reattendance at a high-risk breast cancer clinic.

    Science.gov (United States)

    Ormseth, Sarah R; Wellisch, David K; Aréchiga, Adam E; Draper, Taylor L

    2015-10-01

    The research about follow-up patterns of women attending high-risk breast-cancer clinics is sparse. This study sought to profile daughters of breast-cancer patients who are likely to return versus those unlikely to return for follow-up care in a high-risk clinic. Our investigation included 131 patients attending the UCLA Revlon Breast Center High Risk Clinic. Predictor variables included age, computed breast-cancer risk, participants' perceived personal risk, clinically significant depressive symptomatology (CES-D score ≥ 16), current level of anxiety (State-Trait Anxiety Inventory), and survival status of participants' mothers (survived or passed away from breast cancer). A greater likelihood of reattendance was associated with older age (adjusted odds ratio [AOR] = 1.07, p = 0.004), computed breast-cancer risk (AOR = 1.10, p = 0.017), absence of depressive symptomatology (AOR = 0.25, p = 0.009), past psychiatric diagnosis (AOR = 3.14, p = 0.029), and maternal loss to breast cancer (AOR = 2.59, p = 0.034). Also, an interaction was found between mother's survival and perceived risk (p = 0.019), such that reattendance was associated with higher perceived risk among participants whose mothers survived (AOR = 1.04, p = 0.002), but not those whose mothers died (AOR = 0.99, p = 0.685). Furthermore, a nonlinear inverted "U" relationship was observed between state anxiety and reattendance (p = 0.037); participants with moderate anxiety were more likely to reattend than those with low or high anxiety levels. Demographic, medical, and psychosocial factors were found to be independently associated with reattendance to a high-risk breast-cancer clinic. Explication of the profiles of women who may or may not reattend may serve to inform the development and implementation of interventions to increase the likelihood of follow-up care.

  20. Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin

    2018-02-01

    Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.

  1. An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology

    Science.gov (United States)

    Qiu, Yuchen; Wang, Yunzhi; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Liu, Hong; Zheng, Bin

    2016-03-01

    In order to establish a new personalized breast cancer screening paradigm, it is critically important to accurately predict the short-term risk of a woman having image-detectable cancer after a negative mammographic screening. In this study, we developed and tested a novel short-term risk assessment model based on deep learning method. During the experiment, a number of 270 "prior" negative screening cases was assembled. In the next sequential ("current") screening mammography, 135 cases were positive and 135 cases remained negative. These cases were randomly divided into a training set with 200 cases and a testing set with 70 cases. A deep learning based computer-aided diagnosis (CAD) scheme was then developed for the risk assessment, which consists of two modules: adaptive feature identification module and risk prediction module. The adaptive feature identification module is composed of three pairs of convolution-max-pooling layers, which contains 20, 10, and 5 feature maps respectively. The risk prediction module is implemented by a multiple layer perception (MLP) classifier, which produces a risk score to predict the likelihood of the woman developing short-term mammography-detectable cancer. The result shows that the new CAD-based risk model yielded a positive predictive value of 69.2% and a negative predictive value of 74.2%, with a total prediction accuracy of 71.4%. This study demonstrated that applying a new deep learning technology may have significant potential to develop a new short-term risk predicting scheme with improved performance in detecting early abnormal symptom from the negative mammograms.

  2. Nonvisible tumors on multiparametric magnetic resonance imaging does not predict low-risk prostate cancer

    Directory of Open Access Journals (Sweden)

    Seung Hwan Lee

    2015-12-01

    Conclusions: Even though cancer foci were not visualized by postbiopsy MRI, the pathological tumor volumes and extent of GS upgrading were relatively high. Therefore, nonvisible tumors by multiparametric MRI do not appear to be predictive of low-risk PCA.

  3. The REDUCE metagram: a comprehensive prediction tool for determining the utility of dutasteride chemoprevention in men at risk for prostate cancer

    Directory of Open Access Journals (Sweden)

    Carvell eNguyen

    2012-10-01

    Full Text Available Introduction: 5-alpha reductase inhibitors can reduce the risk of prostate cancer but can be associated with significant side effects. A library of nomograms which predict the risk of clinical endpoints relevant to dutasteride treatment may help determine if chemoprevention is suited to the individual patient. Methods: Data from the REDUCE trial was used to identify predictive factors for nine endpoints relevant to dutasteride treatment. Using the treatment and placebo groups from the biopsy cohort, Cox proportional hazards and competing risks regression models were used to build 18 nomograms, whose predictive ability was measured by concordance index and calibration plots. Results: A total of 18 nomograms assessing the risks of cancer, high-grade cancer, high grade prostatic intraepithelial neoplasia (HGPIN, atypical small acinar proliferation (ASAP, erectile dysfunction (ED, acute urinary retention (AUR, gynecomastia, urinary tract infection (UTI and BPH-related surgery either on or off dutasteride were created. The nomograms for cancer, high grade cancer, ED, AUR, and BPH-related surgery demonstrated good discrimination and calibration while those for gynecomastia, UTI, HGPIN, and ASAP predicted no better than random chance. Conclusions: To aid patients in determining whether the benefits of dutasteride use outweigh the risks, we have developed a comprehensive metagram that can generate individualized risks of 9 outcomes relevant to men considering chemoprevention. Better models based on more predictive markers are needed for some of the endpoints but the current metagram demonstrates potential as a tool for patient counseling and decision making that is accessible, intuitive, and clinically relevant.

  4. The REDUCE metagram: a comprehensive prediction tool for determining the utility of dutasteride chemoprevention in men at risk for prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Carvell T.; Isariyawongse, Brandon [Department of Urology, Glickman Urological and Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH (United States); Yu, Changhong; Kattan, Michael W., E-mail: kattanm@ccf.org [Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH (United States)

    2012-10-11

    Introduction: 5-alpha reductase inhibitors can reduce the risk of prostate cancer (PCa) but can be associated with significant side effects. A library of nomograms which predict the risk of clinical endpoints relevant to dutasteride treatment may help determine if chemoprevention is suited to the individual patient. Methods: Data from the REDUCE trial was used to identify predictive factors for 9 endpoints relevant to dutasteride treatment. Using the treatment and placebo groups from the biopsy cohort, Cox proportional hazards (PH) and competing risks regression (CRR) models were used to build 18 nomograms, whose predictive ability was measured by concordance index (CI) and calibration plots. Results: A total of 18 nomograms assessing the risks of cancer, high grade cancer, high grade prostatic intraepithelial neoplasia (HGPIN), atypical small acinar proliferation (ASAP), erectile dysfunction (ED), acute urinary retention (AUR), gynecomastia, urinary tract infection (UTI) and BPH-related surgery either on or off dutasteride were created. The nomograms for cancer, high grade cancer, ED, AUR, and BPH-related surgery demonstrated good discrimination and calibration while those for gynecomastia, UTI, HGPIN, and ASAP predicted no better than random chance. Conclusions: To aid patients in determining whether the benefits of dutasteride use outweigh the risks, we have developed a comprehensive metagram that can generate individualized risks of 9 outcomes relevant to men considering chemoprevention. Better models based on more predictive markers are needed for some of the endpoints but the current metagram demonstrates potential as a tool for patient counseling and decision-making that is accessible, intuitive, and clinically relevant.

  5. The REDUCE metagram: a comprehensive prediction tool for determining the utility of dutasteride chemoprevention in men at risk for prostate cancer

    International Nuclear Information System (INIS)

    Nguyen, Carvell T.; Isariyawongse, Brandon; Yu, Changhong; Kattan, Michael W.

    2012-01-01

    Introduction: 5-alpha reductase inhibitors can reduce the risk of prostate cancer (PCa) but can be associated with significant side effects. A library of nomograms which predict the risk of clinical endpoints relevant to dutasteride treatment may help determine if chemoprevention is suited to the individual patient. Methods: Data from the REDUCE trial was used to identify predictive factors for 9 endpoints relevant to dutasteride treatment. Using the treatment and placebo groups from the biopsy cohort, Cox proportional hazards (PH) and competing risks regression (CRR) models were used to build 18 nomograms, whose predictive ability was measured by concordance index (CI) and calibration plots. Results: A total of 18 nomograms assessing the risks of cancer, high grade cancer, high grade prostatic intraepithelial neoplasia (HGPIN), atypical small acinar proliferation (ASAP), erectile dysfunction (ED), acute urinary retention (AUR), gynecomastia, urinary tract infection (UTI) and BPH-related surgery either on or off dutasteride were created. The nomograms for cancer, high grade cancer, ED, AUR, and BPH-related surgery demonstrated good discrimination and calibration while those for gynecomastia, UTI, HGPIN, and ASAP predicted no better than random chance. Conclusions: To aid patients in determining whether the benefits of dutasteride use outweigh the risks, we have developed a comprehensive metagram that can generate individualized risks of 9 outcomes relevant to men considering chemoprevention. Better models based on more predictive markers are needed for some of the endpoints but the current metagram demonstrates potential as a tool for patient counseling and decision-making that is accessible, intuitive, and clinically relevant.

  6. Evaluation of Polygenic Risk Scores for Breast and Ovarian Cancer Risk Prediction in BRCA1 and BRCA2 Mutation Carriers

    Science.gov (United States)

    Kuchenbaecker, Karoline B.; McGuffog, Lesley; Barrowdale, Daniel; Lee, Andrew; Soucy, Penny; Healey, Sue; Dennis, Joe; Lush, Michael; Robson, Mark; Spurdle, Amanda B.; Ramus, Susan J.; Mavaddat, Nasim; Terry, Mary Beth; Neuhausen, Susan L.; Hamann, Ute; Southey, Melissa; John, Esther M.; Chung, Wendy K.; Daly, Mary B.; Buys, Saundra S.; Goldgar, David E.; Dorfling, Cecilia M.; van Rensburg, Elizabeth J.; Ding, Yuan Chun; Ejlertsen, Bent; Gerdes, Anne-Marie; Hansen, Thomas V. O.; Slager, Susan; Hallberg, Emily; Benitez, Javier; Osorio, Ana; Cohen, Nancy; Lawler, William; Weitzel, Jeffrey N.; Peterlongo, Paolo; Pensotti, Valeria; Dolcetti, Riccardo; Barile, Monica; Bonanni, Bernardo; Azzollini, Jacopo; Manoukian, Siranoush; Peissel, Bernard; Radice, Paolo; Savarese, Antonella; Papi, Laura; Giannini, Giuseppe; Fostira, Florentia; Konstantopoulou, Irene; Adlard, Julian; Brewer, Carole; Cook, Jackie; Davidson, Rosemarie; Eccles, Diana; Eeles, Ros; Ellis, Steve; Frost, Debra; Hodgson, Shirley; Izatt, Louise; Lalloo, Fiona; Ong, Kai-ren; Godwin, Andrew K.; Arnold, Norbert; Dworniczak, Bernd; Engel, Christoph; Gehrig, Andrea; Hahnen, Eric; Hauke, Jan; Kast, Karin; Meindl, Alfons; Niederacher, Dieter; Schmutzler, Rita Katharina; Varon-Mateeva, Raymonda; Wang-Gohrke, Shan; Wappenschmidt, Barbara; Barjhoux, Laure; Collonge-Rame, Marie-Agnès; Elan, Camille; Golmard, Lisa; Barouk-Simonet, Emmanuelle; Lesueur, Fabienne; Mazoyer, Sylvie; Sokolowska, Joanna; Stoppa-Lyonnet, Dominique; Isaacs, Claudine; Claes, Kathleen B. M.; Poppe, Bruce; de la Hoya, Miguel; Garcia-Barberan, Vanesa; Aittomäki, Kristiina; Nevanlinna, Heli; Ausems, Margreet G. E. M.; de Lange, J. L.; Gómez Garcia, Encarna B.; Hogervorst, Frans B. L.; Kets, Carolien M.; Meijers-Heijboer, Hanne E. J.; Oosterwijk, Jan C.; Rookus, Matti A.; van Asperen, Christi J.; van den Ouweland, Ans M. W.; van Doorn, Helena C.; van Os, Theo A. M.; Kwong, Ava; Olah, Edith; Diez, Orland; Brunet, Joan; Lazaro, Conxi; Teulé, Alex; Gronwald, Jacek; Jakubowska, Anna; Kaczmarek, Katarzyna; Lubinski, Jan; Sukiennicki, Grzegorz; Barkardottir, Rosa B.; Chiquette, Jocelyne; Agata, Simona; Montagna, Marco; Teixeira, Manuel R.; Park, Sue Kyung; Olswold, Curtis; Tischkowitz, Marc; Foretova, Lenka; Gaddam, Pragna; Vijai, Joseph; Pfeiler, Georg; Rappaport-Fuerhauser, Christine; Singer, Christian F.; Tea, Muy-Kheng M.; Greene, Mark H.; Loud, Jennifer T.; Rennert, Gad; Imyanitov, Evgeny N.; Hulick, Peter J.; Hays, John L.; Piedmonte, Marion; Rodriguez, Gustavo C.; Martyn, Julie; Glendon, Gord; Mulligan, Anna Marie; Andrulis, Irene L.; Toland, Amanda Ewart; Jensen, Uffe Birk; Kruse, Torben A.; Pedersen, Inge Sokilde; Thomassen, Mads; Caligo, Maria A.; Teo, Soo-Hwang; Berger, Raanan; Friedman, Eitan; Laitman, Yael; Arver, Brita; Borg, Ake; Ehrencrona, Hans; Rantala, Johanna; Olopade, Olufunmilayo I.; Ganz, Patricia A.; Nussbaum, Robert L.; Bradbury, Angela R.; Domchek, Susan M.; Nathanson, Katherine L.; Arun, Banu K.; James, Paul; Karlan, Beth Y.; Lester, Jenny; Simard, Jacques; Pharoah, Paul D. P.; Offit, Kenneth; Couch, Fergus J.; Chenevix-Trench, Georgia; Easton, Douglas F.

    2017-01-01

    Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]–positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2×10−53). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2×10−20). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management. PMID

  7. Toxicity ratios: Their use and abuse in predicting the risk from induced cancer

    International Nuclear Information System (INIS)

    Mays, C.W.; Taylor, G.N.; Lloyd, R.D.

    1986-01-01

    The toxicity ratio concept assumes the validity of certain relationships. In some examples for bone sarcoma induction, the approximate toxicity of 239 Pu in man can be calculated algebraically from the observed toxicity in the radium-dial painters and the ratio of 239 Pu/ 226 Ra toxicities in suitable laboratory mammals. In a species highly susceptible to bone sarcoma induction, the risk coefficients for both 239 Pu and 226 Ra are elevated, but the toxicity ratio of 239 Pu to 226 Ra tends to be similar to the ratio in resistant species. Among the tested species the toxicity ratio of 239 Pu to 226 Ra ranged from 6 to 22 (a fourfold range), whereas their relative sensitivities to 239 Pu varied by a factor of 150. The toxicity ratio approach can also be used to estimate the actinide risk to man from liver cancer, by comparing to the Thorotrast patients; from lung cancer, by comparing to the uranium miners and the atomic-bomb survivors; and from neutron-induced cancers, by comparing to cancers induced by gamma rays. The toxicity ratio can be used to predict the risk to man from a specific type of cancer that has been reliably induced by a reference radiation in humans and that can be induced by both the reference and the investigated radiation in suitable laboratory animals. 26 refs., 3 figs., 1 tab

  8. Risk determination and prevention of breast cancer.

    Science.gov (United States)

    Howell, Anthony; Anderson, Annie S; Clarke, Robert B; Duffy, Stephen W; Evans, D Gareth; Garcia-Closas, Montserat; Gescher, Andy J; Key, Timothy J; Saxton, John M; Harvie, Michelle N

    2014-09-28

    Breast cancer is an increasing public health problem. Substantial advances have been made in the treatment of breast cancer, but the introduction of methods to predict women at elevated risk and prevent the disease has been less successful. Here, we summarize recent data on newer approaches to risk prediction, available approaches to prevention, how new approaches may be made, and the difficult problem of using what we already know to prevent breast cancer in populations. During 2012, the Breast Cancer Campaign facilitated a series of workshops, each covering a specialty area of breast cancer to identify gaps in our knowledge. The risk-and-prevention panel involved in this exercise was asked to expand and update its report and review recent relevant peer-reviewed literature. The enlarged position paper presented here highlights the key gaps in risk-and-prevention research that were identified, together with recommendations for action. The panel estimated from the relevant literature that potentially 50% of breast cancer could be prevented in the subgroup of women at high and moderate risk of breast cancer by using current chemoprevention (tamoxifen, raloxifene, exemestane, and anastrozole) and that, in all women, lifestyle measures, including weight control, exercise, and moderating alcohol intake, could reduce breast cancer risk by about 30%. Risk may be estimated by standard models potentially with the addition of, for example, mammographic density and appropriate single-nucleotide polymorphisms. This review expands on four areas: (a) the prediction of breast cancer risk, (b) the evidence for the effectiveness of preventive therapy and lifestyle approaches to prevention, (c) how understanding the biology of the breast may lead to new targets for prevention, and (d) a summary of published guidelines for preventive approaches and measures required for their implementation. We hope that efforts to fill these and other gaps will lead to considerable advances in our

  9. Risk-optimized proton therapy to minimize radiogenic second cancers

    DEFF Research Database (Denmark)

    Rechner, Laura A; Eley, John G; Howell, Rebecca M

    2015-01-01

    Proton therapy confers substantially lower predicted risk of second cancer compared with photon therapy. However, no previous studies have used an algorithmic approach to optimize beam angle or fluence-modulation for proton therapy to minimize those risks. The objectives of this study were...... to demonstrate the feasibility of risk-optimized proton therapy and to determine the combination of beam angles and fluence weights that minimizes the risk of second cancer in the bladder and rectum for a prostate cancer patient. We used 6 risk models to predict excess relative risk of second cancer. Treatment...

  10. Risk Prediction Models for Other Cancers or Multiple Sites

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry.

    Science.gov (United States)

    Wang, Shengfeng; Qian, Frank; Zheng, Yonglan; Ogundiran, Temidayo; Ojengbede, Oladosu; Zheng, Wei; Blot, William; Nathanson, Katherine L; Hennis, Anselm; Nemesure, Barbara; Ambs, Stefan; Olopade, Olufunmilayo I; Huo, Dezheng

    2018-04-01

    Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models. We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC). Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512-0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506-0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532-0.640). We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.

  12. Accounting for individualized competing mortality risks in estimating postmenopausal breast cancer risk

    Science.gov (United States)

    Schonberg, Mara A.; Li, Vicky W.; Eliassen, A. Heather; Davis, Roger B.; LaCroix, Andrea Z.; McCarthy, Ellen P.; Rosner, Bernard A.; Chlebowski, Rowan T.; Hankinson, Susan E.; Marcantonio, Edward R.; Ngo, Long H.

    2016-01-01

    Purpose Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death. Methods We included 73,066 women who completed the 2004 Nurses’ Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors), 7 risk factors for non-breast cancer death (comorbidities, functional dependency), and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women’s Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years). Results Within 5 years, 1.8% of NHS participants were diagnosed with breast cancer (vs. 2.0% in WHI-ES, p=0.02) and 6.6% experienced non-breast cancer death (vs. 5.2% in WHI-ES, prisk factors, 5 comorbidities, functional dependency, and mammography use. The model’s c-statistic was 0.61 (95% CI [0.60–0.63]) in NHS and 0.57 (0.55–0.58) in WHI-ES. On average our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88–0.97]). Conclusions We developed a novel prediction model that factors in postmenopausal women’s individualized competing risks of non-breast cancer death when estimating breast cancer risk. PMID:27770283

  13. Predicting death from surgery for lung cancer

    DEFF Research Database (Denmark)

    O'Dowd, Emma L; Lüchtenborg, Margreet; Baldwin, David R

    2016-01-01

    OBJECTIVES: Current British guidelines advocate the use of risk prediction scores such as Thoracoscore to estimate mortality prior to radical surgery for non-small cell lung cancer (NSCLC). A recent publication used the National Lung Cancer Audit (NLCA) to produce a score to predict 90day mortali...

  14. A prospective investigation of predictive and modifiable risk factors for breast cancer in unaffected BRCA1 and BRCA2 gene carriers

    International Nuclear Information System (INIS)

    Guinan, Emer M; Hussey, Juliette; McGarrigle, Sarah A; Healy, Laura A; O’Sullivan, Jacintha N; Bennett, Kathleen; Connolly, Elizabeth M

    2013-01-01

    Breast cancer is the most common female cancer worldwide. The lifetime risk of a woman being diagnosed with breast cancer is approximately 12.5%. For women who carry the deleterious mutation in either of the BRCA genes, BRCA1 or BRCA2, the risk of developing breast or ovarian cancer is significantly increased. In recent years there has been increased penetrance of BRCA1 and BRCA2 associated breast cancer, prompting investigation into the role of modifiable risk factors in this group. Previous investigations into this topic have relied on participants recalling lifetime weight changes and subjective methods of recording physical activity. The influence of obesity-related biomarkers, which may explain the link between obesity, physical activity and breast cancer risk, has not been investigated prospectively in this group. This paper describes the design of a prospective cohort study investigating the role of predictive and modifiable risk factors for breast cancer in unaffected BRCA1 and BRCA2 gene mutation carriers. Participants will be recruited from breast cancer family risk clinics and genetics clinics. Lifestyle risk factors that will be investigated will include body composition, metabolic syndrome and its components, physical activity and dietary intake. PBMC telomere length will be measured as a potential predictor of breast cancer occurrence. Measurements will be completed on entry to the study and repeated at two years and five years. Participants will also be followed annually by questionnaire to track changes in risk factor status and to record cancer occurrence. Data will be analysed using multiple regression models. The study has an accrual target of 352 participants. The results from this study will provide valuable information regarding the role of modifiable lifestyle risk factors for breast cancer in women with a deleterious mutation in the BRCA gene. Additionally, the study will attempt to identify potential blood biomarkers which may be predictive

  15. Predicting Cancer-Prevention Behavior: Disentangling the Effects of Risk Aversion and Risk Perceptions.

    Science.gov (United States)

    Riddel, Mary; Hales, David

    2018-05-16

    Experimental and survey research spanning the last two decades concludes that people who are more risk tolerant are more likely to engage in risky health activities such as smoking and heavy alcohol consumption, and are more likely to be obese. Subjective perceptions of the risk associated with different activities have also been found to be associated with health behaviors. While there are numerous studies that link risk perceptions with risky behavior, it is notable that none of these controls for risk aversion. Similarly, studies that control for risk aversion fail to control for risk misperceptions. We use a survey of 474 men and women to investigate the influence of risk aversion, risk misperceptions, and cognitive ability on the choice to engage in behaviors that either increase or mitigate cancer risk. We measure optimism in two dimensions: baseline optimists are those who inaccurately believe their cancer risk to be below its expert-assessed level, while control optimists are those who believe they can reduce their risk of cancer (by changing their lifestyle choices) to a greater extent than is actually the case. Our results indicate that baseline optimism is significantly and negatively correlated with subjects' tendencies to engage in cancer-risk-reducing behaviors, and positively correlated with risky behaviors. Subjects' control misperceptions also appear to play a role in their tendency to engage in risky and prevention behaviors. When controlling for both of these types of risk misperception, risk aversion plays a much smaller role in determining health behaviors than found in past studies. © 2018 Society for Risk Analysis.

  16. Development and validation of risk prediction equations to estimate survival in patients with colorectal cancer: cohort study

    OpenAIRE

    Hippisley-Cox, Julia; Coupland, Carol

    2017-01-01

    Objective: To develop and externally validate risk prediction equations to estimate absolute and conditional survival in patients with colorectal cancer. \\ud \\ud Design: Cohort study.\\ud \\ud Setting: General practices in England providing data for the QResearch database linked to the national cancer registry.\\ud \\ud Participants: 44 145 patients aged 15-99 with colorectal cancer from 947 practices to derive the equations. The equations were validated in 15 214 patients with colorectal cancer ...

  17. Providing access to risk prediction tools via the HL7 XML-formatted risk web service.

    Science.gov (United States)

    Chipman, Jonathan; Drohan, Brian; Blackford, Amanda; Parmigiani, Giovanni; Hughes, Kevin; Bosinoff, Phil

    2013-07-01

    Cancer risk prediction tools provide valuable information to clinicians but remain computationally challenging. Many clinics find that CaGene or HughesRiskApps fit their needs for easy- and ready-to-use software to obtain cancer risks; however, these resources may not fit all clinics' needs. The HughesRiskApps Group and BayesMendel Lab therefore developed a web service, called "Risk Service", which may be integrated into any client software to quickly obtain standardized and up-to-date risk predictions for BayesMendel tools (BRCAPRO, MMRpro, PancPRO, and MelaPRO), the Tyrer-Cuzick IBIS Breast Cancer Risk Evaluation Tool, and the Colorectal Cancer Risk Assessment Tool. Software clients that can convert their local structured data into the HL7 XML-formatted family and clinical patient history (Pedigree model) may integrate with the Risk Service. The Risk Service uses Apache Tomcat and Apache Axis2 technologies to provide an all Java web service. The software client sends HL7 XML information containing anonymized family and clinical history to a Dana-Farber Cancer Institute (DFCI) server, where it is parsed, interpreted, and processed by multiple risk tools. The Risk Service then formats the results into an HL7 style message and returns the risk predictions to the originating software client. Upon consent, users may allow DFCI to maintain the data for future research. The Risk Service implementation is exemplified through HughesRiskApps. The Risk Service broadens the availability of valuable, up-to-date cancer risk tools and allows clinics and researchers to integrate risk prediction tools into their own software interface designed for their needs. Each software package can collect risk data using its own interface, and display the results using its own interface, while using a central, up-to-date risk calculator. This allows users to choose from multiple interfaces while always getting the latest risk calculations. Consenting users contribute their data for future

  18. Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk

    Science.gov (United States)

    Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Patel, Bhavika; Heidari, Morteza; Liu, Hong; Zheng, Bin

    2018-05-01

    This study aims to investigate the feasibility of identifying a new quantitative imaging marker based on false-positives generated by a computer-aided detection (CAD) scheme to help predict short-term breast cancer risk. An image dataset including four view mammograms acquired from 1044 women was retrospectively assembled. All mammograms were originally interpreted as negative by radiologists. In the next subsequent mammography screening, 402 women were diagnosed with breast cancer and 642 remained negative. An existing CAD scheme was applied ‘as is’ to process each image. From CAD-generated results, four detection features including the total number of (1) initial detection seeds and (2) the final detected false-positive regions, (3) average and (4) sum of detection scores, were computed from each image. Then, by combining the features computed from two bilateral images of left and right breasts from either craniocaudal or mediolateral oblique view, two logistic regression models were trained and tested using a leave-one-case-out cross-validation method to predict the likelihood of each testing case being positive in the next subsequent screening. The new prediction model yielded the maximum prediction accuracy with an area under a ROC curve of AUC  =  0.65  ±  0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of (2.95, 6.83). The results also showed an increasing trend in the adjusted odds ratio and risk prediction scores (p  breast cancer risk.

  19. An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study.

    Science.gov (United States)

    Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

    2017-01-01

    No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; the area under the curve was used to evaluate discriminatory ability of models. Area under the curve was 0.93 for the full model (including age, smoking and coffee habits, DNA adducts, 12 genotypes) and 0.86 for the short model (including smoking, DNA adducts, 3 genotypes). Using the "best cut-off" of predicted probability of a positive outcome, percentage of cases correctly classified was 92% (full model) against 75% (short model). Cancers classified as "positive outcome" are those to be referred for evaluation by an occupational physician for etiological diagnosis; these patients were 28 (full model) or 60 (short model). Using 3 genotypes instead of 12 can double the number of patients with suspect of aromatic amine related cancer, thus increasing costs of etiologic appraisal. Integrating clinical, laboratory and genetic factors, we developed the first etiologic prediction model for aromatic amine related bladder cancer. Discriminatory ability was excellent, particularly for the full model, allowing individualized predictions. Validation of our model in external populations is essential for practical use in the clinical setting.

  20. Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model

    Science.gov (United States)

    Tice, Jeffrey A.; Cummings, Steven R.; Smith-Bindman, Rebecca; Ichikawa, Laura; Barlow, William E.; Kerlikowske, Karla

    2009-01-01

    Background Current models for assessing breast cancer risk are complex and do not include breast density, a strong risk factor for breast cancer that is routinely reported with mammography. Objective To develop and validate an easy-to-use breast cancer risk prediction model that includes breast density. Design Empirical model based on Surveillance, Epidemiology, and End Results incidence, and relative hazards from a prospective cohort. Setting Screening mammography sites participating in the Breast Cancer Surveillance Consortium. Patients 1 095 484 women undergoing mammography who had no previous diagnosis of breast cancer. Measurements Self-reported age, race or ethnicity, family history of breast cancer, and history of breast biopsy. Community radiologists rated breast density by using 4 Breast Imaging Reporting and Data System categories. Results During 5.3 years of follow-up, invasive breast cancer was diagnosed in 14 766 women. The breast density model was well calibrated overall (expected–observed ratio, 1.03 [95% CI, 0.99 to 1.06]) and in racial and ethnic subgroups. It had modest discriminatory accuracy (concordance index, 0.66 [CI, 0.65 to 0.67]). Women with low-density mammograms had 5-year risks less than 1.67% unless they had a family history of breast cancer and were older than age 65 years. Limitation The model has only modest ability to discriminate between women who will develop breast cancer and those who will not. Conclusion A breast cancer prediction model that incorporates routinely reported measures of breast density can estimate 5-year risk for invasive breast cancer. Its accuracy needs to be further evaluated in independent populations before it can be recommended for clinical use. PMID:18316752

  1. Cancer risk in humans predicted by increased levels of chromosomal aberrations in lymphocytes: Nordic study group on the health risk of chromosome damage

    DEFF Research Database (Denmark)

    Hagmar, L; Brøgger, A; Hansteen, I L

    1994-01-01

    Cytogenetic assays in peripheral blood lymphocytes (PBL) have been used extensively to survey the exposure of humans to genotoxic agents. The conceptual basis for this has been the hypothesis that the extent of genetic damage in PBL reflects critical events for carcinogenic processes in target...... tissues. Until now, no follow-up studies have been performed to assess the predictive value of these methods for subsequent cancer risk. In an ongoing Nordic cohort study of cancer incidence, 3182 subjects were examined between 1970 and 1988 for chromosomal aberrations (CA), sister chromatid exchange.......0009) in CA strata with regard to subsequent cancer risk. The point estimates of the standardized incidence ratio in the three CA strata were 0.9, 0.7, and 2.1, respectively. Thus, an increased level of chromosome breakage appears to be a relevant biomarker of future cancer risk....

  2. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    Science.gov (United States)

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

  3. Combining gene signatures improves prediction of breast cancer survival.

    Directory of Open Access Journals (Sweden)

    Xi Zhao

    Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves

  4. Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

    OpenAIRE

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

    2014-01-01

    We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

  5. Post-bronchoscopy pneumonia in patients suffering from lung cancer: Development and validation of a risk prediction score.

    Science.gov (United States)

    Takiguchi, Hiroto; Hayama, Naoki; Oguma, Tsuyoshi; Harada, Kazuki; Sato, Masako; Horio, Yukihiro; Tanaka, Jun; Tomomatsu, Hiromi; Tomomatsu, Katsuyoshi; Takihara, Takahisa; Niimi, Kyoko; Nakagawa, Tomoki; Masuda, Ryota; Aoki, Takuya; Urano, Tetsuya; Iwazaki, Masayuki; Asano, Koichiro

    2017-05-01

    The incidence, risk factors, and consequences of pneumonia after flexible bronchoscopy in patients with lung cancer have not been studied in detail. We retrospectively analyzed the data from 237 patients with lung cancer who underwent diagnostic bronchoscopy between April 2012 and July 2013 (derivation sample) and 241 patients diagnosed between August 2013 and July 2014 (validation sample) in a tertiary referral hospital in Japan. A score predictive of post-bronchoscopy pneumonia was developed in the derivation sample and tested in the validation sample. Pneumonia developed after bronchoscopy in 6.3% and 4.1% of patients in the derivation and validation samples, respectively. Patients who developed post-bronchoscopy pneumonia needed to change or cancel their planned cancer therapy more frequently than those without pneumonia (56% vs. 6%, ppneumonia, which we added to develop our predictive score. The incidence of pneumonia associated with scores=0, 1, and ≥2 was 0, 3.7, and 13.4% respectively in the derivation sample (p=0.003), and 0, 2.9, and 9.7% respectively in the validation sample (p=0.016). The incidence of post-bronchoscopy pneumonia in patients with lung cancer was not rare and associated with adverse effects on the clinical course. A simple 3-point predictive score identified patients with lung cancer at high risk of post-bronchoscopy pneumonia prior to the procedure. Copyright © 2017 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

  6. Risk perception among Brazilian individuals with high risk for colorectal cancer and colonoscopy

    Directory of Open Access Journals (Sweden)

    Santos Erika M

    2011-07-01

    Full Text Available Abstract Background Risk perception is considered a motivating factor for adopting preventive behaviors. This study aimed to verify the demographic characteristics and cancer family history that are predictors of risk perception and to verify if risk perception is a predictor of colonoscopy adherence. Methods Individuals with a family colorectal cancer history as indicated by a proband with cancer were interviewed by telephone. They responded to a questionnaire covering demographic characteristics, colonoscopy history and four questions on risk perception. Tests of multiple linear regression and logistic regression were used to identify associations between dependent and independent variables. Results The 117 participants belonged to 62 families and had a mean age of 45.2 years. The majority of these individuals were female (74.4% and from families who met the Amsterdam Criteria (54.7%. The average risk perception was 47.6%, with a median of 50%. The average population perception of individual risk was 55.4%, with a median of 50%. Variables associated with a higher risk perception were age, gender, religion, school level, income, and death of a family member. The variable predicting colonoscopy was receiving medical information regarding risk (odds ratio OR 8.40. Conclusions We found that family cancer history characteristics (number of relatives with cancer, risk classification are associated with adequate risk perception. Risk perception does not predict colonoscopy in this sample. The only variable that predicted colonoscopy was receiving medical information recommending screening.

  7. Repeated assessments of symptom severity improve predictions for risk of death among patients with cancer.

    Science.gov (United States)

    Sutradhar, Rinku; Atzema, Clare; Seow, Hsien; Earle, Craig; Porter, Joan; Barbera, Lisa

    2014-12-01

    Although prior studies show the importance of self-reported symptom scores as predictors of cancer survival, most are based on scores recorded at a single point in time. To show that information on repeated assessments of symptom severity improves predictions for risk of death and to use updated symptom information for determining whether worsening of symptom scores is associated with a higher hazard of death. This was a province-based longitudinal study of adult outpatients who had a cancer diagnosis and had assessments of symptom severity. We implemented a time-to-death Cox model with a time-varying covariate for each symptom to account for changing symptom scores over time. This model was compared with that using only a time-fixed (baseline) covariate for each symptom. The regression coefficients of each model were derived based on a randomly selected 60% of patients, and then, the predictive performance of each model was assessed via concordance probabilities when applied to the remaining 40% of patients. This study had 66,112 patients diagnosed with cancer and more than 310,000 assessments of symptoms. The use of repeated assessments of symptom scores improved predictions for risk of death compared with using only baseline symptom scores. Increased pain and fatigue and reduced appetite were the strongest predictors for death. If available, researchers should consider including changing information on symptom scores, as opposed to only baseline information on symptom scores, when examining hazard of death among patients with cancer. Worsening of pain, fatigue, and appetite may be a flag for impending death. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  8. Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer.

    Science.gov (United States)

    Engmann, Natalie J; Golmakani, Marzieh K; Miglioretti, Diana L; Sprague, Brian L; Kerlikowske, Karla

    2017-09-01

    Many established breast cancer risk factors are used in clinical risk prediction models, although the proportion of breast cancers explained by these factors is unknown. To determine the population-attributable risk proportion (PARP) for breast cancer associated with clinical breast cancer risk factors among premenopausal and postmenopausal women. Case-control study with 1:10 matching on age, year of risk factor assessment, and Breast Cancer Surveillance Consortium (BCSC) registry. Risk factor data were collected prospectively from January 1, 1996, through October 31, 2012, from BCSC community-based breast imaging facilities. A total of 18 437 women with invasive breast cancer or ductal carcinoma in situ were enrolled as cases and matched to 184 309 women without breast cancer, with a total of 58 146 premenopausal and 144 600 postmenopausal women enrolled in the study. Breast Imaging Reporting and Data System (BI-RADS) breast density (heterogeneously or extremely dense vs scattered fibroglandular densities), first-degree family history of breast cancer, body mass index (>25 vs 18.5-25), history of benign breast biopsy, and nulliparity or age at first birth (≥30 years vs breast cancer. Of the 18 437 women with breast cancer, the mean (SD) age was 46.3 (3.7) years among premenopausal women and 61.7 (7.2) years among the postmenopausal women. Overall, 4747 (89.8%) premenopausal and 12 502 (95.1%) postmenopausal women with breast cancer had at least 1 breast cancer risk factor. The combined PARP of all risk factors was 52.7% (95% CI, 49.1%-56.3%) among premenopausal women and 54.7% (95% CI, 46.5%-54.7%) among postmenopausal women. Breast density was the most prevalent risk factor for both premenopausal and postmenopausal women and had the largest effect on the PARP; 39.3% (95% CI, 36.6%-42.0%) of premenopausal and 26.2% (95% CI, 24.4%-28.0%) of postmenopausal breast cancers could potentially be averted if all women with heterogeneously or extremely dense

  9. Androgen receptor profiling predicts prostate cancer outcome

    NARCIS (Netherlands)

    S. Stelloo (Suzan); E. Nevedomskaya (Ekaterina); H.G. van der Poel (Henk G.); J. de Jong (Jeroen); G.J.H.L. Leenders (Geert); G.W. Jenster (Guido); L. Wessels (Lodewyk); A.M. Bergman (Andries); W. Zwart (Wilbert)

    2015-01-01

    textabstractProstate cancer is the second most prevalent malignancy in men. Biomarkers for outcome prediction are urgently needed, so that high-risk patients could be monitored more closely postoperatively. To identify prognostic markers and to determine causal players in prostate cancer

  10. Prediction Model for Gastric Cancer Incidence in Korean Population.

    Directory of Open Access Journals (Sweden)

    Bang Wool Eom

    Full Text Available Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea.Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell's C-statistics, and the calibration was evaluated using a calibration plot and slope.During a median of 11.4 years of follow-up, 19,465 (1.4% and 5,579 (0.7% newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women.In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance.

  11. Family history of cancer predicts endometrial cancer risk independently of Lynch Syndrome: Implications for genetic counselling.

    Science.gov (United States)

    Johnatty, Sharon E; Tan, Yen Y; Buchanan, Daniel D; Bowman, Michael; Walters, Rhiannon J; Obermair, Andreas; Quinn, Michael A; Blomfield, Penelope B; Brand, Alison; Leung, Yee; Oehler, Martin K; Kirk, Judy A; O'Mara, Tracy A; Webb, Penelope M; Spurdle, Amanda B

    2017-11-01

    To determine endometrial cancer (EC) risk according to family cancer history, including assessment by degree of relatedness, type of and age at cancer diagnosis of relatives. Self-reported family cancer history was available for 1353 EC patients and 628 controls. Logistic regression was used to quantify the association between EC and cancer diagnosis in ≥1 first or second degree relative, and to assess whether level of risk differed by degree of relationship and/or relative's age at diagnosis. Risk was also evaluated for family history of up to three cancers from known familial syndromes (Lynch, Cowden, hereditary breast and ovarian cancer) overall, by histological subtype and, for a subset of 678 patients, by EC tumor mismatch repair (MMR) gene expression. Report of EC in ≥1 first- or second-degree relative was associated with significantly increased risk of EC (P=3.8×10 -7 ), independent of lifestyle risk factors. There was a trend in increasing EC risk with closer relatedness and younger age at EC diagnosis in relatives (P Trend =4.43×10 -6 ), and with increasing numbers of Lynch cancers in relatives (P Trend ≤0.0001). EC risk associated with family history did not differ by proband tumor MMR status, or histological subtype. Reported EC in first- or second-degree relatives remained associated with EC risk after conservative correction for potential misreported family history (OR 2.0; 95% CI, 1.24-3.37, P=0.004). The strongest predictor of EC risk was closer relatedness and younger EC diagnosis age in ≥1 relative. Associations remained significant irrespective of proband MMR status, and after excluding MMR pathogenic variant carriers, indicating that Lynch syndrome genes do not fully explain familial EC risk. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Prediction of metastasis from low-malignant breast cancer by gene expression profiling

    DEFF Research Database (Denmark)

    Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

    2007-01-01

    examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...

  13. Risk Prediction for Epithelial Ovarian Cancer in 11 United States–Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

    Science.gov (United States)

    Clyde, Merlise A.; Palmieri Weber, Rachel; Iversen, Edwin S.; Poole, Elizabeth M.; Doherty, Jennifer A.; Goodman, Marc T.; Ness, Roberta B.; Risch, Harvey A.; Rossing, Mary Anne; Terry, Kathryn L.; Wentzensen, Nicolas; Whittemore, Alice S.; Anton-Culver, Hoda; Bandera, Elisa V.; Berchuck, Andrew; Carney, Michael E.; Cramer, Daniel W.; Cunningham, Julie M.; Cushing-Haugen, Kara L.; Edwards, Robert P.; Fridley, Brooke L.; Goode, Ellen L.; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B.; Olson, Sara H.; Pearce, Celeste Leigh; Pike, Malcolm C.; Rothstein, Joseph H.; Sellers, Thomas A.; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J.; Vierkant, Robert A.; Wicklund, Kristine G.; Wu, Anna H.; Ziogas, Argyrios; Tworoger, Shelley S.; Schildkraut, Joellen M.

    2016-01-01

    Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted. PMID:27698005

  14. Prediction of Febrile Neutropenia after Chemotherapy Based on Pretreatment Risk Factors among Cancer Patients

    Science.gov (United States)

    Aagaard, Theis; Roen, Ashley; Daugaard, Gedske; Brown, Peter; Sengeløv, Henrik; Mocroft, Amanda; Lundgren, Jens; Helleberg, Marie

    2017-01-01

    Abstract Background Febrile neutropenia (FN) is a common complication to chemotherapy associated with a high burden of morbidity and mortality. Reliable prediction of individual risk based on pretreatment risk factors allows for stratification of preventive interventions. We aimed to develop such a risk stratification model to predict FN in the 30 days after initiation of chemotherapy. Methods We included consecutive treatment-naïve patients with solid cancers and diffuse large B-cell lymphomas at Copenhagen University Hospital, 2010–2015. Data were obtained from the PERSIMUNE repository of electronic health records. FN was defined as neutrophils ≤0.5 × 10E9/L ​at the time of either a blood culture sample or death. Time from initiation of chemotherapy to FN was analyzed using Fine-Gray models with death as a competing event. Risk factors investigated were: age, sex, body surface area, haemoglobin, albumin, neutrophil-to-lymphocyte ratio, Charlson Comorbidity Index (CCI) and chemotherapy drugs. Parameter estimates were scaled and summed to create the risk score. The scores were grouped into four: low, intermediate, high and very high risk. Results Among 8,585 patients, 467 experienced FN, incidence rate/30 person-days 0.05 (95% CI, 0.05–0.06). Age (1 point if > 65 years), albumin (1 point if 2) and chemotherapy (range -5 to 6 points/drug) predicted FN. Median score at inclusion was 2 points (range –5 to 9). The cumulative incidence and the incidence rates and hazard ratios of FN are shown in Figure 1 and Table 1, respectively. Conclusion We developed a risk score to predict FN the first month after initiation of chemotherapy. The score is easy to use and provides good differentiation of risk groups; the score needs independent validation before routine use. Disclosures All authors: No reported disclosures.

  15. Fall risk in community-dwelling elderly cancer survivors: a predictive model for gerontological nurses.

    Science.gov (United States)

    Spoelstra, Sandra; Given, Barbara; von Eye, Alexander; Given, Charles

    2010-02-01

    The aim of this predictive study was to test a structural model to establish predictors of fall risk in elderly cancer survivors. An aging and nursing model of care was synthesized and used to examine the Minimum Data Set for 6,912 low-income older adult participants in a community setting in the midwestern United States. Data analysis established relationships among fall risk and age, race/ethnicity, history of a previous fall, depression, pain, activities of daily living, instrumental activities of daily living, incontinence, vision, and cognitive status. Factors leading to fall risk can direct nursing activities that have the potential to prevent falls, thus improving older adults' quality of life. Copyright 2010, SLACK Incorporated.

  16. Screening frequency and atypical cells and the prediction of cervical cancer risk.

    Science.gov (United States)

    Chen, Yun-Yuan; You, San-Lin; Koong, Shin-Lan; Liu, Jessica; Chen, Chi-An; Chen, Chien-Jen

    2014-05-01

    To evaluate the screening efficacy and importance of atypical squamous cells and atypical glandular cells in predicting subsequent cervical cancer risk. This national cohort study in Taiwan analyzed associations between Pap test screening frequency and findings in 1995-2000 and subsequent risk of squamous cell carcinoma and adenocarcinoma after 2002. Women aged 30 years or older in 1995 without a cervical cancer history were included. Multivariate-adjusted hazard ratios and their 95% confidence intervals (CIs) were assessed using Cox regression analysis. During a total follow-up of 31,693,980 person-years in 2002-2008, 9,471 squamous cell carcinoma and 1,455 adenocarcinoma cases were newly diagnosed, resulting in 2,067 deaths. The risk of developing and dying from squamous cell carcinoma decreased significantly with increasing attendance frequency between 1995 and 2000 (all P values for trend1995-2000 had 0.69-fold and 0.35-fold decrease in incidence and mortality of adenocarcinoma, respectively, compared with women who never attended any screenings. Abnormal cytologic findings were significant predictors of the incidence and mortality of cervical cancers. The adjusted hazard ratio (95% CI) of developing squamous cell carcinoma was 29.94 (22.83-39.25) for atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesions, and the adjusted hazard ratio (95% CI) of developing adenocarcinoma was 49.43 (36.49-66.97) for atypical glandular cells. Significant reductions in cervical adenocarcinoma occurred in women who attend three or more annual screenings in 6 years. High-grade atypical squamous cells and atypical glandular cells are important predictors of subsequent adenocarcinoma and squamous cell carcinoma. II.

  17. Risk-optimized proton therapy to minimize radiogenic second cancers

    Science.gov (United States)

    Rechner, Laura A.; Eley, John G.; Howell, Rebecca M.; Zhang, Rui; Mirkovic, Dragan; Newhauser, Wayne D.

    2015-01-01

    Proton therapy confers substantially lower predicted risk of second cancer compared with photon therapy. However, no previous studies have used an algorithmic approach to optimize beam angle or fluence-modulation for proton therapy to minimize those risks. The objectives of this study were to demonstrate the feasibility of risk-optimized proton therapy and to determine the combination of beam angles and fluence weights that minimize the risk of second cancer in the bladder and rectum for a prostate cancer patient. We used 6 risk models to predict excess relative risk of second cancer. Treatment planning utilized a combination of a commercial treatment planning system and an in-house risk-optimization algorithm. When normal-tissue dose constraints were incorporated in treatment planning, the risk model that incorporated the effects of fractionation, initiation, inactivation, and repopulation selected a combination of anterior and lateral beams, which lowered the relative risk by 21% for the bladder and 30% for the rectum compared to the lateral-opposed beam arrangement. Other results were found for other risk models. PMID:25919133

  18. Genetically Predicted Body Mass Index and Breast Cancer Risk

    DEFF Research Database (Denmark)

    Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou

    2016-01-01

    BACKGROUND: Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or enviro...

  19. A Risk Prediction Model Based on Lymph-Node Metastasis in Poorly Differentiated-Type Intramucosal Gastric Cancer.

    Directory of Open Access Journals (Sweden)

    Jeung Hui Pyo

    Full Text Available Endoscopic submucosal dissection (ESD for undifferentiated type early gastric cancer is regarded as an investigational treatment. Few studies have tried to identify the risk factors that predict lymph-node metastasis (LNM in intramucosal poorly differentiated adenocarcinomas (PDC. This study was designed to develop a risk scoring system (RSS for predicting LNM in intramucosal PDC.From January 2002 to July 2015, patients diagnosed with mucosa-confined PDC, among those who underwent curative gastrectomy with lymph node dissection were reviewed. A risk model based on independent predicting factors of LNM was developed, and its performance was internally validated using a split sample approach.Overall, LNM was observed in 5.2% (61 of 1169 patients. Four risk factors [Female sex, tumor size ≥ 3.2 cm, muscularis mucosa (M3 invasion, and lymphatic-vascular involvement] were significantly associated with LNM, which were incorporated into the RSS. The area under the receiver operating characteristic curve for predicting LNM after internal validation was 0.69 [95% confidence interval (CI, 0.59-0.79]. A total score of 2 points corresponded to the optimal RSS threshold with a discrimination of 0.75 (95% CI 0.69-0.81. The LNM rates were 1.6% for low risk (<2 points and 8.9% for high-risk (≥2 points patients, with a negative predictive value of 98.6% (95% CI 0.98-1.00.A RSS could be useful in clinical practice to determine which patients with intramucosal PDC have low risk of LNM.

  20. Individual Prediction of Heart Failure Among Childhood Cancer Survivors

    NARCIS (Netherlands)

    Chow, Eric J.; Chen, Yan; Kremer, Leontien C.; Breslow, Norman E.; Hudson, Melissa M.; Armstrong, Gregory T.; Border, William L.; Feijen, Elizabeth A. M.; Green, Daniel M.; Meacham, Lillian R.; Meeske, Kathleen A.; Mulrooney, Daniel A.; Ness, Kirsten K.; Oeffinger, Kevin C.; Sklar, Charles A.; Stovall, Marilyn; van der Pal, Helena J.; Weathers, Rita E.; Robison, Leslie L.; Yasui, Yutaka

    2015-01-01

    Purpose To create clinically useful models that incorporate readily available demographic and cancer treatment characteristics to predict individual risk of heart failure among 5-year survivors of childhood cancer. Patients and Methods Survivors in the Childhood Cancer Survivor Study (CCSS) free of

  1. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

    Science.gov (United States)

    Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

    2017-05-22

    PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age

  2. Methodology to predict long-term cancer survival from short-term data using Tobacco Cancer Risk and Absolute Cancer Cure models

    International Nuclear Information System (INIS)

    Mould, R F; Lederman, M; Tai, P; Wong, J K M

    2002-01-01

    Three parametric statistical models have been fully validated for cancer of the larynx for the prediction of long-term 15, 20 and 25 year cancer-specific survival fractions when short-term follow-up data was available for just 1-2 years after the end of treatment of the last patient. In all groups of cases the treatment period was only 5 years. Three disease stage groups were studied, T1N0, T2N0 and T3N0. The models are the Standard Lognormal (SLN) first proposed by Boag (1949 J. R. Stat. Soc. Series B 11 15-53) but only ever fully validated for cancer of the cervix, Mould and Boag (1975 Br. J. Cancer 32 529-50), and two new models which have been termed Tobacco Cancer Risk (TCR) and Absolute Cancer Cure (ACC). In each, the frequency distribution of survival times of defined groups of cancer deaths is lognormally distributed: larynx only (SLN), larynx and lung (TCR) and all cancers (ACC). All models each have three unknown parameters but it was possible to estimate a value for the lognormal parameter S a priori. By reduction to two unknown parameters the model stability has been improved. The material used to validate the methodology consisted of case histories of 965 patients, all treated during the period 1944-1968 by Dr Manuel Lederman of the Royal Marsden Hospital, London, with follow-up to 1988. This provided a follow-up range of 20- 44 years and enabled predicted long-term survival fractions to be compared with the actual survival fractions, calculated by the Kaplan and Meier (1958 J. Am. Stat. Assoc. 53 457-82) method. The TCR and ACC models are better than the SLN model and for a maximum short-term follow-up of 6 years, the 20 and 25 year survival fractions could be predicted. Therefore the numbers of follow-up years saved are respectively 14 years and 19 years. Clinical trial results using the TCR and ACC models can thus be analysed much earlier than currently possible. Absolute cure from cancer was also studied, using not only the prediction models which

  3. Individual Prediction of Heart Failure Among Childhood Cancer Survivors

    Science.gov (United States)

    Chow, Eric J.; Chen, Yan; Kremer, Leontien C.; Breslow, Norman E.; Hudson, Melissa M.; Armstrong, Gregory T.; Border, William L.; Feijen, Elizabeth A.M.; Green, Daniel M.; Meacham, Lillian R.; Meeske, Kathleen A.; Mulrooney, Daniel A.; Ness, Kirsten K.; Oeffinger, Kevin C.; Sklar, Charles A.; Stovall, Marilyn; van der Pal, Helena J.; Weathers, Rita E.; Robison, Leslie L.; Yasui, Yutaka

    2015-01-01

    Purpose To create clinically useful models that incorporate readily available demographic and cancer treatment characteristics to predict individual risk of heart failure among 5-year survivors of childhood cancer. Patients and Methods Survivors in the Childhood Cancer Survivor Study (CCSS) free of significant cardiovascular disease 5 years after cancer diagnosis (n = 13,060) were observed through age 40 years for the development of heart failure (ie, requiring medications or heart transplantation or leading to death). Siblings (n = 4,023) established the baseline population risk. An additional 3,421 survivors from Emma Children's Hospital (Amsterdam, the Netherlands), the National Wilms Tumor Study, and the St Jude Lifetime Cohort Study were used to validate the CCSS prediction models. Results Heart failure occurred in 285 CCSS participants. Risk scores based on selected exposures (sex, age at cancer diagnosis, and anthracycline and chest radiotherapy doses) achieved an area under the curve of 0.74 and concordance statistic of 0.76 at or through age 40 years. Validation cohort estimates ranged from 0.68 to 0.82. Risk scores were collapsed to form statistically distinct low-, moderate-, and high-risk groups, corresponding to cumulative incidences of heart failure at age 40 years of 0.5% (95% CI, 0.2% to 0.8%), 2.4% (95% CI, 1.8% to 3.0%), and 11.7% (95% CI, 8.8% to 14.5%), respectively. In comparison, siblings had a cumulative incidence of 0.3% (95% CI, 0.1% to 0.5%). Conclusion Using information available to clinicians soon after completion of childhood cancer therapy, individual risk for subsequent heart failure can be predicted with reasonable accuracy and discrimination. These validated models provide a framework on which to base future screening strategies and interventions. PMID:25287823

  4. Familial Risk and Heritability of Cancer Among Twins in Nordic Countries

    DEFF Research Database (Denmark)

    Mucci, Lorelei A.; Hjelmborg, Jacob B.; Harris, Jennifer R.

    2016-01-01

    Importance: Estimates of familial cancer risk from population-based studies are essential components of cancer risk prediction. Objective: To estimate familial risk and heritability of cancer types in a large twin cohort. Design, Setting, and Participants: Prospective study of 80 309 monozygotic ...

  5. Contralateral breast cancer risk

    International Nuclear Information System (INIS)

    Unnithan, Jaya; Macklis, Roger M.

    2001-01-01

    The use of breast-conserving treatment approaches for breast cancer has now become a standard option for early stage disease. Numerous randomized studies have shown medical equivalence when mastectomy is compared to lumpectomy followed by radiotherapy for the local management of this common problem. With an increased emphasis on patient involvement in the therapeutic decision making process, it is important to identify and quantify any unforeseen risks of the conservation approach. One concern that has been raised is the question of radiation- related contralateral breast cancer after breast radiotherapy. Although most studies do not show statistically significant evidence that patients treated with breast radiotherapy are at increased risk of developing contralateral breast cancer when compared to control groups treated with mastectomy alone, there are clear data showing the amount of scattered radiation absorbed by the contralateral breast during a routine course of breast radiotherapy is considerable (several Gy) and is therefore within the range where one might be concerned about radiogenic contralateral tumors. While radiation related risks of contralateral breast cancer appear to be small enough to be statistically insignificant for the majority of patients, there may exist a smaller subset which, for genetic or environmental reasons, is at special risk for scatter related second tumors. If such a group could be predicted, it would seem appropriate to offer either special counselling or special prevention procedures aimed at mitigating this second tumor risk. The use of genetic testing, detailed analysis of breast cancer family history, and the identification of patients who acquired their first breast cancer at a very early age may all be candidate screening procedures useful in identifying such at- risk groups. Since some risk mitigation strategies are convenient and easy to utilize, it makes sense to follow the classic 'ALARA' (as low as reasonably

  6. Polygenic risk score is associated with increased disease risk in 52 Finnish breast cancer families

    OpenAIRE

    Muranen, Taru A.; Mavaddat, Nasim; Khan, Sofia; Fagerholm, Rainer; Pelttari, Liisa; Lee, Andrew; Aittom?ki, Kristiina; Blomqvist, Carl; Easton, Douglas F.; Nevanlinna, Heli

    2016-01-01

    The risk of developing breast cancer is increased in women with family history of breast cancer and particularly in families with multiple cases of breast or ovarian cancer. Nevertheless, many women with a positive family history never develop the disease. Polygenic risk scores (PRSs) based on the risk effects of multiple common genetic variants have been proposed for individual risk assessment on a population level. We investigate the applicability of the PRS for risk prediction within breas...

  7. Urinary metalloproteinases: noninvasive biomarkers for breast cancer risk assessment

    DEFF Research Database (Denmark)

    Pories, Susan E; Zurakowski, David; Roy, Roopali

    2008-01-01

    Matrix metalloproteinases (MMP) and a disintegrin and metalloprotease 12 (ADAM 12) can be detected in the urine of breast cancer patients and provide independent prediction of disease status. To evaluate the potential of urinary metalloproteinases as biomarkers to predict breast cancer risk statu...

  8. The Cancer of the Prostate Risk Assessment (CAPRA) score predicts biochemical recurrence in intermediate-risk prostate cancer treated with external beam radiotherapy (EBRT) dose escalation or low-dose rate (LDR) brachytherapy.

    Science.gov (United States)

    Krishnan, Vimal; Delouya, Guila; Bahary, Jean-Paul; Larrivée, Sandra; Taussky, Daniel

    2014-12-01

    To study the prognostic value of the University of California, San Francisco Cancer of the Prostate Risk Assessment (CAPRA) score to predict biochemical failure (bF) after various doses of external beam radiotherapy (EBRT) and/or permanent seed low-dose rate (LDR) prostate brachytherapy (PB). We retrospectively analysed 345 patients with intermediate-risk prostate cancer, with PSA levels of 10-20 ng/mL and/or Gleason 7 including 244 EBRT patients (70.2-79.2 Gy) and 101 patients treated with LDR PB. The minimum follow-up was 3 years. No patient received primary androgen-deprivation therapy. bF was defined according to the Phoenix definition. Cox regression analysis was used to estimate the differences between CAPRA groups. The overall bF rate was 13% (45/345). The CAPRA score, as a continuous variable, was statistically significant in multivariate analysis for predicting bF (hazard ratio [HR] 1.37, 95% confidence interval [CI] 1.10-1.72, P = 0.006). There was a trend for a lower bF rate in patients treated with LDR PB when compared with those treated by EBRT ≤ 74 Gy (HR 0.234, 95% CI 0.05-1.03, P = 0.055) in multivariate analysis. In the subgroup of patients with a CAPRA score of 3-5, CAPRA remained predictive of bF as a continuous variable (HR 1.51, 95% CI 1.01-2.27, P = 0.047) in multivariate analysis. The CAPRA score is useful for predicting biochemical recurrence in patients treated for intermediate-risk prostate cancer with EBRT or LDR PB. It could help in treatment decisions. © 2013 The Authors. BJU International © 2013 BJU International.

  9. Prediction of breast cancer risk based on profiling with common genetic variants

    DEFF Research Database (Denmark)

    Mavaddat, Nasim; Pharoah, Paul D P; Michailidou, Kyriaki

    2015-01-01

    BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. M...

  10. Prediction of breast cancer risk based on profiling with common genetic variants

    NARCIS (Netherlands)

    N. Mavaddat (Nasim); P.D.P. Pharoah (Paul); K. Michailidou (Kyriaki); J.P. Tyrer (Jonathan); M.N. Brook (Mark N.); M.K. Bolla (Manjeet); Q. Wang (Qing); J. Dennis (Joe); A.M. Dunning (Alison); M. Shah (Mitul); R.N. Luben (Robert); J. Brown (Judith); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); S.F. Nielsen (Sune F.); H. Flyger (Henrik); K. Czene (Kamila); H. Darabi (Hatef); M. Eriksson (Mikael); J. Peto (Julian); I. dos Santos Silva (Isabel); F. Dudbridge (Frank); N. Johnson (Nichola); M.K. Schmidt (Marjanka); A. Broeks (Annegien); S. Verhoef; E.J. Rutgers (Emiel J.); A.J. Swerdlow (Anthony ); A. Ashworth (Alan); N. Orr (Nick); M. Schoemaker (Minouk); J.D. Figueroa (Jonine); S.J. Chanock (Stephen); L.A. Brinton (Louise); J. Lissowska (Jolanta); F.J. Couch (Fergus); J.E. Olson (Janet); C. Vachon (Celine); V.S. Pankratz (Shane); D. Lambrechts (Diether); H. Wildiers (Hans); C. van Ongeval (Chantal); E. van Limbergen (Erik); V. Kristensen (Vessela); G. Grenaker Alnæs (Grethe); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); H. Nevanlinna (Heli); T.A. Muranen (Taru); K. Aittomäki (Kristiina); C. Blomqvist (Carl); J. Chang-Claude (Jenny); A. Rudolph (Anja); P. Seibold (Petra); D. Flesch-Janys (Dieter); P.A. Fasching (Peter); L. Haeberle (Lothar); A.B. Ekici (Arif); M.W. Beckmann (Matthias); B. Burwinkel (Barbara); F. Marme (Federick); A. Schneeweiss (Andreas); C. Sohn (Christof); A. Trentham-Dietz (Amy); P. Newcomb (Polly); L. Titus (Linda); K.M. Egan (Kathleen M.); D. Hunter (David); S. Lindstrom (Stephen); R. Tamimi (Rulla); P. Kraft (Peter); N. Rahman (Nazneen); C. Turnbull (Clare); A. Renwick (Anthony); S. Seal (Sheila); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); J. Benítez (Javier); M.P. Zamora (Pilar); J.I. Arias Pérez (José Ignacio); P. Menéndez (Primitiva); A. Jakubowska (Anna); J. Lubinski (Jan); K. Jaworska-Bieniek (Katarzyna); K. Durda (Katarzyna); N.V. Bogdanova (Natalia); N.N. Antonenkova (Natalia); T. Dörk (Thilo); H. Anton-Culver (Hoda); S.L. Neuhausen (Susan); A. Ziogas (Argyrios); L. Bernstein (Leslie); P. Devilee (Peter); R.A.E.M. Tollenaar (Rob); C.M. Seynaeve (Caroline); C.J. van Asperen (Christi); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); E.K. Khusnutdinova (Elza); M. Bermisheva (Marina); D. Prokofyeva (Darya); Z. Takhirova (Zalina); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Sutter (Christian); R. Yang (Rongxi); P. Schürmann (Peter); M. Bremer (Michael); H. Christiansen (Hans); T.-W. Park-Simon; P. Hillemanns (Peter); P. Guénel (Pascal); T. Truong (Thérèse); F. Menegaux (Florence); M. Sanchez (Marie); P. Radice (Paolo); P. Peterlongo (Paolo); S. Manoukian (Siranoush); V. Pensotti (Valeria); J. Hopper (John); H. Tsimiklis (Helen); C. Apicella (Carmel); M.C. Southey (Melissa); H. Brauch (Hiltrud); T. Brüning (Thomas); Y.-D. Ko (Yon-Dschun); A.J. Sigurdson (Alice); M.M. Doody (Michele M.); U. Hamann (Ute); D. Torres (Diana); H.U. Ulmer (Hans); A. Försti (Asta); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); A. Marie Mulligan (Anna); G. Chenevix-Trench (Georgia); R. Balleine (Rosemary); G.G. Giles (Graham); R.L. Milne (Roger); C.A. McLean (Catriona Ann); A. Lindblom (Annika); S. Margolin (Sara); C.A. Haiman (Christopher); B.E. Henderson (Brian); F. Schumacher (Fredrick); L. Le Marchand (Loic); U. Eilber (Ursula); S. Wang-Gohrke (Shan); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); A.M.W. van den Ouweland (Ans); L.B. Koppert (Lisa); J. Carpenter (Jane); C. Clarke (Christine); R.J. Scott (Rodney J.); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti); J.M. Hartikainen (J.); H. Brenner (Hermann); V. Arndt (Volker); C. Stegmaier (Christa); A. Karina Dieffenbach (Aida); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); K. Offit (Kenneth); J. Vijai (Joseph); M. Robson (Mark); R. Rau-Murthy (Rohini); M. Dwek (Miriam); R. Swann (Ruth); K. Annie Perkins (Katherine); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); D. Eccles (Diana); W. Tapper (William); M. Rafiq (Meena); E.M. John (Esther M.); A.S. Whittemore (Alice); S. Slager (Susan); D. Yannoukakos (Drakoulis); A.E. Toland (Amanda); S. Yao (Song); W. Zheng (Wei); S.L. Halverson (Sandra L.); A. González-Neira (Anna); G. Pita (Guillermo); M. Rosario Alonso; N. Álvarez (Nuria); D. Herrero (Daniel); D.C. Tessier (Daniel C.); D. Vincent (Daniel); F. Bacot (Francois); C. Luccarini (Craig); C. Baynes (Caroline); S. Ahmed (Shahana); M. Maranian (Melanie); S. Healey (Sue); J. Simard (Jacques); P. Hall (Per); D.F. Easton (Douglas); M. García-Closas (Montserrat)

    2015-01-01

    textabstractBackground: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is

  11. Breast cancer and the "materiality of risk": the rise of morphological prediction.

    Science.gov (United States)

    Löwy, Ilana

    2007-01-01

    This paper follows the history of "morphological risk" of breast cancer. In the early twentieth century, surgeons and pathologists arrived at the conclusion that specific anatomical and cytological changes in the breast are related to a heightened risk of developing a malignancy in the future. This conclusion was directly related to a shift from macroscopic to microscopic diagnosis of malignancies, and to the integration of the frozen section into routine surgery for breast cancer. In the interwar era, conditions such as "chronic mastitis" and "cystic disease of the breast" were defined as precancerous, and women diagnosed with these conditions were advised to undergo mastectomy. In the post-World War II era, these entities were replaced by "carcinoma in situ." The recent development of tests for hereditary predisposition to breast cancer is a continuation of attempts to detect an "embodied risk" of cancer and to eliminate this risk by cutting it out.

  12. Risk prediction and impaired tactile sensory perception among cancer patients during chemotherapy.

    Science.gov (United States)

    Cardoso, Ana Carolina Lima Ramos; Araújo, Diego Dias de; Chianca, Tânia Couto Machado

    2018-01-08

    to estimate the prevalence of impaired tactile sensory perception, identify risk factors, and establish a risk prediction model among adult patients receiving antineoplastic chemotherapy. historical cohort study based on information obtained from the medical files of 127 patients cared for in the cancer unit of a private hospital in a city in Minas Gerais, Brazil. Data were analyzed using descriptive and bivariate statistics, with survival and multivariate analysis by Cox regression. 57% of the 127 patients included in the study developed impaired tactile sensory perception. The independent variables that caused significant impact, together with time elapsed from the beginning of treatment up to the onset of the condition, were: bone, hepatic and regional lymph node metastases; alcoholism; palliative chemotherapy; and discomfort in lower limbs. impaired tactile sensory perception was common among adult patients during chemotherapy, indicating the need to implement interventions designed for early identification and treatment of this condition.

  13. Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm.

    Science.gov (United States)

    Reinbolt, Raquel E; Sonis, Stephen; Timmers, Cynthia D; Fernández-Martínez, Juan Luis; Cernea, Ana; de Andrés-Galiana, Enrique J; Hashemi, Sepehr; Miller, Karin; Pilarski, Robert; Lustberg, Maryam B

    2018-01-01

    Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor-related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm (NAA) to predict AIA using germline single nucleotide polymorphisms (SNP) data obtained before treatment initiation. Systematic chart review of 700 AI-treated patients with stage I-III BC identified asymptomatic patients (n = 39) and those with clinically significant AIA resulting in AI termination or therapy switch (n = 123). Germline DNA was obtained and SNP genotyping performed using the Affymetrix UK BioBank Axiom Array to yield 695,277 SNPs. SNP clusters that most closely defined AIA risk were discovered using an NAA that sequentially combined statistical filtering and a machine-learning algorithm. NCBI PhenGenI and Ensemble databases defined gene attribution of the most discriminating SNPs. Phenotype, pathway, and ontologic analyses assessed functional and mechanistic validity. Demographics were similar in cases and controls. A cluster of 70 SNPs, correlating to 57 genes, was identified. This SNP group predicted AIA occurrence with a maximum accuracy of 75.93%. Strong associations with arthralgia, breast cancer, and estrogen phenotypes were seen in 19/57 genes (33%) and were functionally consistent. Using a NAA, we identified a 70 SNP cluster that predicted AIA risk with fair accuracy. Phenotype, functional, and pathway analysis of attributed genes was consistent with clinical phenotypes. This study is the first to link a specific SNP/gene cluster to AIA risk independent of candidate gene bias. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  14. Assessing Breast Cancer Risk with an Artificial Neural Network

    Science.gov (United States)

    Sepandi, Mojtaba; Taghdir, Maryam; Rezaianzadeh, Abbas; Rahimikazerooni, Salar

    2018-04-25

    Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learning techniques have been widely applied in detection/recognition of cancer. This study aimed to establish a model to aid radiologists in breast cancer risk estimation. This incorporated imaging methods and fine needle aspiration biopsy (FNAB) for cyto-pathological diagnosis. Methods: An artificial neural network (ANN) technique was used on a retrospectively collected dataset including mammographic results, risk factors, and clinical findings to accurately predict the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: The network incorporating the selected features performed best (AUC = 0.955). Sensitivity and specificity of the ANN were respectively calculated as 0.82 and 0.90. In addition, negative and positive predictive values were respectively computed as 0.90 and 0.80. Conclusion: ANN has potential applications as a decision-support tool to help underperforming practitioners to improve the positive predictive value of biopsy recommendations. Creative Commons Attribution License

  15. The potential of large studies for building genetic risk prediction models

    Science.gov (United States)

    NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

  16. Estimated risk for secondary cancer in the contra-lateral breast following radiation therapy of breast cancer

    International Nuclear Information System (INIS)

    Johansen, Safora; Danielsen, Turi; Olsen, Dag Rune

    2008-01-01

    Purpose. To facilitate a discussion about the impact of dose heterogeneity on the risk for secondary contralateral breast (CB) cancer predicted with linear and non linear models associated with primary breast irradiation. Methods and materials. Dose volume statistics of the CB calculated for eight patients using a collapsed cone algorithm were used to predict the excess relative risk (ERR) for cancer induction in CB. Both linear and non-linear models were employed. A sensitivity analysis demonstrating the impact of different parameter values on calculated ERR for the eight patients was also included in this study. Results. A proportionality assumption was established to make the calculations with a linear and non-linear model comparable. ERR of secondary cancer predicted by the linear model varied considerably between the patients, while the predicted ERR for the same patients using the non-linear model showed very small variation. The predicted ERRs by the two models were indistinguishable for small doses, i.e. below ∼3 Gy. The sensitivity analysis showed that the quadratic component of the radiation-induction pre-malignant cell term is negligible for lower dose level. The ERR is highly sensitive to the value of agr1 and agr2. Conclusions. Optimization of breast cancer radiation therapy, where also the risk for radiation induced secondary malignancies in the contralateral breast is taken into account, requires robust and valid risk assessment. The linear dose-risk model does not account for the complexity in the mechanisms underlying the development of secondary malignancies following exposure to radiation; this is particularly important when estimating risk associated with highly heterogeneous dose distributions as is the case in the contralateral breast of women receiving breast cancer irradiation

  17. Limiting overdiagnosis of low-risk prostate cancer through an evaluation of the predictive value of transrectal and power Doppler ultrasonography.

    Science.gov (United States)

    Sauvain, Jean Luc; Sauvain, Elise; Papavero, Roger; Louis, Didier; Rohmer, Paul

    2016-12-01

    Overdiagnosis induced by prostate cancer screening makes necessary a better selection of candidate patients for prostate biopsy. The objective of our study is to assess the probability of having a high- or low-risk lesion that could require active surveillance (AS) after biopsies and a normal or abnormal examination, including transrectal and power Doppler ultrasonography (TRUS-PDS). Four hundred and twenty-nine consecutive patients with a PSA level risk of a biological recurrence and Dall'Era's criteria to assess possible AS. The TRUS-PDS was considered positive if one biopsy was positive in the same sextant as the suspect image. One hundred and seventy-seven out of 429 (41 %) T1c cancers were diagnosed; 131 out of 177 (74 %) could be qualified as low risk, and 119 out of 177 (67 %) could require AS. The TRUS-PDS was normal in 285 of 429 patients (66 %). With a normal TRUS-PDS, the probability of not having cancer with a high or intermediate risk was 96 % (negative predictive value). With an abnormal TRUS-PDS, the probability of having a positive biopsy was 59 %, and the probability of having a significant cancer was 30 %, according to the Dall'Era criteria. When TRUS-PDS was normal, these probabilities significantly decreased to 32 and 5 %, respectively ( p  risk of high- or intermediate-risk cancer.

  18. High-Risk and Low-Risk Human Papillomavirus and the Absolute Risk of Cervical Intraepithelial Neoplasia or Cancer

    DEFF Research Database (Denmark)

    Thomsen, Louise T; Frederiksen, Kirsten; Munk, Christian

    2014-01-01

    OBJECTIVE: To determine the absolute risk of cervical intraepithelial neoplasia (CIN) grade 3 or cervical cancer (CIN 3 or worse) after detection of low-risk human papillomavirus (HPV) and after a negative high-risk HPV test. METHODS: In this prospective cohort study, consecutive liquid......-based cervical cytology samples were collected from women screened for cervical cancer in Copenhagen, Denmark, during 2002-2005. Samples were tested with a clinical test for 13 high-risk and five low-risk HPV types. The cohort (N=35,539; aged 14-90 years) was monitored in a nationwide pathology register for up...... cytology. Detection of low-risk HPV does not predict CIN 3 or worse. Cervical cancer screening should not include testing for low-risk HPV types. LEVEL OF EVIDENCE: II....

  19. Fall-risk prediction in older adults with cancer: an unmet need.

    Science.gov (United States)

    Wildes, Tanya M; Depp, Brittany; Colditz, Graham; Stark, Susan

    2016-09-01

    Falls in older adults with cancer are more common than in noncancer controls, yet no fall-risk screening tool has been validated in this population. We undertook a cross-sectional pilot study of the Falls Risk Questionnaire (FRQ) in 21 adults aged ≥65 receiving systemic cancer therapy. Participants completed the FRQ, geriatric assessment measures, and a measure of fear-of-falling. The recruitment rate was 87.5 %, with 95.2 % completion of the FRQ and additional geriatric assessment and quality of life measures. The FRQ correlated significantly with the Timed Up and Go test (Pearson r 0.479, p = 0.028). In addition, the FRQ score correlated directly with fear-of-falling and inversely with QOL, particularly physical health and neurotoxicity subscales. In conclusion, the FRQ was feasible in older adults receiving cancer therapy and correlates with measures of physical performance, functional status, and fear-of-falling. The FRQ may prove to be a valuable fall-risk screening tool to implement fall-prevention interventions in this vulnerable population of older adults with cancer.

  20. Prostate cancer (PCa) risk variants and risk of fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium.

    Science.gov (United States)

    Shui, Irene M; Lindström, Sara; Kibel, Adam S; Berndt, Sonja I; Campa, Daniele; Gerke, Travis; Penney, Kathryn L; Albanes, Demetrius; Berg, Christine; Bueno-de-Mesquita, H Bas; Chanock, Stephen; Crawford, E David; Diver, W Ryan; Gapstur, Susan M; Gaziano, J Michael; Giles, Graham G; Henderson, Brian; Hoover, Robert; Johansson, Mattias; Le Marchand, Loic; Ma, Jing; Navarro, Carmen; Overvad, Kim; Schumacher, Fredrick R; Severi, Gianluca; Siddiq, Afshan; Stampfer, Meir; Stevens, Victoria L; Travis, Ruth C; Trichopoulos, Dimitrios; Vineis, Paolo; Mucci, Lorelei A; Yeager, Meredith; Giovannucci, Edward; Kraft, Peter

    2014-06-01

    Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM). To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM. We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred. The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls. Among the cases, we found that 8 of the 47 SNPs were significantly associated (pPCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only. Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa. In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that

  1. Predictions of space radiation fatality risk for exploration missions.

    Science.gov (United States)

    Cucinotta, Francis A; To, Khiet; Cacao, Eliedonna

    2017-05-01

    In this paper we describe revisions to the NASA Space Cancer Risk (NSCR) model focusing on updates to probability distribution functions (PDF) representing the uncertainties in the radiation quality factor (QF) model parameters and the dose and dose-rate reduction effectiveness factor (DDREF). We integrate recent heavy ion data on liver, colorectal, intestinal, lung, and Harderian gland tumors with other data from fission neutron experiments into the model analysis. In an earlier work we introduced distinct QFs for leukemia and solid cancer risk predictions, and here we consider liver cancer risks separately because of the higher RBE's reported in mouse experiments compared to other tumors types, and distinct risk factors for liver cancer for astronauts compared to the U.S. The revised model is used to make predictions of fatal cancer and circulatory disease risks for 1-year deep space and International Space Station (ISS) missions, and a 940 day Mars mission. We analyzed the contribution of the various model parameter uncertainties to the overall uncertainty, which shows that the uncertainties in relative biological effectiveness (RBE) factors at high LET due to statistical uncertainties and differences across tissue types and mouse strains are the dominant uncertainty. NASA's exposure limits are approached or exceeded for each mission scenario considered. Two main conclusions are made: 1) Reducing the current estimate of about a 3-fold uncertainty to a 2-fold or lower uncertainty will require much more expansive animal carcinogenesis studies in order to reduce statistical uncertainties and understand tissue, sex and genetic variations. 2) Alternative model assumptions such as non-targeted effects, increased tumor lethality and decreased latency at high LET, and non-cancer mortality risks from circulatory diseases could significantly increase risk estimates to several times higher than the NASA limits. Copyright © 2017 The Committee on Space Research (COSPAR

  2. Quantifying predictive capability of electronic health records for the most harmful breast cancer

    Science.gov (United States)

    Wu, Yirong; Fan, Jun; Peissig, Peggy; Berg, Richard; Tafti, Ahmad Pahlavan; Yin, Jie; Yuan, Ming; Page, David; Cox, Jennifer; Burnside, Elizabeth S.

    2018-03-01

    Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such prediction models for the "most harmful" breast cancers have rarely been developed. Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHR variables in the "most harmful" breast cancer risk prediction. We identified 794 subjects who had breast cancer with primary non-benign tumors with their earliest diagnosis on or after 1/1/2004 from an existing personalized medicine data repository, including 395 "most harmful" breast cancer cases and 399 "least harmful" breast cancer cases. For these subjects, we collected EHR data comprised of 6 components: demographics, diagnoses, symptoms, procedures, medications, and laboratory results. We developed two regularized prediction models, Ridge Logistic Regression (Ridge-LR) and Lasso Logistic Regression (Lasso-LR), to predict the "most harmful" breast cancer one year in advance. The area under the ROC curve (AUC) was used to assess model performance. We observed that the AUCs of Ridge-LR and Lasso-LR models were 0.818 and 0.839 respectively. For both the Ridge-LR and LassoLR models, the predictive performance of the whole EHR variables was significantly higher than that of each individual component (pbreast cancer, providing the possibility to personalize care for those women at the highest risk in clinical practice.

  3. Life history theory and breast cancer risk: methodological and theoretical challenges: Response to "Is estrogen receptor negative breast cancer risk associated with a fast life history strategy?".

    Science.gov (United States)

    Aktipis, Athena

    2016-01-01

    In a meta-analysis published by myself and co-authors, we report differences in the life history risk factors for estrogen receptor negative (ER-) and estrogen receptor positive (ER+) breast cancers. Our meta-analysis did not find the association of ER- breast cancer risk with fast life history characteristics that Hidaka and Boddy suggest in their response to our article. There are a number of possible explanations for the differences between their conclusions and the conclusions we drew from our meta-analysis, including limitations of our meta-analysis and methodological challenges in measuring and categorizing estrogen receptor status. These challenges, along with the association of ER+ breast cancer with slow life history characteristics, may make it challenging to find a clear signal of ER- breast cancer with fast life history characteristics, even if that relationship does exist. The contradictory results regarding breast cancer risk and life history characteristics illustrate a more general challenge in evolutionary medicine: often different sub-theories in evolutionary biology make contradictory predictions about disease risk. In this case, life history models predict that breast cancer risk should increase with faster life history characteristics, while the evolutionary mismatch hypothesis predicts that breast cancer risk should increase with delayed reproduction. Whether life history tradeoffs contribute to ER- breast cancer is still an open question, but current models and several lines of evidence suggest that it is a possibility. © The Author(s) 2016. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

  4. Predicting risk of cancer during HIV infection: the role of inflammatory and coagulation biomarkers.

    Science.gov (United States)

    Borges, Álvaro H; Silverberg, Michael J; Wentworth, Deborah; Grulich, Andrew E; Fätkenheuer, Gerd; Mitsuyasu, Ronald; Tambussi, Giuseppe; Sabin, Caroline A; Neaton, James D; Lundgren, Jens D

    2013-06-01

    To investigate the relationship between inflammatory [interleukin-6 (IL-6) and C-reactive protein (CRP)] and coagulation (D-dimer) biomarkers and cancer risk during HIV infection. A prospective cohort. HIV-infected patients on continuous antiretroviral therapy (ART) in the control arms of three randomized trials (N=5023) were included in an analysis of predictors of cancer (any type, infection-related or infection-unrelated). Hazard ratios for IL-6, CRP and D-dimer levels (log2-transformed) were calculated using Cox models stratified by trial and adjusted for demographics and CD4+ cell counts and adjusted also for all biomarkers simultaneously. To assess the possibility that biomarker levels were elevated at entry due to undiagnosed cancer, analyses were repeated excluding early cancer events (i.e. diagnosed during first 2 years of follow-up). During approximately 24,000 person-years of follow-up (PYFU), 172 patients developed cancer (70 infection-related; 102 infection-unrelated). The risk of developing cancer was associated with higher levels (per doubling) of IL-6 (hazard ratio 1.38, Passociated with cancer risk when all biomarkers were considered simultaneously. Results for infection-related and infection-unrelated cancers were similar to results for any cancer. Hazard ratios excluding 69 early cancer events were 1.31 (P=0.007), 1.14 (P=0.02) and 1.07 (P=0.49) for IL-6, CRP and D-dimer, respectively. Activated inflammation and coagulation pathways are associated with increased cancer risk during HIV infection. This association was stronger for IL-6 and persisted after excluding early cancer. Trials of interventions may be warranted to assess whether cancer risk can be reduced by lowering IL-6 levels in HIV-positive individuals.

  5. Validation of an online risk calculator for the prediction of anastomotic leak after colon cancer surgery and preliminary exploration of artificial intelligence-based analytics.

    Science.gov (United States)

    Sammour, T; Cohen, L; Karunatillake, A I; Lewis, M; Lawrence, M J; Hunter, A; Moore, J W; Thomas, M L

    2017-11-01

    Recently published data support the use of a web-based risk calculator ( www.anastomoticleak.com ) for the prediction of anastomotic leak after colectomy. The aim of this study was to externally validate this calculator on a larger dataset. Consecutive adult patients undergoing elective or emergency colectomy for colon cancer at a single institution over a 9-year period were identified using the Binational Colorectal Cancer Audit database. Patients with a rectosigmoid cancer, an R2 resection, or a diverting ostomy were excluded. The primary outcome was anastomotic leak within 90 days as defined by previously published criteria. Area under receiver operating characteristic curve (AUROC) was derived and compared with that of the American College of Surgeons National Surgical Quality Improvement Program ® (ACS NSQIP) calculator and the colon leakage score (CLS) calculator for left colectomy. Commercially available artificial intelligence-based analytics software was used to further interrogate the prediction algorithm. A total of 626 patients were identified. Four hundred and fifty-six patients met the inclusion criteria, and 402 had complete data available for all the calculator variables (126 had a left colectomy). Laparoscopic surgery was performed in 39.6% and emergency surgery in 14.7%. The anastomotic leak rate was 7.2%, with 31.0% requiring reoperation. The anastomoticleak.com calculator was significantly predictive of leak and performed better than the ACS NSQIP calculator (AUROC 0.73 vs 0.58) and the CLS calculator (AUROC 0.96 vs 0.80) for left colectomy. Artificial intelligence-predictive analysis supported these findings and identified an improved prediction model. The anastomotic leak risk calculator is significantly predictive of anastomotic leak after colon cancer resection. Wider investigation of artificial intelligence-based analytics for risk prediction is warranted.

  6. HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors

    International Nuclear Information System (INIS)

    Jong, Monique C. de; Pramana, Jimmy; Knegjens, Joost L.; Balm, Alfons J.M.; Brekel, Michiel W.M. van den; Hauptmann, Michael; Begg, Adrian C.; Rasch, Coen R.N.

    2010-01-01

    Purpose: The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. Material and methods: Gene expression data were available for a series of 92 advanced stage head and neck cancer patients treated with primary chemoradiotherapy. The effect of the Chung high-risk and Slebos HPV expression profiles on local control was analyzed in a model with age at diagnosis, gender, tumor site, tumor volume, T-stage and N-stage and HPV profile status. Results: Among 75 patients included in the study, the only factors significantly predicting local control were tumor site (oral cavity vs. Pharynx, hazard ratio 4.2 [95% CI 1.4-12.5]), Chung gene expression status (high vs. Low risk profile, hazard ratio 4.4 [95% CI 1.5-13.3]) and HPV profile (negative vs. Positive profile, hazard ratio 6.2 [95% CI 1.7-22.5]). Conclusions: Chung high-risk expression profile and a negative HPV expression profile were significantly associated with increased risk of local recurrence after chemoradiotherapy in advanced pharynx and oral cavity tumors, independent of clinical factors.

  7. Predictive value of pretreatment lymphocyte count in stage II colorectal cancer and in high-risk patients treated with adjuvant chemotherapy.

    Science.gov (United States)

    Liang, Lei; Zhu, Ji; Jia, Huixun; Huang, Liyong; Li, Dawei; Li, Qingguo; Li, Xinxiang

    2016-01-05

    Pretreatment lymphocyte count (LC) has been associated with prognosis and chemotherapy response in several cancers. The predictive value of LC for stage II colorectal cancer (CRC) and for high-risk patients treated with adjuvant chemotherapy (AC) has not been determined. A retrospective review of prospectively collected data from 1332 consecutive stage II CRC patients who underwent curative tumor resection was conducted. A pretreatment LC value risk, 459 (62.2%) of whom received AC. Patients with low LCs had significantly worse 5-year OS (74.6% vs. 90.2%, p risk patients with low LCs had the poorest DFS (p value or combined with high-risk status were both independent prognostic factors(p risk, AC-treated patients with high LCs had significantly longer DFS than untreated patients (HR, 0.594; 95% CI, 0.364-0.970; p = 0.035). There was no difference or trend for DFS or OS in patients with low LCs, regardless of the use of AC (DFS, p = 0.692; OS, p = 0.522). Low LC was also independently associated with poorer DFS in high-risk, AC-treated patients (HR, 1.885; 95% CI, 1.112-3.196; p = 0.019). Pretreatment LC is an independent prognostic factor for survival in stage II CRC. Furthermore, pretreatment LC reliably predicts chemotherapeutic efficacy in high-risk patients with stage II CRC.

  8. Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk

    Science.gov (United States)

    Li, Yane; Fan, Ming; Cheng, Hu; Zhang, Peng; Zheng, Bin; Li, Lihua

    2018-01-01

    This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All ‘prior’ images acquired in the two screening series were negative, while in the ‘current’ screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the ‘prior’ negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863  ±  0.0237 to 0.6870  ±  0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p  =  0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p  =  0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555  ±  0.0437, 0.6958  ±  0.0290, and 0.7054  ±  0.0529 for the three age groups of 37

  9. Understanding PSA and its derivatives in prediction of tumor volume: Addressing health disparities in prostate cancer risk stratification.

    Science.gov (United States)

    Chinea, Felix M; Lyapichev, Kirill; Epstein, Jonathan I; Kwon, Deukwoo; Smith, Paul Taylor; Pollack, Alan; Cote, Richard J; Kryvenko, Oleksandr N

    2017-03-28

    To address health disparities in risk stratification of U.S. Hispanic/Latino men by characterizing influences of prostate weight, body mass index, and race/ethnicity on the correlation of PSA derivatives with Gleason score 6 (Grade Group 1) tumor volume in a diverse cohort. Using published PSA density and PSA mass density cutoff values, men with higher body mass indices and prostate weights were less likely to have a tumor volume PSA derivatives when predicting for tumor volume. In receiver operator characteristic analysis, area under the curve values for all PSA derivatives varied across race/ethnicity with lower optimal cutoff values for Hispanic/Latino (PSA=2.79, PSA density=0.06, PSA mass=0.37, PSA mass density=0.011) and Non-Hispanic Black (PSA=3.75, PSA density=0.07, PSA mass=0.46, PSA mass density=0.008) compared to Non-Hispanic White men (PSA=4.20, PSA density=0.11 PSA mass=0.53, PSA mass density=0.014). We retrospectively analyzed 589 patients with low-risk prostate cancer at radical prostatectomy. Pre-operative PSA, patient height, body weight, and prostate weight were used to calculate all PSA derivatives. Receiver operating characteristic curves were constructed for each PSA derivative per racial/ethnic group to establish optimal cutoff values predicting for tumor volume ≥0.5 cm3. Increasing prostate weight and body mass index negatively influence PSA derivatives for predicting tumor volume. PSA derivatives' ability to predict tumor volume varies significantly across race/ethnicity. Hispanic/Latino and Non-Hispanic Black men have lower optimal cutoff values for all PSA derivatives, which may impact risk assessment for prostate cancer.

  10. Prediction of Breast and Prostate Cancer Risks in Male BRCA1 and BRCA2 Mutation Carriers Using Polygenic Risk Scores

    DEFF Research Database (Denmark)

    Lecarpentier, Julie; Silvestri, Valentina; Kuchenbaecker, Karoline B.

    2017-01-01

    Purpose BRCA1/2 mutations increase the risk of breast and prostate cancer in men. Common genetic variants modify cancer risks for female carriers of BRCA1/2 mutations. We investigated-for the first time to our knowledge-associations of common genetic variants with breast and prostate cancer risks...

  11. Machine learning applications in cancer prognosis and prediction.

    Science.gov (United States)

    Kourou, Konstantina; Exarchos, Themis P; Exarchos, Konstantinos P; Karamouzis, Michalis V; Fotiadis, Dimitrios I

    2015-01-01

    Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research, as it can facilitate the subsequent clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of machine learning (ML) methods. Therefore, these techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. In addition, the ability of ML tools to detect key features from complex datasets reveals their importance. A variety of these techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Support Vector Machines (SVMs) and Decision Trees (DTs) have been widely applied in cancer research for the development of predictive models, resulting in effective and accurate decision making. Even though it is evident that the use of ML methods can improve our understanding of cancer progression, an appropriate level of validation is needed in order for these methods to be considered in the everyday clinical practice. In this work, we present a review of recent ML approaches employed in the modeling of cancer progression. The predictive models discussed here are based on various supervised ML techniques as well as on different input features and data samples. Given the growing trend on the application of ML methods in cancer research, we present here the most recent publications that employ these techniques as an aim to model cancer risk or patient outcomes.

  12. Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies.

    Directory of Open Access Journals (Sweden)

    Ruth M Pfeiffer

    Full Text Available Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in the general population, and none for endometrial cancer.Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial [PLCO] and the National Institutes of Health-AARP Diet and Health Study [NIH-AARP], we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI; the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval [CI]: 0.96-1.04 for breast cancer and 1.08 (95% CI: 0.97-1.19 for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11-1.29. The areas under the receiver operating characteristic curves (AUCs; discriminatory power were 0.58 (95% CI: 0.57-0.59, 0.59 (95% CI: 0.56-0.63, and 0.68 (95% CI: 0.66-0.70 for the breast, ovarian, and endometrial models, respectively.These models predict absolute risks for breast, endometrial, and ovarian cancers from easily obtainable risk factors and may

  13. Evaluation of the Prostate Cancer Prevention Trial Risk Calculator in a High-Risk Screening Population

    Science.gov (United States)

    Kaplan, David J.; Boorjian, Stephen A.; Ruth, Karen; Egleston, Brian L.; Chen, David Y.T.; Viterbo, Rosalia; Uzzo, Robert G.; Buyyounouski, Mark K.; Raysor, Susan; Giri, Veda N.

    2009-01-01

    Introduction Clinical factors in addition to PSA have been evaluated to improve risk assessment for prostate cancer. The Prostate Cancer Prevention Trial (PCPT) risk calculator provides an assessment of prostate cancer risk based on age, PSA, race, prior biopsy, and family history. This study evaluated the risk calculator in a screening cohort of young, racially diverse, high-risk men with a low baseline PSA enrolled in the Prostate Cancer Risk Assessment Program. Patients and Methods Eligibility for PRAP include men ages 35-69 who are African-American, have a family history of prostate cancer, or have a known BRCA1/2 mutation. PCPT risk scores were determined for PRAP participants, and were compared to observed prostate cancer rates. Results 624 participants were evaluated, including 382 (61.2%) African-American men and 375 (60%) men with a family history of prostate cancer. Median age was 49.0 years (range 34.0-69.0), and median PSA was 0.9 (range 0.1-27.2). PCPT risk score correlated with prostate cancer diagnosis, as the median baseline risk score in patients diagnosed with prostate cancer was 31.3%, versus 14.2% in patients not diagnosed with prostate cancer (p<0.0001). The PCPT calculator similarly stratified the risk of diagnosis of Gleason score ≥7 disease, as the median risk score was 36.2% in patients diagnosed with Gleason ≥7 prostate cancer versus 15.2% in all other participants (p<0.0001). Conclusion PCPT risk calculator score was found to stratify prostate cancer risk in a cohort of young, primarily African-American men with a low baseline PSA. These results support further evaluation of this predictive tool for prostate cancer risk assessment in high-risk men. PMID:19709072

  14. The value of endorectal MR imaging to predict positive biopsies in clinically intermediate-risk prostate cancer patients

    International Nuclear Information System (INIS)

    Vilanova, J.C.; Barcelo, J.; Comet, J.; Capdevila, A.; Dolz, J.L.; Huguet, M.; Aldoma, J.; Delgado, E.; Barcelo, C.

    2001-01-01

    The aim of this study was to assess the effectiveness of endorectal MR imaging in predicting the positive biopsy results in patients with clinically intermediate risk for prostate cancer. We performed a prospective endorectal MR imaging study with 81 patients at intermediate risk to detect prostate cancer between January 1997 and December 1998. Intermediate risk was defined as: prostatic specific antigen (PSA) levels between 4 and 10 ng/ml or PSA levels in the range of 10-20 ng/ml but negative digital rectal examination (DRE) or PSA levels progressively higher (0.75 ng/ml year -1 ). A transrectal sextant biopsy was performed after the endorectal MR exam, and also of the area of suspicion detected by MR imaging. The accuracies were measured, both singly for MR imaging and combined for PSA level and DRE, by calculating the area index of the receiver operating characteristics (ROC) curve. Cancer was detected in 23 patients (28 %). Overall sensitivity and specificity of endorectal MRI was 70 and 76 %, respectively. Accuracy was 71 % estimated from the area under the ROC curve for the total patient group and 84 % for the group of patients with PSA level between 10-20 ng/ml. Positive biopsy rate (PBR) was 63 % for the group with PSA 10-20 ng/ml and a positive MR imaging, and 15 % with a negative MR exam. The PBR was 43 % for the group with PSA 4-10 ng/ml and a positive MR study, and 13 % with a negative MR imaging examination. We would have avoided 63 % of negative biopsies, while missing 30 % of cancers for the total group of patients. Endorectal MR imaging was not a sufficient predictor of positive biopsies for patients clinically at intermediate risk for prostate cancer. Although we should not avoid performing systematic biopsies in patients with endorectal MR imaging negative results, as it will miss a significant number of cancers, selected patients with a PSA levels between 10-20 ng/ml or clinical-biopsy disagreement might benefit from endorectal MR imaging. (orig.)

  15. The value of endorectal MR imaging to predict positive biopsies in clinically intermediate-risk prostate cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Vilanova, J.C.; Barcelo, J. [Ressonancia Girona, Clinica Girona, Girona (Spain); Comet, J. [Dept. of Urology, Univ. Hospital of Girona (Spain); Capdevila, A.; Dolz, J.L.; Huguet, M.; Aldoma, J.; Delgado, E. [Centre Diagnostic Pedralbes, Cetir Grup Medic, Barcelona (Spain); Barcelo, C. [Dept. of Computer Science and Applied Mathematics, University of Girona (Spain)

    2001-02-01

    The aim of this study was to assess the effectiveness of endorectal MR imaging in predicting the positive biopsy results in patients with clinically intermediate risk for prostate cancer. We performed a prospective endorectal MR imaging study with 81 patients at intermediate risk to detect prostate cancer between January 1997 and December 1998. Intermediate risk was defined as: prostatic specific antigen (PSA) levels between 4 and 10 ng/ml or PSA levels in the range of 10-20 ng/ml but negative digital rectal examination (DRE) or PSA levels progressively higher (0.75 ng/ml year{sup -1}). A transrectal sextant biopsy was performed after the endorectal MR exam, and also of the area of suspicion detected by MR imaging. The accuracies were measured, both singly for MR imaging and combined for PSA level and DRE, by calculating the area index of the receiver operating characteristics (ROC) curve. Cancer was detected in 23 patients (28 %). Overall sensitivity and specificity of endorectal MRI was 70 and 76 %, respectively. Accuracy was 71 % estimated from the area under the ROC curve for the total patient group and 84 % for the group of patients with PSA level between 10-20 ng/ml. Positive biopsy rate (PBR) was 63 % for the group with PSA 10-20 ng/ml and a positive MR imaging, and 15 % with a negative MR exam. The PBR was 43 % for the group with PSA 4-10 ng/ml and a positive MR study, and 13 % with a negative MR imaging examination. We would have avoided 63 % of negative biopsies, while missing 30 % of cancers for the total group of patients. Endorectal MR imaging was not a sufficient predictor of positive biopsies for patients clinically at intermediate risk for prostate cancer. Although we should not avoid performing systematic biopsies in patients with endorectal MR imaging negative results, as it will miss a significant number of cancers, selected patients with a PSA levels between 10-20 ng/ml or clinical-biopsy disagreement might benefit from endorectal MR imaging

  16. Pelvic Lymph Node Status Assessed by 18F-Fluorodeoxyglucose Positron Emission Tomography Predicts Low-Risk Group for Distant Recurrence in Locally Advanced Cervical Cancer: A Prospective Study

    International Nuclear Information System (INIS)

    Kang, Sokbom; Park, Jung-Yeol; Lim, Myung-Chul; Song, Yong-Joong; Park, Se-Hyun; Kim, Seok-Ki; Chung, Dae-Chul; Seo, Sang-Soo; Kim, Joo-Young; Park, Sang-Yoon

    2011-01-01

    Purpose: To develop a prediction model to identify a low-risk group for distant recurrence in patients with locally advanced cervical cancer treated by concurrent chemoradiation. Methods and Materials: Prospectively, 62 patients with locally advanced cervical cancer were recruited as a training cohort. Clinical variables and parameters obtained from positron emission tomography (PET) and magnetic resonance imaging were analyzed by logistic regression. For the test set, 54 patients were recruited independently. To identify the low-risk group, negative likelihood ratio (LR) less than 0.2 was set to be a cutoff. Results: Among the training cohort, multivariate logistic analysis revealed that advanced International Federation of Gynecology and Obstetrics (FIGO) stage and a high serum squamous cancer cell (SCC) antigen level were significant risk factors (p = 0.015 and 0.025, respectively). Using the two parameters, criteria to determine a low-risk subset for distant recurrence were postulated: (1) FIGO Stage IIB or less and (2) pretreatment SCC < 2.4 (Model A). Positive pelvic node on PET completely predicted all cases with distant recurrence and thus was considered as another prediction model (Model B). In the test cohort, although Model A did not showed diagnostic performance, Model B completely predicted all cases with distant recurrence and showed a sensitivity of 100% with negative LR of 0. Across the training and test cohort (n = 116), the false negative rate was 0 (95% confidence interval 0%-7.6%). Conclusions: Positive pelvic node on PET is a useful marker in prediction of distant recurrence in patients with locally advanced cervical cancer who are treated with concurrent chemoradiation.

  17. Psychosocial factors and uptake of risk-reducing salpingo-oophorectomy in women at high risk for ovarian cancer.

    Science.gov (United States)

    Meiser, Bettina; Price, Melanie A; Butow, Phyllis N; Karatas, Janan; Wilson, Judy; Heiniger, Louise; Baylock, Brandi; Charles, Margaret; McLachlan, Sue-Anne; Phillips, Kelly-Anne

    2013-03-01

    Bilateral risk-reducing salpingo-oophorectomy (RRSO) has been shown to significantly reduce the risk of ovarian cancer. This study assessed factors predicting uptake of RRSO. Women participating in a large multiple-case breast cancer family cohort study who were at increased risk for ovarian and fallopian tube cancer (i.e. BRCA1 or BRCA2 mutation carrier or family history including at least one first- or second-degree relative with ovarian or fallopian tube cancer), with no personal history of cancer and with at least one ovary in situ at cohort enrolment, were eligible for this study. Women who knew they did not carry the BRCA1 or BRCA2 mutation segregating in their family (true negatives) were excluded. Sociodemographic, biological and psychosocial factors, including cancer-specific anxiety, perceived ovarian cancer risk, optimism and social support, were assessed using self-administered questionnaires and interviews at cohort enrolment. RRSO uptake was self-reported every three years during systematic follow-up. Of 2,859 women, 571 were eligible. Mean age was 43.3 years; 62 women (10.9 %) had RRSO a median of two years after cohort entry. Factors predicting RRSO were: being parous (OR 3.3, p = 0.015); knowing one's mutation positive status (OR 2.9, p cancer (OR 2.5, p = 0.013). Psychological variables measured at cohort entry were not associated with RRSO. These results suggest that women at high risk for ovarian cancer make decisions about RRSO based on risk and individual socio-demographic characteristics, rather than in response to psychological factors such as anxiety.

  18. Predicting Lymph Node Metastasis in Endometrial Cancer Using Serum CA125 Combined with Immunohistochemical Markers PR and Ki67, and a Comparison with Other Prediction Models.

    Directory of Open Access Journals (Sweden)

    Bingyi Yang

    Full Text Available We aimed to evaluate the value of immunohistochemical markers and serum CA125 in predicting the risk of lymph node metastasis (LNM in women with endometrial cancer and to identify a low-risk group of LNM. The medical records of 370 patients with endometrial endometrioid adenocarcinoma who underwent surgical staging in the Obstetrics & Gynecology Hospital of Fudan University were collected and retrospectively reviewed. Immunohistochemical markers were screened. A model using serum cancer antigen 125 (CA125 level, the immunohistochemical markers progesterone receptor (PR and Ki67 was created for prediction of LNM. A predicted probability of 4% among these patients was defined as low risk. The developed model was externally validated in 200 patients from Shanghai Cancer Center. The efficiency of the model was compared with three other reported prediction models. Patients with serum CA125 50% and Ki67 < 40% in cancer lesion were defined as low risk for LNM. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.82. The model classified 61.9% (229/370 of patients as being at low risk for LNM. Among these 229 patients, 6 patients (2.6% had LNM and the negative predictive value was 97.4% (223/229. The sensitivity and specificity of the model were 84.6% and 67.4% respectively. In the validation cohort, the model classified 59.5% (119/200 of patients as low-risk, 3 out of these 119 patients (2.5% has LNM. Our model showed a predictive power similar to those of two previously reported prediction models. The prediction model using serum CA125 and the immunohistochemical markers PR and Ki67 is useful to predict patients with a low risk of LNM and has the potential to provide valuable guidance to clinicians in the treatment of patients with endometrioid endometrial cancer.

  19. Ionizing radiation-induced DNA damage and repair as a potential biomarker in biodosimetry, cancer risk analysis and for prediction of radiotherapy induced toxicity

    International Nuclear Information System (INIS)

    Satish Rao, B.S.

    2017-01-01

    Lymphocytes isolated from peripheral blood from 100 healthy individuals, 232 cancer patients (cervical, breast cancer and head and neck cancer) irradiated in vitro or in vivo were used for measuring DNA damage and repair. The microscopic method of the γ-H2AX assay was adopted to elucidate the significance of DSB in biodosimetry, cancer risk susceptibility, and normal tissue toxicity prediction. We validated the use of H2AX assay in early triage biodosimetry by using lymphocytes from cervical cancer patients exposed to radiotherapy. Further, the basal and residual damage was significantly higher in cancer individuals compared to the healthy individuals. In cancer patients undergoing radiotherapy, we could able to show the increase in normal tissue toxicity with decreased DSB repair capacity. In conclusion this study indicates the DSB estimation by γ-H2AX foci analysis can serve as a tool to understand the triage of radiation exposed individuals, identifying individuals at cancer risk and normal tissue toxicity

  20. Cancer risks from ingestion of radiostrontium

    Energy Technology Data Exchange (ETDEWEB)

    Raabe, O. G.

    2004-07-01

    Studies have been conducted of the lifetime effects in 403 beagles of the skeletal uptake in seven logarithmically increasing dosage groups of ingested Sr-90. The Sr-90 was fed during skeletal developmental from mid-gestation to adulthood at age 540 days resulting in lifetime protracted beta radiation exposure of the skeleton and some adjacent tissues. Statistical analysis of all types of cancer deaths in the 403 exposed beagles and in 162 unexposed controls indicated that deaths caused by five types of cancer were significantly elevated by high level exposure to Sr-90; these were (1) myeloid leukemia, (2) bone sarcoma, (3) squamous cell carcinoma of periodontal origin, (4) nasal carcinoma, and (5) oral carcinoma. Dose response analysis of these radiation-induced cancer deaths showed non-linear relationships with marked thresholds. A mean lifetime skeletal absorbed dose of 22.5 +/-5.7 Gy SD (22.5 +/-5.7 Sv SD) was associated with the lowest dosage group in which any radiation induced cancer deaths were observed. Three-dimensional models of the observed dose-rate/time/response relationships were fir with maximum likelihood regression methods to describe the risks of death associated with the different types of radiation-induced cancer. The models show that a life-time virtual threshold for cancer risk occurs because the time required to induce cancer is longer at lower radiation dose rates and may exceed the natural life span. Scaling these results to predict human cancer risks from ingestion of Sr-90 shows negligible risks for people whose lifetime cumulative skeletal dose is less than 10 Sv. (Author)

  1. Prediction model for recurrence probabilities after intravesical chemotherapy in patients with intermediate-risk non-muscle-invasive bladder cancer, including external validation

    NARCIS (Netherlands)

    Lammers, R.J.M.; Hendriks, J.C.M.; Rodriguez Faba, O.; Witjes, W.P.J.; Palou, J.; Witjes, J.A.

    2016-01-01

    PURPOSE: To develop a model to predict recurrence for patients with intermediate-risk (IR) non-muscle-invasive bladder cancer (NMIBC) treated with intravesical chemotherapy which can be challenging because of the heterogeneous characteristics of these patients. METHODS: Data from three Dutch trials

  2. Prostate cancer staging with extracapsular extension risk scoring using multiparametric MRI

    DEFF Research Database (Denmark)

    Boesen, Lars; Chabanova, Elizaveta; Løgager, Vibeke

    2015-01-01

    OBJECTIVES: To evaluate the diagnostic performance of preoperative multiparametric MRI with extracapsular extension (ECE) risk-scoring in the assessment of prostate cancer tumour stage (T-stage) and prediction of ECE at final pathology. MATERIALS AND METHODS: Eighty-seven patients with clinically....../87 (36 %) patients. ECE risk-scoring showed an AUC of 0.65-0.86 on ROC-curve for both readers, with sensitivity and specificity of 81 % and 78 % at best cutoff level (reader A), respectively. When tumour characteristics were influenced by personal opinion, the sensitivity and specificity for prediction...... technique for preoperative prostate cancer staging • ECE risk scoring predicts extracapsular tumour extension at final pathology • ECE risk scoring shows an AUC of 0.86 on the ROC-curve • ECE risk scoring shows a moderate inter-reader agreement (K = 0.45) • Multiparametric MRI provides essential knowledge...

  3. Evidence that breast tissue stiffness is associated with risk of breast cancer.

    Science.gov (United States)

    Boyd, Norman F; Li, Qing; Melnichouk, Olga; Huszti, Ella; Martin, Lisa J; Gunasekara, Anoma; Mawdsley, Gord; Yaffe, Martin J; Minkin, Salomon

    2014-01-01

    Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.

  4. Development and External Validation of the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer: Comparison with Two Western Risk Calculators in an Asian Cohort.

    Science.gov (United States)

    Park, Jae Young; Yoon, Sungroh; Park, Man Sik; Choi, Hoon; Bae, Jae Hyun; Moon, Du Geon; Hong, Sung Kyu; Lee, Sang Eun; Park, Chanwang; Byun, Seok-Soo

    2017-01-01

    We developed the Korean Prostate Cancer Risk Calculator for High-Grade Prostate Cancer (KPCRC-HG) that predicts the probability of prostate cancer (PC) of Gleason score 7 or higher at the initial prostate biopsy in a Korean cohort (http://acl.snu.ac.kr/PCRC/RISC/). In addition, KPCRC-HG was validated and compared with internet-based Western risk calculators in a validation cohort. Using a logistic regression model, KPCRC-HG was developed based on the data from 602 previously unscreened Korean men who underwent initial prostate biopsies. Using 2,313 cases in a validation cohort, KPCRC-HG was compared with the European Randomized Study of Screening for PC Risk Calculator for high-grade cancer (ERSPCRC-HG) and the Prostate Cancer Prevention Trial Risk Calculator 2.0 for high-grade cancer (PCPTRC-HG). The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots. PC was detected in 172 (28.6%) men, 120 (19.9%) of whom had PC of Gleason score 7 or higher. Independent predictors included prostate-specific antigen levels, digital rectal examination findings, transrectal ultrasound findings, and prostate volume. The AUC of the KPCRC-HG (0.84) was higher than that of the PCPTRC-HG (0.79, pexternal validation. Calibration plots also revealed better performance of KPCRC-HG and ERSPCRC-HG than that of PCPTRC-HG on external validation. At a cut-off of 5% for KPCRC-HG, 253 of the 2,313 men (11%) would not have been biopsied, and 14 of the 614 PC cases with Gleason score 7 or higher (2%) would not have been diagnosed. KPCRC-HG is the first web-based high-grade prostate cancer prediction model in Korea. It had higher predictive accuracy than PCPTRC-HG in a Korean population and showed similar performance with ERSPCRC-HG in a Korean population. This prediction model could help avoid unnecessary biopsy and reduce overdiagnosis and overtreatment in clinical settings.

  5. Prostate cancer risk prediction based on complete prostate cancer family history

    OpenAIRE

    Albright, Frederick; Stephenson, Robert A; Agarwal, Neeraj; Teerlink, Craig C; Lowrance, William T; Farnham, James M; Albright, Lisa A Cannon

    2014-01-01

    Background Prostate cancer (PC) relative risks (RRs) are typically estimated based on status of close relatives or presence of any affected relatives. This study provides RR estimates using extensive and specific PC family history. Methods A retrospective population-based study was undertaken to estimate RRs for PC based on complete family history of PC. A total of 635,443 males, all with ancestral genealogy data, were analyzed. RRs for PC were determined based upon PC rates estimated from ma...

  6. Prediction of individual genetic risk to prostate cancer using a polygenic score

    DEFF Research Database (Denmark)

    Szulkin, Robert; Whitington, Thomas; Eklund, Martin

    2015-01-01

    BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate ca...

  7. Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

    2018-03-01

    Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p breast cancer detected in the next subsequent mammography screening.

  8. Risk factors and a prediction model for lower limb lymphedema following lymphadenectomy in gynecologic cancer: a hospital-based retrospective cohort study.

    Science.gov (United States)

    Kuroda, Kenji; Yamamoto, Yasuhiro; Yanagisawa, Manami; Kawata, Akira; Akiba, Naoya; Suzuki, Kensuke; Naritaka, Kazutoshi

    2017-07-25

    Lower limb lymphedema (LLL) is a chronic and incapacitating condition afflicting patients who undergo lymphadenectomy for gynecologic cancer. This study aimed to identify risk factors for LLL and to develop a prediction model for its occurrence. Pelvic lymphadenectomy (PLA) with or without para-aortic lymphadenectomy (PALA) was performed on 366 patients with gynecologic malignancies at Yaizu City Hospital between April 2002 and July 2014; we retrospectively analyzed 264 eligible patients. The intervals between surgery and diagnosis of LLL were calculated; the prevalence and risk factors were evaluated using the Kaplan-Meier and Cox proportional hazards methods. We developed a prediction model with which patients were scored and classified as low-risk or high-risk. The cumulative incidence of LLL was 23.1% at 1 year, 32.8% at 3 years, and 47.7% at 10 years post-surgery. LLL developed after a median 13.5 months. Using regression analysis, body mass index (BMI) ≥25 kg/m 2 (hazard ratio [HR], 1.616; 95% confidence interval [CI], 1.030-2.535), PLA + PALA (HR, 2.323; 95% CI, 1.126-4.794), postoperative radiation therapy (HR, 2.469; 95% CI, 1.148-5.310), and lymphocyst formation (HR, 1.718; 95% CI, 1.120-2.635) were found to be independently associated with LLL; age, type of cancer, number of lymph nodes, retroperitoneal suture, chemotherapy, lymph node metastasis, herbal medicine, self-management education, or infection were not associated with LLL. The predictive score was based on the 4 associated variables; patients were classified as high-risk (scores 3-6) and low-risk (scores 0-2). LLL incidence was significantly greater in the high-risk group than in the low-risk group (HR, 2.19; 95% CI, 1.440-3.324). The cumulative incidence at 5 years was 52.1% [95% CI, 42.9-62.1%] for the high-risk group and 28.9% [95% CI, 21.1-38.7%] for the low-risk group. The area under the receiver operator characteristics curve for the prediction model was 0.631 at 1 year, 0

  9. A mathematical prediction model incorporating molecular subtype for risk of non-sentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients: a retrospective analysis and nomogram development.

    Science.gov (United States)

    Wang, Na-Na; Yang, Zheng-Jun; Wang, Xue; Chen, Li-Xuan; Zhao, Hong-Meng; Cao, Wen-Feng; Zhang, Bin

    2018-04-25

    Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P model based on the results of multivariate analysis was established to predict the risk of non

  10. Lung cancer risk of airborne particles for Italian population

    Energy Technology Data Exchange (ETDEWEB)

    Buonanno, G., E-mail: buonanno@unicas.it [Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via Di Biasio 43, 03043 Cassino, FR (Italy); International Laboratory for Air Quality and Health, Queensland University of Technology, 2 George Street 2, 4001 Brisbane, Qld. (Australia); Giovinco, G., E-mail: giovinco@unicas.it [Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via Di Biasio 43, 03043 Cassino, FR (Italy); Morawska, L., E-mail: morawska@qut.edu.au [International Laboratory for Air Quality and Health, Queensland University of Technology, 2 George Street 2, 4001 Brisbane, Qld. (Australia); Stabile, L., E-mail: stabile@unicas.it [Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via Di Biasio 43, 03043 Cassino, FR (Italy)

    2015-10-15

    Airborne particles, including both ultrafine and supermicrometric particles, contain various carcinogens. Exposure and risk-assessment studies regularly use particle mass concentration as dosimetry parameter, therefore neglecting the potential impact of ultrafine particles due to their negligible mass compared to supermicrometric particles. The main purpose of this study was the characterization of lung cancer risk due to exposure to polycyclic aromatic hydrocarbons and some heavy metals associated with particle inhalation by Italian non-smoking people. A risk-assessment scheme, modified from an existing risk model, was applied to estimate the cancer risk contribution from both ultrafine and supermicrometric particles. Exposure assessment was carried out on the basis of particle number distributions measured in 25 smoke-free microenvironments in Italy. The predicted lung cancer risk was then compared to the cancer incidence rate in Italy to assess the number of lung cancer cases attributed to airborne particle inhalation, which represents one of the main causes of lung cancer, apart from smoking. Ultrafine particles are associated with a much higher risk than supermicrometric particles, and the modified risk-assessment scheme provided a more accurate estimate than the conventional scheme. Great attention has to be paid to indoor microenvironments and, in particular, to cooking and eating times, which represent the major contributors to lung cancer incidence in the Italian population. The modified risk assessment scheme can serve as a tool for assessing environmental quality, as well as setting up exposure standards for particulate matter. - Highlights: • Lung cancer risk for non-smoking Italian population due to particle inhalation. • The average lung cancer risk for Italian population is equal to 1.90×10{sup −2}. • Ultrafine particle is the aerosol metric mostly contributing to lung cancer risk. • B(a)P is the main (particle-bounded) compound

  11. Lung cancer risk of airborne particles for Italian population

    International Nuclear Information System (INIS)

    Buonanno, G.; Giovinco, G.; Morawska, L.; Stabile, L.

    2015-01-01

    Airborne particles, including both ultrafine and supermicrometric particles, contain various carcinogens. Exposure and risk-assessment studies regularly use particle mass concentration as dosimetry parameter, therefore neglecting the potential impact of ultrafine particles due to their negligible mass compared to supermicrometric particles. The main purpose of this study was the characterization of lung cancer risk due to exposure to polycyclic aromatic hydrocarbons and some heavy metals associated with particle inhalation by Italian non-smoking people. A risk-assessment scheme, modified from an existing risk model, was applied to estimate the cancer risk contribution from both ultrafine and supermicrometric particles. Exposure assessment was carried out on the basis of particle number distributions measured in 25 smoke-free microenvironments in Italy. The predicted lung cancer risk was then compared to the cancer incidence rate in Italy to assess the number of lung cancer cases attributed to airborne particle inhalation, which represents one of the main causes of lung cancer, apart from smoking. Ultrafine particles are associated with a much higher risk than supermicrometric particles, and the modified risk-assessment scheme provided a more accurate estimate than the conventional scheme. Great attention has to be paid to indoor microenvironments and, in particular, to cooking and eating times, which represent the major contributors to lung cancer incidence in the Italian population. The modified risk assessment scheme can serve as a tool for assessing environmental quality, as well as setting up exposure standards for particulate matter. - Highlights: • Lung cancer risk for non-smoking Italian population due to particle inhalation. • The average lung cancer risk for Italian population is equal to 1.90×10 −2 . • Ultrafine particle is the aerosol metric mostly contributing to lung cancer risk. • B(a)P is the main (particle-bounded) compound contributing

  12. A new approach to reduce uncertainties in space radiation cancer risk predictions.

    Directory of Open Access Journals (Sweden)

    Francis A Cucinotta

    Full Text Available The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF to the dose and dose-rate reduction effectiveness factor (DDREF parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBEmax, I developed an alternate QF model, denoted QFγAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy. The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL for space missions show a reduction of about 40% (CL∼50% using the QFγAcute model compared the QFs based on RBEmax and about 25% (CL∼35% compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.

  13. Living in the context of poverty and trajectories of breast cancer worry, knowledge, and perceived risk after a breast cancer risk education session.

    Science.gov (United States)

    Bartle-Haring, Suzanne

    2010-01-01

    The purpose of this paper was to demonstrate how living in neighborhoods with high levels of poverty (while controlling for personal income) impacts personal characteristics, which in turn impacts retention of breast cancer risk knowledge and changes in worry and perceived risk. The data from this project come from a larger, National Cancer Institute-funded study that included a pretest, a breast cancer risk education session, a posttest, the option of an individualized risk assessment via the Gail Model and three follow-up phone calls over the next 9 months. The percent of individuals living below poverty in the community in which the participant resided was predictive of the personal characteristics assessed, and these characteristics were predictive of changes in breast cancer worry and knowledge across time. Differentiation of self and monitoring, two of the individual characteristics that seem to allow people to process and use information to make "rational" decisions about health care, seem to be impacted by the necessity for adaptation to a culture of poverty. Thus, as a health care community, we need to tailor our messages and our recommendations with an understanding of the complex intersection of poverty and health care decision making. Copyright © 2010 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

  14. TGFbeta1 (Leu10Pro), p53 (Arg72Pro) can predict for increased risk for breast cancer in south Indian women and TGFbeta1 Pro (Leu10Pro) allele predicts response to neo-adjuvant chemo-radiotherapy.

    Science.gov (United States)

    Rajkumar, Thangarajan; Samson, Mani; Rama, Ranganathan; Sridevi, Veluswami; Mahji, Urmila; Swaminathan, Rajaraman; Nancy, Nirmala K

    2008-11-01

    The breast cancer incidence has been increasing in the south Indian women. A case (n=250)-control (n=500) study was undertaken to investigate the role of Single Nucleotide Polymorphisms (SNP's) in GSTM1 (Present/Null); GSTP1 (Ile105Val), p53 (Arg72Pro), TGFbeta1 (Leu10Pro), c-erbB2 (Ile655Val), and GSTT1 (Null/Present) in breast cancer. In addition, the value of the SNP's in predicting primary tumor's pathologic response following neo-adjuvant chemo-radiotherapy was assessed. Genotyping was done using PCR (GSTM1, GSTT1), Taqman Allelic discrimination assay (GSTP1, c-erbB2) and PCR-CTPP (p53 and TGFbeta1). None of the gene SNP's studied were associated with a statistically significant increased risk for the breast cancer. However, combined analysis of the SNP's showed that p53 (Arg/Arg and Arg/Pro) with TGFbeta1 (Pro/Pro and Leu/Pro) were associated with greater than 2 fold increased risk for breast cancer in Univariate (P=0.01) and Multivariate (P=0.003) analysis. There was no statistically significant association for the GST family members with the breast cancer risk. TGFbeta1 (Pro/Pro) allele was found to predict complete pathologic response in the primary tumour following neo-adjuvant chemo-radiotherapy (OR=6.53 and 10.53 in Univariate and Multivariate analysis respectively) (P=0.004) and was independent of stage. This study suggests that SNP's can help predict breast cancer risk in south Indian women and that TGFbeta1 (Pro/Pro) allele is associated with a better pCR in the primary tumour.

  15. Non-genetic risk factors and predicting efficacy for docetaxel--drug-induced liver injury among metastatic breast cancer patients.

    Science.gov (United States)

    Wang, Zheng; Liang, Xu; Yu, Jing; Zheng, Xiaohui; Zhu, Yulin; Yan, Ying; Dong, Ningning; Di, Lijun; Song, Guohong; Zhou, Xinna; Wang, Xiaoli; Yang, Huabing; Ren, Jun; Lyerly, Herbert Kim

    2012-08-01

    Docetaxel has been chosen as one of the most popular anticancer drugs in the treatment of breast cancer for more than a decade. There is increasingly awareness for the occurrence of docetaxel and/or docetaxel-drug-induced liver injury (DILI), although the underlying mechanism of occurrence and its risk factors remain unclear. We conducted a retrospective cohort study to identify non-genetic risk factors for docetaxel-DILI among 647 metastasis breast cancer patients treated with docetaxel-containing regimens. Sixty-seven (10.36%) patients were diagnosed as docetaxel-DILI. By logistic regression analysis, premenopausal status (odds ratio [OR][95% confidence interval {CI}] = 2.24 [1.30-3.87]), past hepatitis B virus (HBV) infections (OR [95% CI] = 4.23 [1.57-11.42]), liver metastasis (OR [95% CI] = 3.70 [2.16-6.34]). The predominant occurrence of DILI was seen in groups with docetaxel combination regimens. (OR [95% CI] = 2.66 [1.59-4.55]). The potential increasing occurrence of docetaxel-DILI was associated with multiple risk factors in an exposure-response manner (P < 0.001), and patients with more than three risk factors would be exposed to a 36.61-fold risk of DILI (95% CI = 10.18-131.62). Further analysis by the risk score and area under the receiver-operator characteristic curve (AUC) showed that those four factors contributed to an AUC of 0.7536 (95% CI = 0.70-0.81), with a predictive sensitivity of 74.63% and specificity of 65.17%. Docetaxel-DILI with a relatively higher incidence should be addressed among metastatic breast cancer patients. Four predominant risk factors, including premenopausal status, past HBV infection, liver metastasis, and docetaxel combination regimens, were potential predicators for DILI. © 2012 Journal of Gastroenterology and Hepatology Foundation and Blackwell Publishing Asia Pty Ltd.

  16. Indoor Tanning and the MC1R Genotype: Risk Prediction for Basal Cell Carcinoma Risk in Young People

    OpenAIRE

    Molinaro, Annette M.; Ferrucci, Leah M.; Cartmel, Brenda; Loftfield, Erikka; Leffell, David J.; Bale, Allen E.; Mayne, Susan T.

    2015-01-01

    Basal cell carcinoma (BCC) incidence is increasing, particularly in young people, and can be associated with significant morbidity and treatment costs. To identify young individuals at risk of BCC, we assessed existing melanoma or overall skin cancer risk prediction models and built a novel risk prediction model, with a focus on indoor tanning and the melanocortin 1 receptor gene, MC1R. We evaluated logistic regression models among 759 non-Hispanic whites from a case-control study of patients...

  17. Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

    NARCIS (Netherlands)

    Wille, M.M.W.; Riel, S.J. van; Saghir, Z.; Dirksen, A.; Pedersen, J.H.; Jacobs, C.; Thomsen, L.H.u.; Scholten, E.T.; Skovgaard, L.T.; Ginneken, B. van

    2015-01-01

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models.From the DLCST database, 1,152

  18. MicroRNA classifier and nomogram for metastasis prediction in colon cancer.

    Science.gov (United States)

    Goossens-Beumer, Inès J; Derr, Remco S; Buermans, Henk P J; Goeman, Jelle J; Böhringer, Stefan; Morreau, Hans; Nitsche, Ulrich; Janssen, Klaus-Peter; van de Velde, Cornelis J H; Kuppen, Peter J K

    2015-01-01

    Colon cancer prognosis and treatment are currently based on a classification system still showing large heterogeneity in clinical outcome, especially in TNM stages II and III. Prognostic biomarkers for metastasis risk are warranted as development of distant recurrent disease mainly accounts for the high lethality rates of colon cancer. miRNAs have been proposed as potential biomarkers for cancer. Furthermore, a verified standard for normalization of the amount of input material in PCR-based relative quantification of miRNA expression is lacking. A selection of frozen tumor specimens from two independent patient cohorts with TNM stage II-III microsatellite stable primary adenocarcinomas was used for laser capture microdissection. Next-generation sequencing was performed on small RNAs isolated from colorectal tumors from the Dutch cohort (N = 50). Differential expression analysis, comparing in metastasized and nonmetastasized tumors, identified prognostic miRNAs. Validation was performed on colon tumors from the German cohort (N = 43) using quantitative PCR (qPCR). miR25-3p and miR339-5p were identified and validated as independent prognostic markers and used to construct a multivariate nomogram for metastasis risk prediction. The nomogram showed good probability prediction in validation. In addition, we recommend combination of miR16-5p and miR26a-5p as standard for normalization in qPCR of colon cancer tissue-derived miRNA expression. In this international study, we identified and validated a miRNA classifier in primary cancers, and propose a nomogram capable of predicting metastasis risk in microsatellite stable TNM stage II-III colon cancer. In conjunction with TNM staging, by means of a nomogram, this miRNA classifier may allow for personalized treatment decisions based on individual tumor characteristics. ©2014 American Association for Cancer Research.

  19. A Novel Risk prediction Model for Patients with Combined Hepatocellular-Cholangiocarcinoma.

    Science.gov (United States)

    Tian, Meng-Xin; He, Wen-Jun; Liu, Wei-Ren; Yin, Jia-Cheng; Jin, Lei; Tang, Zheng; Jiang, Xi-Fei; Wang, Han; Zhou, Pei-Yun; Tao, Chen-Yang; Ding, Zhen-Bin; Peng, Yuan-Fei; Dai, Zhi; Qiu, Shuang-Jian; Zhou, Jian; Fan, Jia; Shi, Ying-Hong

    2018-01-01

    Backgrounds: Regarding the difficulty of CHC diagnosis and potential adverse outcomes or misuse of clinical therapies, an increasing number of patients have undergone liver transplantation, transcatheter arterial chemoembolization (TACE) or other treatments. Objective: To construct a convenient and reliable risk prediction model for identifying high-risk individuals with combined hepatocellular-cholangiocarcinoma (CHC). Methods: 3369 patients who underwent surgical resection for liver cancer at Zhongshan Hospital were enrolled in this study. The epidemiological and clinical characteristics of the patients were collected at the time of tumor diagnosis. Variables ( P model discrimination. Calibration was performed using the Hosmer-Lemeshow test and a calibration curve. Internal validation was performed using a bootstrapping approach. Results: Among the entire study population, 250 patients (7.42%) were pathologically defined with CHC. Age, HBcAb, red blood cells (RBC), blood urea nitrogen (BUN), AFP, CEA and portal vein tumor thrombus (PVTT) were included in the final risk prediction model (area under the curve, 0.69; 95% confidence interval, 0.51-0.77). Bootstrapping validation presented negligible optimism. When the risk threshold of the prediction model was set at 20%, 2.73% of the patients diagnosed with liver cancer would be diagnosed definitely, which could identify CHC patients with 12.40% sensitivity, 98.04% specificity, and a positive predictive value of 33.70%. Conclusions: Herein, the study established a risk prediction model which incorporates the clinical risk predictors and CT/MRI-presented PVTT status that could be adopted to facilitate the diagnosis of CHC patients preoperatively.

  20. Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer.

    Directory of Open Access Journals (Sweden)

    Jianfei Fu

    Full Text Available The features related to the prognosis of patients with mucinous breast cancer (MBC remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes.The Surveillance, Epidemiology, and End Results (SEER database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC.There were 136569 (97.82% infiltrative ductal cancer (IDC patients and 3042 (2.18% MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively than patients with IDC (91.44 and 85.48%, respectively. Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816. Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789 than the traditional TNM system (C-index = 0.704, P< 0.001.Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in clinical practice. The competing risk

  1. The Cost-Effectiveness of High-Risk Lung Cancer Screening and Drivers of Program Efficiency.

    Science.gov (United States)

    Cressman, Sonya; Peacock, Stuart J; Tammemägi, Martin C; Evans, William K; Leighl, Natasha B; Goffin, John R; Tremblay, Alain; Liu, Geoffrey; Manos, Daria; MacEachern, Paul; Bhatia, Rick; Puksa, Serge; Nicholas, Garth; McWilliams, Annette; Mayo, John R; Yee, John; English, John C; Pataky, Reka; McPherson, Emily; Atkar-Khattra, Sukhinder; Johnston, Michael R; Schmidt, Heidi; Shepherd, Frances A; Soghrati, Kam; Amjadi, Kayvan; Burrowes, Paul; Couture, Christian; Sekhon, Harmanjatinder S; Yasufuku, Kazuhiro; Goss, Glenwood; Ionescu, Diana N; Hwang, David M; Martel, Simon; Sin, Don D; Tan, Wan C; Urbanski, Stefan; Xu, Zhaolin; Tsao, Ming-Sound; Lam, Stephen

    2017-08-01

    Lung cancer risk prediction models have the potential to make programs more affordable; however, the economic evidence is limited. Participants in the National Lung Cancer Screening Trial (NLST) were retrospectively identified with the risk prediction tool developed from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. The high-risk subgroup was assessed for lung cancer incidence and demographic characteristics compared with those in the low-risk subgroup and the Pan-Canadian Early Detection of Lung Cancer Study (PanCan), which is an observational study that was high-risk-selected in Canada. A comparison of high-risk screening versus standard care was made with a decision-analytic model using data from the NLST with Canadian cost data from screening and treatment in the PanCan study. Probabilistic and deterministic sensitivity analyses were undertaken to assess uncertainty and identify drivers of program efficiency. Use of the risk prediction tool developed from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial with a threshold set at 2% over 6 years would have reduced the number of individuals who needed to be screened in the NLST by 81%. High-risk screening participants in the NLST had more adverse demographic characteristics than their counterparts in the PanCan study. High-risk screening would cost $20,724 (in 2015 Canadian dollars) per quality-adjusted life-year gained and would be considered cost-effective at a willingness-to-pay threshold of $100,000 in Canadian dollars per quality-adjusted life-year gained with a probability of 0.62. Cost-effectiveness was driven primarily by non-lung cancer outcomes. Higher noncurative drug costs or current costs for immunotherapy and targeted therapies in the United States would render lung cancer screening a cost-saving intervention. Non-lung cancer outcomes drive screening efficiency in diverse, tobacco-exposed populations. Use of risk selection can reduce the budget impact, and

  2. Development and external multicenter validation of Chinese Prostate Cancer Consortium prostate cancer risk calculator for initial prostate biopsy.

    Science.gov (United States)

    Chen, Rui; Xie, Liping; Xue, Wei; Ye, Zhangqun; Ma, Lulin; Gao, Xu; Ren, Shancheng; Wang, Fubo; Zhao, Lin; Xu, Chuanliang; Sun, Yinghao

    2016-09-01

    Substantial differences exist in the relationship of prostate cancer (PCa) detection rate and prostate-specific antigen (PSA) level between Western and Asian populations. Classic Western risk calculators, European Randomized Study for Screening of Prostate Cancer Risk Calculator, and Prostate Cancer Prevention Trial Risk Calculator, were shown to be not applicable in Asian populations. We aimed to develop and validate a risk calculator for predicting the probability of PCa and high-grade PCa (defined as Gleason Score sum 7 or higher) at initial prostate biopsy in Chinese men. Urology outpatients who underwent initial prostate biopsy according to the inclusion criteria were included. The multivariate logistic regression-based Chinese Prostate Cancer Consortium Risk Calculator (CPCC-RC) was constructed with cases from 2 hospitals in Shanghai. Discriminative ability, calibration and decision curve analysis were externally validated in 3 CPCC member hospitals. Of the 1,835 patients involved, PCa was identified in 338/924 (36.6%) and 294/911 (32.3%) men in the development and validation cohort, respectively. Multivariate logistic regression analyses showed that 5 predictors (age, logPSA, logPV, free PSA ratio, and digital rectal examination) were associated with PCa (Model 1) or high-grade PCa (Model 2), respectively. The area under the curve of Model 1 and Model 2 was 0.801 (95% CI: 0.771-0.831) and 0.826 (95% CI: 0.796-0.857), respectively. Both models illustrated good calibration and substantial improvement in decision curve analyses than any single predictors at all threshold probabilities. Higher predicting accuracy, better calibration, and greater clinical benefit were achieved by CPCC-RC, compared with European Randomized Study for Screening of Prostate Cancer Risk Calculator and Prostate Cancer Prevention Trial Risk Calculator in predicting PCa. CPCC-RC performed well in discrimination and calibration and decision curve analysis in external validation compared

  3. Does folic acid supplementation prevent or promote colorectal cancer? Results from model-based predictions.

    Science.gov (United States)

    Luebeck, E Georg; Moolgavkar, Suresh H; Liu, Amy Y; Boynton, Alanna; Ulrich, Cornelia M

    2008-06-01

    Folate is essential for nucleotide synthesis, DNA replication, and methyl group supply. Low-folate status has been associated with increased risks of several cancer types, suggesting a chemopreventive role of folate. However, recent findings on giving folic acid to patients with a history of colorectal polyps raise concerns about the efficacy and safety of folate supplementation and the long-term health effects of folate fortification. Results suggest that undetected precursor lesions may progress under folic acid supplementation, consistent with the role of folate role in nucleotide synthesis and cell proliferation. To better understand the possible trade-offs between the protective effects due to decreased mutation rates and possibly concomitant detrimental effects due to increased cell proliferation of folic acid, we used a biologically based mathematical model of colorectal carcinogenesis. We predict changes in cancer risk based on timing of treatment start and the potential effect of folic acid on cell proliferation and mutation rates. Changes in colorectal cancer risk in response to folic acid supplementation are likely a complex function of treatment start, duration, and effect on cell proliferation and mutations rates. Predicted colorectal cancer incidence rates under supplementation are mostly higher than rates without folic acid supplementation unless supplementation is initiated early in life (before age 20 years). To the extent to which this model predicts reality, it indicates that the effect on cancer risk when starting folic acid supplementation late in life is small, yet mostly detrimental. Experimental studies are needed to provide direct evidence for this dual role of folate in colorectal cancer and to validate and improve the model predictions.

  4. Association analysis identifies 65 new breast cancer risk loci.

    Science.gov (United States)

    Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D; Qing Chen, Xiao; Fachal, Laura; McCue, Karen; McCart Reed, Amy E; Ghoussaini, Maya; Carroll, Jason S; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Aronson, Kristan J; Arun, Banu; Auer, Paul L; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D; Castelao, Jose E; Chan, Tsun L; David Cheng, Ting-Yuan; Seng Chia, Kee; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L; Collée, Margriet; Conroy, Don M; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Doheny, Kimberly F; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M; Ekici, Arif B; Eliassen, A Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M; García-Sáenz, José A; Gaudet, Mia M; Georgoulias, Vassilios; Giles, Graham G; Glendon, Gord; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Grenaker Alnæs, Grethe I; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Robert N; Hopper, John L; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Kosma, Veli-Matti; Kristensen, Vessela N; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Le Marchand, Loic; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Neng Lee, Chuen; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P; Ma, Edmond S K; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Taib, Nur Aishah Mohd; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F; Noh, Dong-Young; Nordestgaard, Børge G; Norman, Aaron; Olopade, Olufunmilayo I; Olson, Janet E; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V Shane; Park, Sue K; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofyeva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J T; Saloustros, Emmanouil; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schmutzler, Rita K; Schneeweiss, Andreas; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E; Shrubsole, Martha J; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A; Tengström, Maria; Teo, Soo H; Beth Terry, Mary; Tessier, Daniel C; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-Chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van der Kolk, Lizet; van der Luijt, Rob B; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R; Wendt, Camilla; Whittemore, Alice S; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R; Har Yip, Cheng; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R; Antoniou, Antonis C; Droit, Arnaud; Andrulis, Irene L; Amos, Christopher I; Couch, Fergus J; Pharoah, Paul D P; Chang-Claude, Jenny; Hall, Per; Hunter, David J; Milne, Roger L; García-Closas, Montserrat; Schmidt, Marjanka K; Chanock, Stephen J; Dunning, Alison M; Edwards, Stacey L; Bader, Gary D; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F

    2017-11-02

    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10 -8 . The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

  5. Adult body mass index and risk of ovarian cancer by subtype

    DEFF Research Database (Denmark)

    Dixon, Suzanne C; Nagle, Christina M; Thrift, Aaron P

    2016-01-01

    BACKGROUND: Observational studies have reported a positive association between body mass index (BMI) and ovarian cancer risk. However, questions remain as to whether this represents a causal effect, or holds for all histological subtypes. The lack of association observed for serous cancers may......, for instance, be due to disease-associated weight loss. Mendelian randomization (MR) uses genetic markers as proxies for risk factors to overcome limitations of observational studies. We used MR to elucidate the relationship between BMI and ovarian cancer, hypothesizing that genetically predicted BMI would...... be associated with increased risk of non-high grade serous ovarian cancers (non-HGSC) but not HGSC. METHODS: We pooled data from 39 studies (14 047 cases, 23 003 controls) in the Ovarian Cancer Association Consortium. We constructed a weighted genetic risk score (GRS, partial F-statistic = 172), summing alleles...

  6. Physical activity and the risk of colorectal cancer in Lynch syndrome.

    Science.gov (United States)

    Dashti, S Ghazaleh; Win, Aung Ko; Hardikar, Sheetal S; Glombicki, Stephen E; Mallenahalli, Sheila; Thirumurthi, Selvi; Peterson, Susan K; You, Y Nancy; Buchanan, Daniel D; Figueiredo, Jane C; Campbell, Peter T; Gallinger, Steven; Newcomb, Polly A; Potter, John D; Lindor, Noralane M; Le Marchand, Loic; Haile, Robert W; Hopper, John L; Jenkins, Mark A; Basen-Engquist, Karen M; Lynch, Patrick M; Pande, Mala

    2018-06-14

    Greater physical activity is associated with a decrease in risk of colorectal cancer for the general population; however, little is known about its relationship with colorectal cancer risk for people with Lynch syndrome, carriers of inherited pathogenic mutations in genes affecting DNA mismatch repair (MMR). We studied a cohort of 2,042 MMR gene mutations carriers (n=807, diagnosed with colorectal cancer), from the Colon Cancer Family Registry. Self-reported physical activity in three age-periods (20-29, 30-49, and ≥50 years) was summarized as average metabolic equivalent of task hours per week (MET-h/week) during the age-period of cancer diagnosis or censoring (near-term exposure), and across all age-periods preceding cancer diagnosis or censoring (long-term exposure). Weighted Cox regression was used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) for the association between physical activity and colorectal cancer risk. Near-term physical activity was associated with a small reduction in the risk of colorectal cancer (HR ≥35 vs. Lynch syndrome, however, further confirmation is warranted. The potential modifying effect of physical activity on colorectal cancer risk for people with Lynch syndrome could be useful for risk prediction and support counseling advice for lifestyle modification to reduce cancer risk. This article is protected by copyright. All rights reserved. © 2018 UICC.

  7. Unilateral Prostate Cancer Cannot be Accurately Predicted in Low-Risk Patients

    International Nuclear Information System (INIS)

    Isbarn, Hendrik; Karakiewicz, Pierre I.; Vogel, Susanne

    2010-01-01

    Purpose: Hemiablative therapy (HAT) is increasing in popularity for treatment of patients with low-risk prostate cancer (PCa). The validity of this therapeutic modality, which exclusively treats PCa within a single prostate lobe, rests on accurate staging. We tested the accuracy of unilaterally unremarkable biopsy findings in cases of low-risk PCa patients who are potential candidates for HAT. Methods and Materials: The study population consisted of 243 men with clinical stage ≤T2a, a prostate-specific antigen (PSA) concentration of <10 ng/ml, a biopsy-proven Gleason sum of ≤6, and a maximum of 2 ipsilateral positive biopsy results out of 10 or more cores. All men underwent a radical prostatectomy, and pathology stage was used as the gold standard. Univariable and multivariable logistic regression models were tested for significant predictors of unilateral, organ-confined PCa. These predictors consisted of PSA, %fPSA (defined as the quotient of free [uncomplexed] PSA divided by the total PSA), clinical stage (T2a vs. T1c), gland volume, and number of positive biopsy cores (2 vs. 1). Results: Despite unilateral stage at biopsy, bilateral or even non-organ-confined PCa was reported in 64% of all patients. In multivariable analyses, no variable could clearly and independently predict the presence of unilateral PCa. This was reflected in an overall accuracy of 58% (95% confidence interval, 50.6-65.8%). Conclusions: Two-thirds of patients with unilateral low-risk PCa, confirmed by clinical stage and biopsy findings, have bilateral or non-organ-confined PCa at radical prostatectomy. This alarming finding questions the safety and validity of HAT.

  8. Insignificant disease among men with intermediate-risk prostate cancer.

    Science.gov (United States)

    Hong, Sung Kyu; Vertosick, Emily; Sjoberg, Daniel D; Scardino, Peter T; Eastham, James A

    2014-12-01

    A paucity of data exists on the insignificant disease potentially suitable for active surveillance (AS) among men with intermediate-risk prostate cancer (PCa). We tried to identify pathologically insignificant disease and its preoperative predictors in men who underwent radical prostatectomy (RP) for intermediate-risk PCa. We analyzed data of 1,630 men who underwent RP for intermediate-risk disease. Total tumor volume (TTV) data were available in 332 men. We examined factors associated with classically defined pathologically insignificant cancer (organ-confined disease with TTV ≤0.5 ml with no Gleason pattern 4 or 5) and pathologically favorable cancer (organ-confined disease with no Gleason pattern 4 or 5) potentially suitable for AS. Decision curve analysis was used to assess clinical utility of a multivariable model including preoperative variables for predicting pathologically unfavorable cancer. In the entire cohort, 221 of 1,630 (13.6 %) total patients had pathologically favorable cancer. Among 332 patients with TTV data available, 26 (7.8 %) had classically defined pathologically insignificant cancer. Between threshold probabilities of 20 and 40 %, decision curve analysis demonstrated that using multivariable model to identify AS candidates would not provide any benefit over simply treating all men who have intermediate-risk disease with RP. Although a minority of patients with intermediate-risk disease may harbor pathologically favorable or insignificant cancer, currently available conventional tools are not sufficiently able to identify those patients.

  9. Prostate-specific antigen and long-term prediction of prostate cancer incidence and mortality in the general population

    DEFF Research Database (Denmark)

    Ørsted, David Dynnes; Nordestgaard, Børge G; Jensen, Gorm B

    2012-01-01

    It is largely unknown whether prostate-specific antigen (PSA) level at first date of testing predicts long-term risk of prostate cancer (PCa) incidence and mortality in the general population.......It is largely unknown whether prostate-specific antigen (PSA) level at first date of testing predicts long-term risk of prostate cancer (PCa) incidence and mortality in the general population....

  10. Predicting Scheduling and Attending for an Oral Cancer Examination

    Science.gov (United States)

    Shepperd, James A.; Emanuel, Amber S.; Howell, Jennifer L.; Logan, Henrietta L.

    2015-01-01

    Background Oral and pharyngeal cancer is highly treatable if diagnosed early, yet late diagnosis is commonplace apparently because of delays in undergoing an oral cancer examination. Purpose We explored predictors of scheduling and attending an oral cancer examination among a sample of Black and White men who were at high risk for oral cancer because they smoked. Methods During an in-person interview, participants (N = 315) from rural Florida learned about oral and pharyngeal cancer, completed survey measures, and were offered a free examination in the next week. Later, participants received a follow-up phone call to explore why they did or did not attend their examination. Results Consistent with the notion that scheduling and attending an oral cancer exam represent distinct decisions, we found that the two outcomes had different predictors. Defensive avoidance and exam efficacy predicted scheduling an examination; exam efficacy and having coping resources, time, and transportation predicted attending the examination. Open-ended responses revealed that the dominant reasons participants offered for missing a scheduled examination was conflicting obligations, forgetting, and confusion or misunderstanding about the examination. Conclusions The results suggest interventions to increase scheduling and attending an oral cancer examination. PMID:26152644

  11. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. The influence of family history on cognitive heuristics, risk perceptions, and prostate cancer screening behavior.

    Science.gov (United States)

    McDowell, Michelle E; Occhipinti, Stefano; Chambers, Suzanne K

    2013-11-01

    To examine how family history of prostate cancer, risk perceptions, and heuristic decision strategies influence prostate cancer screening behavior. Men with a first-degree family history of prostate cancer (FDRs; n = 207) and men without a family history (PM; n = 239) completed a Computer Assisted Telephone Interview (CATI) examining prostate cancer risk perceptions, PSA testing behaviors, perceptions of similarity to the typical man who gets prostate cancer (representativeness heuristic), and availability of information about prostate cancer (availability heuristic). A path model explored family history as influencing the availability of information about prostate cancer (number of acquaintances with prostate cancer and number of recent discussions about prostate cancer) to mediate judgments of risk and to predict PSA testing behaviors and family history as a moderator of the relationship between representativeness (perceived similarity) and risk perceptions. FDRs reported greater risk perceptions and a greater number of PSA tests than did PM. Risk perceptions predicted increased PSA testing only in path models and was significant only for PM in multi-Group SEM analyses. Family history moderated the relationship between similarity perceptions and risk perceptions such that the relationship between these variables was significant only for FDRs. Recent discussions about prostate cancer mediated the relationships between family history and risk perceptions, and the number of acquaintances men knew with prostate cancer mediated the relationship between family history and PSA testing behavior. Family history interacts with the individuals' broader social environment to influence risk perceptions and screening behavior. Research into how risk perceptions develop and what primes behavior change is crucial to underpin psychological or public health intervention that seeks to influence health decision making.

  13. Development and validation of risk models and molecular diagnostics to permit personalized management of cancer.

    Science.gov (United States)

    Pu, Xia; Ye, Yuanqing; Wu, Xifeng

    2014-01-01

    Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. © 2013 American Cancer Society.

  14. Assessing the Risk of Occult Cancer and 30-day Morbidity in Women Undergoing Risk-reducing Surgery: A Prospective Experience.

    Science.gov (United States)

    Bogani, Giorgio; Tagliabue, Elena; Signorelli, Mauro; Chiappa, Valentina; Carcangiu, Maria Luisa; Paolini, Biagio; Casarin, Jvan; Scaffa, Cono; Gennaro, Massimiliano; Martinelli, Fabio; Borghi, Chiara; Ditto, Antonino; Lorusso, Domenica; Raspagliesi, Francesco

    To investigate the incidence and predictive factors of 30-day surgery-related morbidity and occult precancerous and cancerous conditions for women undergoing risk-reducing surgery. A prospective study (Canadian Task Force classification II-1). A gynecologic oncology referral center. Breast-related cancer antigen (BRCA) mutation carriers and BRCAX patients (those with a significant family history of breast and ovarian cancer). Minimally invasive risk-reduction surgery. Overall, 85 women underwent risk-reducing surgery: 30 (35%) and 55 (65%) had hysterectomy plus bilateral salpingo-oophorectomy (BSO) and BSO alone, respectively. Overall, in 6 (7%) patients, the final pathology revealed unexpected cancer: 3 early-stage ovarian/fallopian tube cancers, 2 advanced-stage ovarian cancers (stage IIIA and IIIB), and 1 serous endometrial carcinoma. Additionally, 3 (3.6%) patients had incidental finding of serous tubal intraepithelial carcinoma. Four (4.7%) postoperative complications within 30 days from surgery were registered, including fever (n = 3) and postoperative ileus (n = 1); no severe (grade 3 or more) complications were observed. All complications were managed conservatively. The presence of occult cancer was the only factor predicting the development of postoperative complications (p = .02). Minimally invasive risk-reducing surgery is a safe and effective strategy to manage BRCA mutation carriers. Patients should benefit from an appropriate counseling about the high prevalence of undiagnosed cancers observed at the time of surgery. Copyright © 2017 AAGL. Published by Elsevier Inc. All rights reserved.

  15. Ovarian Cancer Risk Factors by Histologic Subtype: An Analysis From the Ovarian Cancer Cohort Consortium.

    Science.gov (United States)

    Wentzensen, Nicolas; Poole, Elizabeth M; Trabert, Britton; White, Emily; Arslan, Alan A; Patel, Alpa V; Setiawan, V Wendy; Visvanathan, Kala; Weiderpass, Elisabete; Adami, Hans-Olov; Black, Amanda; Bernstein, Leslie; Brinton, Louise A; Buring, Julie; Butler, Lesley M; Chamosa, Saioa; Clendenen, Tess V; Dossus, Laure; Fortner, Renee; Gapstur, Susan M; Gaudet, Mia M; Gram, Inger T; Hartge, Patricia; Hoffman-Bolton, Judith; Idahl, Annika; Jones, Michael; Kaaks, Rudolf; Kirsh, Victoria; Koh, Woon-Puay; Lacey, James V; Lee, I-Min; Lundin, Eva; Merritt, Melissa A; Onland-Moret, N Charlotte; Peters, Ulrike; Poynter, Jenny N; Rinaldi, Sabina; Robien, Kim; Rohan, Thomas; Sandler, Dale P; Schairer, Catherine; Schouten, Leo J; Sjöholm, Louise K; Sieri, Sabina; Swerdlow, Anthony; Tjonneland, Anna; Travis, Ruth; Trichopoulou, Antonia; van den Brandt, Piet A; Wilkens, Lynne; Wolk, Alicja; Yang, Hannah P; Zeleniuch-Jacquotte, Anne; Tworoger, Shelley S

    2016-08-20

    An understanding of the etiologic heterogeneity of ovarian cancer is important for improving prevention, early detection, and therapeutic approaches. We evaluated 14 hormonal, reproductive, and lifestyle factors by histologic subtype in the Ovarian Cancer Cohort Consortium (OC3). Among 1.3 million women from 21 studies, 5,584 invasive epithelial ovarian cancers were identified (3,378 serous, 606 endometrioid, 331 mucinous, 269 clear cell, 1,000 other). By using competing-risks Cox proportional hazards regression stratified by study and birth year and adjusted for age, parity, and oral contraceptive use, we assessed associations for all invasive cancers by histology. Heterogeneity was evaluated by likelihood ratio test. Most risk factors exhibited significant heterogeneity by histology. Higher parity was most strongly associated with endometrioid (relative risk [RR] per birth, 0.78; 95% CI, 0.74 to 0.83) and clear cell (RR, 0.68; 95% CI, 0.61 to 0.76) carcinomas (P value for heterogeneity [P-het] < .001). Similarly, age at menopause, endometriosis, and tubal ligation were only associated with endometrioid and clear cell tumors (P-het ≤ .01). Family history of breast cancer (P-het = .008) had modest heterogeneity. Smoking was associated with an increased risk of mucinous (RR per 20 pack-years, 1.26; 95% CI, 1.08 to 1.46) but a decreased risk of clear cell (RR, 0.72; 95% CI, 0.55 to 0.94) tumors (P-het = .004). Unsupervised clustering by risk factors separated endometrioid, clear cell, and low-grade serous carcinomas from high-grade serous and mucinous carcinomas. The heterogeneous associations of risk factors with ovarian cancer subtypes emphasize the importance of conducting etiologic studies by ovarian cancer subtypes. Most established risk factors were more strongly associated with nonserous carcinomas, which demonstrate challenges for risk prediction of serous cancers, the most fatal subtype. © 2016 by American Society of Clinical Oncology.

  16. Which risk models perform best in selecting ever-smokers for lung cancer screening?

    Science.gov (United States)

    A new analysis by scientists at NCI evaluates nine different individualized lung cancer risk prediction models based on their selections of ever-smokers for computed tomography (CT) lung cancer screening.

  17. Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction.

    Science.gov (United States)

    Zhao, Di; Weng, Chunhua

    2011-10-01

    In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

  18. Predicting Adverse Health Outcomes in Long-Term Survivors of a Childhood Cancer

    Directory of Open Access Journals (Sweden)

    Chaya S. Moskowitz

    2014-07-01

    Full Text Available More than 80% of children and young adults diagnosed with invasive cancer will survive five or more years beyond their cancer diagnosis. This population has an increased risk for serious illness- and treatment-related morbidity and premature mortality. A number of these adverse health outcomes, such as cardiovascular disease and some second primary neoplasms, either have modifiable risk factors or can be successfully treated if detected early. Absolute risk models that project a personalized risk of developing a health outcome can be useful in patient counseling, in designing intervention studies, in forming prevention strategies, and in deciding upon surveillance programs. Here, we review existing absolute risk prediction models that are directly applicable to survivors of a childhood cancer, discuss the concepts and interpretation of absolute risk models, and examine ways in which these models can be used applied in clinical practice and public health.

  19. Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment

    Energy Technology Data Exchange (ETDEWEB)

    Zheng, Bin, E-mail: zhengb@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Sumkin, Jules H., E-mail: jsumkin@mail.magee.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Zuley, Margarita L., E-mail: zuleyml@upmc.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Wang, Xingwei, E-mail: wangx6@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Klym, Amy H., E-mail: klymah@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Gur, David, E-mail: gurd@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States)

    2012-11-15

    To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 {+-} 0.030, 0.535 {+-} 0.036, 0.567 {+-} 0.031, and 0.719 {+-} 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 {+-} 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.

  20. Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment

    International Nuclear Information System (INIS)

    Zheng, Bin; Sumkin, Jules H.; Zuley, Margarita L.; Wang, Xingwei; Klym, Amy H.; Gur, David

    2012-01-01

    To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 ± 0.030, 0.535 ± 0.036, 0.567 ± 0.031, and 0.719 ± 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 ± 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.

  1. Risks of cancer - All sites

    International Nuclear Information System (INIS)

    Anon.

    1990-01-01

    This chapter describes the BEIR Committee's radiation risk models and the total risks of cancer following whole body exposure. This report focuses on the data from A-bomb survivors since this cohort contains persons of all ages at exposure. Because of large statistical uncertainties, it was not possible for the committee to provide risk estimates for cancers at all specific sites of interest. Estimates were made for risk of leukemia, breast cancer, thyroid cancer, and cancers of the respiratory and digestive systems. To obtain an estimate of the total risk of mortality from all cancers, the committee also modeled cancers other than those listed above as a group

  2. ["Screening" in special situations. Assessing predictive genetic screening for hereditary breast and colorectal cancer].

    Science.gov (United States)

    Jonas, Susanna; Wild, Claudia; Schamberger, Chantal

    2003-02-01

    The aim of this health technology assessment was to analyse the current scientific and genetic counselling on predictive genetic testing for hereditary breast and colorectal cancer. Predictive genetic testing will be available for several common diseases in the future and questions related to financial issues and quality standards will be raised. This report is based on a systematic/nonsystematic literature search in several databases (e.g. EmBase, Medline, Cochrane Library) and on a specific health technology assessment report (CCOHTA) and review (American Gastroenterological Ass.), respectively. Laboratory test methods, early detection methods and the benefit from prophylactic interventions were analysed and social consequences interpreted. Breast and colorectal cancer are counted among the most frequently cancer diseases. Most of them are based on random accumulation of risk factors, 5-10% show a familial determination. A hereditary modified gene is responsible for the increased cancer risk. In these families, high tumour frequency, young age at diagnosis and multiple primary tumours are remarkable. GENETIC DIAGNOSIS: Sequence analysis is the gold standard. Denaturing high performance liquid chromatography is a quick alternative method. The identification of the responsible gene defect in an affected family member is important. If the test result is positive there is an uncertainty whether the disease will develop or not, when and in which degree, which is founded in the geno-/phenotype correlation. The individual risk estimation is based upon empirical evidence. The test results affect the whole family. Currently, primary prevention is possible for familial adenomatous polyposis (celecoxib, prophylactic colectomy) and for hereditary mamma carcinoma (prophylactic mastectomy). The so-called preventive medical check-ups are early detection examinations. The evidence about early detection methods for colorectal cancer is better than for breast cancer. Prophylactic

  3. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

    DEFF Research Database (Denmark)

    Milne, Roger L; Kuchenbaecker, Karoline B; Michailidou, Kyriaki

    2017-01-01

    associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA......Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9......1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer....

  4. Background risk of breast cancer and the association between physical activity and mammographic density.

    Science.gov (United States)

    Trinh, Thang; Eriksson, Mikael; Darabi, Hatef; Bonn, Stephanie E; Brand, Judith S; Cuzick, Jack; Czene, Kamila; Sjölander, Arvid; Bälter, Katarina; Hall, Per

    2015-04-02

    High physical activity has been shown to decrease the risk of breast cancer, potentially by a mechanism that also reduces mammographic density. We tested the hypothesis that the risk of developing breast cancer in the next 10 years according to the Tyrer-Cuzick prediction model influences the association between physical activity and mammographic density. We conducted a population-based cross-sectional study of 38,913 Swedish women aged 40-74 years. Physical activity was assessed using the validated web-questionnaire Active-Q and mammographic density was measured by the fully automated volumetric Volpara method. The 10-year risk of breast cancer was estimated using the Tyrer-Cuzick (TC) prediction model. Linear regression analyses were performed to assess the association between physical activity and volumetric mammographic density and the potential interaction with the TC breast cancer risk. Overall, high physical activity was associated with lower absolute dense volume. As compared to women with the lowest total activity level (association was seen for any type of physical activity among women with association between total activity and absolute dense volume was modified by the TC breast cancer risk (P interaction = 0.05). As anticipated, high physical activity was also associated with lower non-dense volume. No consistent association was found between physical activity and percent dense volume. Our results suggest that physical activity may decrease breast cancer risk through reducing mammographic density, and that the physical activity needed to reduce mammographic density may depend on background risk of breast cancer.

  5. Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study.

    Science.gov (United States)

    Kerlikowske, Karla; Scott, Christopher G; Mahmoudzadeh, Amir P; Ma, Lin; Winham, Stacey; Jensen, Matthew R; Wu, Fang Fang; Malkov, Serghei; Pankratz, V Shane; Cummings, Steven R; Shepherd, John A; Brandt, Kathleen R; Miglioretti, Diana L; Vachon, Celine M

    2018-06-05

    -RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density. National Cancer Institute.

  6. Dose-stress synergism in cancer risk assessment

    International Nuclear Information System (INIS)

    Pop-Jordanova, N.; Pop-Jordanov, J.

    2001-01-01

    Our hypothesis is that the relatively low risk of cancer or leukaemia from depleted uranium, as predicted by the World Health Organization and the International Atomic Energy Agency, is a result of neglecting the synergism between physico-chemical agents and psychological stress agents (here shortly denoted as dose-stress synergism). We use the modified risk assessment model that comprises a psycho-somatic extension, originally developed by us for assessing the risks of energy sources. Our preliminary meta-analysis of animal and human studies on cancers confirmed the existence of stress effects, including the amplifying synergism. Consequently, the psychological stress can increase the probability of even small toxic chemical or ionizing radiation exposure to produce malignancy. Such dose-stress synergism might influence the health risks among military personnel and the residents in the highly stressful environment in the Balkans. Further investigation is needed to estimate the order of magnitude of these combined effects in particular circumstances. (Original)

  7. A TCP model for external beam treatment of intermediate-risk prostate cancer.

    LENUS (Irish Health Repository)

    Walsh, Seán

    2013-03-01

    Biological models offer the ability to predict clinical outcomes. The authors describe a model to predict the clinical response of intermediate-risk prostate cancer to external beam radiotherapy for a variety of fractionation regimes.

  8. Nutrition-Related Cancer Prevention Cognitions and Behavioral Intentions: Testing the Risk Perception Attitude Framework

    Science.gov (United States)

    Sullivan, Helen W.; Beckjord, Ellen Burke; Finney Rutten, Lila J.; Hesse, Bradford W.

    2008-01-01

    This study tested whether the risk perception attitude framework predicted nutrition-related cancer prevention cognitions and behavioral intentions. Data from the 2003 Health Information National Trends Survey were analyzed to assess respondents' reported likelihood of developing cancer (risk) and perceptions of whether they could lower their…

  9. Thinking through cancer risk: characterizing smokers' process of risk determination.

    Science.gov (United States)

    Hay, Jennifer; Shuk, Elyse; Cruz, Gustavo; Ostroff, Jamie

    2005-10-01

    The perception of cancer risk motivates cancer risk reduction behaviors. However, common measurement strategies for cancer risk perceptions, which involve numerical likelihood estimates, do not adequately capture individuals' thoughts and feelings about cancer risk. To guide the development of novel measurement strategies, the authors used semistructured interviews to examine the thought processes used by smokers (N = 15) as they considered their cancer risk. They used grounded theory to guide systematic data coding and develop a heuristic model describing smokers' risk perception process that includes a cognitive, primarily rational process whereby salient personal risk factors for cancer are considered and combined, and an affective/attitudinal process, which shifts risk perceptions either up or down. The model provides a tentative explanation concerning how people hold cancer risk perceptions that diverge from rational assessment of their risks and will be useful in guiding the development of non-numerical measurements strategies for cancer risk perceptions.

  10. Age at exposure and attained age variations of cancer risk in the Japanese A-bomb and radiotherapy cohorts.

    Science.gov (United States)

    Schneider, Uwe; Walsh, Linda

    2015-08-01

    Phenomenological risk models for radiation-induced cancer are frequently applied to estimate the risk of radiation-induced cancers at radiotherapy doses. Such models often include the effect modification, of the main risk to radiation dose response, by age at exposure and attained age. The aim of this paper is to compare the patterns in risk effect modification by age, between models obtained from the Japanese atomic-bomb (A-bomb) survivor data and models for cancer risks previously reported for radiotherapy patients. Patterns in risk effect modification by age from the epidemiological studies of radiotherapy patients were also used to refine and extend the risk effect modification by age obtained from the A-bomb survivor data, so that more universal models can be presented here. Simple log-linear and power functions of age for the risk effect modification applied in models of the A-bomb survivor data are compared to risks from epidemiological studies of second cancers after radiotherapy. These functions of age were also refined and fitted to radiotherapy risks. The resulting age models provide a refined and extended functional dependence of risk with age at exposure and attained age especially beyond 40 and 65 yr, respectively, and provide a better representation than the currently available simple age functions. It was found that the A-bomb models predict risk similarly to the outcomes of testicular cancer survivors. The survivors of Hodgkin's disease show steeper variations of risk with both age at exposure and attained age. The extended models predict solid cancer risk increase as a function of age at exposure beyond 40 yr and the risk decrease as a function of attained age beyond 65 yr better than the simple models. The standard functions for risk effect modification by age, based on the A-bomb survivor data, predict second cancer risk in radiotherapy patients for ages at exposure prior to 40 yr and attained ages before 55 yr reasonably well. However, for

  11. Sun Protection Motivational Stages and Behavior: Skin Cancer Risk Profiles

    Science.gov (United States)

    Pagoto, Sherry L.; McChargue, Dennis E.; Schneider, Kristin; Cook, Jessica Werth

    2004-01-01

    Objective: To create skin cancer risk profiles that could be used to predict sun protection among Midwest beachgoers. Method: Cluster analysis was used with study participants (N=239), who provided information about sun protection motivation and behavior, perceived risk, burn potential, and tan importance. Participants were clustered according to…

  12. Epidemiological evidence for the risk of cancer from diagnostic X-rays

    International Nuclear Information System (INIS)

    Berrington, A.

    2001-01-01

    -rays (p<0.0001). However, three case-control studies that relied solely on information from medical records did not find evidence of an association between risk of cancer and diagnostic X-rays. Also, the risks of cancer estimated from the studies with self-reported exposures were much larger than extrapolations from higher dose studies predicted. Differential reporting by cases and controls, in the studies that used self-reporting, may account for these discrepancies. The accuracy of self-reported X-ray exposures was examined in case-control studies of thyroid cancer in Sweden and in the U.S., by comparing interview and medical record data. Results from both studies suggested that self-reporting was unreliable. There was some evidence that reporting of X-rays by controls was significantly poorer than reporting by cases, and the difference increased as the number of X-ray exposures increased. Such differential reporting could produce a spurious trend in the risk of cancer with increasing numbers of X-rays in studies based on self-reported exposures. The evidence for differential reporting, and the fact that three case-control studies based solely on medical records did not find significant excess risks, suggests that the risk of cancer from diagnostic X-rays is probably smaller than estimated by the studies that used self-reported exposures. To detect directly a risk of cancer of the size predicted from higher dose studies would require studies based on medical records with several thousand cases and controls. (author)

  13. ATM, radiation, and the risk of second primary breast cancer.

    Science.gov (United States)

    Bernstein, Jonine L; Concannon, Patrick

    2017-10-01

    It was first suggested more than 40 years ago that heterozygous carriers for the human autosomal recessive disorder Ataxia-Telangiectasia (A-T) might also be at increased risk for cancer. Subsequent studies have identified the responsible gene, Ataxia-Telangiectasia Mutated (ATM), characterized genetic variation at this locus in A-T and a variety of different cancers, and described the functions of the ATM protein with regard to cellular DNA damage responses. However, an overall model of how ATM contributes to cancer risk, and in particular, the role of DNA damage in this process, remains lacking. This review considers these questions in the context of contralateral breast cancer (CBC). Heterozygous carriers of loss of function mutations in ATM that are A-T causing, are at increased risk of breast cancer. However, examination of a range of genetic variants, both rare and common, across multiple cancers, suggests that ATM may have additional effects on cancer risk that are allele-dependent. In the case of CBC, selected common alleles at ATM are associated with a reduced incidence of CBC, while other rare and predicted deleterious variants may act jointly with radiation exposure to increase risk. Further studies that characterize germline and somatic ATM mutations in breast cancer and relate the detected genetic changes to functional outcomes, particularly with regard to radiation responses, are needed to gain a complete picture of the complex relationship between ATM, radiation and breast cancer.

  14. Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction

    DEFF Research Database (Denmark)

    Antoniou, Antonis C; Beesley, Jonathan; McGuffog, Lesley

    2010-01-01

    The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs650495...

  15. A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening.

    Science.gov (United States)

    Katki, Hormuzd A; Cheung, Li C; Fetterman, Barbara; Castle, Philip E; Sundaram, Rajeshwari

    2015-10-01

    New cervical cancer screening guidelines in the US and many European countries recommend that women get tested for human papillomavirus (HPV). To inform decisions about screening intervals, we calculate the increase in precancer/cancer risk per year of continued HPV infection. However, both time to onset of precancer/cancer and time to HPV clearance are interval-censored, and onset of precancer/cancer strongly informatively censors HPV clearance. We analyze this bivariate informatively interval-censored data by developing a novel joint model for time to clearance of HPV and time to precancer/cancer using shared random-effects, where the estimated mean duration of each woman's HPV infection is a covariate in the submodel for time to precancer/cancer. The model was fit to data on 9,553 HPV-positive/Pap-negative women undergoing cervical cancer screening at Kaiser Permanente Northern California, data that were pivotal to the development of US screening guidelines. We compare the implications for screening intervals of this joint model to those from population-average marginal models of precancer/cancer risk. In particular, after 2 years the marginal population-average precancer/cancer risk was 5%, suggesting a 2-year interval to control population-average risk at 5%. In contrast, the joint model reveals that almost all women exceeding 5% individual risk in 2 years also exceeded 5% in 1 year, suggesting that a 1-year interval is better to control individual risk at 5%. The example suggests that sophisticated risk models capable of predicting individual risk may have different implications than population-average risk models that are currently used for informing medical guideline development.

  16. Reader performance in visual assessment of breast density using visual analogue scales: Are some readers more predictive of breast cancer?

    Science.gov (United States)

    Rayner, Millicent; Harkness, Elaine F.; Foden, Philip; Wilson, Mary; Gadde, Soujanya; Beetles, Ursula; Lim, Yit Y.; Jain, Anil; Bundred, Sally; Barr, Nicky; Evans, D. Gareth; Howell, Anthony; Maxwell, Anthony; Astley, Susan M.

    2018-03-01

    Mammographic breast density is one of the strongest risk factors for breast cancer, and is used in risk prediction and for deciding appropriate imaging strategies. In the Predicting Risk Of Cancer At Screening (PROCAS) study, percent density estimated by two readers on Visual Analogue Scales (VAS) has shown a strong relationship with breast cancer risk when assessed against automated methods. However, this method suffers from reader variability. This study aimed to assess the performance of PROCAS readers using VAS, and to identify those most predictive of breast cancer. We selected the seven readers who had estimated density on over 6,500 women including at least 100 cancer cases, analysing their performance using multivariable logistic regression and Receiver Operator Characteristic (ROC) analysis. All seven readers showed statistically significant odds ratios (OR) for cancer risk according to VAS score after adjusting for classical risk factors. The OR was greatest for reader 18 at 1.026 (95% Cl 1.018-1.034). Adjusted Area Under the ROC Curves (AUCs) were statistically significant for all readers, but greatest for reader 14 at 0.639. Further analysis of the VAS scores for these two readers showed reader 14 had higher sensitivity (78.0% versus 42.2%), whereas reader 18 had higher specificity (78.0% versus 46.0%). Our results demonstrate individual differences when assigning VAS scores; one better identified those with increased risk, whereas another better identified low risk individuals. However, despite their different strengths, both readers showed similar predictive abilities overall. Standardised training for VAS may improve reader variability and consistency of VAS scoring.

  17. Integration of second cancer risk calculations in a radiotherapy treatment planning system

    International Nuclear Information System (INIS)

    Hartmann, M; Schneider, U

    2014-01-01

    Second cancer risk in patients, in particular in children, who were treated with radiotherapy is an important side effect. It should be minimized by selecting an appropriate treatment plan for the patient. The objectives of this study were to integrate a risk model for radiation induced cancer into a treatment planning system which allows to judge different treatment plans with regard to second cancer induction and to quantify the potential reduction in predicted risk. A model for radiation induced cancer including fractionation effects which is valid for doses in the radiotherapy range was integrated into a treatment planning system. From the three-dimensional (3D) dose distribution the 3D-risk equivalent dose (RED) was calculated on an organ specific basis. In addition to RED further risk coefficients like OED (organ equivalent dose), EAR (excess absolute risk) and LAR (lifetime attributable risk) are computed. A risk model for radiation induced cancer was successfully integrated in a treatment planning system. Several risk coefficients can be viewed and used to obtain critical situations were a plan can be optimised. Risk-volume-histograms and organ specific risks were calculated for different treatment plans and were used in combination with NTCP estimates for plan evaluation. It is concluded that the integration of second cancer risk estimates in a commercial treatment planning system is feasible. It can be used in addition to NTCP modelling for optimising treatment plans which result in the lowest possible second cancer risk for a patient.

  18. Identification of patients with cancer with a high risk to develop delirium.

    Science.gov (United States)

    Neefjes, Elisabeth C W; van der Vorst, Maurice J D L; Verdegaal, Bertha A T T; Beekman, Aartjan T F; Berkhof, Johannes; Verheul, Henk M W

    2017-08-01

    Delirium deteriorates the quality of life in patients with cancer, but is frequently underdiagnosed and not adequately treated. In this study, we evaluated the occurrence of delirium and its risk factors in patients admitted to the hospital for treatment or palliative care in order to develop a prediction model to identify patients at high risk for delirium. In a period of 1.5 years, we evaluated the risk of developing delirium in 574 consecutively admitted patients with cancer to our academic oncology department with the Delirium Observation Screening Scale. Risk factors for delirium were extracted from the patient's chart. A delirium prediction algorithm was constructed using tree analysis, and validated with fivefold cross-validation. A total of 574 patients with cancer were acutely (42%) or electively (58%) admitted 1733 times. The incidence rate of delirium was 3.5 per 100 admittances. Tree analysis revealed that the predisposing factors of an unscheduled admittance and a metabolic imbalance accurately predicted the development of delirium. In this group the incidence rate of delirium was 33 per 100 patients (1:3). The AUC of the model was 0.81, and 0.65 after fivefold cross-validation. We identified that especially patients undergoing an unscheduled admittance with a metabolic imbalance do have a clinically relevant high risk to develop a delirium. Based on these factors, we propose to evaluate preventive treatment of these patients when admitted to the hospital in order to improve their quality of life. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  19. [Establishment of risk evaluation model of peritoneal metastasis in gastric cancer and its predictive value].

    Science.gov (United States)

    Zhao, Junjie; Zhou, Rongjian; Zhang, Qi; Shu, Ping; Li, Haojie; Wang, Xuefei; Shen, Zhenbin; Liu, Fenglin; Chen, Weidong; Qin, Jing; Sun, Yihong

    2017-01-25

    To establish an evaluation model of peritoneal metastasis in gastric cancer, and to assess its clinical significance. Clinical and pathologic data of the consecutive cases of gastric cancer admitted between April 2015 and December 2015 in Department of General Surgery, Zhongshan Hospital of Fudan University were analyzed retrospectively. A total of 710 patients were enrolled in the study after 18 patients with other distant metastasis were excluded. The correlations between peritoneal metastasis and different factors were studied through univariate (Pearson's test or Fisher's exact test) and multivariate analyses (Binary Logistic regression). Independent predictable factors for peritoneal metastasis were combined to establish a risk evaluation model (nomogram). The nomogram was created with R software using the 'rms' package. In the nomogram, each factor had different scores, and every patient could have a total score by adding all the scores of each factor. A higher total score represented higher risk of peritoneal metastasis. Receiver operating characteristic (ROC) curve analysis was used to compare the sensitivity and specificity of the established nomogram. Delong. Delong. Clarke-Pearson test was used to compare the difference of the area under the curve (AUC). The cut-off value was determined by the AUC, when the ROC curve had the biggest AUC, the model had the best sensitivity and specificity. Among 710 patients, 47 patients had peritoneal metastasis (6.6%), including 30 male (30/506, 5.9%) and 17 female (17/204, 8.3%); 31 were ≥ 60 years old (31/429, 7.2%); 38 had tumor ≥ 3 cm(38/461, 8.2%). Lauren classification indicated that 2 patients were intestinal type(2/245, 0.8%), 8 patients were mixed type(8/208, 3.8%), 11 patients were diffuse type(11/142, 7.7%), and others had no associated data. CA19-9 of 13 patients was ≥ 37 kU/L(13/61, 21.3%); CA125 of 11 patients was ≥ 35 kU/L(11/36, 30.6%); CA72-4 of 11 patients was ≥ 10 kU/L(11/39, 28

  20. A proposal for a comprehensive risk scoring system for predicting postoperative complications in octogenarian patients with medically operable lung cancer: JACS1303.

    Science.gov (United States)

    Saji, Hisashi; Ueno, Takahiko; Nakamura, Hiroshige; Okumura, Norihito; Tsuchida, Masanori; Sonobe, Makoto; Miyazaki, Takuro; Aokage, Keiju; Nakao, Masayuki; Haruki, Tomohiro; Ito, Hiroyuki; Kataoka, Kazuhiko; Okabe, Kazunori; Tomizawa, Kenji; Yoshimoto, Kentaro; Horio, Hirotoshi; Sugio, Kenji; Ode, Yasuhisa; Takao, Motoshi; Okada, Morihito; Chida, Masayuki

    2018-04-01

    Although some retrospective studies have reported clinicopathological scoring systems for predicting postoperative complications and survival outcomes for elderly lung cancer patients, optimized scoring systems remain controversial. The Japanese Association for Chest Surgery (JACS) conducted a nationwide multicentre prospective cohort and enrolled a total of 1019 octogenarians with medically operable lung cancer. Details of the clinical factors, comorbidities and comprehensive geriatric assessment were recorded for 895 patients to develop a comprehensive risk scoring (RS) system capable of predicting severe complications. Operative (30 days) and hospital mortality rates were 1.0% and 1.6%, respectively. Complications were observed in 308 (34%) patients, of whom 81 (8.4%) had Grade 3-4 severe complications. Pneumonia was the most common severe complication, observed in 27 (3.0%) patients. Five predictive factors, gender, comprehensive geriatric assessment75: memory and Simplified Comorbidity Score (SCS): diabetes mellitus, albumin and percentage vital capacity, were identified as independent predictive factors for severe postoperative complications (odds ratio = 2.73, 1.86, 1.54, 1.66 and 1.61, respectively) through univariate and multivariate analyses. A 5-fold cross-validation was performed as an internal validation to reconfirm these 5 predictive factors (average area under the curve 0.70). We developed a simplified RS system as follows: RS = 3 (gender: male) + 2 (comprehensive geriatric assessment 75: memory: yes) + 2 (albumin: <3.8 ng/ml) + 1 (percentage vital capacity: ≤90) + 1 (SCS: diabetes mellitus: yes). The current series shows that octogenarians can be successfully treated for lung cancer with surgical resection with an acceptable rate of severe complications and mortality. We propose a simplified RS system to predict severe complications in octogenarian patients with medically operative lung cancer. JACS1303 (UMIN000016756).

  1. Inflammatory Genetic Markers of Prostate Cancer Risk

    International Nuclear Information System (INIS)

    Tindall, Elizabeth A.; Hayes, Vanessa M.; Petersen, Desiree C.

    2010-01-01

    Prostate cancer is the most common cancer in Western society males, with incidence rates predicted to rise with global aging. Etiology of prostate cancer is however poorly understood, while current diagnostic tools can be invasive (digital rectal exam or biopsy) and/or lack specificity for the disease (prostate-specific antigen (PSA) testing). Substantial histological, epidemiological and molecular genetic evidence indicates that inflammation is important in prostate cancer pathogenesis. In this review, we summarize the current status of inflammatory genetic markers influencing susceptibility to prostate cancer. The focus will be on inflammatory cytokines regulating T-helper cell and chemokine homeostasis, together with the Toll-like receptors as key players in the host innate immune system. Although association studies indicating a genetic basis for prostate cancer are presently limited mainly due to lack of replication, larger and more ethnically and clinically defined study populations may help elucidate the true contribution of inflammatory gene variants to prostate cancer risk

  2. Inflammatory Genetic Markers of Prostate Cancer Risk

    Energy Technology Data Exchange (ETDEWEB)

    Tindall, Elizabeth A.; Hayes, Vanessa M. [Cancer Genetics Group, Children’s Cancer Institute Australia for Medical Research, Lowy Cancer Research Centre, University of New South Wales, PO Box 81, Randwick, NSW 2031 (Australia); University of New South Wales, Kensington Campus, Sydney, NSW 2052 (Australia); Petersen, Desiree C., E-mail: dpetersen@ccia.unsw.edu.au [Cancer Genetics Group, Children’s Cancer Institute Australia for Medical Research, Lowy Cancer Research Centre, University of New South Wales, PO Box 81, Randwick, NSW 2031 (Australia)

    2010-06-08

    Prostate cancer is the most common cancer in Western society males, with incidence rates predicted to rise with global aging. Etiology of prostate cancer is however poorly understood, while current diagnostic tools can be invasive (digital rectal exam or biopsy) and/or lack specificity for the disease (prostate-specific antigen (PSA) testing). Substantial histological, epidemiological and molecular genetic evidence indicates that inflammation is important in prostate cancer pathogenesis. In this review, we summarize the current status of inflammatory genetic markers influencing susceptibility to prostate cancer. The focus will be on inflammatory cytokines regulating T-helper cell and chemokine homeostasis, together with the Toll-like receptors as key players in the host innate immune system. Although association studies indicating a genetic basis for prostate cancer are presently limited mainly due to lack of replication, larger and more ethnically and clinically defined study populations may help elucidate the true contribution of inflammatory gene variants to prostate cancer risk.

  3. Are preoperative histology and MRI useful for classification of endometrial cancer risk?

    International Nuclear Information System (INIS)

    Body, Noemie; Lavoué, Vincent; De Kerdaniel, Olivier; Foucher, Fabrice; Henno, Sébastien; Cauchois, Aurélie; Laviolle, Bruno; Leblanc, Marc; Levêque, Jean

    2016-01-01

    The 2010 guidelines of the French National Cancer Institute (INCa) classify patients with endometrial cancer into three risk groups for lymph node invasion and recurrence on the basis of MRI and histological analysis of an endometrial specimen obtained preoperatively. The classification guides therapeutic choices, which may include pelvic and/or para-aortic lymphadenectomy. The purpose of this study was to evaluate the diagnostic performance of preoperative assessment to help identify intermediate- or high-risk patients requiring lymphadenectomy. The study included all patients who underwent surgery for endometrial cancer between January 2010 and December 2013 at either Rennes University Hospital or Vannes Regional Hospital. The criteria for eligibility included a preoperative assessment with MRI and histological examination of an endometrial sample. A histological comparison was made between the preoperative and surgical specimens. Among the 91 patients who underwent a full preoperative assessment, the diagnosis of intermediate- or high-risk endometrial cancer was established by MRI and histology with a sensitivity of 70 %, specificity of 82 %, positive predictive value (PPV) of 87 %, negative predictive value (NPV) of 61 %, positive likelihood ratio (LR+) of 3.8 and negative likelihood ratio (LR-) of 0.3. The risk group was underestimated in 32 % of patients and overestimated in 7 % of patients. MRI underestimated endometrial cancer stage in 20 % of cases, while endometrial sampling underestimated the histological type in 4 % of cases and the grade in 9 % of cases. The preoperative assessment overestimated or underestimated the risk of recurrence in nearly 40 % of cases, with errors in lesion type, grade or stage. Erroneous preoperative risk assessment leads to suboptimal initial surgical management of patients with endometrial cancer

  4. The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer.

    Science.gov (United States)

    Reeh, Matthias; Metze, Johannes; Uzunoglu, Faik G; Nentwich, Michael; Ghadban, Tarik; Wellner, Ullrich; Bockhorn, Maximilian; Kluge, Stefan; Izbicki, Jakob R; Vashist, Yogesh K

    2016-02-01

    Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score.

  5. Cancer antigen-125 and risk of atrial fibrillation

    DEFF Research Database (Denmark)

    Cheung, Angel; Gong, Mengqi; Bellanti, Roberto

    2018-01-01

    Background: Cancer antigen-125 (Ca-125) is traditionally recognised as a tumour marker and its role in cardiovascular diseases has been studied only in recent years. Whether Ca-125 is elevated in patients with atrial fibrillation (AF) and its levels predict the risk of AF remains controversial. T...

  6. Risk of second bone sarcoma following childhood cancer: role of radiation therapy treatment

    OpenAIRE

    Schwartz, Boris; Benadjaoud, Mohamed Amine; Clero, Enora; Haddy, Nadia; El-Fayech, Chiraz; Guibout, Catherine; Teinturier, Cecile; Oberlin, Odile; Veres, Cristina; Pacquement, Helene; Munzer, Martine; Tan Dat N'Guyen; Bondiau, Pierre-Yves; Berchery, Delphine; Laprie, Anne

    2014-01-01

    International audience; : Bone sarcoma as a second malignancy is rare but highly fatal. The present knowledge about radiation-absorbed organ dose-response is insufficient to predict the risks induced by radiation therapy techniques. The objective of the present study was to assess the treatment-induced risk for bone sarcoma following a childhood cancer and particularly the related risk of radiotherapy. Therefore, a retrospective cohort of 4,171 survivors of a solid childhood cancer treated be...

  7. Prognostic and predictive biomarkers in colorectal cancer. Towards precision medicine

    NARCIS (Netherlands)

    Reimers, Marlies Suzanne

    2015-01-01

    The aim of this thesis was to define prognostic and predictive biomarkers in colorectal cancer for improved risk stratification and treatment benefit in the individual patient, with the introduction of precision medicine in the near future as the ultimate goal. By definition, precision medicine is

  8. Risk assessment and remedial policy evaluation using predictive modeling

    International Nuclear Information System (INIS)

    Linkov, L.; Schell, W.R.

    1996-01-01

    As a result of nuclear industry operation and accidents, large areas of natural ecosystems have been contaminated by radionuclides and toxic metals. Extensive societal pressure has been exerted to decrease the radiation dose to the population and to the environment. Thus, in making abatement and remediation policy decisions, not only economic costs but also human and environmental risk assessments are desired. This paper introduces a general framework for risk assessment and remedial policy evaluation using predictive modeling. Ecological risk assessment requires evaluation of the radionuclide distribution in ecosystems. The FORESTPATH model is used for predicting the radionuclide fate in forest compartments after deposition as well as for evaluating the efficiency of remedial policies. Time of intervention and radionuclide deposition profile was predicted as being crucial for the remediation efficiency. Risk assessment conducted for a critical group of forest users in Belarus shows that consumption of forest products (berries and mushrooms) leads to about 0.004% risk of a fatal cancer annually. Cost-benefit analysis for forest cleanup suggests that complete removal of organic layer is too expensive for application in Belarus and a better methodology is required. In conclusion, FORESTPATH modeling framework could have wide applications in environmental remediation of radionuclides and toxic metals as well as in dose reconstruction and, risk-assessment

  9. Risk of second primary cancer following differentiated thyroid cancer

    International Nuclear Information System (INIS)

    Berthe, Emmanuelle; Berthet, Pascaline; Bardet, Stephane; Henry-Amar, Michel; Michels, Jean-Jacques; Rame, Jean-Pierre; Babin, Emmanuel; Icard, Philippe; Samama, Guy; Galateau-Salle, Francoise; Mahoudeau, Jacques

    2004-01-01

    Concerns remain over the risk of cancer following differentiated thyroid carcinoma and its causes. Iodine-131 ( 131 I) and external irradiation are known to have potential carcinogenic effects. Thyroid carcinoma is a polygenic disease which may be associated with other malignancies. We investigated the incidence of second cancer and its aetiology in a cohort of 875 patients (146 men, 729 women) with differentiated thyroid carcinoma originating from Basse-Normandie, France. Cancer incidence was compared with that of the general population of the Departement du Calvados matched for age, gender and period. The cumulative proportion of second cancer was estimated using the life-table method. Factors that correlated with the risk of second cancer were studied using the Cox model. After a median follow-up of 8 years, 58 second cancers had been observed. Compared with general population incidence rates, there was an overall increased risk of second cancer in women [standardised incidence ratio (SIR)=1.52; P 0.20). Increased risk related to cancers of the genitourinary tract (SIR=3.31; P 131 I was related to the risk. These data confirm that women with differentiated thyroid carcinoma are at risk of developing a second cancer of the genitourinary tract and kidney. Only age and medical history of primary cancer before thyroid carcinoma are risk factors for second cancer. Common environmental or genetic factors as well as long-term carcinogenic effects of primary cancer therapy should be considered. (orig.)

  10. Confusing Relative Risk with Absolute Risk Is Associated with More Enthusiastic Beliefs about the Value of Cancer Screening.

    Science.gov (United States)

    Caverly, Tanner J; Prochazka, Allan V; Binswanger, Ingrid A; Kutner, Jean S; Matlock, Daniel D

    2014-07-01

    Reviews of how data are presented in medical literature document that the benefit from an intervention is often exaggerated relative to the harm (e.g., relative risk for benefit and absolute risk for harm). Such mismatched presentations may create unwarranted enthusiasm, especially among those who misinterpret the statistics presented. The objective was to determine whether misinterpretation of risk data predicts enthusiasm for cancer screening. The authors administered a survey with 14 items assessing beliefs about cancer screening and 6 items measuring data interpretation ability. Multiple linear regression was used to evaluate the association between data interpretation and enthusiasm for cancer screening, with adjustment for gender and year graduated from medical school. Eighty-eight of 139 physicians at a state-wide professional meeting returned completed surveys (63% response rate). Lower data interpretation scores were associated with higher enthusiasm for cancer screening scores (P = 0.004) in the adjusted primary analysis. Confusing relative risk with absolute risk appeared to drive the overall association. Biased presentations of risk data could affect general beliefs about the value of cancer screening, especially among physicians who uncritically accept mismatched presentations of data. © The Author(s) 2014.

  11. Obesity and Cancer Risk

    Science.gov (United States)

    ... Common Cancer Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer ... hormone therapy and for tumors that express hormone receptors . Obesity is also a risk factor for breast ...

  12. Do Lung Cancer Eligibility Criteria Align with Risk among Blacks and Hispanics?

    Directory of Open Access Journals (Sweden)

    Kevin Fiscella

    Full Text Available Black patients have higher lung cancer risk despite lower pack years of smoking. We assessed lung cancer risk by race, ethnicity, and sex among a nationally representative population eligible for lung cancer screening based on Medicare criteria.We used data from the National Health and Nutrition Examination Survey, 2007-2012 to assess lung cancer risk by sex, race and ethnicity among persons satisfying Medicare age and pack-year smoking eligibility criteria for lung cancer screening. We assessed Medicare eligibility based on age (55-77 years and pack-years (≥ 30. We assessed 6-year lung cancer risk using a risk prediction model from Prostate, Lung, Colorectal and Ovarian Cancer Screening trial that was modified in 2012 (PLCOm2012. We compared the proportions of eligible persons by sex, race and ethnicity using Medicare criteria with a risk cut-point that was adjusted to achieve comparable total number of persons eligible for screening.Among the 29.7 million persons aged 55-77 years who ever smoked, we found that 7.3 million (24.5% were eligible for lung cancer screening under Medicare criteria. Among those eligible, Blacks had statistically significant higher (4.4% and Hispanics lower lung cancer risk (1.2% than non-Hispanic Whites (3.2%. At a cut-point of 2.12% risk for lung screening eligibility, the percentage of Blacks and Hispanics showed statistically significant changes. Blacks eligible rose by 48% and Hispanics eligible declined by 63%. Black men and Hispanic women were affected the most. There was little change in eligibility among Whites.Medicare eligibility criteria for lung cancer screening do not align with estimated risk for lung cancer among Blacks and Hispanics. Data are urgently needed to determine whether use of risk-based eligibility screening improves lung cancer outcomes among minority patients.

  13. A METHOD OF PREDICTING BREAST CANCER USING QUESTIONNAIRES

    Directory of Open Access Journals (Sweden)

    V. N. Malashenko

    2017-01-01

    Full Text Available Purpose. Simplify and increase the accuracy of the questionnaire method of predicting breast cancer (BC for subsequent computer processing and Automated dispensary at risk without the doctor.Materials and methods. The work was based on statistical data obtained by surveying 305 women. The questionnaire included 63 items: 17 open-ended questions, 46 — with a choice of response. It was established multifactor model, the development of which, in addition to the survey data were used materials from the medical histories of patients and respondents data immuno-histochemical studies. Data analysis was performed using Statistica 10.0 and MedCalc 12.7.0 programs.Results. The ROC analysis was performas and the questionnaire data revealed 8 significant predictors of breast cancer. On their basis we created the formula for calculating the prognostic factor of risk of development of breast cancer with a sensitivity 83,12% and a specificity of 91,43%.Conclusions. The completed developments allow to create a computer program for automated processing of profiles on the formation of groups at risk of breast cancer and clinical supervision. The introduction of a screening questionnaire over the Internet with subsequent computer processing of the results, without the direct involvement of doctors, will increase the coverage of the female population of the Russian Federation activities related to the prevention of breast cancer. It can free up time for physicians to receive primary patients, as well as improve oncological vigilance of the female population of the Russian Federation.

  14. A Review of Current Machine Learning Methods Used for Cancer Recurrence Modeling and Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Hemphill, Geralyn M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-27

    Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The early diagnosis and prognosis of a cancer type has become a necessity in cancer research. A major challenge in cancer management is the classification of patients into appropriate risk groups for better treatment and follow-up. Such risk assessment is critically important in order to optimize the patient’s health and the use of medical resources, as well as to avoid cancer recurrence. This paper focuses on the application of machine learning methods for predicting the likelihood of a recurrence of cancer. It is not meant to be an extensive review of the literature on the subject of machine learning techniques for cancer recurrence modeling. Other recent papers have performed such a review, and I will rely heavily on the results and outcomes from these papers. The electronic databases that were used for this review include PubMed, Google, and Google Scholar. Query terms used include “cancer recurrence modeling”, “cancer recurrence and machine learning”, “cancer recurrence modeling and machine learning”, and “machine learning for cancer recurrence and prediction”. The most recent and most applicable papers to the topic of this review have been included in the references. It also includes a list of modeling and classification methods to predict cancer recurrence.

  15. Age at exposure and attained age variations of cancer risk in the Japanese A-bomb and radiotherapy cohorts

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Uwe, E-mail: uwe.schneider@uzh.ch [Institute of Physics, Science Faculty, University of Zürich, Zürich 8057, Switzerland and Radiotherapy Hirslanden, Uwe Schneider Institute of Radiotherapy, Witellikerstr. 40, Zürich 8032 (Switzerland); Walsh, Linda [Institute of Physics, Science Faculty, University of Zürich, Zürich 8057, Switzerland and BfS - Federal Office for Radiation Protection, Radiation Protection and Health, Neuherberg 85764 (Germany)

    2015-08-15

    Purpose: Phenomenological risk models for radiation-induced cancer are frequently applied to estimate the risk of radiation-induced cancers at radiotherapy doses. Such models often include the effect modification, of the main risk to radiation dose response, by age at exposure and attained age. The aim of this paper is to compare the patterns in risk effect modification by age, between models obtained from the Japanese atomic-bomb (A-bomb) survivor data and models for cancer risks previously reported for radiotherapy patients. Patterns in risk effect modification by age from the epidemiological studies of radiotherapy patients were also used to refine and extend the risk effect modification by age obtained from the A-bomb survivor data, so that more universal models can be presented here. Methods: Simple log-linear and power functions of age for the risk effect modification applied in models of the A-bomb survivor data are compared to risks from epidemiological studies of second cancers after radiotherapy. These functions of age were also refined and fitted to radiotherapy risks. The resulting age models provide a refined and extended functional dependence of risk with age at exposure and attained age especially beyond 40 and 65 yr, respectively, and provide a better representation than the currently available simple age functions. Results: It was found that the A-bomb models predict risk similarly to the outcomes of testicular cancer survivors. The survivors of Hodgkin’s disease show steeper variations of risk with both age at exposure and attained age. The extended models predict solid cancer risk increase as a function of age at exposure beyond 40 yr and the risk decrease as a function of attained age beyond 65 yr better than the simple models. Conclusions: The standard functions for risk effect modification by age, based on the A-bomb survivor data, predict second cancer risk in radiotherapy patients for ages at exposure prior to 40 yr and attained ages

  16. Erlotinib and the Risk of Oral Cancer

    Science.gov (United States)

    William, William N.; Papadimitrakopoulou, Vassiliki; Lee, J. Jack; Mao, Li; Cohen, Ezra E.W.; Lin, Heather Y.; Gillenwater, Ann M.; Martin, Jack W.; Lingen, Mark W.; Boyle, Jay O.; Shin, Dong M.; Vigneswaran, Nadarajah; Shinn, Nancy; Heymach, John V.; Wistuba, Ignacio I.; Tang, Ximing; Kim, Edward S.; Saintigny, Pierre; Blair, Elizabeth A.; Meiller, Timothy; Gutkind, J. Silvio; Myers, Jeffrey; El-Naggar, Adel; Lippman, Scott M.

    2016-01-01

    IMPORTANCE Standard molecularly based strategies to predict and/or prevent oral cancer development in patients with oral premalignant lesions (OPLs) are lacking. OBJECTIVE To test if the epidermal growth factor receptor inhibitor erlotinib would reduce oral cancer development in patients with high-risk OPLs defined by specific loss of heterozygosity (LOH) profiles. Secondary objectives included prospective determination of LOH as a prognostic marker in OPLs. DESIGN The Erlotinib Prevention of Oral Cancer (EPOC) study was a randomized, placebo-controlled, double-bind trial. Accrual occurred from November 2006 through July 2012, with a median follow-up time of 35 months in an ambulatory care setting in 5 US academic referral institutions. Patients with OPLs were enrolled in the protocol, and each underwent LOH profiling (N = 379); they were classified as high-risk (LOH-positive) or low-risk (LOH-negative) patients based on their LOH profiles and oral cancer history. The randomized sample consisted of 150 LOH-positive patients. INTERVENTIONS Oral erlotinib treatment (150mg/d) or placebo for 12 months. MAIN OUTCOMES AND MEASURES Oral cancer–free survival (CFS). RESULTS A total of 395 participants were classified with LOH profiles, and 254 were classified LOH positive. Of these, 150 (59%) were randomized, 75 each to the placebo and erlotinib groups. The 3-year CFS rates in placebo- and erlotinib-treated patients were 74%and 70%, respectively (hazard ratio [HR], 1.27; 95%CI, 0.68–2.38; P = .45). The 3-year CFS was significantly lower for LOH-positive compared with LOH-negative groups (74%vs 87%, HR, 2.19; 95%CI, 1.25–3.83; P = .01). Increased EGFR gene copy number correlated with LOH-positive status (P < .001) and lower CFS (P = .01). The EGFR gene copy number was not predictive of erlotinib efficacy. Erlotinib-induced skin rash was associated with improved CFS (P = .01). CONCLUSIONS AND RELEVANCE In this trial, LOH was validated as a marker of oral cancer risk and

  17. Infective Endocarditis and Cancer Risk

    Science.gov (United States)

    Sun, Li-Min; Wu, Jung-Nan; Lin, Cheng-Li; Day, Jen-Der; Liang, Ji-An; Liou, Li-Ren; Kao, Chia-Hung

    2016-01-01

    Abstract This study investigated the possible relationship between endocarditis and overall and individual cancer risk among study participants in Taiwan. We used data from the National Health Insurance program of Taiwan to conduct a population-based, observational, and retrospective cohort study. The case group consisted of 14,534 patients who were diagnosed with endocarditis between January 1, 2000 and December 31, 2010. For the control group, 4 patients without endocarditis were frequency matched to each endocarditis patient according to age, sex, and index year. Competing risks regression analysis was conducted to determine the effect of endocarditis on cancer risk. A large difference was noted in Charlson comorbidity index between endocarditis and nonendocarditis patients. In patients with endocarditis, the risk for developing overall cancer was significant and 119% higher than in patients without endocarditis (adjusted subhazard ratio = 2.19, 95% confidence interval = 1.98–2.42). Regarding individual cancers, in addition to head and neck, uterus, female breast and hematological malignancies, the risks of developing colorectal cancer, and some digestive tract cancers were significantly higher. Additional analyses determined that the association of cancer with endocarditis is stronger within the 1st 5 years after endocarditis diagnosis. This population-based cohort study found that patients with endocarditis are at a higher risk for colorectal cancer and other cancers in Taiwan. The risk was even higher within the 1st 5 years after endocarditis diagnosis. It suggested that endocarditis is an early marker of colorectal cancer and other cancers. The underlying mechanisms must still be explored and may account for a shared risk factor of infection in both endocarditis and malignancy. PMID:27015220

  18. An NRG Oncology/GOG study of molecular classification for risk prediction in endometrioid endometrial cancer.

    Science.gov (United States)

    Cosgrove, Casey M; Tritchler, David L; Cohn, David E; Mutch, David G; Rush, Craig M; Lankes, Heather A; Creasman, William T; Miller, David S; Ramirez, Nilsa C; Geller, Melissa A; Powell, Matthew A; Backes, Floor J; Landrum, Lisa M; Timmers, Cynthia; Suarez, Adrian A; Zaino, Richard J; Pearl, Michael L; DiSilvestro, Paul A; Lele, Shashikant B; Goodfellow, Paul J

    2018-01-01

    The purpose of this study was to assess the prognostic significance of a simplified, clinically accessible classification system for endometrioid endometrial cancers combining Lynch syndrome screening and molecular risk stratification. Tumors from NRG/GOG GOG210 were evaluated for mismatch repair defects (MSI, MMR IHC, and MLH1 methylation), POLE mutations, and loss of heterozygosity. TP53 was evaluated in a subset of cases. Tumors were assigned to four molecular classes. Relationships between molecular classes and clinicopathologic variables were assessed using contingency tests and Cox proportional methods. Molecular classification was successful for 982 tumors. Based on the NCI consensus MSI panel assessing MSI and loss of heterozygosity combined with POLE testing, 49% of tumors were classified copy number stable (CNS), 39% MMR deficient, 8% copy number altered (CNA) and 4% POLE mutant. Cancer-specific mortality occurred in 5% of patients with CNS tumors; 2.6% with POLE tumors; 7.6% with MMR deficient tumors and 19% with CNA tumors. The CNA group had worse progression-free (HR 2.31, 95%CI 1.53-3.49) and cancer-specific survival (HR 3.95; 95%CI 2.10-7.44). The POLE group had improved outcomes, but the differences were not statistically significant. CNA class remained significant for cancer-specific survival (HR 2.11; 95%CI 1.04-4.26) in multivariable analysis. The CNA molecular class was associated with TP53 mutation and expression status. A simple molecular classification for endometrioid endometrial cancers that can be easily combined with Lynch syndrome screening provides important prognostic information. These findings support prospective clinical validation and further studies on the predictive value of a simplified molecular classification system. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy.

    Science.gov (United States)

    van Leeuwen, Pim J; Hayen, Andrew; Thompson, James E; Moses, Daniel; Shnier, Ron; Böhm, Maret; Abuodha, Magdaline; Haynes, Anne-Maree; Ting, Francis; Barentsz, Jelle; Roobol, Monique; Vass, Justin; Rasiah, Krishan; Delprado, Warick; Stricker, Phillip D

    2017-12-01

    To develop and externally validate a predictive model for detection of significant prostate cancer. Development of the model was based on a prospective cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling. In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P prostate cancer. Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

  20. Predicting Brain Metastasis in Breast Cancer Patients: Stage Versus Biology.

    Science.gov (United States)

    Azim, Hamdy A; Abdel-Malek, Raafat; Kassem, Loay

    2018-04-01

    Brain metastasis (BM) is a life-threatening event in breast cancer patients. Identifying patients at a high risk for BM can help to adopt screening programs and test preventive interventions. We tried to identify the incidence of BM in different stages and subtypes of breast cancer. We reviewed the clinical records of 2193 consecutive breast cancer patients who presented between January 1999 and December 2010. We explored the incidence of BM in relation to standard clinicopathological factors, and determined the cumulative risk of BM according to the disease stage and phenotype. Of the 2193 included women, 160 (7.3%) developed BM at a median follow-up of 5.8 years. Age younger than 60 years (P = .015), larger tumors (P = .004), lymph node (LN) positivity (P < .001), high tumor grade (P = .012), and HER2 positivity (P < .001) were associated with higher incidence of BM in the whole population. In patients who presented with locoregional disease, 3 factors independently predicted BM: large tumors (hazard ratio [HR], 3.60; 95% confidence interval [CI], 1.54-8.38; P = .003), axillary LN metastasis (HR, 4.03; 95% CI, 1.91-8.52; P < .001), and HER2 positivity (HR, 1.89; 95% CI, 1.0-3.41; P = .049). A Brain Relapse Index was formulated using those 3 factors, with 5-year cumulative incidence of BM of 19.2% in those having the 2 or 3 risk factors versus 2.5% in those with no or 1 risk factor (P < .001). In metastatic patients, 3 factors were associated with higher risk of BM: HER2 positivity (P = .007), shorter relapse-free interval (P < .001), and lung metastasis (P < .001). Disease stage and biological subtypes predict the risk for BM and subsequent treatment outcome. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.

    Science.gov (United States)

    Paik, Soonmyung; Shak, Steven; Tang, Gong; Kim, Chungyeul; Baker, Joffre; Cronin, Maureen; Baehner, Frederick L; Walker, Michael G; Watson, Drew; Park, Taesung; Hiller, William; Fisher, Edwin R; Wickerham, D Lawrence; Bryant, John; Wolmark, Norman

    2004-12-30

    The likelihood of distant recurrence in patients with breast cancer who have no involved lymph nodes and estrogen-receptor-positive tumors is poorly defined by clinical and histopathological measures. We tested whether the results of a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of 21 prospectively selected genes in paraffin-embedded tumor tissue would correlate with the likelihood of distant recurrence in patients with node-negative, tamoxifen-treated breast cancer who were enrolled in the National Surgical Adjuvant Breast and Bowel Project clinical trial B-14. The levels of expression of 16 cancer-related genes and 5 reference genes were used in a prospectively defined algorithm to calculate a recurrence score and to determine a risk group (low, intermediate, or high) for each patient. Adequate RT-PCR profiles were obtained in 668 of 675 tumor blocks. The proportions of patients categorized as having a low, intermediate, or high risk by the RT-PCR assay were 51, 22, and 27 percent, respectively. The Kaplan-Meier estimates of the rates of distant recurrence at 10 years in the low-risk, intermediate-risk, and high-risk groups were 6.8 percent (95 percent confidence interval, 4.0 to 9.6), 14.3 percent (95 percent confidence interval, 8.3 to 20.3), and 30.5 percent (95 percent confidence interval, 23.6 to 37.4). The rate in the low-risk group was significantly lower than that in the high-risk group (P<0.001). In a multivariate Cox model, the recurrence score provided significant predictive power that was independent of age and tumor size (P<0.001). The recurrence score was also predictive of overall survival (P<0.001) and could be used as a continuous function to predict distant recurrence in individual patients. The recurrence score has been validated as quantifying the likelihood of distant recurrence in tamoxifen-treated patients with node-negative, estrogen-receptor-positive breast cancer. Copyright 2004 Massachusetts Medical Society.

  2. Cancer risk as a radiation detriment

    International Nuclear Information System (INIS)

    Servomaa, A.; Komppa, T.; Servomaa, K.

    1992-11-01

    Potential radiation detriment means a risk of cancer or other somatic disease, genetic damage of fetal injury. Quantative information about the relation between a radiation dose and cancer risk is needed to enable decision-making in radiation protection. However, assessment of cancer risk by means of the radiation dose is controversial, as epidemiological and biological information about factors affecting the origin of cancers show that risk assessment is imprecise when the radiation dose is used as the only factor. Focusing on radiation risk estimates for breast cancer, lung cancer and leukemia, the report is based on the models given in the Beir V report, on sources of radiation exposure and the uncertainty of risk estimates. Risk estimates are assessed using the relative risk model and the cancer mortality rates in Finland. Cancer incidence and mortality rates for men and women are shown in graphs as a function of age and time. Relative risks are shown as a function of time after exposure and lifetime risks as a function of age at exposure. Uncertainty factors affecting the radiation risk are examined from the point of view of epidemiology and molecular biology. (orig.)

  3. Pretreatment anti-Müllerian hormone predicts for loss of ovarian function after chemotherapy for early breast cancer

    DEFF Research Database (Denmark)

    Anderson, Richard A; Rosendahl, Mikkel; Kelsey, Thomas W

    2013-01-01

    Improving survival for women with early breast cancer (eBC) requires greater attention to the consequences of treatment, including risk to ovarian function. We have assessed whether biochemical markers of the ovarian reserve might improve prediction of chemotherapy related amenorrhoea.......Improving survival for women with early breast cancer (eBC) requires greater attention to the consequences of treatment, including risk to ovarian function. We have assessed whether biochemical markers of the ovarian reserve might improve prediction of chemotherapy related amenorrhoea....

  4. Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones.

    Science.gov (United States)

    Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Ziv, Elad; Kerlikowske, Karla; Cummings, Steven R

    2017-11-01

    Models that predict the risk of estrogen receptor (ER)-positive breast cancers may improve our ability to target chemoprevention. We investigated the contributions of sex hormones to the discrimination of the Breast Cancer Surveillance Consortium (BCSC) risk model and a polygenic risk score comprised of 83 single nucleotide polymorphisms. We conducted a nested case-control study of 110 women with ER-positive breast cancers and 214 matched controls within a mammography screening cohort. Participants were postmenopausal and not on hormonal therapy. The associations of estradiol, estrone, testosterone, and sex hormone binding globulin with ER-positive breast cancer were evaluated using conditional logistic regression. We assessed the individual and combined discrimination of estradiol, the BCSC risk score, and polygenic risk score using the area under the receiver operating characteristic curve (AUROC). Of the sex hormones assessed, estradiol (OR 3.64, 95% CI 1.64-8.06 for top vs bottom quartile), and to a lesser degree estrone, was most strongly associated with ER-positive breast cancer in unadjusted analysis. The BCSC risk score (OR 1.32, 95% CI 1.00-1.75 per 1% increase) and polygenic risk score (OR 1.58, 95% CI 1.06-2.36 per standard deviation) were also associated with ER-positive cancers. A model containing the BCSC risk score, polygenic risk score, and estradiol levels showed good discrimination for ER-positive cancers (AUROC 0.72, 95% CI 0.65-0.79), representing a significant improvement over the BCSC risk score (AUROC 0.58, 95% CI 0.50-0.65). Adding estradiol and a polygenic risk score to a clinical risk model improves discrimination for postmenopausal ER-positive breast cancers.

  5. Prostate Cancer Predictive Simulation Modelling, Assessing the Risk Technique (PCP-SMART): Introduction and Initial Clinical Efficacy Evaluation Data Presentation of a Simple Novel Mathematical Simulation Modelling Method, Devised to Predict the Outcome of Prostate Biopsy on an Individual Basis.

    Science.gov (United States)

    Spyropoulos, Evangelos; Kotsiris, Dimitrios; Spyropoulos, Katherine; Panagopoulos, Aggelos; Galanakis, Ioannis; Mavrikos, Stamatios

    2017-02-01

    We developed a mathematical "prostate cancer (PCa) conditions simulating" predictive model (PCP-SMART), from which we derived a novel PCa predictor (prostate cancer risk determinator [PCRD] index) and a PCa risk equation. We used these to estimate the probability of finding PCa on prostate biopsy, on an individual basis. A total of 371 men who had undergone transrectal ultrasound-guided prostate biopsy were enrolled in the present study. Given that PCa risk relates to the total prostate-specific antigen (tPSA) level, age, prostate volume, free PSA (fPSA), fPSA/tPSA ratio, and PSA density and that tPSA ≥ 50 ng/mL has a 98.5% positive predictive value for a PCa diagnosis, we hypothesized that correlating 2 variables composed of 3 ratios (1, tPSA/age; 2, tPSA/prostate volume; and 3, fPSA/tPSA; 1 variable including the patient's tPSA and the other, a tPSA value of 50 ng/mL) could operate as a PCa conditions imitating/simulating model. Linear regression analysis was used to derive the coefficient of determination (R 2 ), termed the PCRD index. To estimate the PCRD index's predictive validity, we used the χ 2 test, multiple logistic regression analysis with PCa risk equation formation, calculation of test performance characteristics, and area under the receiver operating characteristic curve analysis using SPSS, version 22 (P regression revealed the PCRD index as an independent PCa predictor, and the formulated risk equation was 91% accurate in predicting the probability of finding PCa. On the receiver operating characteristic analysis, the PCRD index (area under the curve, 0.926) significantly (P < .001) outperformed other, established PCa predictors. The PCRD index effectively predicted the prostate biopsy outcome, correctly identifying 9 of 10 men who were eventually diagnosed with PCa and correctly ruling out PCa for 9 of 10 men who did not have PCa. Its predictive power significantly outperformed established PCa predictors, and the formulated risk equation

  6. Risk Stratification in Differentiated Thyroid Cancer: An Ongoing Process

    Directory of Open Access Journals (Sweden)

    Gal Omry-Orbach

    2016-01-01

    Full Text Available Thyroid cancer is an increasingly common malignancy, with a rapidly rising prevalence worldwide. The social and economic ramifications of the increase in thyroid cancer are multiple. Though mortality from thyroid cancer is low, and most patients will do well, the risk of recurrence is not insignificant, up to 30%. Therefore, it is important to accurately identify those patients who are more or less likely to be burdened by their disease over years and tailor their treatment plan accordingly. The goal of risk stratification is to do just that. The risk stratification process generally starts postoperatively with histopathologic staging, based on the AJCC/UICC staging system as well as others designed to predict mortality. These do not, however, accurately assess the risk of recurrence/persistence. Patients initially considered to be at high risk may ultimately do very well yet be burdened by frequent unnecessary monitoring. Conversely, patients initially thought to be low risk, may not respond to their initial treatment as expected and, if left unmonitored, may have higher morbidity. The concept of risk-adaptive management has been adopted, with an understanding that risk stratification for differentiated thyroid cancer is dynamic and ongoing. A multitude of variables not included in AJCC/UICC staging are used initially to classify patients as low, intermediate, or high risk for recurrence. Over the course of time, a response-to-therapy variable is incorporated, and patients essentially undergo continuous risk stratification. Additional tools such as biochemical markers, genetic mutations, and molecular markers have been added to this complex risk stratification process such that this is essentially a continuum of risk. In recent years, additional considerations have been discussed with a suggestion of pre-operative risk stratification based on certain clinical and/or biologic characteristics. With the increasing prevalence of thyroid cancer but

  7. The EPOS-CC Score: An Integration of Independent, Tumor- and Patient-Associated Risk Factors to Predict 5-years Overall Survival Following Colorectal Cancer Surgery.

    Science.gov (United States)

    Haga, Yoshio; Ikejiri, Koji; Wada, Yasuo; Ikenaga, Masakazu; Koike, Shoichiro; Nakamura, Seiji; Koseki, Masato

    2015-06-01

    Surgical audit is an essential task for the estimation of postoperative outcome and comparison of quality of care. Previous studies on surgical audits focused on short-term outcomes, such as postoperative mortality. We propose a surgical audit evaluating long-term outcome following colorectal cancer surgery. The predictive model for this audit is designated as 'Estimation of Postoperative Overall Survival for Colorectal Cancer (EPOS-CC)'. Thirty-one tumor-related and physiological variables were prospectively collected in 889 patients undergoing elective resection for colorectal cancer between April 2005 and April 2007 in 16 Japanese hospitals. Postoperative overall survival was assessed over a 5-years period. The EPOS-CC score was established by selecting significant variables in a uni- and multivariate analysis and allocating a risk-adjusted multiplication factor to each variable using Cox regression analysis. For validation, the EPOS-CC score was compared to the predictive power of UICC stage. Inter-hospital variability of the observed-to-estimated 5-years survival was assessed to estimate quality of care. Among the 889 patients, 804 (90%) completed the 5-years follow-up. Univariate analysis displayed a significant correlation with 5-years survival for 14 physiological and nine tumor-related variables (p model for the prediction of survival. Risk-adjusted multiplication factors between 1.5 (distant metastasis) and 0.16 (serum sodium level) were accorded to the different variables. The predictive power of EPOS-CC was superior to the one of UICC stage; area under the curve 0.87, 95% CI 0.85-0.90 for EPOS-CC, and 0.80, 0.76-0.83 for UICC stage, p < 0.001. Quality of care did not differ between hospitals. The EPOS-CC score including the independent variables age, performance status, serum sodium level, TNM stage, and lymphatic invasion is superior to the UICC stage in the prediction of 5-years overall survival. This higher accuracy might be explained by the

  8. Epigenetic Biomarkers of Breast Cancer Risk: Across the Breast Cancer Prevention Continuum.

    Science.gov (United States)

    Terry, Mary Beth; McDonald, Jasmine A; Wu, Hui Chen; Eng, Sybil; Santella, Regina M

    2016-01-01

    Epigenetic biomarkers, such as DNA methylation, can increase cancer risk through altering gene expression. The Cancer Genome Atlas (TCGA) Network has demonstrated breast cancer-specific DNA methylation signatures. DNA methylation signatures measured at the time of diagnosis may prove important for treatment options and in predicting disease-free and overall survival (tertiary prevention). DNA methylation measurement in cell free DNA may also be useful in improving early detection by measuring tumor DNA released into the blood (secondary prevention). Most evidence evaluating the use of DNA methylation markers in tertiary and secondary prevention efforts for breast cancer comes from studies that are cross-sectional or retrospective with limited corresponding epidemiologic data, raising concerns about temporality. Few prospective studies exist that are large enough to address whether DNA methylation markers add to the prediction of tertiary and secondary outcomes over and beyond standard clinical measures. Determining the role of epigenetic biomarkers in primary prevention can help in identifying modifiable pathways for targeting interventions and reducing disease incidence. The potential is great for DNA methylation markers to improve cancer outcomes across the prevention continuum. Large, prospective epidemiological studies will provide essential evidence of the overall utility of adding these markers to primary prevention efforts, screening, and clinical care.

  9. Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort.

    Science.gov (United States)

    Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens

    2014-10-15

    To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.

  10. Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study

    NARCIS (Netherlands)

    K. ten Haaf (Kevin); J. Jeon (Jihyoun); M.C. Tammemagi (Martin); S.S. Han (Summer); C.Y. Kong (Chung Yin); S.K. Plevritis (Sylvia); E. Feuer (Eric); H.J. de Koning (Harry); E.W. Steyerberg (Ewout W.); R. Meza (Rafael)

    2017-01-01

    textabstractBackground: Selection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years). Nine previously established risk models were assessed for their ability to identify those most

  11. Household-level disparities in cancer risks from vehicular air pollution in Miami

    International Nuclear Information System (INIS)

    Collins, Timothy W; Grineski, Sara E; Chakraborty, Jayajit

    2015-01-01

    Environmental justice (EJ) research has relied on ecological analyses of socio-demographic data from areal units to determine if particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (a) examining whether statistical associations found for geographic units translate to relationships at the household level; (b) testing alternative explanations for distributional injustices never before investigated; and (c) applying a novel statistical technique appropriate for geographically-clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Miami (Florida) metropolitan area, based on primary household-level survey data and census block-level cancer risk estimates of hazardous air pollutant (HAP) exposure from on-road mobile emission sources. In addition to modeling determinants of on-road HAP cancer risk among all survey participants, two subgroup models are estimated to examine whether determinants of risk differ based on disadvantaged minority (Hispanic and non-Hispanic Black) versus non-Hispanic white racial/ethnic status. Results reveal multiple determinants of risk exposure disparities. In the model including all survey participants, renter-occupancy, Hispanic and non-Hispanic black race/ethnicity, the desire to live close to work/urban services or public transportation, and higher risk perception are associated with greater on-road HAP cancer risk; the desire to live in an amenity-rich environment is associated with less risk. Divergent subgroup model results shed light on the previously unexamined role of racial/ethnic status in shaping determinants of risk exposures. While lower socioeconomic status and higher risk perception predict significantly greater on-road HAP cancer risk among disadvantaged minorities, the desire to live near work/urban services or public transport predict significantly greater risk among

  12. Irregular menses predicts ovarian cancer: Prospective evidence from the Child Health and Development Studies.

    Science.gov (United States)

    Cirillo, Piera M; Wang, Erica T; Cedars, Marcelle I; Chen, Lee-May; Cohn, Barbara A

    2016-09-01

    We tested the hypothesis that irregular menstruation predicts lower risk for ovarian cancer, possibly due to less frequent ovulation. We conducted a 50-year prospective study of 15,528 mothers in the Child Health and Development Studies cohort recruited from the Kaiser Foundation Health Plan from 1959 to 1966. Irregular menstruation was classified via medical record and self-report at age 26. We identified 116 cases and 84 deaths due to ovarian cancer through 2011 via linkage to the California Cancer Registry and Vital Statistics. Contrary to expectation, women with irregular menstrual cycles had a higher risk of ovarian cancer incidence and mortality over the 50-year follow-up. Associations increased with age (p irregular menstruation and ovarian cancer-we unexpectedly found higher risk for women with irregular cycles. These women are easy to identify and many may have polycystic ovarian syndrome. Classifying high-risk phenotypes such as irregular menstruation creates opportunities to find novel early biomarkers, refine clinical screening protocols and potentially develop new risk reduction strategies. These efforts can lead to earlier detection and better survival for ovarian cancer. © 2016 UICC.

  13. Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

    International Nuclear Information System (INIS)

    Mayr, Nina A.; Huang Zhibin; Wang, Jian Z.; Lo, Simon S.; Fan, Joline M.; Grecula, John C.; Sammet, Steffen; Sammet, Christina L.; Jia Guang; Zhang Jun; Knopp, Michael V.; Yuh, William T.C.

    2012-01-01

    Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB 2 –IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity ( 20, >13, and >5 cm 3 , respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 × 10 −8 , 2.0 × 10 −8 ) and disease-specific survival (p = 1.9 × 10 −4 , 2.1 × 10 −6 , 2.5 × 10 −7 , respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2–5 weeks into treatment.

  14. Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

    Directory of Open Access Journals (Sweden)

    Kimmel Marek

    2011-05-01

    Full Text Available Abstract Background Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome. Methods Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data. Results Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET. Conclusions The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.

  15. Nonlinear joint models for individual dynamic prediction of risk of death using Hamiltonian Monte Carlo: application to metastatic prostate cancer

    Directory of Open Access Journals (Sweden)

    Solène Desmée

    2017-07-01

    Full Text Available Abstract Background Joint models of longitudinal and time-to-event data are increasingly used to perform individual dynamic prediction of a risk of event. However the difficulty to perform inference in nonlinear models and to calculate the distribution of individual parameters has long limited this approach to linear mixed-effect models for the longitudinal part. Here we use a Bayesian algorithm and a nonlinear joint model to calculate individual dynamic predictions. We apply this approach to predict the risk of death in metastatic castration-resistant prostate cancer (mCRPC patients with frequent Prostate-Specific Antigen (PSA measurements. Methods A joint model is built using a large population of 400 mCRPC patients where PSA kinetics is described by a biexponential function and the hazard function is a PSA-dependent function. Using Hamiltonian Monte Carlo algorithm implemented in Stan software and the estimated population parameters in this population as priors, the a posteriori distribution of the hazard function is computed for a new patient knowing his PSA measurements until a given landmark time. Time-dependent area under the ROC curve (AUC and Brier score are derived to assess discrimination and calibration of the model predictions, first on 200 simulated patients and then on 196 real patients that are not included to build the model. Results Satisfying coverage probabilities of Monte Carlo prediction intervals are obtained for longitudinal and hazard functions. Individual dynamic predictions provide good predictive performances for landmark times larger than 12 months and horizon time of up to 18 months for both simulated and real data. Conclusions As nonlinear joint models can characterize the kinetics of biomarkers and their link with a time-to-event, this approach could be useful to improve patient’s follow-up and the early detection of most at risk patients.

  16. Bone scintigraphy predicts the risk of spinal cord compression in hormone-refractory prostate cancer

    International Nuclear Information System (INIS)

    Soerdjbalie-Maikoe, Vidija; Pelger, Rob C.M.; Nijeholt, Guus A.B. Lycklama; Arndt, Jan-Willem; Zwinderman, Aeilko H.; Bril, Herman; Papapoulos, Socrates E.; Hamdy, Neveen A.T.

    2004-01-01

    In prostate cancer, confirmation of metastatic involvement of the skeleton has traditionally been achieved by bone scintigraphy, although the widespread availability of prostate-specific antigen (PSA) measurements has tended to eliminate the need for this investigation. The potential of bone scintigraphy to predict skeletal-related events, particularly spinal cord compression, after the onset of hormone refractoriness has never been investigated. The aim of this study was to establish whether a new method of evaluating bone scintigraphy would offer a better predictive value for this complication of the metastatic process than is achieved with currently available grading methods. We studied 84 patients with hormone-refractory prostate cancer who had undergone bone scintigraphy at the time of hormone escape. Tumour grading and parameters of tumour load (PSA and alkaline phosphatase activity) were available in all patients. The incidence of spinal cord compression was documented and all patients were followed up until death. Bone scintigraphy was evaluated by the conventional Soloway grading and by an additional analysis determining total or partial involvement of individual vertebrae. In contrast to the Soloway method, the new method was able to predict spinal cord compression at various spinal levels. Our data suggest that there is still a place for bone scintigraphy in the management of hormone-refractory prostate cancer. (orig.)

  17. Predictive cytogenetic biomarkers for colorectal neoplasia in medium risk patients.

    Science.gov (United States)

    Ionescu, E M; Nicolaie, T; Ionescu, M A; Becheanu, G; Andrei, F; Diculescu, M; Ciocirlan, M

    2015-01-01

    DNA damage and chromosomal alterations in peripheral lymphocytes parallels DNA mutations in tumor tissues. The aim of our study was to predict the presence of neoplastic colorectal lesions by specific biomarkers in "medium risk" individuals (age 50 to 75, with no personal or family of any colorectal neoplasia). We designed a prospective cohort observational study including patients undergoing diagnostic or opportunistic screening colonoscopy. Specific biomarkers were analyzed for each patient in peripheral lymphocytes - presence of micronuclei (MN), nucleoplasmic bridges (NPB) and the Nuclear Division Index (NDI) by the cytokinesis-blocked micronucleus assay (CBMN). Of 98 patients included, 57 were "medium risk" individuals. MN frequency and NPB presence were not significantly different in patients with neoplastic lesions compared to controls. In "medium risk" individuals, mean NDI was significantly lower for patients with any neoplastic lesions (adenomas and adenocarcinomas, AUROC 0.668, p 00.5), for patients with advanced neoplasia (advanced adenoma and adenocarcinoma, AUROC 0.636 p 0.029) as well as for patients with adenocarcinoma (AUROC 0.650, p 0.048), for each comparison with the rest of the population. For a cut-off of 1.8, in "medium risk" individuals, an NDI inferior to that value may predict any neoplastic lesion with a sensitivity of 97.7%, an advanced neoplastic lesion with a sensitivity of 97% and adenocarcinoma with a sensitivity of 94.4%. NDI score may have a role as a colorectal cancer-screening test in "medium risk" individuals. DNA = deoxyribonucleic acid; CRC = colorectal cancer; EU = European Union; WHO = World Health Organization; FOBT = fecal occult blood test; CBMN = cytokinesis-blocked micronucleus assay; MN = micronuclei; NPB = nucleoplasmic bridges; NDI = Nuclear Division Index; FAP = familial adenomatous polyposis; HNPCC = hereditary non-polypoid colorectal cancer; IBD = inflammatory bowel diseases; ROC = receiver operating

  18. Prostate Cancer Probability Prediction By Machine Learning Technique.

    Science.gov (United States)

    Jović, Srđan; Miljković, Milica; Ivanović, Miljan; Šaranović, Milena; Arsić, Milena

    2017-11-26

    The main goal of the study was to explore possibility of prostate cancer prediction by machine learning techniques. In order to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results. Machine learning techniques are the most common techniques for the creation of the predictive models. Therefore in this study several machine techniques were applied and compared. The obtained results were analyzed and discussed. It was concluded that the machine learning techniques could be used for the relevant prediction of prostate cancer.

  19. Factors Influencing Cancer Risk Perception in High Risk Populations: A Systematic Review

    Science.gov (United States)

    2011-01-01

    Background Patients at higher than average risk of heritable cancer may process risk information differently than the general population. However, little is known about clinical, demographic, or psychosocial predictors that may impact risk perception in these groups. The objective of this study was to characterize factors associated with perceived risk of developing cancer in groups at high risk for cancer based on genetics or family history. Methods We searched Ovid MEDLINE, Ovid Embase, Ovid PsycInfo, and Scopus from inception through April 2009 for English-language, original investigations in humans using core concepts of "risk" and "cancer." We abstracted key information and then further restricted articles dealing with perceived risk of developing cancer due to inherited risk. Results Of 1028 titles identified, 53 articles met our criteria. Most (92%) used an observational design and focused on women (70%) with a family history of or contemplating genetic testing for breast cancer. Of the 53 studies, 36 focused on patients who had not had genetic testing for cancer risk, 17 included studies of patients who had undergone genetic testing for cancer risk. Family history of cancer, previous prophylactic tests and treatments, and younger age were associated with cancer risk perception. In addition, beliefs about the preventability and severity of cancer, personality factors such as "monitoring" personality, the ability to process numerical information, as well as distress/worry also were associated with cancer risk perception. Few studies addressed non-breast cancer or risk perception in specific demographic groups (e.g. elderly or minority groups) and few employed theory-driven analytic strategies to decipher interrelationships of factors. Conclusions Several factors influence cancer risk perception in patients at elevated risk for cancer. The science of characterizing and improving risk perception in cancer for high risk groups, although evolving, is still

  20. Factors Influencing Cancer Risk Perception in High Risk Populations: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Tilburt Jon C

    2011-05-01

    Full Text Available Abstract Background Patients at higher than average risk of heritable cancer may process risk information differently than the general population. However, little is known about clinical, demographic, or psychosocial predictors that may impact risk perception in these groups. The objective of this study was to characterize factors associated with perceived risk of developing cancer in groups at high risk for cancer based on genetics or family history. Methods We searched Ovid MEDLINE, Ovid Embase, Ovid PsycInfo, and Scopus from inception through April 2009 for English-language, original investigations in humans using core concepts of "risk" and "cancer." We abstracted key information and then further restricted articles dealing with perceived risk of developing cancer due to inherited risk. Results Of 1028 titles identified, 53 articles met our criteria. Most (92% used an observational design and focused on women (70% with a family history of or contemplating genetic testing for breast cancer. Of the 53 studies, 36 focused on patients who had not had genetic testing for cancer risk, 17 included studies of patients who had undergone genetic testing for cancer risk. Family history of cancer, previous prophylactic tests and treatments, and younger age were associated with cancer risk perception. In addition, beliefs about the preventability and severity of cancer, personality factors such as "monitoring" personality, the ability to process numerical information, as well as distress/worry also were associated with cancer risk perception. Few studies addressed non-breast cancer or risk perception in specific demographic groups (e.g. elderly or minority groups and few employed theory-driven analytic strategies to decipher interrelationships of factors. Conclusions Several factors influence cancer risk perception in patients at elevated risk for cancer. The science of characterizing and improving risk perception in cancer for high risk groups, although

  1. Combination antiretroviral therapy and cancer risk

    DEFF Research Database (Denmark)

    Borges, Álvaro H

    2017-01-01

    PURPOSE OF REVIEW: To review the newest research about the effects of combination antiretroviral therapy (cART) on cancer risk. RECENT FINDINGS: HIV+ persons are at increased risk of cancer. As this risk is higher for malignancies driven by viral and bacterial coinfections, classifying malignanci......ART initiation in reducing cancer risk, understand the relationship between long-term cART exposure and cancer incidence and assess whether adjuvant anti-inflammatory therapies can reduce cancer risk during treated HIV infection.......PURPOSE OF REVIEW: To review the newest research about the effects of combination antiretroviral therapy (cART) on cancer risk. RECENT FINDINGS: HIV+ persons are at increased risk of cancer. As this risk is higher for malignancies driven by viral and bacterial coinfections, classifying malignancies...... into infection-related and infection-unrelated has been an emerging trend. Cohorts have detected major reductions in the incidence of Kaposi sarcoma and non-Hodgkin lymphoma (NHL) following cART initiation among immunosuppressed HIV+ persons. However, recent randomized data indicate that cART reduces risk...

  2. Comparison of risk of radiogenic second cancer following photon and proton craniospinal irradiation for a pediatric medulloblastoma patient

    Science.gov (United States)

    Zhang, Rui; Howell, Rebecca M.; Giebeler, Annelise; Taddei, Phillip J.; Mahajan, Anita; Newhauser, Wayne D.

    2013-02-01

    Pediatric patients who received radiation therapy are at risk of developing side effects such as radiogenic second cancer. We compared proton and photon therapies in terms of the predicted risk of second cancers for a 4 year old medulloblastoma patient receiving craniospinal irradiation (CSI). Two CSI treatment plans with 23.4 Gy or Gy (RBE) prescribed dose were computed: a three-field 6 MV photon therapy plan and a four-field proton therapy plan. The primary doses for both plans were determined using a commercial treatment planning system. Stray radiation doses for proton therapy were determined from Monte Carlo simulations, and stray radiation doses for photon therapy were determined from measured data. Dose-risk models based on the Biological Effects of Ionization Radiation VII report were used to estimate the risk of second cancer in eight tissues/organs. Baseline predictions of the relative risk for each organ were always less for proton CSI than for photon CSI at all attained ages. The total lifetime attributable risk of the incidence of second cancer considered after proton CSI was much lower than that after photon CSI, and the ratio of lifetime risk was 0.18. Uncertainty analysis revealed that the qualitative findings of this study were insensitive to any plausible changes of dose-risk models and mean radiation weighting factor for neutrons. Proton therapy confers lower predicted risk of second cancer than photon therapy for the pediatric medulloblastoma patient.

  3. Long working hours and cancer risk

    DEFF Research Database (Denmark)

    Heikkila, Katriina; Nyberg, Solja T.; Madsen, Ida E. H.

    2016-01-01

    in 116 462 men and women who were free of cancer at baseline. Incident cancers were ascertained from national cancer, hospitalisation and death registers; weekly working hours were self-reported. Results: During median follow-up of 10.8 years, 4371 participants developed cancer (n colorectal cancer: 393......Background: Working longer than the maximum recommended hours is associated with an increased risk of cardiovascular disease, but the relationship of excess working hours with incident cancer is unclear. Methods: This multi-cohort study examined the association between working hours and cancer risk......; n lung cancer: 247; n breast cancer: 833; and n prostate cancer: 534). We found no clear evidence for an association between working hours and the overall cancer risk. Working hours were also unrelated the risk of incident colorectal, lung or prostate cancers. Working greater than or equal to55 h...

  4. Quality of life in pediatric cancer survivors: contributions of parental distress and psychosocial family risk.

    Science.gov (United States)

    Racine, N M; Khu, M; Reynolds, K; Guilcher, G M T; Schulte, F S M

    2018-02-01

    Pediatric survivors of childhood cancer are at increased risk of poor quality of life and social-emotional outcomes following treatment. The relationship between parent psychological distress and child adjustment in pediatric cancer survivors has been well established. However, limited research has examined the factors that may buffer this association. The current study examined the associations between psychosocial family risk factors, parental psychological distress, and health-related quality of life (hrql) in pediatric cancer survivors. Fifty-two pediatric cancer survivors (34 males, 18 females, mean age = 11.92) and their parents were recruited from a long-term cancer survivor clinic. Children and their parents who consented to participate completed the Pediatric Quality of Life Inventory 4.0. Parents completed a demographic information form, the Psychosocial Assessment Tool (pat 2.0) and the Brief Symptom Inventory (bsi). The Intensity of Treatment Rating (itr-3) was evaluated by the research team. Multiple regression analyses revealed that parental psychological distress negatively predicted parent-reported hrql, while treatment intensity, gender, and psychosocial risk negatively predicted parent and child-reported hrql. Psychosocial risk moderated the association between parent psychological distress and parent-reported child hrql ( p = 0.03), whereby parents with high psychological distress but low levels of psychosocial risk reported their children to have higher hrql. Low levels of family psychosocial risk buffer the impact of parent psychological distress on child hrql in pediatric cancer survivors. The findings highlight the importance of identifying parents and families with at-risk psychological distress and psychosocial risk in order to provide targeted support interventions to mitigate the impact on hrql.

  5. Microarray-based cancer prediction using soft computing approach.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2009-05-26

    One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

  6. Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

    Science.gov (United States)

    Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

    2017-09-05

    Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

  7. Work stress and risk of cancer

    DEFF Research Database (Denmark)

    Heikkilä, Katriina; Nyberg, Solja T; Theorell, Töres

    2013-01-01

    To investigate whether work related stress, measured and defined as job strain, is associated with the overall risk of cancer and the risk of colorectal, lung, breast, or prostate cancers.......To investigate whether work related stress, measured and defined as job strain, is associated with the overall risk of cancer and the risk of colorectal, lung, breast, or prostate cancers....

  8. Is it possible to predict the presence of colorectal cancer in a blood test? A probabilistic approach method.

    Science.gov (United States)

    Navarro Rodríguez, José Manuel; Gallego Plazas, Javier; Borrás Rocher, Fernando; Calpena Rico, Rafael; Ruiz Macia, José Antonio; Morcillo Ródenas, Miguel Ángel

    2017-10-01

    The assessment of the state of immunosurveillance (the ability of the organism to prevent the development of neoplasias) in the blood has prognostic implications of interest in colorectal cancer. We evaluated and quantified a possible predictive character of the disease in a blood test using a mathematical interaction index of several blood parameters. The predictive capacity of the index to detect colorectal cancer was also assessed. We performed a retrospective case-control study of a comparative analysis of the distribution of blood parameters in 266 patients with colorectal cancer and 266 healthy patients during the period from 2009 to 2013. Statistically significant differences (p indexes (neutrophil to lymphocyte ratio and platelet to lymphocyte ratio), hemoglobin, hematocrit and eosinophil levels. These differences allowed the design of a blood analytical profile that calculates the risk of colorectal cancer. This risk profile can be quantified via a mathematical formula with a probabilistic capacity to identify patients with the highest risk of the presence of colorectal cancer (area under the ROC curve = 0.85). We showed that a colorectal cancer predictive character exists in blood which can be quantified by an interaction index of several blood parameters. The design and development of interaction indexes of blood parameters constitutes an interesting research line for the development and improvement of programs for the screening of colorectal cancer.

  9. Cognitive and emotional factors predicting decisional conflict among high-risk breast cancer survivors who receive uninformative BRCA1/2 results.

    Science.gov (United States)

    Rini, Christine; O'Neill, Suzanne C; Valdimarsdottir, Heiddis; Goldsmith, Rachel E; Jandorf, Lina; Brown, Karen; DeMarco, Tiffani A; Peshkin, Beth N; Schwartz, Marc D

    2009-09-01

    To investigate high-risk breast cancer survivors' risk reduction decision making and decisional conflict after an uninformative BRCA1/2 test. Prospective, longitudinal study of 182 probands undergoing BRCA1/2 testing, with assessments 1-, 6-, and 12-months postdisclosure. Primary predictors were health beliefs and emotional responses to testing assessed 1-month postdisclosure. Main outcomes included women's perception of whether they had made a final risk management decision (decision status) and decisional conflict related to this issue. There were four patterns of decision making, depending on how long it took women to make a final decision and the stability of their decision status across assessments. Late decision makers and nondecision makers reported the highest decisional conflict; however, substantial numbers of women--even early and intermediate decision makers--reported elevated decisional conflict. Analyses predicting decisional conflict 1- and 12-months postdisclosure found that, after accounting for control variables and decision status, health beliefs and emotional factors predicted decisional conflict at different timepoints, with health beliefs more important 1 month after test disclosure and emotional factors more important 1 year later. Many of these women may benefit from decision making assistance. Copyright 2009 APA, all rights reserved.

  10. Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

    Directory of Open Access Journals (Sweden)

    Raed I. Hamed

    2015-04-01

    Full Text Available Esophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs, where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models.

  11. Causes of Mortality After Dose-Escalated Radiation Therapy and Androgen Deprivation for High-Risk Prostate Cancer

    International Nuclear Information System (INIS)

    Tendulkar, Rahul D.; Hunter, Grant K.; Reddy, Chandana A.; Stephans, Kevin L.; Ciezki, Jay P.; Abdel-Wahab, May; Stephenson, Andrew J.; Klein, Eric A.; Mahadevan, Arul; Kupelian, Patrick A.

    2013-01-01

    Purpose: Men with high-risk prostate cancer have other competing causes of mortality; however, current risk stratification schema do not account for comorbidities. We aim to identify the causes of death and factors predictive for mortality in this population. Methods and Materials: A total of 660 patients with high-risk prostate cancer were treated with definitive high-dose external beam radiation therapy (≥74 Gy) and androgen deprivation (AD) between 1996 and 2009 at a single institution. Cox proportional hazards regression analysis was conducted to determine factors predictive of survival. Results: The median radiation dose was 78 Gy, median duration of AD was 6 months, and median follow-up was 74 months. The 10-year overall survival (OS) was 60.6%. Prostate cancer was the leading single cause of death, with 10-year mortality of 14.1% (95% CI 10.7-17.6), compared with other cancers (8.4%, 95% CI 5.7-11.1), cardiovascular disease (7.3%, 95% CI 4.7-9.9), and all other causes (10.4%, 95% CI 7.2-13.6). On multivariate analysis, older age (HR 1.55, P=.002) and Charlson comorbidity index score (CS) ≥1 (HR 2.20, P<.0001) were significant factors predictive of OS, whereas Gleason score, T stage, prostate-specific antigen, duration of AD, radiation dose, smoking history, and body mass index were not. Men younger than 70 years of age with CS = 0 were more likely to die of prostate cancer than any other cause, whereas older men or those with CS ≥1 more commonly suffered non-prostate cancer death. The cumulative incidences of prostate cancer-specific mortality were similar regardless of age or comorbidities (P=.60). Conclusions: Men with high-risk prostate cancer are more likely to die of causes other than prostate cancer, except for the subgroup of men younger than 70 years of age without comorbidities. Only older age and presence of comorbidities significantly predicted for OS, whereas prostate cancer- and treatment-related factors did not

  12. Cancer risks: Strategies for elimination

    International Nuclear Information System (INIS)

    Bannasch, P.

    1987-01-01

    This book deals with the possibilities for identifying and eliminating cancer risk factors. The current state of knowledge on the detection, assessment and elimination of chemical, physical (radiation), and biological (viruses) risk factors are comprehensively presented in 15 contributions. Chemical risk factors resulting from smoking and environmental contamination are given special attention. The coverage of cancer risks by radiation includes some of the consequences of the Chernobyl disaster. Finally, the discussion of the possible risks that certain viruses hold for cancer in man is intended to further the development of vaccinations against these viral infections. The information is directed not only at specialists, but also at a wider interested audience. Its primary aim is to convey established findings that are already being used for cancer prevention. Furthermore, the book aims to promote more intense research in the field of primary cancer prevention. Contents: General aspects; chemical carcinogens: Risk assessment; chemical carcinogens: Primary prevention; physical carcinogens - Oncogenic viruses and subject index

  13. Breast Cancer Risk in American Women

    Science.gov (United States)

    ... of Breast & Gynecologic Cancers Breast Cancer Screening Research Breast Cancer Risk in American Women On This Page What ... risk of developing the disease. Personal history of breast cancer : Women who have had breast cancer are more ...

  14. [Risk Prediction Using Routine Data: Development and Validation of Multivariable Models Predicting 30- and 90-day Mortality after Surgical Treatment of Colorectal Cancer].

    Science.gov (United States)

    Crispin, Alexander; Strahwald, Brigitte; Cheney, Catherine; Mansmann, Ulrich

    2018-06-04

    Quality control, benchmarking, and pay for performance (P4P) require valid indicators and statistical models allowing adjustment for differences in risk profiles of the patient populations of the respective institutions. Using hospital remuneration data for measuring quality and modelling patient risks has been criticized by clinicians. Here we explore the potential of prediction models for 30- and 90-day mortality after colorectal cancer surgery based on routine data. Full census of a major statutory health insurer. Surgical departments throughout the Federal Republic of Germany. 4283 and 4124 insurants with major surgery for treatment of colorectal cancer during 2013 and 2014, respectively. Age, sex, primary and secondary diagnoses as well as tumor locations as recorded in the hospital remuneration data according to §301 SGB V. 30- and 90-day mortality. Elixhauser comorbidities, Charlson conditions, and Charlson scores were generated from the ICD-10 diagnoses. Multivariable prediction models were developed using a penalized logistic regression approach (logistic ridge regression) in a derivation set (patients treated in 2013). Calibration and discrimination of the models were assessed in an internal validation sample (patients treated in 2014) using calibration curves, Brier scores, receiver operating characteristic curves (ROC curves) and the areas under the ROC curves (AUC). 30- and 90-day mortality rates in the learning-sample were 5.7 and 8.4%, respectively. The corresponding values in the validation sample were 5.9% and once more 8.4%. Models based on Elixhauser comorbidities exhibited the highest discriminatory power with AUC values of 0.804 (95% CI: 0.776 -0.832) and 0.805 (95% CI: 0.782-0.828) for 30- and 90-day mortality. The Brier scores for these models were 0.050 (95% CI: 0.044-0.056) and 0.067 (95% CI: 0.060-0.074) and similar to the models based on Charlson conditions. Regardless of the model, low predicted probabilities were well calibrated, while

  15. Diabetes, insulin and cancer risk

    OpenAIRE

    Yang, Xi-Lin; Chan, Juliana CN

    2012-01-01

    There is a consensus that both type 1 and type 2 diabetes are associated with a spectrum of cancers but the underlying mechanisms are largely unknown. On the other hand, there are ongoing debates about the risk association of insulin use with cancer. We have briefly reviewed recent related research on exploration of risk factors for cancer and pharmacoepidemiological investigations into drug use in diabetes on the risk of cancer, as well as the current understanding of metabolic pathways impl...

  16. Predicted vitamin D status and colon cancer recurrence and mortality in CALGB 89803 (Alliance).

    Science.gov (United States)

    Fuchs, M A; Yuan, C; Sato, K; Niedzwiecki, D; Ye, X; Saltz, L B; Mayer, R J; Mowat, R B; Whittom, R; Hantel, A; Benson, A; Atienza, D; Messino, M; Kindler, H; Venook, A; Innocenti, F; Warren, R S; Bertagnolli, M M; Ogino, S; Giovannucci, E L; Horvath, E; Meyerhardt, J A; Ng, K

    2017-06-01

    Observational studies suggest that higher levels of 25-hydroxyvitamin D3 (25(OH)D) are associated with a reduced risk of colorectal cancer and improved survival of colorectal cancer patients. However, the influence of vitamin D status on cancer recurrence and survival of patients with stage III colon cancer is unknown. We prospectively examined the influence of post-diagnosis predicted plasma 25(OH)D on outcome among 1016 patients with stage III colon cancer who were enrolled in a National Cancer Institute-sponsored adjuvant therapy trial (CALGB 89803). Predicted 25(OH)D scores were computed using validated regression models. We examined the influence of predicted 25(OH)D scores on cancer recurrence and mortality (disease-free survival; DFS) using Cox proportional hazards. Patients in the highest quintile of predicted 25(OH)D score had an adjusted hazard ratio (HR) for colon cancer recurrence or mortality (DFS) of 0.62 (95% confidence interval [CI], 0.44-0.86), compared with those in the lowest quintile (Ptrend = 0.005). Higher predicted 25(OH)D score was also associated with a significant improvement in recurrence-free survival and overall survival (Ptrend = 0.01 and 0.0004, respectively). The benefit associated with higher predicted 25(OH)D score appeared consistent across predictors of cancer outcome and strata of molecular tumor characteristics, including microsatellite instability and KRAS, BRAF, PIK3CA, and TP53 mutation status. Higher predicted 25(OH)D levels after a diagnosis of stage III colon cancer may be associated with decreased recurrence and improved survival. Clinical trials assessing the benefit of vitamin D supplementation in the adjuvant setting are warranted. NCT00003835. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  17. Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.

    Directory of Open Access Journals (Sweden)

    Heewon Park

    Full Text Available The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc. and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.

  18. Optimized outcome prediction in breast cancer by combining the 70-gene signature with clinical risk prediction algorithms

    NARCIS (Netherlands)

    Drukker, C.A.; Nijenhuis, M.V.; Bueno de Mesquita, J.M.; Retel, V.P.; Retel, Valesca; van Harten, Willem H.; van Tinteren, H.; Wesseling, J.; Schmidt, M.K.; van 't Veer, L.J.; Sonke, G.S.; Rutgers, E.J.T.; van de Vijver, M.J.; Linn, S.C.

    2014-01-01

    Clinical guidelines for breast cancer treatment differ in their selection of patients at a high risk of recurrence who are eligible to receive adjuvant systemic treatment (AST). The 70-gene signature is a molecular tool to better guide AST decisions. The aim of this study was to evaluate whether

  19. Second cancers after conservative surgery and radiation for stages I-II breast cancer: identifying a subset of women at increased risk

    International Nuclear Information System (INIS)

    Fowble, Barbara; Hanlon, Alexandra; Freedman, Gary; Nicolaou, Nicos; Anderson, Penny

    2001-01-01

    second malignancy. A positive family history increased the risk of contralateral breast cancer, but not non-breast cancer malignancies. The risk of a contralateral breast cancer increased as the number of affected relatives increased. Tamoxifen resulted in a nonsignificant decrease in contralateral breast cancer and an increase in non-breast cancer second malignancies. The 5-and 10-year cumulative incidences for leukemia and lung cancer were 0.08% and 0.2%, and 0.8% and 1%, respectively. There was no significant effect of chemotherapy or the regions treated with radiation on contralateral breast cancer or non-breast cancer second malignancy. The most common types of second non-breast cancer malignancies were skin cancers, followed by gynecologic malignancies (endometrial), and gastrointestinal malignancies (colorectal and pancreas). Conclusion: The 10-years cumulative incidence of a second cancer in this study was 16%. Young age and family history predicted for an increased risk of contralateral breast cancer, and older age predicted for an increased risk of non-breast cancer malignancy. The majority of patients treated with conservative surgery and radiation with or without adjuvant systemic therapy will not develop a second cancer. Long-term follow-up is important to document the risk and patterns of second cancer, and knowledge of this risk and the patterns will influence surveillance and prevention strategies

  20. Common breast cancer risk alleles and risk assessment

    DEFF Research Database (Denmark)

    Näslund-Koch, C; Nordestgaard, B G; Bojesen, S E

    2017-01-01

    general population were followed in Danish health registries for up to 21 years after blood sampling. After genotyping 72 breast cancer risk loci, each with 0-2 alleles, the sum for each individual was calculated. We used the simple allele sum instead of the conventional polygenic risk score......, as it is likely more sensitive in detecting associations with risks of other endpoints than breast cancer. RESULTS: Breast cancer incidence in the 19,010 women was increased across allele sum quintiles (log-rank trend test; p=1*10(-12)), but not incidence of other cancers (p=0.41). Age- and study-adjusted hazard...... ratio for the 5(th) vs. 1(st) allele sum quintile was 1.82(95% confidence interval;1.53-2.18). Corresponding hazard ratios per allele were 1.04(1.03-1.05) and 1.05(1.02-1.08) for breast cancer incidence and mortality, similar across risk factors. In 50-year old women, the starting age for screening...

  1. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

    Science.gov (United States)

    Milne, Roger L; Kuchenbaecker, Karoline B; Michailidou, Kyriaki; Beesley, Jonathan; Kar, Siddhartha; Lindström, Sara; Hui, Shirley; Lemaçon, Audrey; Soucy, Penny; Dennis, Joe; Jiang, Xia; Rostamianfar, Asha; Finucane, Hilary; Bolla, Manjeet K; McGuffog, Lesley; Wang, Qin; Aalfs, Cora M; Adams, Marcia; Adlard, Julian; Agata, Simona; Ahmed, Shahana; Ahsan, Habibul; Aittomäki, Kristiina; Al-Ejeh, Fares; Allen, Jamie; Ambrosone, Christine B; Amos, Christopher I; Andrulis, Irene L; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Auber, Bernd; Auer, Paul L; Ausems, Margreet G E M; Azzollini, Jacopo; Bacot, François; Balmaña, Judith; Barile, Monica; Barjhoux, Laure; Barkardottir, Rosa B; Barrdahl, Myrto; Barnes, Daniel; Barrowdale, Daniel; Baynes, Caroline; Beckmann, Matthias W; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Bignon, Yves-Jean; Blazer, Kathleen R; Blok, Marinus J; Blomqvist, Carl; Blot, William; Bobolis, Kristie; Boeckx, Bram; Bogdanova, Natalia V; Bojesen, Anders; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Bozsik, Aniko; Bradbury, Angela R; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Bressac-de Paillerets, Brigitte; Brewer, Carole; Brinton, Louise; Broberg, Per; Brooks-Wilson, Angela; Brunet, Joan; Brüning, Thomas; Burwinkel, Barbara; Buys, Saundra S; Byun, Jinyoung; Cai, Qiuyin; Caldés, Trinidad; Caligo, Maria A; Campbell, Ian; Canzian, Federico; Caron, Olivier; Carracedo, Angel; Carter, Brian D; Castelao, J Esteban; Castera, Laurent; Caux-Moncoutier, Virginie; Chan, Salina B; Chang-Claude, Jenny; Chanock, Stephen J; Chen, Xiaoqing; Cheng, Ting-Yuan David; Chiquette, Jocelyne; Christiansen, Hans; Claes, Kathleen B M; Clarke, Christine L; Conner, Thomas; Conroy, Don M; Cook, Jackie; Cordina-Duverger, Emilie; Cornelissen, Sten; Coupier, Isabelle; Cox, Angela; Cox, David G; Cross, Simon S; Cuk, Katarina; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Damiola, Francesca; Darabi, Hatef; Davidson, Rosemarie; De Leeneer, Kim; Devilee, Peter; Dicks, Ed; Diez, Orland; Ding, Yuan Chun; Ditsch, Nina; Doheny, Kimberly F; Domchek, Susan M; Dorfling, Cecilia M; Dörk, Thilo; dos-Santos-Silva, Isabel; Dubois, Stéphane; Dugué, Pierre-Antoine; Dumont, Martine; Dunning, Alison M; Durcan, Lorraine; Dwek, Miriam; Dworniczak, Bernd; Eccles, Diana; Eeles, Ros; Ehrencrona, Hans; Eilber, Ursula; Ejlertsen, Bent; Ekici, Arif B; Engel, Christoph; Eriksson, Mikael; Fachal, Laura; Faivre, Laurence; Fasching, Peter A; Faust, Ulrike; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Foulkes, William D; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gabrielson, Marike; Gaddam, Pragna; Gammon, Marilie D; Ganz, Patricia A; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; García-Sáenz, José A; Gaudet, Mia M; Gauthier-Villars, Marion; Gehrig, Andrea; Georgoulias, Vassilios; Gerdes, Anne-Marie; Giles, Graham G; Glendon, Gord; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Goodfellow, Paul; Greene, Mark H; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Gschwantler-Kaulich, Daphne; Guénel, Pascal; Guo, Qi; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hallberg, Emily; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Hansen, Thomas V O; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Healey, Catherine S; Hein, Alexander; Helbig, Sonja; Henderson, Alex; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Hodgson, Shirley; Hogervorst, Frans B; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Bob; Hopper, John L; Hu, Chunling; Huang, Guanmengqian; Hulick, Peter J; Humphreys, Keith; Hunter, David J; Imyanitov, Evgeny N; Isaacs, Claudine; Iwasaki, Motoki; Izatt, Louise; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Janni, Wolfgang; Jensen, Uffe Birk; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kast, Karin; Keeman, Renske; Kerin, Michael J; Kets, Carolien M; Keupers, Machteld; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Konstantopoulou, Irene; Kosma, Veli-Matti; Kristensen, Vessela N; Kruse, Torben A; Kwong, Ava; Lænkholm, Anne-Vibeke; Laitman, Yael; Lalloo, Fiona; Lambrechts, Diether; Landsman, Keren; Lasset, Christine; Lazaro, Conxi; Le Marchand, Loic; Lecarpentier, Julie; Lee, Andrew; Lee, Eunjung; Lee, Jong Won; Lee, Min Hyuk; Lejbkowicz, Flavio; Lesueur, Fabienne; Li, Jingmei; Lilyquist, Jenna; Lincoln, Anne; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Loud, Jennifer T; Lubinski, Jan; Luccarini, Craig; Lush, Michael; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Kostovska, Ivana Maleva; Malone, Kathleen E; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Martens, John W M; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; Mazoyer, Sylvie; McLean, Catriona; Meijers-Heijboer, Hanne; Menéndez, Primitiva; Meyer, Jeffery; Miao, Hui; Miller, Austin; Miller, Nicola; Mitchell, Gillian; Montagna, Marco; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Nadesan, Sue; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Nevelsteen, Ines; Niederacher, Dieter; Nielsen, Sune F; Nordestgaard, Børge G; Norman, Aaron; Nussbaum, Robert L; Olah, Edith; Olopade, Olufunmilayo I; Olson, Janet E; Olswold, Curtis; Ong, Kai-ren; Oosterwijk, Jan C; Orr, Nick; Osorio, Ana; Pankratz, V Shane; Papi, Laura; Park-Simon, Tjoung-Won; Paulsson-Karlsson, Ylva; Lloyd, Rachel; Pedersen, Inge Søkilde; Peissel, Bernard; Peixoto, Ana; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Pfeiler, Georg; Phelan, Catherine M; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Poppe, Bruce; Porteous, Mary E; Prentice, Ross; Presneau, Nadege; Prokofieva, Darya; Pugh, Elizabeth; Pujana, Miquel Angel; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rantala, Johanna; Rappaport-Fuerhauser, Christine; Rennert, Gad; Rennert, Hedy S; Rhenius, Valerie; Rhiem, Kerstin; Richardson, Andrea; Rodriguez, Gustavo C; Romero, Atocha; Romm, Jane; Rookus, Matti A; Rudolph, Anja; Ruediger, Thomas; Saloustros, Emmanouil; Sanders, Joyce; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Schwentner, Lukas; Scott, Christopher; Scott, Rodney J; Seal, Sheila; Senter, Leigha; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Xin; Shimelis, Hermela; Shrubsole, Martha J; Shu, Xiao-Ou; Side, Lucy E; Singer, Christian F; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Spurdle, Amanda B; Stegmaier, Christa; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Surowy, Harald; Sutter, Christian; Swerdlow, Anthony; Szabo, Csilla I; Tamimi, Rulla M; Tan, Yen Y; Taylor, Jack A; Tejada, Maria-Isabel; Tengström, Maria; Teo, Soo H; Terry, Mary B; Tessier, Daniel C; Teulé, Alex; Thöne, Kathrin; Thull, Darcy L; Tibiletti, Maria Grazia; Tihomirova, Laima; Tischkowitz, Marc; Toland, Amanda E; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Tranchant, Martine; Truong, Thérèse; Tucker, Kathy; Tung, Nadine; Tyrer, Jonathan; Ulmer, Hans-Ulrich; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vega, Ana; Viel, Alessandra; Vijai, Joseph; Vincent, Daniel; Vollenweider, Jason; Walker, Lisa; Wang, Zhaoming; Wang-Gohrke, Shan; Wappenschmidt, Barbara; Weinberg, Clarice R; Weitzel, Jeffrey N; Wendt, Camilla; Wesseling, Jelle; Whittemore, Alice S; Wijnen, Juul T; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yang, Xiaohong R; Yannoukakos, Drakoulis; Zaffaroni, Daniela; Zheng, Wei; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Zorn, Kristin K; Gago-Dominguez, Manuela; Mannermaa, Arto; Olsson, Håkan; Teixeira, Manuel R; Stone, Jennifer; Offit, Kenneth; Ottini, Laura; Park, Sue K; Thomassen, Mads; Hall, Per; Meindl, Alfons; Schmutzler, Rita K; Droit, Arnaud; Bader, Gary D; Pharoah, Paul D P; Couch, Fergus J; Easton, Douglas F; Kraft, Peter; Chenevix-Trench, Georgia; García-Closas, Montserrat; Schmidt, Marjanka K; Antoniou, Antonis C; Simard, Jacques

    2018-01-01

    Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 14% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer. PMID:29058716

  2. Germline mutation in RNASEL predicts increased risk of head and neck, uterine cervix and breast cancer.

    Directory of Open Access Journals (Sweden)

    Bo Eskerod Madsen

    Full Text Available UNLABELLED: THE BACKGROUND: Ribonuclease L (RNASEL, encoding the 2'-5'-oligoadenylate (2-5A-dependent RNase L, is a key enzyme in the interferon induced antiviral and anti-proliferate pathway. Mutations in RNASEL segregate with the disease in prostate cancer families and specific genotypes are associated with an increased risk of prostate cancer. Infection by human papillomavirus (HPV is the major risk factor for uterine cervix cancer and for a subset of head and neck squamous cell carcinomas (HNSCC. HPV, Epstein Barr virus (EBV and sequences from mouse mammary tumor virus (MMTV have been detected in breast tumors, and the presence of integrated SV40 T/t antigen in breast carcinomas correlates with an aggressive phenotype and poor prognosis. A genetic predisposition could explain why some viral infections persist and induce cancer, while others disappear spontaneously. This points at RNASEL as a strong susceptibility gene. METHODOLOGY/PRINCIPAL FINDINGS: To evaluate the implication of an abnormal activity of RNase L in the onset and development of viral induced cancers, the study was initiated by searching for germline mutations in patients diagnosed with uterine cervix cancer. The rationale behind is that close to 100% of the cervix cancer patients have a persistent HPV infection, and if a defective RNase L were responsible for the lack of ability to clear the HPV infection, we would expect to find a wide spectrum of mutations in these patients, leading to a decreased RNase L activity. The HPV genotype was established in tumor DNA from 42 patients diagnosed with carcinoma of the uterine cervix and somatic tissue from these patients was analyzed for mutations by direct sequencing of all coding and regulatory regions of RNASEL. Fifteen mutations, including still uncharacterized, were identified. The genotype frequencies of selected single nucleotide polymorphisms (SNPs established in the cervix cancer patients were compared between 382 patients

  3. Lifetime attributable risk as an alternative to effective dose to describe the risk of cancer for patients in diagnostic and therapeutic nuclear medicine

    Science.gov (United States)

    Andersson, Martin; Eckerman, Keith; Mattsson, Sören

    2017-12-01

    The aim of this study is to implement lifetime attributable risk (LAR) predictions of cancer for patients of various age and gender, undergoing diagnostic investigations or treatments in nuclear medicine and to compare the outcome with a population risk estimate using effective dose and the International Commission on Radiological Protection risk coefficients. The radiation induced risk of cancer occurrence (incidence) or death from four nuclear medicine procedures are estimated for both male and female between 0 and 120 years. Estimations of cancer risk are performed using recommended administered activities for two diagnostic (18F-FDG and 99mTc-phosphonate complex) and two therapeutic (131I-iodide and 223Ra-dichloride) radiopharmaceuticals to illustrate the use of cancer risk estimations in nuclear medicine. For 18F-FDG, the cancer incidence for a male of 5, 25, 50 and 75 years at exposure is 0.0021, 0.0010, 0.0008 and 0.0003, respectively. For 99mTc phosphonates complex the corresponding values are 0.000 59, 0.000 34, 0.000 27 and 0.000 13, respectively. For an 131I-iodide treatment with 3.7 GBq and 1% uptake 24 h after administration, the cancer incidence for a male of 25, 50 and 75 years at exposure is 0.041, 0.029 and 0.012, respectively. For 223Ra-dichloride with an administration of 21.9 MBq the cancer incidence for a male of 25, 50 and 75 years is 0.31, 0.21 and 0.09, respectively. The LAR estimations are more suitable in health care situations involving individual patients or specific groups of patients than the health detriment based on effective dose, which represents a population average. The detriment consideration in effective dose adjusts the cancer incidence for suffering of non-lethal cancers while LAR predicts morbidity (incidence) or mortality (cancer). The advantages of these LARs are that they are gender and age specific, allowing risk estimations for specific patients or subgroups thus better representing individuals in health care

  4. Cancer-related symptoms predict psychological wellbeing among prostate cancer survivors: results from the PiCTure study.

    Science.gov (United States)

    Sharp, Linda; O'Leary, Eamonn; Kinnear, Heather; Gavin, Anna; Drummond, Frances J

    2016-03-01

    Prostate cancer treatments are associated with a range of symptoms and physical side-effects. Cancer can also adversely impact on psychological wellbeing. Because many prostate cancer-related symptoms and side-effects are potentially modifiable, we investigated associations between symptoms and psychological wellbeing among prostate cancer survivors. Postal questionnaires were distributed to men diagnosed with prostate cancer 2-18 years previously identified through cancer registries. General and prostate cancer-specific symptoms were assessed using the EORTC QLQ-C30 and QLQ-PR25, with higher symptom scores indicating more/worse symptomatology. Psychological wellbeing was assessed by the DASS-21. Associations between symptoms and each outcome were investigated using multivariate logistic regression, controlling for socio-demographic and clinical factors. A total 3348 men participated (response rate = 54%). Seventeen percent (95%CI 15.2%-17.9%), 16% (95%CI 15.1%-17.8%) and 11% (95%CI 9.5%-11.8%) of survivors scored in the range for depression, anxiety and distress on the DASS scales, respectively. In multivariate models, risk of depression on the DASS scale was significantly higher in men with higher urinary and androgen deprivation therapy (ADT)-related symptoms, and higher scores for fatigue, insomnia and financial difficulties. Risk of anxiety on the DASS scale was higher in men with higher scores for urinary, bowel and ADT-related symptoms and fatigue, dyspnoea and financial difficulties. Risk of distress on the DASS scale was positively associated with urinary, bowel and ADT-related symptoms, fatigue, insomnia and financial difficulties. Cancer-related symptoms significantly predict psychological wellbeing among prostate cancer survivors. Greater use of interventions and medications and to alleviate symptoms might improve psychological wellbeing of prostate cancer survivors. Copyright © 2015 John Wiley & Sons, Ltd.

  5. Predictions of lung cancer based on county averages for indoor radon versus the historic incidence of regional lung cancer

    International Nuclear Information System (INIS)

    Mose, D.G.; Chrosniak, C.E.; Mushrush, G.W.

    1992-01-01

    After a decade of effort to determine the health risk associated with indoor radon, the efforts of the US Environmental Protection Agency have prevailed in the US, and 4 pCi/1 is commonly used as an Action Level. Proposals by other groups supporting lower or higher Action Levels have failed, largely due to paucity of information supporting any particular level of indoor radon. The authors' studies have compared indoor radon for zip code and county size areas with parameters such as geology, precipitation and home construction. Their attempts to verify the relative levels of lung cancer using US-EPA estimates of radon-vs-cancer have not been supportive of the EPA risk estimates. In general, when they compare the number of lung cancer cases in particular geological or geographical areas with the indoor radon levels in that area, they find the EPA predicted number of lung cancer cases to exceed the total number of lung cancer cases from all causes. Comparisons show a correlation between the incidence of lung cancer and indoor radon, but the level of risk is about 1/10 that proposed by the US-EPA. Evidently the assumptions used in their studies are flawed. Even though they find lower risk estimates using many counties in several states, fundamental flaws must be present in this type of investigation. Care must be taken in presenting health risks to the general population in cases, such as in indoor radon, where field data do not support risk estimates obtained by other means

  6. Prediction model and treatment of high-output ileostomy in colorectal cancer surgery.

    Science.gov (United States)

    Fujino, Shiki; Miyoshi, Norikatsu; Ohue, Masayuki; Takahashi, Yuske; Yasui, Masayoshi; Sugimura, Keijiro; Akita, Hirohumi; Takahashi, Hidenori; Kobayashi, Shogo; Yano, Masahiko; Sakon, Masato

    2017-09-01

    The aim of the present study was to examine the risk factors of high-output ileostomy (HOI), which is associated with electrolyte abnormalities and/or stoma complications, and to create a prediction model. The medical records of 68 patients who underwent colorectal cancer surgery with ileostomy between 2011 and 2016 were retrospectively investigated. All the patients underwent surgical resection for colorectal cancer at the Osaka Medical Center for Cancer and Cardiovascular Diseases (Osaka, Japan). A total of 7 patients with inadequate data on ileostomy output were excluded. Using a group of 50 patients who underwent surgery between 2011 and 2013, the risk of HOI was classified by a decision tree model using a partition platform. The HOI prediction model was validated in an additional group of 11 patients who underwent surgery between 2014 and 2016. Univariate analysis of clinical factors demonstrated that young age (P=0.003) and high white blood cell (WBC) count (Pmodel, three factors (gender, age and WBC on postoperative day 1) were generated for the prediction of HOI. The patients were classified into five groups, and HOI was observed in 0-88% of patients in each group. The area under the curve (AUC) was 0.838. The model was validated by an external dataset in an independent patient group, for which the AUC was 0.792. In conclusion, HOI patients were classified and an HOI prediction model was developed that may help clinicians in postoperative care.

  7. Predictive Factors for Developing Venous Thrombosis during Cisplatin-Based Chemotherapy in Testicular Cancer.

    Science.gov (United States)

    Heidegger, Isabel; Porres, Daniel; Veek, Nica; Heidenreich, Axel; Pfister, David

    2017-01-01

    Malignancies and cisplatin-based chemotherapy are both known to correlate with a high risk of venous thrombotic events (VTT). In testicular cancer, the information regarding the incidence and reason of VTT in patients undergoing cisplatin-based chemotherapy is still discussed controversially. Moreover, no risk factors for developing a VTT during cisplatin-based chemotherapy have been elucidated so far. We retrospectively analyzed 153 patients with testicular cancer undergoing cisplatin-based chemotherapy at our institution for the development of a VTT during or after chemotherapy. Clinical and pathological parameters for identifying possible risk factors for VTT were analyzed. The Khorana risk score was used to calculate the risk of VTT. Student t test was applied for calculating the statistical significance of differences between the treatment groups. Twenty-six out of 153 patients (17%) developed a VTT during chemotherapy. When we analyzed the risk factors for developing a VTT, we found that Lugano stage ≥IIc was significantly (p = 0.0006) correlated with the risk of developing a VTT during chemotherapy. On calculating the VTT risk using the Khorana risk score model, we found that only 2 out of 26 patients (7.7%) were in the high-risk Khorana group (≥3). Patients with testicular cancer with a high tumor volume have a significant risk of developing a VTT with cisplatin-based chemotherapy. The Khorana risk score is not an accurate tool for predicting VTT in testicular cancer. © 2017 S. Karger AG, Basel.

  8. Cancer risk from inorganics

    International Nuclear Information System (INIS)

    Swierenga, S.H.; Gilman, J.P.; McLean, J.R.

    1987-01-01

    Inorganic metals and minerals for which there is evidence of carcinogenicity are identified. The risk of cancer from contact with them in the work place, the general environment, and under conditions of clinical (medical) exposure is discussed. The evidence indicates that minerals and metals most often influence cancer development through their action as cocarcinogens. The relationship between the physical form of mineral fibers, smoking and carcinogenic risk is emphasized. Metals are categorized as established (As, Be, Cr, Ni), suspected (Cd, Pb) and possible carcinogens, based on the existing in vitro, animal experimental and human epidemiological data. Cancer risk and possible modes of action of elements in each class are discussed. Views on mechanisms that may be responsible for the carcinogenicity of metals are updated and analysed. Some specific examples of cancer risks associated with the clinical use of potentially carcinogenic metals and from radioactive pharmaceuticals used in therapy and diagnosis are presented. Questions are raised as to the effectiveness of conventional dosimetry in accurately measuring risk from radiopharmaceuticals. 302 references

  9. Skin Cancer: Biology, Risk Factors & Treatment

    Science.gov (United States)

    ... turn Javascript on. Feature: Skin Cancer Skin Cancer: Biology, Risk Factors & Treatment Past Issues / Summer 2013 Table ... Articles Skin Cancer Can Strike Anyone / Skin Cancer: Biology, Risk Factors & Treatment / Timely Healthcare Checkup Catches Melanoma ...

  10. The predictive value of endorectal 3 Tesla multiparametric magnetic resonance imaging for extraprostatic extension in patients with low, intermediate and high risk prostate cancer.

    Science.gov (United States)

    Somford, D M; Hamoen, E H; Fütterer, J J; van Basten, J P; Hulsbergen-van de Kaa, C A; Vreuls, W; van Oort, I M; Vergunst, H; Kiemeney, L A; Barentsz, J O; Witjes, J A

    2013-11-01

    We determined the positive and negative predictive values of multiparametric magnetic resonance imaging for extraprostatic extension at radical prostatectomy for different prostate cancer risk groups. We evaluated a cohort of 183 patients who underwent 3 Tesla multiparametric magnetic resonance imaging, including T2-weighted, diffusion weighted magnetic resonance imaging and dynamic contrast enhanced sequences, with an endorectal coil before radical prostatectomy. Pathological stage at radical prostatectomy was used as standard reference for extraprostatic extension. The cohort was classified into low, intermediate and high risk groups according to the D'Amico criteria. We recorded prevalence of extraprostatic extension at radical prostatectomy and determined sensitivity, specificity, positive predictive value and negative predictive value of multiparametric magnetic resonance imaging for extraprostatic extension in each group. Univariate and multivariate analyses were performed to identify predictors of extraprostatic extension at radical prostatectomy. The overall prevalence of extraprostatic extension at radical prostatectomy was 49.7% ranging from 24.7% to 77.1% between low and high risk categories. Overall staging accuracy of multiparametric magnetic resonance imaging for extraprostatic extension was 73.8%, with sensitivity, specificity, positive predictive value and negative predictive value of 58.2%, 89.1%, 84.1% and 68.3%, respectively. Positive predictive value of multiparametric magnetic resonance imaging for extraprostatic extension was best in the high risk cohort with 88.8%. Negative predictive value was highest in the low risk cohort with 87.7%. With an odds ratio of 10.3 multiparametric magnetic resonance imaging is by far the best preoperative predictor of extraprostatic extension at radical prostatectomy. For adequate patient counseling, knowledge of predictive values of multiparametric magnetic resonance imaging for extraprostatic extension is

  11. Psychological impact of providing women with personalised 10-year breast cancer risk estimates.

    Science.gov (United States)

    French, David P; Southworth, Jake; Howell, Anthony; Harvie, Michelle; Stavrinos, Paula; Watterson, Donna; Sampson, Sarah; Evans, D Gareth; Donnelly, Louise S

    2018-05-08

    The Predicting Risk of Cancer at Screening (PROCAS) study estimated 10-year breast cancer risk for 53,596 women attending NHS Breast Screening Programme. The present study, nested within the PROCAS study, aimed to assess the psychological impact of receiving breast cancer risk estimates, based on: (a) the Tyrer-Cuzick (T-C) algorithm including breast density or (b) T-C including breast density plus single-nucleotide polymorphisms (SNPs), versus (c) comparison women awaiting results. A sample of 2138 women from the PROCAS study was stratified by testing groups: T-C only, T-C(+SNPs) and comparison women; and by 10-year risk estimates received: 'moderate' (5-7.99%), 'average' (2-4.99%) or 'below average' (<1.99%) risk. Postal questionnaires were returned by 765 (36%) women. Overall state anxiety and cancer worry were low, and similar for women in T-C only and T-C(+SNPs) groups. Women in both T-C only and T-C(+SNPs) groups showed lower-state anxiety but slightly higher cancer worry than comparison women awaiting results. Risk information had no consistent effects on intentions to change behaviour. Most women were satisfied with information provided. There was considerable variation in understanding. No major harms of providing women with 10-year breast cancer risk estimates were detected. Research to establish the feasibility of risk-stratified breast screening is warranted.

  12. Early-life family structure and microbially induced cancer risk.

    Directory of Open Access Journals (Sweden)

    Martin J Blaser

    2007-01-01

    Full Text Available Cancer may follow exposure to an environmental agent after many decades. The bacterium Helicobacter pylori, known to be acquired early in life, increases risk for gastric adenocarcinoma, but other factors are also important. In this study, we considered whether early-life family structure affects the risk of later developing gastric cancer among H. pylori+ men.We examined a long-term cohort of Japanese-American men followed for 28 y, and performed a nested case-control study among those carrying H. pylori or the subset carrying the most virulent cagA+ H. pylori strains to address whether family structure predicted cancer development. We found that among the men who were H. pylori+ and/or cagA+ (it is possible to be cagA+ and H. pylori- if the H. pylori test is falsely negative, belonging to a large sibship or higher birth order was associated with a significantly increased risk of developing gastric adenocarcinoma late in life. For those with cagA+ strains, the risk of developing gastric cancer was more than twice as high (odds ratio 2.2; 95% confidence interval 1.2-4.0 among those in a sibship of seven or more individuals than in a sibship of between one and three persons.These results provide evidence that early-life social environment plays a significant role in risk of microbially induced malignancies expressing five to eight decades later, and these findings lead to new models to explain these interactions.

  13. Early-life family structure and microbially induced cancer risk.

    Science.gov (United States)

    Blaser, Martin J; Nomura, Abraham; Lee, James; Stemmerman, Grant N; Perez-Perez, Guillermo I

    2007-01-01

    Cancer may follow exposure to an environmental agent after many decades. The bacterium Helicobacter pylori, known to be acquired early in life, increases risk for gastric adenocarcinoma, but other factors are also important. In this study, we considered whether early-life family structure affects the risk of later developing gastric cancer among H. pylori+ men. We examined a long-term cohort of Japanese-American men followed for 28 y, and performed a nested case-control study among those carrying H. pylori or the subset carrying the most virulent cagA+ H. pylori strains to address whether family structure predicted cancer development. We found that among the men who were H. pylori+ and/or cagA+ (it is possible to be cagA+ and H. pylori- if the H. pylori test is falsely negative), belonging to a large sibship or higher birth order was associated with a significantly increased risk of developing gastric adenocarcinoma late in life. For those with cagA+ strains, the risk of developing gastric cancer was more than twice as high (odds ratio 2.2; 95% confidence interval 1.2-4.0) among those in a sibship of seven or more individuals than in a sibship of between one and three persons. These results provide evidence that early-life social environment plays a significant role in risk of microbially induced malignancies expressing five to eight decades later, and these findings lead to new models to explain these interactions.

  14. Clinical Prediction Model and Tool for Assessing Risk of Persistent Pain After Breast Cancer Surgery

    DEFF Research Database (Denmark)

    Meretoja, Tuomo J; Andersen, Kenneth Geving; Bruce, Julie

    2017-01-01

    are missing. The aim was to develop a clinically applicable risk prediction tool. Methods The prediction models were developed and tested using three prospective data sets from Finland (n = 860), Denmark (n = 453), and Scotland (n = 231). Prediction models for persistent pain of moderate to severe intensity......), high body mass index ( P = .039), axillary lymph node dissection ( P = .008), and more severe acute postoperative pain intensity at the seventh postoperative day ( P = .003) predicted persistent pain in the final prediction model, which performed well in the Danish (ROC-AUC, 0.739) and Scottish (ROC......-AUC, 0.740) cohorts. At the 20% risk level, the model had 32.8% and 47.4% sensitivity and 94.4% and 82.4% specificity in the Danish and Scottish cohorts, respectively. Conclusion Our validated prediction models and an online risk calculator provide clinicians and researchers with a simple tool to screen...

  15. Dietary patterns and colorectal adenoma and cancer risk: a review of the epidemiological evidence.

    Science.gov (United States)

    Miller, Paige E; Lesko, Samuel M; Muscat, Joshua E; Lazarus, Philip; Hartman, Terryl J

    2010-01-01

    A number of studies exploring associations between individual dietary components and colorectal adenoma or cancer risk have yielded conflicting results. The study of food-based dietary patterns in relation to chronic disease risk represents an alternative approach to the evaluation of single dietary exposures in epidemiological investigations. Results from prospective cohort and population-based case-control studies examining associations between dietary patterns and colorectal cancer or adenoma risk were evaluated and described in this review. Despite notable differences in population characteristics, study design, and methods used for characterizing dietary patterns across the different studies, two general dietary patterns were found to modestly predict colorectal adenoma and cancer risk. A healthier pattern consisting of greater intakes of fruits and vegetables, and lower intakes of red and processed meat, appeared protective against colorectal adenoma and cancer incidence. Findings also suggest that a less healthy pattern characterized by higher intakes of red and processed meat, as well as potatoes and refined carbohydrates, may increase risk. Continued research efforts are needed to evaluate the cumulative and interactive effects of numerous dietary exposures on colorectal cancer risk.

  16. Metabolic Syndrome and Breast Cancer Risk.

    Science.gov (United States)

    Wani, Burhan; Aziz, Shiekh Aejaz; Ganaie, Mohammad Ashraf; Mir, Mohammad Hussain

    2017-01-01

    The study was meant to estimate the prevalence of metabolic syndrome in patients with breast cancer and to establish its role as an independent risk factor on occurrence of breast cancer. Fifty women aged between 40 and 80 years with breast cancer and fifty controls of similar age were assessed for metabolic syndrome prevalence and breast cancer risk factors, including age at menarche, reproductive status, live births, breastfeeding, and family history of breast cancer, age at diagnosis of breast cancer, body mass index, and metabolic syndrome parameters. Metabolic syndrome prevalence was found in 40.0% of breast cancer patients, and 18.0% of those in control group ( P = 0.02). An independent and positive association was seen between metabolic syndrome and breast cancer risk (odds ratio = 3.037; 95% confidence interval 1.214-7.597). Metabolic syndrome is more prevalent in breast cancer patients and is an independent risk factor for breast cancer.

  17. The influence of narrative risk communication on feelings of cancer risk.

    Science.gov (United States)

    Janssen, Eva; van Osch, Liesbeth; de Vries, Hein; Lechner, Lilian

    2013-05-01

    Evidence is accumulating for the importance of feelings of risk in explaining cancer preventive behaviours, but best practices for influencing these feelings are limited. The aim of this experimental study was to compare the effects of narrative and non-narrative risk communication about sunbed use on ease of imagination and feelings of cancer risk. A total of 233 female sunbed users in the general Dutch population were randomly assigned to one of three conditions: a narrative message (i.e., personal testimonial), a non-narrative cognitive message (i.e., factual risk information using cognitive-laden words), or a non-narrative affective message (i.e., factual risk information using affective-laden words). Ease of imagination and feelings of risk were assessed directly after the risk information was given (T1). Three weeks after the baseline session, feelings of risk were measured again (T2). The results revealed that sunbed users who were exposed to narrative risk information could better imagine themselves developing skin cancer and reported higher feelings of skin cancer risk at T1. Moreover, ease of imagination mediated the effects of message type on feelings of risk at T1 and T2. The findings provide support for the effects of narrative risk communication in influencing feelings of cancer risk through ease of imagination. Cancer prevention programmes may therefore benefit from including narrative risk information. Future research is important to investigate other mechanisms of narrative information and their most effective content and format. What is already known on this subject? Evidence is growing for the importance of feelings of risk in explaining cancer preventive behaviours. Narratives have increasingly been considered as an effective format for persuasive risk messages and studies have shown narrative risk communication to be effective in influencing cognitive risk beliefs. What does this study add? Increasing understanding of how feelings of cancer

  18. Risk of treatment-related esophageal cancer among breast cancer survivors

    DEFF Research Database (Denmark)

    Morton, L M; Gilbert, E S; Hall, P

    2012-01-01

    Radiotherapy for breast cancer may expose the esophagus to ionizing radiation, but no study has evaluated esophageal cancer risk after breast cancer associated with radiation dose or systemic therapy use.......Radiotherapy for breast cancer may expose the esophagus to ionizing radiation, but no study has evaluated esophageal cancer risk after breast cancer associated with radiation dose or systemic therapy use....

  19. Acceptance of Referral for Cancer-Risk Counseling in Population of Women Undergoing Breast Biopsy: Variables Predicting Followup at a Cancer Genetics Program

    National Research Council Canada - National Science Library

    O'Neill, Suzanne

    2001-01-01

    ..., Shattuck-Eidens, Frank, and BRCAPRO models. Questionnaires assessing psychological status, and knowledge and attitudes about breast cancer, cancer risk counseling, and genetic testing were used to identify predictors of referral uptake...

  20. Bricklayers and lung cancer risk

    NARCIS (Netherlands)

    Cremers, Jan

    2014-01-01

    The article ‘Lung cancer risk among bricklayers in a pooled analysis of case–control studies’ in the International Journal of Cancer publishes findings of an epidemiological study (in the frame of a SYNERGY-project) dedicated to the lung cancer risk among bricklayers. The authors conclude that a

  1. Maternal lung cancer and testicular cancer risk in the offspring.

    Science.gov (United States)

    Kaijser, Magnus; Akre, Olof; Cnattingius, Sven; Ekbom, Anders

    2003-07-01

    It has been hypothesized that smoking during pregnancy could increase the offspring's risk for testicular cancer. This hypothesis is indirectly supported by both ecological studies and studies of cancer aggregations within families. However, results from analytical epidemiological studies are not consistent, possibly due to methodological difficulties. To further study the association between smoking during pregnancy and testicular cancer, we did a population-based cohort study on cancer risk among offspring of women diagnosed with lung cancer. Through the use of the Swedish Cancer Register and the Swedish Second-Generation Register, we identified 8,430 women who developed lung cancer between 1958 and 1997 and delivered sons between 1941 and 1979. Cancer cases among the male offspring were then identified through the Swedish Cancer Register. Standardized incidence ratios were computed, using 95% confidence intervals. We identified 12,592 male offspring of mothers with a subsequent diagnosis of lung cancer, and there were 40 cases of testicular cancer (standardized incidence ratio, 1.90; 95% confidence interval, 1.35-2.58). The association was independent of maternal lung cancer subtype, and the risk of testicular cancer increased stepwise with decreasing time interval between birth and maternal lung cancer diagnosis. Our results support the hypothesis that exposure to cigarette smoking in utero increases the risk of testicular cancer.

  2. Prospective study of major dietary patterns and colorectal cancer risk in women.

    Science.gov (United States)

    Terry, P; Hu, F B; Hansen, H; Wolk, A

    2001-12-15

    A number of prospective cohort studies have examined the relations of individual dietary variables to risk of colorectal cancer. Few studies have addressed the broader eating patterns that reflect many dietary exposures working together. Using data from a prospective study of 61,463 women, with an average follow-up period of 9.6 years (between 1987 and 1998) and 460 incident cases of colorectal cancer, the authors conducted a factor analysis to identify and examine major dietary patterns in relation to colorectal cancer risk. Using proportional hazards regression to estimate relative risks, the authors found no clear association between a "Western," "healthy," or "drinker" dietary pattern and colorectal cancer risk. However, the data suggested that consuming low amounts of foods that constitute a "healthy" dietary pattern may be associated with increased risks of colon and rectal cancers. An inverse association with the "healthy" dietary pattern was found among women under age 50 years, although the number of cancers in this age group was limited and interpretation of this finding should be cautious. In this age group, relative risks for women in increasing quintiles of the "healthy" dietary pattern, compared with the lowest quintile, were 0.74 (95% confidence interval (CI): 0.41, 1.31), 0.69 (95% CI: 0.39, 1.24), 0.59 (95% CI: 0.32, 1.07), and 0.45 (95% CI: 0.23, 0.88) (p for trend = 0.03). The role of overall eating patterns in predicting colorectal cancer risk requires further investigation.

  3. Adequacy of relative and absolute risk models for lifetime risk estimate of radiation-induced cancer

    International Nuclear Information System (INIS)

    McBride, M.; Coldman, A.J.

    1988-03-01

    This report examines the applicability of the relative (multiplicative) and absolute (additive) models in predicting lifetime risk of radiation-induced cancer. A review of the epidemiologic literature, and a discussion of the mathematical models of carcinogenesis and their relationship to these models of lifetime risk, are included. Based on the available data, the relative risk model for the estimation of lifetime risk is preferred for non-sex-specific epithelial tumours. However, because of lack of knowledge concerning other determinants of radiation risk and of background incidence rates, considerable uncertainty in modelling lifetime risk still exists. Therefore, it is essential that follow-up of exposed cohorts be continued so that population-based estimates of lifetime risk are available

  4. Evaluation of BRCA1 and BRCA2 mutation prevalence, risk prediction models and a multistep testing approach in French‐Canadian families with high risk of breast and ovarian cancer

    Science.gov (United States)

    Simard, Jacques; Dumont, Martine; Moisan, Anne‐Marie; Gaborieau, Valérie; Vézina, Hélène; Durocher, Francine; Chiquette, Jocelyne; Plante, Marie; Avard, Denise; Bessette, Paul; Brousseau, Claire; Dorval, Michel; Godard, Béatrice; Houde, Louis; Joly, Yann; Lajoie, Marie‐Andrée; Leblanc, Gilles; Lépine, Jean; Lespérance, Bernard; Malouin, Hélène; Parboosingh, Jillian; Pichette, Roxane; Provencher, Louise; Rhéaume, Josée; Sinnett, Daniel; Samson, Carolle; Simard, Jean‐Claude; Tranchant, Martine; Voyer, Patricia; BRCAs, INHERIT; Easton, Douglas; Tavtigian, Sean V; Knoppers, Bartha‐Maria; Laframboise, Rachel; Bridge, Peter; Goldgar, David

    2007-01-01

    Background and objective In clinical settings with fixed resources allocated to predictive genetic testing for high‐risk cancer predisposition genes, optimal strategies for mutation screening programmes are critically important. These depend on the mutation spectrum found in the population under consideration and the frequency of mutations detected as a function of the personal and family history of cancer, which are both affected by the presence of founder mutations and demographic characteristics of the underlying population. The results of multistep genetic testing for mutations in BRCA1 or BRCA2 in a large series of families with breast cancer in the French‐Canadian population of Quebec, Canada are reported. Methods A total of 256 high‐risk families were ascertained from regional familial cancer clinics throughout the province of Quebec. Initially, families were tested for a panel of specific mutations known to occur in this population. Families in which no mutation was identified were then comprehensively tested. Three algorithms to predict the presence of mutations were evaluated, including the prevalence tables provided by Myriad Genetics Laboratories, the Manchester Scoring System and a logistic regression approach based on the data from this study. Results 8 of the 15 distinct mutations found in 62 BRCA1/BRCA2‐positive families had never been previously reported in this population, whereas 82% carried 1 of the 4 mutations currently observed in ⩾2 families. In the subset of 191 families in which at least 1 affected individual was tested, 29% carried a mutation. Of these 27 BRCA1‐positive and 29 BRCA2‐positive families, 48 (86%) were found to harbour a mutation detected by the initial test. Among the remaining 143 inconclusive families, all 8 families found to have a mutation after complete sequencing had Manchester Scores ⩾18. The logistic regression and Manchester Scores provided equal predictive power, and both were significantly better

  5. Body Fat and Breast Cancer Risk in Postmenopausal Women: A Longitudinal Study

    International Nuclear Information System (INIS)

    Rohan, T. E.; Heo, M.; Kamensky, V.; Kabat, G. C.

    2013-01-01

    Associations between anthropometric indices of obesity and breast cancer risk may fail to capture the true relationship between excess body fat and risk. We used dual-energy-X-ray-absorptiometry- (DXA-) derived measures of body fat obtained in the Women’s Health Initiative to examine the association between body fat and breast cancer risk; we compared these risk estimates with those for conventional anthropometric measurements. The study included 10,960 postmenopausal women aged 50-79 years at recruitment, with baseline DXA measurements and no history of breast cancer. During followup (median: 12.9 years), 503 incident breast cancer cases were diagnosed. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards models. All baseline DXA-derived body fat measures showed strong positive associations with breast cancer risk. The multivariable-adjusted HR for the uppermost quintile level (versus lowest) ranged from 1.53 (95% CI 1.14-2.07) for fat mass of the right leg to 2.05 (1.50-2.79) for fat mass of the trunk. Anthropometric indices (categorized by quintiles) of obesity (BMI (1.97, 1.45-2.68), waist circumference (1.97, 1.46-2.65), and waist-: hip ratio (1.91, 1.41-2.58)) were all strongly, positively associated with risk and did not differ from DXA-derived measures in prediction of risk.

  6. Predicted risks of second malignant neoplasm incidence and mortality due to secondary neutrons in a girl and boy receiving proton craniospinal irradiation

    International Nuclear Information System (INIS)

    Taddei, Phillip J; Mirkovic, Dragan; Zhang Rui; Giebeler, Annelise; Harvey, Mark; Newhauser, Wayne D; Mahajan, Anita; Kornguth, David; Woo, Shiao

    2010-01-01

    The purpose of this study was to compare the predicted risks of second malignant neoplasm (SMN) incidence and mortality from secondary neutrons for a 9-year-old girl and a 10-year-old boy who received proton craniospinal irradiation (CSI). SMN incidence and mortality from neutrons were predicted from equivalent doses to radiosensitive organs for cranial, spinal and intracranial boost fields. Therapeutic proton absorbed dose and equivalent dose from neutrons were calculated using Monte Carlo simulations. Risks of SMN incidence and mortality in most organs and tissues were predicted by applying risks models from the National Research Council of the National Academies to the equivalent dose from neutrons; for non-melanoma skin cancer, risk models from the International Commission on Radiological Protection were applied. The lifetime absolute risks of SMN incidence due to neutrons were 14.8% and 8.5%, for the girl and boy, respectively. The risks of a fatal SMN were 5.3% and 3.4% for the girl and boy, respectively. The girl had a greater risk for any SMN except colon and liver cancers, indicating that the girl's higher risks were not attributable solely to greater susceptibility to breast cancer. Lung cancer predominated the risk of SMN mortality for both patients. This study suggests that the risks of SMN incidence and mortality from neutrons may be greater for girls than for boys treated with proton CSI.

  7. Industrial risk factors for colorectal cancer

    International Nuclear Information System (INIS)

    Lashner, B.A.; Epstein, S.S.

    1990-01-01

    Colorectal cancer is the second most common malignancy in the United States, and its incidence rates have sharply increased recently, especially in males. Industrial exposures, both occupational and environmental, are important colorectal cancer risk factors that are generally unrecognized by clinicians. Migration studies have documented that colorectal cancer is strongly associated with environmental risk factors. The causal role of occupational exposures is evidenced by a substantial literature associating specific work practices with increased colorectal cancer risks. Industrially related environmental exposures, including polluted drinking water and ionizing radiation, have also been associated with excess risks. Currently, there is a tendency to attribute colorectal cancer, largely or exclusively, to dietary and other lifestyle factors, thus neglecting these industrially related effects. Concerted efforts are needed to recognize the causal role of industrial risk factors and to encourage government and industry to reduce carcinogenic exposures. Furthermore, cost-effective screening programs for high-risk population groups are critically needed to further reduce deaths from colorectal cancer. 143 references

  8. Cancer stem cell marker Musashi-1 rs2522137 genotype is associated with an increased risk of lung cancer.

    Directory of Open Access Journals (Sweden)

    Xu Wang

    Full Text Available Gene single nucleotide polymorphisms (SNPs have been extensively studied in association with development and prognosis of various malignancies. However, the potential role of genetic polymorphisms of cancer stem cell (CSC marker genes with respect to cancer risk has not been examined. We conducted a case-control study involving a total of 1000 subjects (500 lung cancer patients and 500 age-matched cancer-free controls from northeastern China. Lung cancer risk was analyzed in a logistic regression model in association with genotypes of four lung CSC marker genes (CD133, ALDH1, Musashi-1, and EpCAM. Using univariate analysis, the Musashi-1 rs2522137 GG genotype was found to be associated with a higher incidence of lung cancer compared with the TT genotype. No significant associations were observed for gene variants of CD133, ALDH1, or EpCAM. In multivariate analysis, Musashi-1 rs2522137 was still significantly associated with lung cancer when environmental and lifestyle factors were incorporated in the model, including lower BMI; family history of cancer; prior diagnosis of chronic obstructive pulmonary disease, pneumonia, or pulmonary tuberculosis; occupational exposure to pesticide; occupational exposure to gasoline or diesel fuel; heavier smoking; and exposure to heavy cooking emissions. The value of the area under the receiver-operating characteristic (ROC curve (AUC was 0.7686. To our knowledge, this is the first report to show an association between a Musashi-1 genotype and lung cancer risk. Further, the prediction model in this study may be useful in determining individuals with high risk of lung cancer.

  9. Obesity, physical activity and cancer risks: Results from the Cancer, Lifestyle and Evaluation of Risk Study (CLEAR).

    Science.gov (United States)

    Nunez, Carlos; Bauman, Adrian; Egger, Sam; Sitas, Freddy; Nair-Shalliker, Visalini

    2017-04-01

    Physical activity (PA) has been associated with lower risk of cardiovascular diseases, but the evidence linking PA with lower cancer risk is inconclusive. We examined the independent and interactive effects of PA and obesity using body mass index (BMI) as a proxy for obesity, on the risk of developing prostate (PC), postmenopausal breast (BC), colorectal (CRC), ovarian (OC) and uterine (UC) cancers. We estimated odds ratios (OR) and 95% confidence intervals (CI), adjusting for cancer specific confounders, in 6831 self-reported cancer cases and 1992 self-reported cancer-free controls from the Cancer Lifestyle and Evaluation of Risk Study, using unconditional logistic regression. For women, BMI was positively associated with UC risk; specifically, obese women (BMI≥30kg/m 2 ) had nearly twice the risk of developing UC compared to women with healthy-BMI-range (risk of developing any cancer type, CRC and PC. In particular, obese men had 37% (OR=1.37;CI:1.11-1.70), 113% (OR=2.13;CI:1.55-2.91) and 51% (OR=1.51;CI:1.17-1.94) higher risks of developing any cancer, CRC and PC respectively, when compared to men with healthy-BMI-range (BMIrisks of CRC, UC and BC. In particular, the highest level of PA (versus nil activity) was associated with reduced risks of CRC (OR=0.60;CI:0.44-0.84) and UC (OR=0.47;CI:0.27-0.80). Reduced risks of BC were associated with low (OR=0.66;CI:0.51-0.86) and moderate (OR=0.72;CI:0.57-0.91) levels of PA. There was no association between PA levels and cancer risks for men. We found no evidence of an interaction between BMI and PA in the CLEAR study. These findings suggest that PA and obesity are independent cancer risk factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Risks of Skin Cancer Screening

    Science.gov (United States)

    ... factors increase or decrease the risk of skin cancer. Skin cancer is a disease in which malignant (cancer) ... following PDQ summaries for more information about skin cancer: Skin Cancer Prevention Skin Cancer Treatment Melanoma Treatment Genetics ...

  11. Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers

    DEFF Research Database (Denmark)

    Schmidt, Marjanka K; Hogervorst, Frans; van Hien, Richard R

    2016-01-01

    PURPOSE: CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor...... subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS: CHEK2*1100delC genotyping was mostly done by a custom Taqman assay....... Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS: Proportions...

  12. Risk of cancer formation by radiotherapy

    International Nuclear Information System (INIS)

    Fuji, Hiroshi

    2011-01-01

    Described are the difference between exposures to radiation for medical purpose and to environmental radiation at low dose, estimation of carcinogenic risk by medical radiation, and notice for referring the risk at clinical practice. ICRP employs linear non-threshold (LNT) model for risk of cancer formation even at <200 mSv for safety, with a recognition that it is scientifically obscure. The model essentially stands on data of A-bomb survivors (the Gold Standard), where the relationship between 5-10% excess relative risk (ERR) of cancer formation and dose 0.05-2.5 Sv is linear. Analyses of the secondary carcinogenesis after radiotherapy have begun to be reported since around 2005: e.g., the secondary thyroid cancer risk in pediatric patients treated with radiotherapy has a peak at 20 Gy, suggesting the actual risk depends both on the linearity of carcinogenic increase and on the exponential probability of cell death increase. On this concept, the risk of cancer formation is not always linear to dose. At the practical radiotherapy, its secondary carcinogenic risk should be estimated not only on the dose but also on other factors such as the individual organ, patient's age and attainable age/time after the treatment. In treated teen-ager patients, ERRs of mortality/Gy are 2.28 for cancers of the skin of non-malignant melanoma, 1.32 of bladder and 1.21 of thyroid and in patients of fifties, 1.15 of bladder and lung. The EER tends to become lower as the treated age is older. Pediatric cancer patients to be treated with radiotherapy should be informed about the secondary cancer that the low dose risk given by ICRP is not always appropriate, a certain cancer risk has a peak dose, and ERR of cancer mortality is not a cancer risk of an organ. Many factors like anticancers and immuno-modifiers, modify the outcome of radiotherapy and should be carefully speculated for evaluating the outcome. (T.T.)

  13. Is it possible to predict the presence of colorectal cancer in a blood test?: a probabilistic approach method

    Directory of Open Access Journals (Sweden)

    José Manuel Navarro-Rodríguez

    Full Text Available Introduction: The assessment of the state of immunosurveillance (the ability of the organism to prevent the development of neoplasias in the blood has prognostic implications of interest in colorectal cancer. We evaluated and quantified a possible predictive character of the disease in a blood test using a mathematical interaction index of several blood parameters. The predictive capacity of the index to detect colorectal cancer was also assessed. Methods: We performed a retrospective case-control study of a comparative analysis of the distribution of blood parameters in 266 patients with colorectal cancer and 266 healthy patients during the period from 2009 to 2013. Results: Statistically significant differences (p < 0.05 were observed between patients with colorectal cancer and the control group in terms of platelet counts, fibrinogen, total leukocytes, neutrophils, systemic immunovigilance indexes (neutrophil to lymphocyte ratio and platelet to lymphocyte ratio, hemoglobin, hematocrit and eosinophil levels. These differences allowed the design of a blood analytical profile that calculates the risk of colorectal cancer. This risk profile can be quantified via a mathematical formula with a probabilistic capacity to identify patients with the highest risk of the presence of colorectal cancer (area under the ROC curve = 0.85. Conclusions: We showed that a colorectal cancer predictive character exists in blood which can be quantified by an interaction index of several blood parameters. The design and development of interaction indexes of blood parameters constitutes an interesting research line for the development and improvement of programs for the screening of colorectal cancer.

  14. Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures

    OpenAIRE

    Stone, Jennifer; Thompson, Deborah J.; dos-Santos-Silva, Isabel; Scott, Christopher; Tamimi, Rulla M.; Lindstrom, Sara; Kraft, Peter; Hazra, Aditi; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Hall, Per; Jensen, Matt; Cunningham, Julie; Olson, Janet E.

    2015-01-01

    Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute non-dense area adjusted for study, age and BMI using mixed linear modeling. We found strong suppo...

  15. Risk factor assessment in high-risk, bacillus Calmette–Guérin-treated, non-muscle-invasive bladder cancer

    Directory of Open Access Journals (Sweden)

    Holz S

    2017-09-01

    Full Text Available Serge Holz,* Simone Albisinni,* Jacques Gilsoul, Michel Pirson, Véronique Duthie, Thierry Quackels, Marc Vanden Bossche, Thierry Roumeguère Department of Urology, Erasme Hospital, Université libre de Bruxelles, Belgium *These authors contributed equally to this work Objective: To assess the risk factors associated with recurrence, progression and survival in high-risk non-muscle-invasive bladder cancer (NMIBC patients treated with bacillus Calmette–Guérin (BCG and validate the European Organization for Research and Treatment of Cancer (EORTC and Spanish Urological Club for Oncological Treatment (CUETO scores.Patients and methods: We retrospectively analyzed all BCG-treated NMIBC patients from 1998 to 2012. Multiple variables were tested as risk factors for recurrence-free survival and progression-free survival (PFS. Variables included age, sex, grade, stage, tumor size, number of tumors, carcinoma in situ (CIS, recurrence status, BCG strain used, smoking status, use of re-staging transurethral resection and use of single immediate postoperative instillation. We also tested the accuracy of EORTC and CUETO scores in predicting recurrence and progression.Results: Overall, 123 patients were analyzed. Median (interquartile range follow-up was 49 months. The 5-year overall survival, cancer-specific survival, recurrence-free survival and PFS were 75.0%, 89.3%, 59.4% and 79.2%, respectively. On univariate analysis, multiple tumors (≥3, concomitant CIS and smoking influenced recurrence. Regarding progression, multiple tumors, concomitant CIS and Connaught strain (vs Tice negatively influenced PFS on univariate and multivariate analyses were independent prognostic factors. CUETO scores were accurate, with a slight overestimation, while EORTC score was not predictive of recurrence or progression.Conclusion: In this study, CIS and tumor multiplicity were unfavorable predictors of recurrence and progression in patients with NMIBC receiving BCG

  16. Myastenia and risk of cancer

    DEFF Research Database (Denmark)

    Pedersen, Emil Arnspang; Pottegård, Anton; Hallas, Jesper

    2014-01-01

    BACKGROUND AND PURPOSE: To evaluate the association between having non-thymoma myasthenia and the risk of extra-thymic cancer in a population-based setting. METHODS: A nationwide case-control study was conducted in Denmark based on medical registries. The study included all cases with a first time...... diagnosis of cancer during 2000-2009. Each case was matched by birth year and gender with eight population controls using risk set sampling. Subjects with myasthenia were identified through a validated register-based algorithm. Conditional logistic regression was used to compute crude and adjusted odds...... risk of overall cancer (OR 1.1; 95% CI 0.9-1.4). Adjusted ORs for major cancer sites were also close to unity, whereas an elevated risk of lymphomas was observed (OR 2.0; 95% CI 0.8-5.5). Early-onset myasthenia was associated with a slightly increased OR for overall cancer (1.5; 95% CI 1...

  17. A novel method for monitoring high-risk breast cancer with tumor markers

    DEFF Research Database (Denmark)

    Sölétormos, G; Nielsen, D; Schiøler, V

    1993-01-01

    cancer. METHODS: Ninety females with high-risk breast cancer were included in the study. Response evaluation was based upon clinical examination, x-rays or histology and elaborated marker criteria. RESULTS: During the marker monitoring period, metastases in four patients were confined to skin or lymph......BACKGROUND: An early and reliable diagnosis of metastatic spread has increased interest in serum tumor markers. This study investigated the ability of CA 15.3, CEA, and TPA to identify, predict, and exclude metastases in bone/viscera during adjuvant treatment and follow-up of high-risk breast...

  18. Update on raloxifene: role in reducing the risk of invasive breast cancer in postmenopausal women

    Directory of Open Access Journals (Sweden)

    Vogel VG

    2011-10-01

    Full Text Available Victor G Vogel Cancer Institute, Geisinger Health System, Danville, PA, USA Abstract: Risk factors allow us to define women who are at increased lifetime risk for breast cancer, and the most important factor is age. Benign breast disease increases risk, and the most important histologies are atypical lobular or ductal hyperplasia and lobular carcinoma in situ. Family history of breast cancer among first-degree relatives (mother, sisters, daughters also increases risk. Quantitative measures of risk give accurate predictions of breast cancer incidence for groups of women but not for individual subjects. Multiple published, randomized controlled trials, which employed selective estrogen receptor (ER modulators (SERMs, have demonstrated consistent reductions of 35% or greater in the risk of ER-positive invasive and noninvasive breast cancer in postmenopausal women. Professional organizations in the US now recommend the use of SERMs to reduce the risk of breast cancer in high-risk, postmenopausal women. Raloxifene and tamoxifen reduce the risk of ER-positive invasive breast cancer with equal efficacy, but raloxifene is associated with a lower risk of thromboembolic disease, benign uterine conditions, and cataracts than tamoxifen in postmenopausal women. No evidence exists establishing whether a reduction in breast cancer risk from either agent translates into reduced breast cancer mortality. Overall quality of life is similar with raloxifene or tamoxifen, but the incidence of dyspareunia, weight gain, and musculoskeletal complaints is higher with raloxifene use, whereas vasomotor symptoms, bladder incontinence, gynecologic symptoms, and leg cramps were higher with tamoxifen use. Keywords: selective estrogen receptor modulators (SERMs, raloxifene, risk reduction, chemoprevention

  19. A germline mutation in the BRCA1 3'UTR predicts Stage IV breast cancer.

    Science.gov (United States)

    Dorairaj, Jemima J; Salzman, David W; Wall, Deirdre; Rounds, Tiffany; Preskill, Carina; Sullivan, Catherine A W; Lindner, Robert; Curran, Catherine; Lezon-Geyda, Kim; McVeigh, Terri; Harris, Lyndsay; Newell, John; Kerin, Michael J; Wood, Marie; Miller, Nicola; Weidhaas, Joanne B

    2014-06-10

    A germline, variant in the BRCA1 3'UTR (rs8176318) was previously shown to predict breast and ovarian cancer risk in women from high-risk families, as well as increased risk of triple negative breast cancer. Here, we tested the hypothesis that this variant predicts tumor biology, like other 3'UTR mutations in cancer. The impact of the BRCA1-3'UTR-variant on BRCA1 gene expression, and altered response to external stimuli was tested in vitro using a luciferase reporter assay. Gene expression was further tested in vivo by immunoflourescence staining on breast tumor tissue, comparing triple negative patient samples with the variant (TG or TT) or non-variant (GG) BRCA1 3'UTR. To determine the significance of the variant on clinically relevant endpoints, a comprehensive collection of West-Irish breast cancer patients were tested for the variant. Finally, an association of the variant with breast screening clinical phenotypes was evaluated using a cohort of women from the High Risk Breast Program at the University of Vermont. Luciferase reporters with the BRCA1-3'UTR-variant (T allele) displayed significantly lower gene expression, as well as altered response to external hormonal stimuli, compared to the non-variant 3'UTR (G allele) in breast cancer cell lines. This was confirmed clinically by the finding of reduced BRCA1 gene expression in triple negative samples from patients carrying the homozygous TT variant, compared to non-variant patients. The BRCA1-3'UTR-variant (TG or TT) also associated with a modest increased risk for developing breast cancer in the West-Irish cohort (OR=1.4, 95% CI 1.1-1.8, p=0.033). More importantly, patients with the BRCA1-3'UTR-variant had a 4-fold increased risk of presenting with Stage IV disease (p=0.018, OR=3.37, 95% CI 1.3-11.0). Supporting that this finding is due to tumor biology, and not difficulty screening, obese women with the BRCA1-3'UTR-variant had significantly less dense breasts (p=0.0398) in the Vermont cohort. A variant in

  20. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

    OpenAIRE

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M

    2014-01-01

    Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectom...

  1. Combining quantitative and qualitative breast density measures to assess breast cancer risk.

    Science.gov (United States)

    Kerlikowske, Karla; Ma, Lin; Scott, Christopher G; Mahmoudzadeh, Amir P; Jensen, Matthew R; Sprague, Brian L; Henderson, Louise M; Pankratz, V Shane; Cummings, Steven R; Miglioretti, Diana L; Vachon, Celine M; Shepherd, John A

    2017-08-22

    Accurately identifying women with dense breasts (Breast Imaging Reporting and Data System [BI-RADS] heterogeneously or extremely dense) who are at high breast cancer risk will facilitate discussions of supplemental imaging and primary prevention. We examined the independent contribution of dense breast volume and BI-RADS breast density to predict invasive breast cancer and whether dense breast volume combined with Breast Cancer Surveillance Consortium (BCSC) risk model factors (age, race/ethnicity, family history of breast cancer, history of breast biopsy, and BI-RADS breast density) improves identifying women with dense breasts at high breast cancer risk. We conducted a case-control study of 1720 women with invasive cancer and 3686 control subjects. We calculated ORs and 95% CIs for the effect of BI-RADS breast density and Volpara™ automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI), and we compared C-statistics between models. We calculated BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume. Compared with women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume, women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84-4.47, and OR 2.56, 95% CI 1.87-3.52, respectively), whereas women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75-3.09, and OR 1.50, 95% CI 0.82-2.73, respectively). Adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623-0.654, vs. C-statistic 0.614, 95% CI 0.598-0.630, respectively; P breasts and fourth

  2. Risks of Breast Cancer Screening

    Science.gov (United States)

    ... is small. Different factors increase or decrease the risk of breast cancer. Anything that increases your chance ... magnetic resonance imaging) in women with a high risk of breast cancer MRI is a procedure that ...

  3. Risks of Lung Cancer Screening

    Science.gov (United States)

    ... in women. Different factors increase or decrease the risk of lung cancer. Anything that increases your chance ... been studied to see if they decrease the risk of dying from lung cancer. The following screening ...

  4. Risks of Endometrial Cancer Screening

    Science.gov (United States)

    ... Health history and certain medicines can affect the risk of developing endometrial cancer. Anything that increases your ... have abnormal vaginal bleeding, check with your doctor. Risks of Endometrial Cancer Screening Key Points Screening tests ...

  5. Risks of Esophageal Cancer Screening

    Science.gov (United States)

    ... alcohol use, and Barrett esophagus can affect the risk of developing esophageal cancer. Anything that increases the ... tissue gives off less light than normal tissue. Risks of Esophageal Cancer Screening Key Points Screening tests ...

  6. Risks of Cervical Cancer Screening

    Science.gov (United States)

    ... women. Human papillomavirus (HPV) infection is the major risk factor for cervical cancer. Although most women with ... clinical trials is available from the NCI website . Risks of Cervical Cancer Screening Key Points Screening tests ...

  7. Unification of favourable intermediate-, unfavourable intermediate-, and very high-risk stratification criteria for prostate cancer.

    Science.gov (United States)

    Zumsteg, Zachary S; Zelefsky, Michael J; Woo, Kaitlin M; Spratt, Daniel E; Kollmeier, Marisa A; McBride, Sean; Pei, Xin; Sandler, Howard M; Zhang, Zhigang

    2017-11-01

    To improve on the existing risk-stratification systems for prostate cancer. This was a retrospective investigation including 2 248 patients undergoing dose-escalated external beam radiotherapy (EBRT) at a single institution. We separated National Comprehensive Cancer Network (NCCN) intermediate-risk prostate cancer into 'favourable' and 'unfavourable' groups based on primary Gleason pattern, percentage of positive biopsy cores (PPBC), and number of NCCN intermediate-risk factors. Similarly, NCCN high-risk prostate cancer was stratified into 'standard' and 'very high-risk' groups based on primary Gleason pattern, PPBC, number of NCCN high-risk factors, and stage T3b-T4 disease. Patients with unfavourable-intermediate-risk (UIR) prostate cancer had significantly inferior prostate-specific antigen relapse-free survival (PSA-RFS, P prostate cancer-specific mortality (PCSM, P prostate cancer. Similarly, patients with very high-risk (VHR) prostate cancer had significantly worse PSA-RFS (P prostate cancer. Moreover, patients with FIR and low-risk prostate cancer had similar outcomes, as did patients with UIR and SHR prostate cancer. Consequently, we propose the following risk-stratification system: Group 1, low risk and FIR; Group 2, UIR and SHR; and Group 3, VHR. These groups have markedly different outcomes, with 8-year distant metastasis rates of 3%, 9%, and 29% (P < 0.001) for Groups 1, 2, and 3, respectively, and 8-year PCSM of 1%, 4%, and 13% (P < 0.001) after EBRT. This modified stratification system was significantly more accurate than the three-tiered NCCN system currently in clinical use for all outcomes. Modifying the NCCN risk-stratification system to group FIR with low-risk patients and UIR with SHR patients, results in modestly improved prediction of outcomes, potentially allowing better personalisation of therapeutic recommendations. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

  8. Risks of Liver (Hepatocellular) Cancer Screening

    Science.gov (United States)

    ... cancer. Having hepatitis or cirrhosis can increase the risk of developing liver cancer. Anything that increases the ... clinical trials is available from the NCI website . Risks of Liver (Hepatocellular) Cancer Screening Key Points Screening ...

  9. Risk factors for deep venous thrombosis in women with ovarian cancer

    Science.gov (United States)

    Ebina, Yasuhiko; Uchiyama, Mihoko; Imafuku, Hitomi; Suzuki, Kaho; Miyahara, Yoshiya; Yamada, Hideto

    2018-01-01

    Abstract We aim to clarify the incidence of deep venous thrombosis (DVT) before treatment in women with ovarian cancer and identify risk factors for DVT. In this prospective study, 110 women underwent venous ultrasonography before cancer treatment and D-dimer levels were measured. We investigated factors predicting DVT by logistic regression. DVT was detected in 25 of 110 women (22.7%) and pulmonary thromboembolism was coexisted in 2 women (1.8%). A total of 21 women (84.4%) with DVT were asymptomatic. D-dimer levels in women with DVT (median, 10.9; range, <0.5–98.2 μg/mL) were significantly higher than those in women without DVT (2.0; <0.5–60.8 μg/mL; P < .01). When 10.9 μg/mL was used as a cutoff value for D-dimer levels to predict DVT, specificity, sensitivity, and positive and negative predictive values were 92.9%, 52.0%, 68.4%, and 86.8%, respectively. The multivariate analysis demonstrated that D-dimer level (odds ratio [OR], 19.7; 95% confidence interval [CI], 5.89–76.76) and clear cell histology (OR, 7.1; 95% CI, 2.12–25.67) were independent factors predicting DVT. Asymptomatic DVT occurred with great frequency before treatment in patients with ovarian cancer. High D-dimer level and clear cell pathology is associated with a higher DVT risk. PMID:29879062

  10. ALDH1 and podoplanin expression patterns predict the risk of malignant transformation in oral leukoplakia.

    Science.gov (United States)

    Habiba, Umma; Hida, Kyoko; Kitamura, Tetsuya; Matsuda, Aya Yanagawa; Higashino, Fumihiro; Ito, Yoichi M; Ohiro, Yoichi; Totsuka, Yasunori; Shindoh, Masanobu

    2017-01-01

    Oral leukoplakia (OL) is a clinically diagnosed preneoplastic lesion of the oral cavity with an increased oral cancer risk. However, the risk of malignant transformation is still difficult to assess. The objective of the present study was to examine the expression patterns of aldehyde dehydrogenase 1 (ALDH1) and podoplanin in OL, and to determine their roles in predicting oral cancer development. In the present study, the expression patterns of ALDH1 and podoplanin were determined in samples from 79 patients with OL. The association between protein expression and clinicopathological parameters, including oral cancer-free survival, was analyzed during a mean follow-up period of 3.4 years. Expression of ALDH1 and podoplanin was observed in 61 and 67% patients, respectively. Kaplan-Meier analysis demonstrated that the expression of the proteins was correlated with the risk of progression to oral cancer. Multivariate analysis revealed that expression of ALDH1 and podoplanin was associated with 3.02- and 2.62-fold increased risk of malignant transformation, respectively. The malignant transformation risk of OL was considerably higher in cases with expression of both proteins. Point-prevalence analysis revealed that 66% of patients with co-expression of ALDH1 and podoplanin developed oral cancer. Taken together, our data indicate that ALDH1 and podoplanin expression patterns in OL are associated with oral cancer development, suggesting that ALDH1 and podoplanin may be useful biomarkers to identify OL patients with a substantially high oral cancer risk.

  11. Increased stomach cancer risk following radiotherapy for testicular cancer

    DEFF Research Database (Denmark)

    Hauptmann, M; Fossa, S D; Stovall, M

    2015-01-01

    BACKGROUND: Abdominal radiotherapy for testicular cancer (TC) increases risk for second stomach cancer, although data on the radiation dose-response relationship are sparse. METHODS: In a cohort of 22,269 5-year TC survivors diagnosed during 1959-1987, doses to stomach subsites were estimated...... for 92 patients who developed stomach cancer and 180 matched controls. Chemotherapy details were recorded. Odds ratios (ORs) were estimated using logistic regression. RESULTS: Cumulative incidence of second primary stomach cancer was 1.45% at 30 years after TC diagnosis. The TC survivors who received...... radiotherapy (87 (95%) cases, 151 (84%) controls) had a 5.9-fold (95% confidence interval (CI) 1.7-20.7) increased risk of stomach cancer. Risk increased with increasing stomach dose (P-trend

  12. Telomere length, ATM mutation status and cancer risk in Ataxia-Telangiectasia families.

    Science.gov (United States)

    Renault, Anne-Laure; Mebirouk, Noura; Cavaciuti, Eve; Le Gal, Dorothée; Lecarpentier, Julie; d'Enghien, Catherine Dubois; Laugé, Anthony; Dondon, Marie-Gabrielle; Labbé, Martine; Lesca, Gaetan; Leroux, Dominique; Gladieff, Laurence; Adenis, Claude; Faivre, Laurence; Gilbert-Dussardier, Brigitte; Lortholary, Alain; Fricker, Jean-Pierre; Dahan, Karin; Bay, Jacques-Olivier; Longy, Michel; Buecher, Bruno; Janin, Nicolas; Zattara, Hélène; Berthet, Pascaline; Combès, Audrey; Coupier, Isabelle; Hall, Janet; Stoppa-Lyonnet, Dominique; Andrieu, Nadine; Lesueur, Fabienne

    2017-10-01

    Recent studies have linked constitutive telomere length (TL) to aging-related diseases including cancer at different sites. ATM participates in the signaling of telomere erosion, and inherited mutations in ATM have been associated with increased risk of cancer, particularly breast cancer. The goal of this study was to investigate whether carriage of an ATM mutation and TL interplay to modify cancer risk in ataxia-telangiectasia (A-T) families.The study population consisted of 284 heterozygous ATM mutation carriers (HetAT) and 174 non-carriers (non-HetAT) from 103 A-T families. Forty-eight HetAT and 14 non-HetAT individuals had cancer, among them 25 HetAT and 6 non-HetAT were diagnosed after blood sample collection. We measured mean TL using a quantitative PCR assay and genotyped seven single-nucleotide polymorphisms (SNPs) recurrently associated with TL in large population-based studies.HetAT individuals were at increased risk of cancer (OR = 2.3, 95%CI = 1.2-4.4, P = 0.01), and particularly of breast cancer for women (OR = 2.9, 95%CI = 1.2-7.1, P = 0.02), in comparison to their non-HetAT relatives. HetAT individuals had longer telomeres than non-HetAT individuals (P = 0.0008) but TL was not associated with cancer risk, and no significant interaction was observed between ATM mutation status and TL. Furthermore, rs9257445 (ZNF311) was associated with TL in HetAT subjects and rs6060627 (BCL2L1) modified cancer risk in HetAT and non-HetAT women.Our findings suggest that carriage of an ATM mutation impacts on the age-related TL shortening and that TL per se is not related to cancer risk in ATM carriers. TL measurement alone is not a good marker for predicting cancer risk in A-T families. © The Author 2017. Published by Oxford University Press.

  13. Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study.

    Directory of Open Access Journals (Sweden)

    Camille Lassale

    Full Text Available Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre was 0.75 (0.72-0.79 to 0.88 (0.84-0.92 for all-cause, 0.76 (0.69-0.83 to 0.84 (0.76-0.92 for CVD and 0.78 (0.73-0.83 to 0.91 (0.85-0.97 for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors.

  14. Lung cancer risk associated with Thr495Pro polymorphism of GHR in Chinese population.

    Science.gov (United States)

    Cao, Guochun; Lu, Hongna; Feng, Jifeng; Shu, Jian; Zheng, Datong; Hou, Yayi

    2008-04-01

    The incidence of lung cancer has been increasing over recent decades. Previous studies showed that polymorphisms of the genes involved in carcinogen-detoxication, DNA repair and cell cycle control comprise risk factors for lung cancer. Recent observations revealed that the growth hormone receptor (GHR) might play important roles in carcinogenesis and Rudd et al. found that the Thr495Pro polymorphism of GHR was strongly associated with lung cancer risk in Caucasians living in the UK (OR = 12.98, P = 0.0019, 95% CI: 1.77-infinity). To test whether this variant of GHR would modify the risk of lung cancer in Chinese population, we compared the polymorphism between 778 lung cancer patients and 781 healthy control subjects. Our results indicate that the frequency of 495Thr (2.8%) allele in cases was significantly higher than in controls (OR = 2.04, P = 0.006, 95% CI: 1.21-3.42) which indicated this allele might be a risk factor for lung cancer. Further analyses revealed Thr495Pro variant was associated with lung cancer in the subpopulation with higher risk for lung cancer: male subpopulation, still-smokers subpopulation and the subpopulation with familial history of cancer. In different histological types of lung cancer, Thr495Pro SNP was significantly associated with small cell and squamous cell lung cancer, but not with adenocarcinoma, which suggested a potential interaction between this polymorphism and metabolic pathways related to smoking. The potential gene-environment interaction on lung cancer risk was evaluated using MDR software. A significant redundant interaction between Thr495Pro polymorphism and smoking dose and familial history of cancer was identified and the combination of genetic factors and smoking status or familial history of cancer barely increased the cancer risk prediction accuracy. In conclusion, our results suggested that the Thr495Pro polymorphism of GHR was associated with the risk of lung cancer in a redundant interaction with smoking and

  15. Familial risks and estrogen receptor-positive breast cancer in Hong Kong Chinese women.

    Science.gov (United States)

    Tse, Lap Ah; Li, Mengjie; Chan, Wing-cheong; Kwok, Chi-hei; Leung, Siu-lan; Wu, Cherry; Yu, Ignatius Tak-sun; Yu, Wai-cho; Lao, Xiangqian; Wang, Xiaorong; Wong, Carmen Ka-man; Lee, Priscilla Ming-yi; Wang, Feng; Yang, Xiaohong Rose

    2015-01-01

    The role of family history to the risk of breast cancer was analyzed by incorporating menopausal status in Hong Kong Chinese women, with a particular respect to the estrogen receptor-positive (ER+) type. Seven hundred and forty seven breast cancer incident cases and 781 hospital controls who had completed information on family cancer history in first-degree relatives (nature father, mother, and siblings) were recruited. Odds ratio for breast cancer were calculated by unconditional multiple logistic regression, stratified by menopausal status (a surrogate of endogenous female sex hormone level and age) and type of relative affected with the disease. Further subgroup analysis by tumor type according to ER status was investigated. Altogether 52 (6.96%) breast cancer cases and 23 (2.95%) controls was found that the patients' one or more first-degree relatives had a history of breast cancer, showing an adjusted odds ratio (OR) of 2.41 (95%CI: 1.45-4.02). An excess risk of breast cancer was restricted to the ER+ tumor (OR = 2.43, 95% CI: 1.38-4.28), with a relatively higher risk associated with an affected mother (OR = 3.97, 95%CI: 1.46-10.79) than an affected sister (OR = 2.06, 95%CI: 1.07-3.97), while the relative risk was more prominent in the subgroup of pre-menopausal women. Compared with the breast cancer overall, the familial risks to the ER+ tumor increased progressively with the number of affected first-degree relatives. This study provides new insights on a relationship between family breast cancer history, menopausal status, and the ER+ breast cancer. A separate risk prediction model for ER+ tumor in Asian population is desired.

  16. Brachytherapy boost and cancer-specific mortality in favorable high-risk versus other high-risk prostate cancer

    Directory of Open Access Journals (Sweden)

    Vinayak Muralidhar

    2016-02-01

    Full Text Available Purpose : Recent retrospective data suggest that brachytherapy (BT boost may confer a cancer-specific survival benefit in radiation-managed high-risk prostate cancer. We sought to determine whether this survival benefit would extend to the recently defined favorable high-risk subgroup of prostate cancer patients (T1c, Gleason 4 + 4 = 8, PSA 20 ng/ml. Material and methods: We identified 45,078 patients in the Surveillance, Epidemiology, and End Results database with cT1c-T3aN0M0 intermediate- to high-risk prostate cancer diagnosed 2004-2011 treated with external beam radiation therapy (EBRT only or EBRT plus BT. We used multivariable competing risks regression to determine differences in the rate of prostate cancer-specific mortality (PCSM after EBRT + BT or EBRT alone in patients with intermediate-risk, favorable high-risk, or other high-risk disease after adjusting for demographic and clinical factors. Results : EBRT + BT was not associated with an improvement in 5-year PCSM compared to EBRT alone among patients with favorable high-risk disease (1.6% vs. 1.8%; adjusted hazard ratio [AHR]: 0.56; 95% confidence interval [CI]: 0.21-1.52, p = 0.258, and intermediate-risk disease (0.8% vs. 1.0%, AHR: 0.83, 95% CI: 0.59-1.16, p = 0.270. Others with high-risk disease had significantly lower 5-year PCSM when treated with EBRT + BT compared with EBRT alone (3.9% vs. 5.3%; AHR: 0.73; 95% CI: 0.55-0.95; p = 0.022. Conclusions : Brachytherapy boost is associated with a decreased rate of PCSM in some men with high-risk prostate cancer but not among patients with favorable high-risk disease. Our results suggest that the recently-defined “favorable high-risk” category may be used to personalize therapy for men with high-risk disease.

  17. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    Science.gov (United States)

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    specific patterns and tissue-specificity, which are driven by aging and other cancer-inducing agents. This framework represents the logics of complex cancer biology as a myriad of phenotypic complexities governed by a limited set of underlying organizing principles. It therefore adds to our understanding of tumor evolution and tumorigenesis, and moreover, potential usefulness of predicting tumors' evolutionary paths and clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for cancer patients, as well as cancer risks for healthy individuals are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial impact on timely diagnosis, personalized treatment and personalized prevention of cancer. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  18. Body Fat and Breast Cancer Risk in Postmenopausal Women: A Longitudinal Study

    Directory of Open Access Journals (Sweden)

    Thomas E. Rohan

    2013-01-01

    Full Text Available Associations between anthropometric indices of obesity and breast cancer risk may fail to capture the true relationship between excess body fat and risk. We used dual-energy-X-ray-absorptiometry- (DXA- derived measures of body fat obtained in the Women’s Health Initiative to examine the association between body fat and breast cancer risk; we compared these risk estimates with those for conventional anthropometric measurements. The study included 10,960 postmenopausal women aged 50–79 years at recruitment, with baseline DXA measurements and no history of breast cancer. During followup (median: 12.9 years, 503 incident breast cancer cases were diagnosed. Hazard ratios (HR and 95% confidence intervals (CI were estimated using Cox proportional hazards models. All baseline DXA-derived body fat measures showed strong positive associations with breast cancer risk. The multivariable-adjusted HR for the uppermost quintile level (versus lowest ranged from 1.53 (95% CI 1.14–2.07 for fat mass of the right leg to 2.05 (1.50–2.79 for fat mass of the trunk. Anthropometric indices (categorized by quintiles of obesity (BMI (1.97, 1.45–2.68, waist circumference (1.97, 1.46–2.65, and waist : hip ratio (1.91, 1.41–2.58 were all strongly, positively associated with risk and did not differ from DXA-derived measures in prediction of risk.

  19. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

    Science.gov (United States)

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

    2014-09-09

    Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

  20. Predictive genetic testing for hereditary breast and ovarian cancer: psychological distress and illness representations 1 year following disclosure.

    Science.gov (United States)

    Claes, E; Evers-Kiebooms, G; Denayer, L; Decruyenaere, M; Boogaerts, A; Philippe, K; Legius, E

    2005-10-01

    This prospective study evaluates emotional functioning and illness representations in 68 unaffected women (34 carriers/34 noncarriers) 1 year after predictive testing for BRCA1/2 mutations when offered within a multidisciplinary approach. Carriers had higher subjective risk perception of breast cancer than noncarriers. Carriers who did not have prophylactic oophorectomy had the highest risk perception of ovarian cancer. No differences were found between carriers and noncarriers regarding perceived seriousness and perceived control of breast and ovarian cancer. Mean levels of distress were within normal ranges. Only few women showed an overall pattern of clinically elevated distress. Cancer-specific distress and state-anxiety significantly decreased in noncarriers from pre- to posttest while general distress remained about the same. There were no significant changes in distress in the group of carriers except for ovarian cancer distress which significantly decreased from pre- to posttest. Our study did not reveal adverse effects of predictive testing when offered in the context of a multidisciplinary approach.

  1. Nomogram to predict rectal toxicity following prostate cancer radiotherapy.

    Directory of Open Access Journals (Sweden)

    Jean-Bernard Delobel

    Full Text Available To identify predictors of acute and late rectal toxicity following prostate cancer radiotherapy (RT, while integrating the potential impact of RT technique, dose escalation, and moderate hypofractionation, thus enabling us to generate a nomogram for individual prediction.In total, 972 patients underwent RT for localized prostate cancer, to a total dose of 70 Gy or 80 Gy, using two different fractionations (2 Gy or 2.5 Gy/day, by means of several RT techniques (3D conformal RT [3DCRT], intensity-modulated RT [IMRT], or image-guided RT [IGRT]. Multivariate analyses were performed to identify predictors of acute and late rectal toxicity. A nomogram was generated based on the logistic regression model used to predict the 3-year rectal toxicity risk, with its accuracy assessed by dividing the cohort into training and validation subgroups.Mean follow-up for the entire cohort was 62 months, ranging from 6 to 235. The rate of acute Grade ≥2 rectal toxicity was 22.2%, decreasing when combining IMRT and IGRT, compared to 3DCRT (RR = 0.4, 95%CI: 0.3-0.6, p<0.01. The 5-year Grade ≥2 risks for rectal bleeding, urgency/tenesmus, diarrhea, and fecal incontinence were 9.9%, 4.5%, 2.8%, and 0.4%, respectively. The 3-year Grade ≥2 risk for overall rectal toxicity increased with total dose (p<0.01, RR = 1.1, 95%CI: 1.0-1.1 and dose per fraction (2Gy vs. 2.5Gy (p = 0.03, RR = 3.3, 95%CI: 1.1-10.0, and decreased when combining IMRT and IGRT (RR = 0.50, 95% CI: 0.3-0.8, p<0.01. Based on these three parameters, a nomogram was generated.Dose escalation and moderate hypofractionation increase late rectal toxicity. IMRT combined with IGRT markedly decreases acute and late rectal toxicity. Performing combined IMRT and IGRT can thus be envisaged for dose escalation and moderate hypofractionation. Our nomogram predicts the 3-year rectal toxicity risk by integrating total dose, fraction dose, and RT technique.

  2. Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

    Science.gov (United States)

    Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

    2018-01-01

    The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

  3. Surrogates of Long-Term Vitamin D Exposure and Ovarian Cancer Risk in Two Prospective Cohort Studies

    International Nuclear Information System (INIS)

    Prescott, Jennifer; Bertrand, Kimberly A.; Poole, Elizabeth M.; Rosner, Bernard A.; Tworoger, Shelley S.

    2013-01-01

    Experimental evidence and ecologic studies suggest a protective role of vitamin D in ovarian carcinogenesis. However, epidemiologic studies using individual level data have been inconsistent. We evaluated ultraviolet (UV)-B radiation, vitamin D intake, and predicted plasma 25-hydroxyvitamin D [25(OH)D] levels as long-term surrogates of vitamin D exposure within the Nurses’ Health Study (NHS) and NHSII. We estimated incidence rate ratios (RRs) and 95% confidence intervals (CIs) for risk of overall ovarian cancer and by histologic subtype using Cox proportional hazards models. Between 1976 and 2010 in NHS and 1989 and 2011 in NHSII, we identified a total of 1,225 incident epithelial ovarian cancer cases (NHS: 970, NHSII: 255) over 4,628,648 person-years of follow-up. Cumulative average UV-B exposure was not associated with ovarian cancer risk in NHS (P trend = 0.08), but was associated with reduced risk in NHSII (highest vs. lowest category RR = 0.67; 95% CI: 0.50, 0.89; P trend < 0.01). When stratified by histologic subtype, UV-B flux was positively associated with risk of serous tumors in NHS (P trend < 0.01), but inversely associated in NHSII (P trend = 0.01). Adjusted for confounders, ovarian cancer risk was not associated with vitamin D intake from food or supplements or with predicted 25(OH)D levels. Our study does not strongly support a protective role for vitamin D in ovarian cancer risk

  4. Surrogates of Long-Term Vitamin D Exposure and Ovarian Cancer Risk in Two Prospective Cohort Studies

    Energy Technology Data Exchange (ETDEWEB)

    Prescott, Jennifer, E-mail: jennifer.prescott@channing.harvard.edu; Bertrand, Kimberly A.; Poole, Elizabeth M.; Rosner, Bernard A.; Tworoger, Shelley S. [Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 181 Longwood Ave. Boston, MA 02115 (United States)

    2013-11-22

    Experimental evidence and ecologic studies suggest a protective role of vitamin D in ovarian carcinogenesis. However, epidemiologic studies using individual level data have been inconsistent. We evaluated ultraviolet (UV)-B radiation, vitamin D intake, and predicted plasma 25-hydroxyvitamin D [25(OH)D] levels as long-term surrogates of vitamin D exposure within the Nurses’ Health Study (NHS) and NHSII. We estimated incidence rate ratios (RRs) and 95% confidence intervals (CIs) for risk of overall ovarian cancer and by histologic subtype using Cox proportional hazards models. Between 1976 and 2010 in NHS and 1989 and 2011 in NHSII, we identified a total of 1,225 incident epithelial ovarian cancer cases (NHS: 970, NHSII: 255) over 4,628,648 person-years of follow-up. Cumulative average UV-B exposure was not associated with ovarian cancer risk in NHS (P{sub trend} = 0.08), but was associated with reduced risk in NHSII (highest vs. lowest category RR = 0.67; 95% CI: 0.50, 0.89; P{sub trend} < 0.01). When stratified by histologic subtype, UV-B flux was positively associated with risk of serous tumors in NHS (P{sub trend} < 0.01), but inversely associated in NHSII (P{sub trend} = 0.01). Adjusted for confounders, ovarian cancer risk was not associated with vitamin D intake from food or supplements or with predicted 25(OH)D levels. Our study does not strongly support a protective role for vitamin D in ovarian cancer risk.

  5. Surrogates of Long-Term Vitamin D Exposure and Ovarian Cancer Risk in Two Prospective Cohort Studies

    Directory of Open Access Journals (Sweden)

    Jennifer Prescott

    2013-11-01

    Full Text Available Experimental evidence and ecologic studies suggest a protective role of vitamin D in ovarian carcinogenesis. However, epidemiologic studies using individual level data have been inconsistent. We evaluated ultraviolet (UV-B radiation, vitamin D intake, and predicted plasma 25-hydroxyvitamin D [25(OHD] levels as long-term surrogates of vitamin D exposure within the Nurses’ Health Study (NHS and NHSII. We estimated incidence rate ratios (RRs and 95% confidence intervals (CIs for risk of overall ovarian cancer and by histologic subtype using Cox proportional hazards models. Between 1976 and 2010 in NHS and 1989 and 2011 in NHSII, we identified a total of 1,225 incident epithelial ovarian cancer cases (NHS: 970, NHSII: 255 over 4,628,648 person-years of follow-up. Cumulative average UV-B exposure was not associated with ovarian cancer risk in NHS (Ptrend = 0.08, but was associated with reduced risk in NHSII (highest vs. lowest category RR = 0.67; 95% CI: 0.50, 0.89; Ptrend < 0.01. When stratified by histologic subtype, UV-B flux was positively associated with risk of serous tumors in NHS (Ptrend < 0.01, but inversely associated in NHSII (Ptrend = 0.01. Adjusted for confounders, ovarian cancer risk was not associated with vitamin D intake from food or supplements or with predicted 25(OHD levels. Our study does not strongly support a protective role for vitamin D in ovarian cancer risk.

  6. Regulatory Forum commentary: alternative mouse models for future cancer risk assessment.

    Science.gov (United States)

    Morton, Daniel; Sistare, Frank D; Nambiar, Prashant R; Turner, Oliver C; Radi, Zaher; Bower, Nancy

    2014-07-01

    International regulatory and pharmaceutical industry scientists are discussing revision of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) S1 guidance on rodent carcinogenicity assessment of small molecule pharmaceuticals. A weight-of-evidence approach is proposed to determine the need for rodent carcinogenicity studies. For compounds with high human cancer risk, the product may be labeled appropriately without conducting rodent carcinogenicity studies. For compounds with minimal cancer risk, only a 6-month transgenic mouse study (rasH2 mouse or p53+/- mouse) or a 2-year mouse study would be needed. If rodent carcinogenicity testing may add significant value to cancer risk assessment, a 2-year rat study and either a 6-month transgenic mouse or a 2-year mouse study is appropriate. In many cases, therefore, one rodent carcinogenicity study could be sufficient. The rasH2 model predicts neoplastic findings relevant to human cancer risk assessment as well as 2-year rodent models, produces fewer irrelevant neoplastic outcomes, and often will be preferable to a 2-year rodent study. Before revising ICH S1 guidance, a prospective evaluation will be conducted to test the proposed weight-of-evidence approach. This evaluation offers an opportunity for a secondary analysis comparing the value of alternative mouse models and 2-year rodent studies in the proposed ICH S1 weight-of-evidence approach for human cancer risk assessment. © 2014 by The Author(s).

  7. Risk Belief and Attitude Formation From Translated Scientific Messages About PFOA, an Environmental Risk Associated With Breast Cancer.

    Science.gov (United States)

    Smith, Sandi W; Hitt, Rose; Russell, Jessica; Nazione, Samantha; Silk, Kami; Atkin, Charles K; Keating, David

    2017-03-01

    Evidence regarding possible environmental causes of breast cancer is advancing. Often, however, the public is not informed about these advances in a manner that is easily understandable. This research translates findings from biologists into messages at two literacy levels about perfluorooctanoic acid (PFOA), a possible environmental contributor to breast cancer. The Heuristic Systematic Model (HSM) was used to investigate how ability, motivation, and systematic and heuristic processing lead to risk beliefs and, ultimately, to negative attitudes for individuals receiving translated scientific messages about PFOA. Participants (N = 1,389) came from the Dr. Susan Love Research Foundation's Army of Women. Findings indicated that ability, in the form of translated messages, predicted systematic processing, operationalized as knowledge gain, which was negatively associated with formation of risk beliefs that led to negative attitudes toward PFOA. Heuristic processing cues, operationalized as perceived message quality and source credibility, were positively associated with risk beliefs, which predicted negative attitudes about PFOA. Overall, more knowledge and lower literacy messages led to lower perceived risk, while greater involvement and ratings of heuristic cues led to greater risk perceptions. This is an example of a research, translation, and dissemination team effort in which biologists created knowledge, communication scholars translated and tested messages, and advocates were participants and those who disseminated messages.

  8. The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer.

    Science.gov (United States)

    Thakur, Satbir Singh; Li, Haocheng; Chan, Angela M Y; Tudor, Roxana; Bigras, Gilbert; Morris, Don; Enwere, Emeka K; Yang, Hua

    2018-01-01

    Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates. The Ki67 indices calculated using this method were highly concordant with manual scoring by a pathologist (Pearson's r = 0.909) and between users (Pearson's r = 0.984). We assessed the clinical validity of this method by scoring Ki67 from 328 whole-slide sections of resected early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. All patients had Oncotype DX testing performed (Genomic Health) and available Recurrence Scores. High Ki67 indices correlated significantly with several clinico-pathological correlates, including higher tumor grade (1 versus 3, P<0.001), higher mitotic score (1 versus 3, P<0.001), and lower Allred scores for estrogen and progesterone receptors (P = 0.002, 0.008). High Ki67 indices were also significantly correlated with higher Oncotype DX risk-of-recurrence group (low versus high, P<0.001). Ki67 index was the major contributor to a machine learning model which, when trained solely on clinico-pathological data and Ki67 scores, identified Oncotype DX high- and low-risk patients with 97% accuracy, 98% sensitivity and 80% specificity. Automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy, in a manner that integrates readily into the workflow of a pathology laboratory. Furthermore, automated Ki67 scores contribute significantly to models that predict risk of

  9. The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer.

    Directory of Open Access Journals (Sweden)

    Satbir Singh Thakur

    predict risk of recurrence in breast cancer.

  10. Perceived breast cancer risk: heuristic reasoning and search for a dominance structure.

    Science.gov (United States)

    Katapodi, Maria C; Facione, Noreen C; Humphreys, Janice C; Dodd, Marylin J

    2005-01-01

    Studies suggest that people construct their risk perceptions by using inferential rules called heuristics. The purpose of this study was to identify heuristics that influence perceived breast cancer risk. We examined 11 interviews from women of diverse ethnic/cultural backgrounds who were recruited from community settings. Narratives in which women elaborated about their own breast cancer risk were analyzed with Argument and Heuristic Reasoning Analysis methodology, which is based on applied logic. The availability, simulation, representativeness, affect, and perceived control heuristics, and search for a dominance structure were commonly used for making risk assessments. Risk assessments were based on experiences with an abnormal breast symptom, experiences with affected family members and friends, beliefs about living a healthy lifestyle, and trust in health providers. Assessment of the potential threat of a breast symptom was facilitated by the search for a dominance structure. Experiences with family members and friends were incorporated into risk assessments through the availability, simulation, representativeness, and affect heuristics. Mistrust in health providers led to an inappropriate dependence on the perceived control heuristic. Identified heuristics appear to create predictable biases and suggest that perceived breast cancer risk is based on common cognitive patterns.

  11. Risk of prostate and bladder cancers in patients with spinal cord injury: a population-based cohort study.

    Science.gov (United States)

    Lee, Wen-Yuan; Sun, Li-Min; Lin, Cheng-Li; Liang, Ji-An; Chang, Yen-Jung; Sung, Fung-Chang; Kao, Chia-Hung

    2014-01-01

    To evaluate the risk of prostate and bladder cancers in patients with spinal cord injury (SCI). We used data obtained from the National Health Insurance system of Taiwan for this study. The SCI cohort contained 54,401 patients with SCI, and each patient was randomly frequency matched with 4 people from the general population (without SCI) based on age, sex, and index date. Incidence rates, SCI cohort to non-SCI cohort rate ratios, and hazard ratios were measured to evaluate the cancer risks. Patients with SCI showed a significantly lower risk of developing prostate cancer compared with subjects without SCI (adjusted hazard ratio = 0.73; 95% confidence interval = 0.59, 0.90), after accounting for the competing risk of death. No significant difference in the risk of bladder cancer emerged between the SCI and control groups. Further analyses found a higher spinal level of SCI tended to predict a lower risk for prostate cancer. Patients with SCI incurred a lower risk for prostate cancer compared with people without SCI. The risk for bladder cancer did not differ between people with or without SCI. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

    Science.gov (United States)

    Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G M; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M

    2014-01-01

    In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

  13. Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

    Directory of Open Access Journals (Sweden)

    Hui Miao

    Full Text Available BACKGROUND: In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. MATERIALS AND METHODS: We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic. RESULTS: We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53 to 0.63 (95% CI, 0.60-0.66. CONCLUSION: The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

  14. Sugars, sucrose and colorectal cancer risk: the Fukuoka colorectal cancer study.

    Science.gov (United States)

    Wang, Zhenjie; Uchida, Kazuhiro; Ohnaka, Keizo; Morita, Makiko; Toyomura, Kengo; Kono, Suminori; Ueki, Takashi; Tanaka, Masao; Kakeji, Yoshihiro; Maehara, Yoshihiko; Okamura, Takeshi; Ikejiri, Koji; Futami, Kitaroh; Maekawa, Takafumi; Yasunami, Yohichi; Takenaka, Kenji; Ichimiya, Hitoshi; Terasaka, Reiji

    2014-05-01

    A diet high in sugars may promote colorectal carcinogenesis, but it remains uncertain whether high intake of sugars or sucrose confers increased risk of colorectal cancer. The authors investigated the associations of sugars and sucrose intake with colorectal cancer risk in a community-based case-control study in Japan. The study subjects comprised 816 incident cases of colorectal cancer and 815 community controls. Consumption frequencies and portion sizes of 148 food and beverage items were ascertained by a computer-assisted interview. The authors used the consumption of 29 food items to estimate sugars and sucrose intake. The odds ratios of colorectal cancer risk according to intake categories were obtained using a logistic regression model with adjustment for potential confounding variables. Overall, intakes of sugars and sucrose were not related to colorectal cancer risk either in men or women. The association between sugars intake and colorectal cancer risk differed by smoking status and alcohol use in men, but not in women. In men, sugars intake tended to be associated with colorectal cancer risk inversely among never-smokers and positively among male ever-smokers (interaction p=0.01). Sugars intake was associated with an increased risk among men with no alcohol consumption, but was unrelated to the risk among male alcohol drinkers (interaction p=0.02). Body mass index did not modify the association with sugars intake in either men or women. Sugars intake was associated with increased risk of colorectal cancer among smokers and non-alcohol drinkers in men selectively.

  15. Using HPV prevalence to predict cervical cancer incidence.

    Science.gov (United States)

    Sharma, Monisha; Bruni, Laia; Diaz, Mireia; Castellsagué, Xavier; de Sanjosé, Silvia; Bosch, F Xavier; Kim, Jane J

    2013-04-15

    Knowledge of a country's cervical cancer (CC) burden is critical to informing decisions about resource allocation to combat the disease; however, many countries lack cancer registries to provide such data. We developed a prognostic model to estimate CC incidence rates in countries without cancer registries, leveraging information on human papilloma virus (HPV) prevalence, screening, and other country-level factors. We used multivariate linear regression models to identify predictors of CC incidence in 40 countries. We extracted age-specific HPV prevalence (10-year age groups) by country from a meta-analysis in women with normal cytology (N = 40) and matched to most recent CC incidence rates from Cancer Incidence in Five Continents when available (N = 36), or Globocan 2008 (N = 4). We evaluated country-level behavioral, economic, and public health indicators. CC incidence was significantly associated with age-specific HPV prevalence in women aged 35-64 (adjusted R-squared 0.41) ("base model"). Adding geographic region to the base model increased the adjusted R-squared to 0.77, but the further addition of screening was not statistically significant. Similarly, country-level macro-indicators did not improve predictive validity. Age-specific HPV prevalence at older ages was found to be a better predictor of CC incidence than prevalence in women under 35. However, HPV prevalence could not explain the entire CC burden as many factors modify women's risk of progression to cancer. Geographic region seemed to serve as a proxy for these country-level indicators. Our analysis supports the assertion that conducting a population-based HPV survey targeting women over age 35 can be valuable in approximating the CC risk in a given country. Copyright © 2012 UICC.

  16. Using an Internet-Based Breast Cancer Risk Assessment Tool to Improve Social-Cognitive Precursors of Physical Activity.

    Science.gov (United States)

    Fowler, Stephanie L; Klein, William M P; Ball, Linda; McGuire, Jaclyn; Colditz, Graham A; Waters, Erika A

    2017-08-01

    Internet-based cancer risk assessment tools might serve as a strategy for translating epidemiological risk prediction research into public health practice. Understanding how such tools affect key social-cognitive precursors of behavior change is crucial for leveraging their potential into effective interventions. To test the effects of a publicly available, Internet-based, breast cancer risk assessment tool on social-cognitive precursors of physical activity. Women (N = 132) aged 40-78 with no personal cancer history indicated their perceived risk of breast cancer and were randomly assigned to receive personalized ( www.yourdiseaserisk.wustl.edu ) or nonpersonalized breast cancer risk information. Immediately thereafter, breast cancer risk perceptions and physical activity-related behavioral intentions, self-efficacy, and response efficacy were assessed. Personalized information elicited higher intentions, self-efficacy, and response efficacy than nonpersonalized information, P values Internet-based risk assessment tools can produce beneficial effects on important social-cognitive precursors of behavior change, but lingering skepticism, possibly due to defensive processing, needs to be addressed before the effects can be maximized.

  17. Validation of the 12-gene colon cancer recurrence score as a predictor of recurrence risk in stage II and III rectal cancer patients.

    Science.gov (United States)

    Reimers, Marlies S; Kuppen, Peter J K; Lee, Mark; Lopatin, Margarita; Tezcan, Haluk; Putter, Hein; Clark-Langone, Kim; Liefers, Gerrit Jan; Shak, Steve; van de Velde, Cornelis J H

    2014-11-01

    The 12-gene Recurrence Score assay is a validated predictor of recurrence risk in stage II and III colon cancer patients. We conducted a prospectively designed study to validate this assay for prediction of recurrence risk in stage II and III rectal cancer patients from the Dutch Total Mesorectal Excision (TME) trial. RNA was extracted from fixed paraffin-embedded primary rectal tumor tissue from stage II and III patients randomized to TME surgery alone, without (neo)adjuvant treatment. Recurrence Score was assessed by quantitative real time-polymerase chain reaction using previously validated colon cancer genes and algorithm. Data were analysed by Cox proportional hazards regression, adjusting for stage and resection margin status. All statistical tests were two-sided. Recurrence Score predicted risk of recurrence (hazard ratio [HR] = 1.57, 95% confidence interval [CI] = 1.11 to 2.21, P = .01), risk of distant recurrence (HR = 1.50, 95% CI = 1.04 to 2.17, P = .03), and rectal cancer-specific survival (HR = 1.64, 95% CI = 1.15 to 2.34, P = .007). The effect of Recurrence Score was most prominent in stage II patients and attenuated with more advanced stage (P(interaction) ≤ .007 for each endpoint). In stage II, five-year cumulative incidence of recurrence ranged from 11.1% in the predefined low Recurrence Score group (48.5% of patients) to 43.3% in the high Recurrence Score group (23.1% of patients). The 12-gene Recurrence Score is a predictor of recurrence risk and cancer-specific survival in rectal cancer patients treated with surgery alone, suggesting a similar underlying biology in colon and rectal cancers. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  18. Negative HPV screening test predicts low cervical cancer risk better than negative Pap test

    Science.gov (United States)

    Based on a study that included more than 1 million women, investigators at NCI have determined that a negative test for HPV infection compared to a negative Pap test provides greater safety, or assurance, against future risk of cervical cancer.

  19. Awareness of risk factors for cancer

    DEFF Research Database (Denmark)

    Lagerlund, Magdalena; Hvidberg, Line; Hajdarevic, Senada

    2015-01-01

    Background: Sweden and Denmark are neighbouring countries with similarities in culture, healthcare, and economics, yet notable differences in cancer statistics. A crucial component of primary prevention is high awareness of risk factors in the general public. We aimed to determine and compare...... awareness of risk factors for cancer between a Danish and a Swedish population sample, and to examine whether there are differences in awareness across age groups. Methods: Data derive from Module 2 of the International Cancer Benchmarking Partnership. Telephone interviews were conducted with 3000 adults...... in Denmark and 3070 in Sweden using the Awareness and Beliefs about Cancer measure. Data reported here relate to awareness of 13 prompted risk factors for cancer. Prevalence ratios with 95 % confidence intervals were calculated to examine associations between country, age, and awareness of risk factors...

  20. Radical prostatectomy for high-risk prostate cancer.

    Science.gov (United States)

    Yossepowitch, Ofer; Eastham, James A

    2008-06-01

    Consensus recommendations for the identification and treatment of men whose apparent organ confined prostate cancer has high risk features are lacking. Despite ongoing refinements in surgical technique and improvements in morbidity and functional outcomes, the tradition of steering high-risk patients away from radical prostatectomy (RP) remains steadfast. We performed a medical literature search in English using MEDLINE/PubMed that addressed high risk prostate cancer. We analyzed the literature with respect to the historical evolution of this concept, current risk stratification schemes and treatment guidelines and related short and long term outcomes following RP. Contemporary evidence suggest that patients classified with high-risk prostate cancer by commonly used definitions do not have a uniformly poor prognosis after RP. Many cancers categorized clinically as high risk are actually pathologically confined to the prostate, and most men with such cancers who undergo RP are alive and free of additional therapy long after surgery. RP in the high-risk setting appears to be associated with a similar morbidity as in lower-risk patients. Men with clinically localized high-risk prostate cancer should not be categorically disqualified from local definitive therapy with RP. With careful attention to surgical technique, cancer control rates should improve further, and adverse effects on quality of life after RP should continue to decrease.

  1. Forecasting Model of Risk of Cancer in Lung Cancer Pedigree in a Case-control Study

    Directory of Open Access Journals (Sweden)

    Huan LIN

    2011-07-01

    Full Text Available Background and objective Annual lung screening using spiral computed tomography (CT, has a high sensitivity of detecting early lung cancer (LC, but its high rates of false-positive often lead to unnecessary surgery. The aim of this study is to create a forecasting model of high risk individuals to lung cancer. Methods The pathologic diagnoses of LC in Guangdong Lung Cancer Institute were consecutively chosen as the probands. All the members of the first-degree relatives of probands' and their spouses' were enrolled in this study. These pedigrees consisted of 633 probands' pedigrees and 565 spouses' pedigrees. Unless otherwise stated, analyses were performed using the SPSS 17.0 statistical software package. Results Compared with the control, a family history of carcinoma in first-degree relatives was significantly associated with LC risk (OR=1.71, P<0.001, the sub-group of either one infected individual or more than two infected individuals in first-degree relatives showed significantly statistical differences (P=0.005, P=0.002. In the forecasting model, the risk compared to that in Chinese population was from 0.38 to 63.08 folds. In the population whose risk was more than 10 times to the Chinese population, the accuracy rate of prediction was 88.1%. Conclusion A family history of carcinoma in first-degree relatives was significantly associated with increased LC risk. The more infected individuals exist in first-degree relatives, the more risk was showed. In the forecasting model, smokers especially heavy ones whose risk were more than 10 times to the Chinese population should be receive annual screening. The population are positive at least any two conditions which including male, lung disease history, occupation expose and history of cancer in first-degree relative.

  2. Development and validation of prediction models for endometrial cancer in postmenopausal bleeding.

    Science.gov (United States)

    Wong, Alyssa Sze-Wai; Cheung, Chun Wai; Fung, Linda Wen-Ying; Lao, Terence Tzu-Hsi; Mol, Ben Willem J; Sahota, Daljit Singh

    2016-08-01

    To develop and assess the accuracy of risk prediction models to diagnose endometrial cancer in women having postmenopausal bleeding (PMB). A retrospective cohort study of 4383 women in a One-stop PMB clinic from a university teaching hospital in Hong Kong. Clinical risk factors, transvaginal ultrasonic measurement of endometrial thickness (ET) and endometrial histology were obtained from consecutive women between 2002 and 2013. Two models to predict risk of endometrial cancer were developed and assessed, one based on patient characteristics alone and a second incorporated ET with patient characteristics. Endometrial histology was used as the reference standard. The split-sample internal validation and bootstrapping technique were adopted. The optimal threshold for prediction of endometrial cancer by the final models was determined using a receiver-operating characteristics (ROC) curve and Youden Index. The diagnostic gain was compared to a reference strategy of measuring ET only by comparing the AUC using the Delong test. Out of 4383 women with PMB, 168 (3.8%) were diagnosed with endometrial cancer. ET alone had an area under curve (AUC) of 0.92 (95% confidence intervals [CIs] 0.89-0.94). In the patient characteristics only model, independent predictors of cancer were age at presentation, age at menopause, body mass index, nulliparity and recurrent vaginal bleeding. The AUC and Youdens Index of the patient characteristic only model were respectively 0.73 (95% CI 0.67-0.80) and 0.72 (Sensitivity=66.5%; Specificity=68.9%; +ve LR=2.14; -ve LR=0.49). ET, age at presentation, nulliparity and recurrent vaginal bleeding were independent predictors in the patient characteristics plus ET model. The AUC and Youdens Index of the patient characteristic plus ET model where respectively 0.92 (95% CI 0.88-0.96) and 0.71 (Sensitivity=82.7%; Specificity=88.3%; +ve LR=6.38; -ve LR=0.2). Comparison of AUC indicated that a history alone model was inferior to a model using ET alone

  3. Reproductive History and Breast Cancer Risk

    Science.gov (United States)

    ... Common Cancer Types Recurrent Cancer Common Cancer Types Bladder Cancer Breast Cancer Colorectal Cancer Kidney (Renal Cell) Cancer ... 4 ). This risk reduction is limited to hormone receptor –positive breast cancer; age at first full-term ...

  4. HSP60 may predict good pathological response to neoadjuvant chemoradiotherapy in bladder cancer

    International Nuclear Information System (INIS)

    Urushibara, Masayasu; Kageyama, Yukio; Akashi, Takumi; Otsuka, Yukihiro; Takizawa, Touichiro; Koike, Morio; Kihara, Kazunori

    2007-01-01

    Heat shock proteins (HSPs) play crucial roles in cellular responses to stressful conditions. Expression of HSPs in invasive or high-risk superficial bladder cancer was investigated to identify whether HSPs predict pathological response to neoadjuvant chemoradiotherapy (CRT). Immunohistochemistry was used to assess expression levels of HSP27, HSP60, HSP70, HSP90 and p53 in 54 patients with invasive or high-risk superficial bladder cancer, prior to low-dose neoadjuvant CRT, followed by radical or partial cystectomy. Patients were classified into two groups (good or poor responders) depending on pathological response to CRT, which was defined as the proportion of morphological therapeutic changes in surgical specimens. Good responders showed morphological therapeutic changes in two-thirds or more of tumor tissues. In contrast, poor responders showed changes in less than two-thirds of tumor tissues. Using a multivariate analysis, positive HSP60 expression prior to CRT was found to be marginally associated with good pathological response to CRT (P=0.0564). None of clinicopathological factors was associated with HSP60 expression level. In the good pathological responders, the 5-year cause-specific survival was 88%, which was significantly better than survival in the poor responders (51%) (P=0.0373). Positive HSP60 expression prior to CRT may predict good pathological response to low-dose neoadjuvant CRT in invasive or high-risk superficial bladder cancer. (author)

  5. A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer

    DEFF Research Database (Denmark)

    Nielsen, Mads; Karemore, Gopal; Loog, Marco

    2011-01-01

    Objective: We investigated whether breast cancer is predicted by a breast cancer risk mammographic texture resemblance (MTR) marker. Methods: A previously published case-control study included 495 women of which 245 were diagnosed with breast cancer. In baseline mammograms, 2-4 years prior...... to diagnosis, the following mammographic parameters were analysed for relation to breast cancer risk: (C) categorical parenchymal pattern scores; (R) radiologist's percentage density, (P) computer-based percentage density; (H) computer-based breast cancer risk MTR marker; (E) computer-based hormone replacement...... treatment MTR marker; and (A) an aggregate of P and H. Results: Density scores, C, R, and P correlated (tau=0.3-0.6); no other pair of scores showed large (tau>0.2) correlation. For the parameters, the odds ratios of future incidence of breast cancer comparing highest to lowest categories (146 and 106...

  6. Increased cancer risk in patients with periodontitis.

    Science.gov (United States)

    Dizdar, Omer; Hayran, Mutlu; Guven, Deniz Can; Yılmaz, Tolga Birtan; Taheri, Sahand; Akman, Abdullah C; Bilgin, Emre; Hüseyin, Beril; Berker, Ezel

    2017-12-01

    Previous studies have noted a possible association between periodontal diseases and the risk of various cancers. We assessed cancer risk in a cohort of patients with moderate to severe periodontitis. Patients diagnosed with moderate to severe periodontitis by a periodontist between 2001 and 2010 were identified from the hospital registry. Patients younger than 35 years of age or with a prior cancer diagnosis were excluded. The age- and gender-standardized incidence rates (SIR) were calculated by dividing the number of observed cases by the number of expected cases from Turkish National Cancer Registry 2013 data. A total of 280 patients were included (median age 49.6, 54% female). Median follow-up was 12 years. Twenty-five new cancer cases were observed. Patients with periodontitis had 77% increased risk of cancer (SIR 1.77, 95% CI 1.17-2.58, p = .004). Women with periodontitis had significantly higher risk of breast cancer (SIR 2.40, 95% CI 0.88-5.33) and men with periodontitis had significantly higher risk of prostate cancer (SIR 3.75, 95% CI 0.95-10.21) and hematological cancers (SIR 6.97, 95% CI 1.77-18.98). Although showing a causal association necessitates further investigation, our results support the idea that periodontitis might be associated with increased cancer risk, particularly with hematological, breast and prostate cancers.

  7. Northeast Regional Cancer Institute's Cancer Surveillance and Risk Factor Program

    Energy Technology Data Exchange (ETDEWEB)

    Lesko, Samuel M.

    2007-07-31

    OBJECTIVES The Northeast Regional Cancer Institute is conducting a program of ongoing epidemiologic research to address cancer disparities in northeast Pennsylvania. Of particular concern are disparities in the incidence of, stage at diagnosis, and mortality from colorectal cancer. In northeast Pennsylvania, age-adjusted incidence and mortality rates for colorectal cancer are higher, and a significantly smaller proportion of new colorectal cancer cases are diagnosed with local stage disease than is observed in comparable national data. Further, estimates of the prevalence of colorectal cancer screening in northeast Pennsylvania are lower than the US average. The Northeast Regional Cancer Institute’s research program supports surveillance of common cancers, investigations of cancer risk factors and screening behaviors, and the development of resources to further cancer research in this community. This project has the following specific objectives: I. To conduct cancer surveillance in northeast Pennsylvania. a. To monitor incidence and mortality for all common cancers, and colorectal cancer, in particular, and b. To document changes in the stage at diagnosis of colorectal cancer in this high-risk, underserved community. II. To conduct a population-based study of cancer risk factors and screening behavior in a six county region of northeast Pennsylvania. a. To monitor and document changes in colorectal cancer screening rates, and b. To document the prevalence of cancer risk factors (especially factors that increase the risk of colorectal cancer) and to identify those risk factors that are unusually common in this community. APPROACH Cancer surveillance was conducted using data from the Northeast Regional Cancer Institute’s population-based Regional Cancer Registry, the Pennsylvania Cancer Registry, and NCI’s SEER program. For common cancers, incidence and mortality were examined by county within the region and compared to data for similar populations in the US

  8. Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

    International Nuclear Information System (INIS)

    Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

    2008-01-01

    It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

  9. Prediction model of critical weight loss in cancer patients during particle therapy.

    Science.gov (United States)

    Zhang, Zhihong; Zhu, Yu; Zhang, Lijuan; Wang, Ziying; Wan, Hongwei

    2018-01-01

    The objective of this study is to investigate the predictors of critical weight loss in cancer patients receiving particle therapy, and build a prediction model based on its predictive factors. Patients receiving particle therapy were enroled between June 2015 and June 2016. Body weight was measured at the start and end of particle therapy. Association between critical weight loss (defined as >5%) during particle therapy and patients' demographic, clinical characteristic, pre-therapeutic nutrition risk screening (NRS 2002) and BMI were evaluated by logistic regression and decision tree analysis. Finally, 375 cancer patients receiving particle therapy were included. Mean weight loss was 0.55 kg, and 11.5% of patients experienced critical weight loss during particle therapy. The main predictors of critical weight loss during particle therapy were head and neck tumour location, total radiation dose ≥70 Gy on the primary tumour, and without post-surgery, as indicated by both logistic regression and decision tree analysis. Prediction model that includes tumour locations, total radiation dose and post-surgery had a good predictive ability, with the area under receiver operating characteristic curve 0.79 (95% CI: 0.71-0.88) and 0.78 (95% CI: 0.69-0.86) for decision tree and logistic regression model, respectively. Cancer patients with head and neck tumour location, total radiation dose ≥70 Gy and without post-surgery were at higher risk of critical weight loss during particle therapy, and early intensive nutrition counselling or intervention should be target at this population. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

    Energy Technology Data Exchange (ETDEWEB)

    Mayr, Nina A., E-mail: Nina.Mayr@osumc.edu [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Huang Zhibin [Department of Radiation Oncology and Department of Physics, East Carolina University, Greenville, NC (United States); Wang, Jian Z. [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Lo, Simon S. [Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH (United States); Fan, Joline M. [Department of Molecular Biology, Stanford University, Stanford, CA (United States); Grecula, John C. [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Sammet, Steffen [Department of Radiology, University of Chicago, Chicago, IL (United States); Department of Radiology, Ohio State University, Columbus, OH (United States); Sammet, Christina L. [Department of Radiology, University of Chicago, Chicago, IL (United States); Jia Guang; Zhang Jun; Knopp, Michael V.; Yuh, William T.C. [Department of Radiology, Ohio State University, Columbus, OH (United States)

    2012-07-01

    Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB{sub 2}-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm{sup 3}, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 Multiplication-Sign 10{sup -8}, 2.0 Multiplication-Sign 10{sup -8}) and disease-specific survival (p = 1.9 Multiplication-Sign 10{sup -4}, 2.1 Multiplication-Sign 10{sup -6}, 2.5 Multiplication-Sign 10{sup -7}, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2

  11. Predicting the probability of mortality of gastric cancer patients using decision tree.

    Science.gov (United States)

    Mohammadzadeh, F; Noorkojuri, H; Pourhoseingholi, M A; Saadat, S; Baghestani, A R

    2015-06-01

    Gastric cancer is the fourth most common cancer worldwide. This reason motivated us to investigate and introduce gastric cancer risk factors utilizing statistical methods. The aim of this study was to identify the most important factors influencing the mortality of patients who suffer from gastric cancer disease and to introduce a classification approach according to decision tree model for predicting the probability of mortality from this disease. Data on 216 patients with gastric cancer, who were registered in Taleghani hospital in Tehran,Iran, were analyzed. At first, patients were divided into two groups: the dead and alive. Then, to fit decision tree model to our data, we randomly selected 20% of dataset to the test sample and remaining dataset considered as the training sample. Finally, the validity of the model examined with sensitivity, specificity, diagnosis accuracy and the area under the receiver operating characteristic curve. The CART version 6.0 and SPSS version 19.0 softwares were used for the analysis of the data. Diabetes, ethnicity, tobacco, tumor size, surgery, pathologic stage, age at diagnosis, exposure to chemical weapons and alcohol consumption were determined as effective factors on mortality of gastric cancer. The sensitivity, specificity and accuracy of decision tree were 0.72, 0.75 and 0.74 respectively. The indices of sensitivity, specificity and accuracy represented that the decision tree model has acceptable accuracy to prediction the probability of mortality in gastric cancer patients. So a simple decision tree consisted of factors affecting on mortality of gastric cancer may help clinicians as a reliable and practical tool to predict the probability of mortality in these patients.

  12. [Prognostic and predictive molecular markers for urologic cancers].

    Science.gov (United States)

    Hartmann, A; Schlomm, T; Bertz, S; Heinzelmann, J; Hölters, S; Simon, R; Stoehr, R; Junker, K

    2014-04-01

    Molecular prognostic factors and genetic alterations as predictive markers for cancer-specific targeted therapies are used today in the clinic for many malignancies. In recent years, many molecular markers for urogenital cancers have also been identified. However, these markers are not clinically used yet. In prostate cancer, novel next-generation sequencing methods revealed a detailed picture of the molecular changes. There is growing evidence that a combination of classical histopathological and validated molecular markers could lead to a more precise estimation of prognosis, thus, resulting in an increasing number of patients with active surveillance as a possible treatment option. In patients with urothelial carcinoma, histopathological factors but also the proliferation of the tumor, mutations in oncogenes leading to an increasing proliferation rate and changes in genes responsible for invasion and metastasis are important. In addition, gene expression profiles which could distinguish aggressive tumors with high risk of metastasis from nonmetastasizing tumors have been recently identified. In the future, this could potentially allow better selection of patients needing systemic perioperative treatment. In renal cell carcinoma, many molecular markers that are associated with metastasis and survival have been identified. Some of these markers were also validated as independent prognostic markers. Selection of patients with primarily organ-confined tumors and increased risk of metastasis for adjuvant systemic therapy could be clinically relevant in the future.

  13. Familial risks and estrogen receptor-positive breast cancer in Hong Kong Chinese women.

    Directory of Open Access Journals (Sweden)

    Lap Ah Tse

    Full Text Available The role of family history to the risk of breast cancer was analyzed by incorporating menopausal status in Hong Kong Chinese women, with a particular respect to the estrogen receptor-positive (ER+ type.Seven hundred and forty seven breast cancer incident cases and 781 hospital controls who had completed information on family cancer history in first-degree relatives (nature father, mother, and siblings were recruited. Odds ratio for breast cancer were calculated by unconditional multiple logistic regression, stratified by menopausal status (a surrogate of endogenous female sex hormone level and age and type of relative affected with the disease. Further subgroup analysis by tumor type according to ER status was investigated.Altogether 52 (6.96% breast cancer cases and 23 (2.95% controls was found that the patients' one or more first-degree relatives had a history of breast cancer, showing an adjusted odds ratio (OR of 2.41 (95%CI: 1.45-4.02. An excess risk of breast cancer was restricted to the ER+ tumor (OR = 2.43, 95% CI: 1.38-4.28, with a relatively higher risk associated with an affected mother (OR = 3.97, 95%CI: 1.46-10.79 than an affected sister (OR = 2.06, 95%CI: 1.07-3.97, while the relative risk was more prominent in the subgroup of pre-menopausal women. Compared with the breast cancer overall, the familial risks to the ER+ tumor increased progressively with the number of affected first-degree relatives.This study provides new insights on a relationship between family breast cancer history, menopausal status, and the ER+ breast cancer. A separate risk prediction model for ER+ tumor in Asian population is desired.

  14. Cost sharing and hereditary cancer risk: predictors of willingness-to-pay for genetic testing.

    Science.gov (United States)

    Matro, Jennifer M; Ruth, Karen J; Wong, Yu-Ning; McCully, Katen C; Rybak, Christina M; Meropol, Neal J; Hall, Michael J

    2014-12-01

    Increasing use of predictive genetic testing to gauge hereditary cancer risk has been paralleled by rising cost-sharing practices. Little is known about how demographic and psychosocial factors may influence individuals' willingness-to-pay for genetic testing. The Gastrointestinal Tumor Risk Assessment Program Registry includes individuals presenting for genetic risk assessment based on personal/family cancer history. Participants complete a baseline survey assessing cancer history and psychosocial items. Willingness-to-pay items include intention for: genetic testing only if paid by insurance; testing with self-pay; and amount willing-to-pay ($25-$2,000). Multivariable models examined predictors of willingness-to-pay out-of-pocket (versus only if paid by insurance) and willingness-to-pay a smaller versus larger sum (≤$200 vs. ≥$500). All statistical tests are two-sided (α = 0.05). Of 385 evaluable participants, a minority (42%) had a personal cancer history, while 56% had ≥1 first-degree relative with colorectal cancer. Overall, 21.3% were willing to have testing only if paid by insurance, and 78.7% were willing-to-pay. Predictors of willingness-to-pay were: 1) concern for positive result; 2) confidence to control cancer risk; 3) fewer perceived barriers to colorectal cancer screening; 4) benefit of testing to guide screening (all p testing (all p testing, and anticipate benefits to reducing cancer risk. Identifying factors associated with willingness-to-pay for genetic services is increasingly important as testing is integrated into routine cancer care.

  15. HIV Infection and Cancer Risk

    Science.gov (United States)

    ... same age ( 1 ). The general term for these cancers is "HIV-associated cancers." Three of these cancers are known as " acquired ... also have an increased cumulative risk of developing HIV-associated cancers. What can people infected with HIV do to ...

  16. Risk of subsequent gastrointestinal cancer among childhood cancer survivors : A systematic review

    NARCIS (Netherlands)

    Teepen, Jop C.; de Vroom, Suzanne L.; van Leeuwen, Flora E.; Tissing, Wim J.; Kremer, Leontien C.; Ronckers, Cecile M.

    Background: Childhood cancer survivors (CCS) are at increased risk of developing subsequent malignant neoplasms, including gastrointestinal (GI) cancer. We performed a systematic review to summarize all available literature on the risk of, risk factors for, and outcome after subsequent GI cancer

  17. High body mass index and cancer risk

    DEFF Research Database (Denmark)

    Benn, Marianne; Tybjærg-Hansen, Anne; Smith, George Davey

    2016-01-01

    of follow-up (range 0-37), 8002 developed non-skin cancer, 3347 non-melanoma skin cancer, 1396 lung cancer, 637 other smoking related cancers, 1203 colon cancer, 159 kidney cancer, 1402 breast cancer, 1062 prostate cancer, and 2804 other cancers. Participants were genotyped for five genetic variants...... with a BMI ≥ 30 versus 18.5-24.9 kg/m(2). Corresponding risk of breast cancer was 20 % (0-44 %) higher in postmenopausal women. BMI was not associated with risk of colon, kidney, other smoking related cancers, prostate cancer, or other cancers. In genetic analyses, carrying 7-10 versus 0-4 BMI increasing......High body mass index (BMI) has been associated with increased risk of some cancer. Whether these reflect causal associations is unknown. We examined this issue. Using a Mendelian randomisation approach, we studied 108,812 individuals from the general population. During a median of 4.7 years...

  18. Optimising preoperative risk stratification tools for prostate cancer using mpMRI

    Energy Technology Data Exchange (ETDEWEB)

    Reisaeter, Lars A.R.; Losnegaard, Are; Biermann, Martin; Roervik, Jarle [Haukeland University Hospital, Department of Radiology, Bergen (Norway); University of Bergen, Department of Clinical Medicine, Bergen (Norway); Fuetterer, Jurgen J. [Radboud University Nijmegen Medical Centre, Department of Radiology, Nijmegen (Netherlands); Nygaard, Yngve [Haukeland University Hospital, Department of Urology, Bergen (Norway); Monssen, Jan [Haukeland University Hospital, Department of Radiology, Bergen (Norway); Gravdal, Karsten [Haukeland University Hospital, Department of Pathology, Bergen (Norway); Halvorsen, Ole J.; Akslen, Lars A. [Haukeland University Hospital, Department of Pathology, Bergen (Norway); Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, University of Bergen (Norway); Haukaas, Svein; Beisland, Christian [University of Bergen, Department of Clinical Medicine, Bergen (Norway); Haukeland University Hospital, Department of Urology, Bergen (Norway)

    2018-03-15

    To improve preoperative risk stratification for prostate cancer (PCa) by incorporating multiparametric MRI (mpMRI) features into risk stratification tools for PCa, CAPRA and D'Amico. 807 consecutive patients operated on by robot-assisted radical prostatectomy at our institution during the period 2010-2015 were followed to identify biochemical recurrence (BCR). 591 patients were eligible for final analysis. We employed stepwise backward likelihood methodology and penalised Cox cross-validation to identify the most significant predictors of BCR including mpMRI features. mpMRI features were then integrated into image-adjusted (IA) risk prediction models and the two risk prediction tools were then evaluated both with and without image adjustment using receiver operating characteristics, survival and decision curve analyses. 37 patients suffered BCR. Apparent diffusion coefficient (ADC) and radiological extraprostatic extension (rEPE) from mpMRI were both significant predictors of BCR. Both IA prediction models reallocated more than 20% of intermediate-risk patients to the low-risk group, reducing their estimated cumulative BCR risk from approximately 5% to 1.1%. Both IA models showed improved prognostic performance with a better separation of the survival curves. Integrating ADC and rEPE from mpMRI of the prostate into risk stratification tools improves preoperative risk estimation for BCR. (orig.)

  19. Coffee and cancer risk: a summary overview.

    Science.gov (United States)

    Alicandro, Gianfranco; Tavani, Alessandra; La Vecchia, Carlo

    2017-09-01

    We reviewed available evidence on coffee drinking and the risk of all cancers and selected cancers updated to May 2016. Coffee consumption is not associated with overall cancer risk. A meta-analysis reported a pooled relative risk (RR) for an increment of 1 cup of coffee/day of 1.00 [95% confidence interval (CI): 0.99-1.01] for all cancers. Coffee drinking is associated with a reduced risk of liver cancer. A meta-analysis of cohort studies found an RR for an increment of consumption of 1 cup/day of 0.85 (95% CI: 0.81-0.90) for liver cancer and a favorable effect on liver enzymes and cirrhosis. Another meta-analysis showed an inverse relation for endometrial cancer risk, with an RR of 0.92 (95% CI: 0.88-0.96) for an increment of 1 cup/day. A possible decreased risk was found in some studies for oral/pharyngeal cancer and for advanced prostate cancer. Although data are mixed, overall, there seems to be some favorable effect of coffee drinking on colorectal cancer in case-control studies, in the absence of a consistent relation in cohort studies. For bladder cancer, the results are not consistent; however, any possible direct association is not dose and duration related, and might depend on a residual confounding effect of smoking. A few studies suggest an increased risk of childhood leukemia after maternal coffee drinking during pregnancy, but data are limited and inconsistent. Although the results of studies are mixed, the overall evidence suggests no association of coffee intake with cancers of the stomach, pancreas, lung, breast, ovary, and prostate overall. Data are limited, with RR close to unity for other neoplasms, including those of the esophagus, small intestine, gallbladder and biliary tract, skin, kidney, brain, thyroid, as well as for soft tissue sarcoma and lymphohematopoietic cancer.

  20. SU-E-T-628: Predicted Risk of Post-Irradiation Cerebral Necrosis in Pediatric Brain Cancer Patients: A Treatment Planning Comparison of Proton Vs. Photon Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Freund, D [Willis Knighton Cancer Center, Shreveport, LA (United States); Zhang, R; Sanders, M [Mary Bird Perkins Cancer Center, Baton Rouge, LA (United States); Newhauser, W [Louisiana State University, Baton Rouge, LA (United States)

    2015-06-15

    Purpose: Post-irradiation cerebral necrosis (PICN) is a severe late effect that can Result from brain cancers treatment using radiation therapy. The purpose of this study was to compare the treatment plans and predicted risk of PICN after volumetric modulated arc therapy (VMAT) to the risk after passively scattered proton therapy (PSPT) and intensity modulated proton therapy (IMPT) in a cohort of pediatric patients. Methods: Thirteen pediatric patients with varying age and sex were selected for this study. A clinical treatment volume (CTV) was constructed for 8 glioma patients and 5 ependymoma patients. Prescribed dose was 54 Gy over 30 fractions to the planning volume. Dosimetric endpoints were compared between VMAT and proton plans. The normal tissue complication probability (NTCP) following VMAT and proton therapy planning was also calculated using PICN as the biological endpoint. Sensitivity tests were performed to determine if predicted risk of PICN was sensitive to positional errors, proton range errors and selection of risk models. Results: Both PSPT and IMPT plans resulted in a significant increase in the maximum dose and reduction in the total brain volume irradiated to low doses compared with the VMAT plans. The average ratios of NTCP between PSPT and VMAT were 0.56 and 0.38 for glioma and ependymoma patients respectively and the average ratios of NTCP between IMPT and VMAT were 0.67 and 0.68 for glioma and ependymoma plans respectively. Sensitivity test revealed that predicted ratios of risk were insensitive to range and positional errors but varied with risk model selection. Conclusion: Both PSPT and IMPT plans resulted in a decrease in the predictive risk of necrosis for the pediatric plans studied in this work. Sensitivity analysis upheld the qualitative findings of the risk models used in this study, however more accurate models that take into account dose and volume are needed.

  1. Height and Breast Cancer Risk

    DEFF Research Database (Denmark)

    Zhang, Ben; Shu, Xiao-Ou; Delahanty, Ryan J

    2015-01-01

    BACKGROUND: Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear. METHODS: We performed a meta......-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using...... a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients. RESULTS: The pooled relative risk of breast cancer was 1.17 (95% confidence...

  2. Genetic cancer risk assessment in practice

    International Nuclear Information System (INIS)

    Gruber, S.

    2004-01-01

    The advent of genetic testing has made a dramatic impact on the management of individuals with inherited susceptibility to cancer and their relatives. Genetic counsel ing, with or without testing, is warranted when clues to familial cancer are recognized. Today, genetic testing for classic cancer genetic syndromes is now the standard of care, and has been complemented by genetic testing for other situations commonly encountered in clinical practice. Genetic testing for colorectal cancer, breast cancer, kidney cancer, thyroid cancer, melanoma, and pancreatic cancer raise important issues about the parameters for testing. Genetic cancer risk assessment can lead to measurable reductions in morbidity and mortality through strategies that rely on surveillance, chemo prevention, and risk-reducing surgery

  3. The Studies of Decision Tree in Estimation of Breast Cancer Risk by Using Polymorphism Nucleotide

    Directory of Open Access Journals (Sweden)

    Frida Seyedmir

    2017-07-01

    Full Text Available Abstract Introduction:   Decision tree is the data mining tools to collect, accurate prediction and sift information from massive amounts of data that are used widely in the field of computational biology and bioinformatics. In bioinformatics can be predict on diseases, including breast cancer. The use of genomic data including single nucleotide polymorphisms is a very important factor in predicting the risk of diseases. The number of seven important SNP among hundreds of thousands genetic markers were identified as factors associated with breast cancer. The objective of this study is to evaluate the training data on decision tree predictor error of the risk of breast cancer by using single nucleotide polymorphism genotype. Methods: The risk of breast cancer were calculated associated with the use of SNP formula:xj = fo * In human,  The decision tree can be used To predict the probability of disease using single nucleotide polymorphisms .Seven SNP with different odds ratio associated with breast cancer considered and coding and design of decision tree model, C4.5, by  Csharp2013 programming language were done. In the decision tree created with the coding, the four important associated SNP was considered. The decision tree error in two case of coding and using WEKA were assessment and percentage of decision tree accuracy in prediction of breast cancer were calculated. The number of trained samples was obtained with systematic sampling. With coding, two scenarios as well as software WEKA, three scenarios with different sets of data and the number of different learning and testing, were evaluated. Results: In both scenarios of coding, by increasing the training percentage from 66/66 to 86/42, the error reduced from 55/56 to 9/09. Also by running of WEKA on three scenarios with different sets of data, the number of different education, and different tests by increasing records number from 81 to 2187, the error rate decreased from 48/15 to 13

  4. Tail Risk Premia and Return Predictability

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Todorov, Viktor; Xu, Lai

    The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be attribu......The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

  5. Long-Term Survival and Risk of Second Cancers After Radiotherapy for Cervical Cancer

    International Nuclear Information System (INIS)

    Ohno, Tatsuya; Kato, Shingo; Sato, Shinichiro; Fukuhisa, Kenjiro; Nakano, Takashi; Tsujii, Hirohiko; Arai, Tatsuo

    2007-01-01

    Purpose: To evaluate the risk of second cancers after cervical cancer treated with radiotherapy for Asian populations. Methods and Materials: We reviewed 2,167 patients with cervical cancer undergoing radiotherapy between 1961 and 1986. Intracavitary brachytherapy was performed with high-dose rate source (82%) or low-dose rate source (12%). Relative risk (RR), absolute excess risk (AR), and cumulative risk of second cancer were calculated using the Japanese disease expectancy table. For 1,031 patients, the impact of smoking habit on the increasing risk of second cancer was also evaluated. Results: The total number of person-years of follow-up was 25,771, with 60 patients being lost to follow-up. Among the 2,167 patients, 1,063 (49%) survived more than 10 years. Second cancers were observed in 210 patients, representing a significant 1.2-fold risk (95% confidence interval [CI], 1.1-1.4) of developing second cancer compared with the general population, 1.6% excess risk per person per decade of follow-up, and elevating cumulative risk up to 23.8% (95% CI, 20.3-27.3) at 30 years after radiotherapy. The RR of second cancer was 1.6-fold for patients with the smoking habit and 1.4-fold for those without. Conclusions: Small but significant increased risk of second cancer was observed among Japanese women with cervical cancer mainly treated with high-dose rate brachytherapy. Considering the fact that about half of the patients survived more than 10 years, the benefit of radiotherapy outweighs the risk of developing second cancer

  6. Depression and under-treatment of depression: potential risks and outcomes in black lung cancer patients

    Science.gov (United States)

    Traeger, Lara; Cannon, Sheila; Pirl, William F.; Park, Elyse R.

    2015-01-01

    In the U.S., black men are at higher risk than white men for lung cancer mortality whereas rates are comparable between black and white women. This paper draws from empirical work in lung cancer, mental health and health disparities to highlight that race and depression may overlap in predicting lower treatment access and utilization and poorer quality of life among patients. Racial barriers to depression identification and treatment in the general population may compound these risks. Prospective data are needed to examine whether depression plays a role in racial disparities in lung cancer outcomes. PMID:23514250

  7. Stressful life events and cancer risk

    DEFF Research Database (Denmark)

    Bergelt, C; Prescott, E; Grønbaek, M

    2006-01-01

    In a prospective cohort study in Denmark of 8736 randomly selected people, no evidence was found among 1011 subjects who developed cancer that self-reported stressful major life events had increased their risk for cancer.......In a prospective cohort study in Denmark of 8736 randomly selected people, no evidence was found among 1011 subjects who developed cancer that self-reported stressful major life events had increased their risk for cancer....

  8. Setting the Threshold for Surgical Prevention in Women at Increased Risk of Ovarian Cancer.

    Science.gov (United States)

    Manchanda, Ranjit; Menon, Usha

    2018-01-01

    The number of ovarian cancer cases is predicted to rise by 14% in Europe and 55% worldwide over the next 2 decades. The current absence of a screening program, rising drug/treatment costs, and only marginal improvements in survival seen over the past 30 years suggest the need for maximizing primary surgical prevention to reduce the burden of ovarian cancer. Primary surgical prevention through risk-reducing salpingo-oophorectomy (RRSO) is well established as the most effective method for preventing ovarian cancer. In the UK, it has traditionally been offered to high-risk women (>10% lifetime risk of ovarian cancer) who have completed their family. The cost-effectiveness of RRSO in BRCA1/BRCA2 carriers older than 35 years is well established. Recently, RRSO has been shown to be cost-effective in postmenopausal women at lifetime ovarian cancer risks of 5% or greater and in premenopausal women at lifetime risks greater than 4%. The acceptability, uptake, and satisfaction with RRSO at these intermediate-risk levels remain to be established. Prospective outcome data on risk-reducing salpingectomy and delayed-oophorectomy for preventing ovarian cancer is lacking, and hence, this is best offered for primary prevention within the context and safe environment of a clinical trial. An estimated 63% of ovarian cancers occur in women with greater than 4% lifetime risk and 53% in those with 5% or greater lifetime-risk. Risk-reducing salpingo-oophorectomy can be offered for primary surgical prevention to women at intermediate risk levels (4%-5% to 10%). This includes unaffected women who have completed their family and have RAD51C, RAD51D, or BRIP1 gene mutations; first-degree relatives of women with invasive epithelial ovarian cancer; BRCA mutation-negative women from high-risk breast-and-ovarian cancer or ovarian-cancer-only families. In those with BRCA1, RAD51C/RAD51D/MMR mutations and the occasional families with a history of ovarian cancer in their 40s, surgery needs to be

  9. Acceptance and adherence to chemoprevention among women at increased risk of breast cancer.

    Science.gov (United States)

    Roetzheim, Richard G; Lee, Ji-Hyun; Fulp, William; Matos Gomez, Elizabeth; Clayton, Elissa; Tollin, Sharon; Khakpour, Nazanin; Laronga, Christine; Lee, Marie Catherine; Kiluk, John V

    2015-02-01

    Chemoprevention is an option for women who are at increased risk of breast cancer (five year risk ≥1.7%). It is uncertain, however, how often women accept and complete five years of therapy and whether clinical or demographic factors predict completion. Medical records were abstracted for 219 women whose five year risk of breast cancer was ≥1.7% and who were offered chemoprevention while attending a high risk breast clinic at the Moffitt Cancer Center. We examined the likelihood of accepting chemoprevention and completing five years of therapy, and potential clinical and demographic predictors of these outcomes, using multivariable logistic regression and survival analysis models. There were 118/219 women (54.4%) who accepted a recommendation for chemoprevention and began therapy. The likelihood of accepting chemoprevention was associated with lifetime breast cancer risk and was higher for women with specific high risk conditions (lobular carcinoma in situ and atypical ductal hyperplasia). Women with osteoporosis and those that consumed alcohol were also more likely to accept medication. There were 58/118 (49.2%) women who stopped medication at least temporarily after starting therapy. Based on survival curves, an estimated 60% of women who begin chemoprevention will complete five years of therapy. A substantial percentage of women at increased risk of breast cancer will decline chemoprevention and among those that accept therapy, approximately 40% will not be able to complete five years of therapy because of side effects. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Risk factors for breast cancer in the breast cancer risk model study of Guam and Saipan.

    Science.gov (United States)

    Leon Guerrero, Rachael T; Novotny, Rachel; Wilkens, Lynne R; Chong, Marie; White, Kami K; Shvetsov, Yurii B; Buyum, Arielle; Badowski, Grazyna; Blas-Laguaña, Michelle

    2017-10-01

    Chamorro Pacific Islanders in the Mariana Islands have breast cancer incidence rates similar to, but mortality rates higher than, those of U.S. women. As breast cancer risk factors of women of the Mariana Islands may be unique because of ethnic and cultural differences, we studied established and suspected risk factors for breast cancer in this unstudied population. From 2010-2013, we conducted retrospective case-control study of female breast cancer (104 cases and 185 controls) among women in the Mariana Islands. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each of various lifestyle-related factors from logistic regression of breast cancer, in all women and in pre- and postmenopausal women separately. Tests for interaction of risk factors with ethnicity were based on the Wald statistics for cross-product terms. Of the medical and reproductive factors considered - age at menarche, breastfeeding, number of live births, age at first live birth, hormone use, and menopause - only age at first live birth was confirmed. Age at first live birth, among parous women, was higher among cases (mean 24.9 years) than controls (mean 23.2 years); with increased breast cancer risk (OR=2.53; 95% CI, 1.04-6.19 for age≥30y compared to risk and only in Filipino women. The association with many other established risk factors, such as BMI, hormone use and physical activity, were in the expected direction but were not significant. Associations for family history of breast cancer and alcohol intake were not evident CONCLUSIONS: The results provide a basis for cancer prevention guidance for women in the Mariana Islands. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  11. Polyunsaturated fatty acids and prostate cancer risk

    DEFF Research Database (Denmark)

    Khankari, Nikhil K; Murff, Harvey J; Zeng, Chenjie

    2016-01-01

    BACKGROUND: Prostate cancer is a common cancer worldwide with no established modifiable lifestyle factors to guide prevention. The associations between polyunsaturated fatty acids (PUFAs) and prostate cancer risk have been inconsistent. Using Mendelian randomisation, we evaluated associations...... and prostate cancer risk. However, risk reductions were observed for short-chain PUFAs, linoleic (ORLA=0.95, 95%CI=0.92, 0.98) and α-linolenic acids (ORALA=0.96, 95%CI=0.93, 0.98), among men ...-chain PUFAs (i.e., arachidonic, eicosapentaenoic, and docosapentaenoic acids), increased risks were observed among men

  12. Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods

    Directory of Open Access Journals (Sweden)

    Antonella Iuliano

    2018-06-01

    Full Text Available Breast cancer is one of the most common invasive tumors causing high mortality among women. It is characterized by high heterogeneity regarding its biological and clinical characteristics. Several high-throughput assays have been used to collect genome-wide information for many patients in large collaborative studies. This knowledge has improved our understanding of its biology and led to new methods of diagnosing and treating the disease. In particular, system biology has become a valid approach to obtain better insights into breast cancer biological mechanisms. A crucial component of current research lies in identifying novel biomarkers that can be predictive for breast cancer patient prognosis on the basis of the molecular signature of the tumor sample. However, the high dimension and low sample size of data greatly increase the difficulty of cancer survival analysis demanding for the development of ad-hoc statistical methods. In this work, we propose novel screening-network methods that predict patient survival outcome by screening key survival-related genes and we assess the capability of the proposed approaches using METABRIC dataset. In particular, we first identify a subset of genes by using variable screening techniques on gene expression data. Then, we perform Cox regression analysis by incorporating network information associated with the selected subset of genes. The novelty of this work consists in the improved prediction of survival responses due to the different types of screenings (i.e., a biomedical-driven, data-driven and a combination of the two before building the network-penalized model. Indeed, the combination of the two screening approaches allows us to use the available biological knowledge on breast cancer and complement it with additional information emerging from the data used for the analysis. Moreover, we also illustrate how to extend the proposed approaches to integrate an additional omic layer, such as copy number

  13. Public support for alcohol policies associated with knowledge of cancer risk.

    Science.gov (United States)

    Buykx, Penny; Gilligan, Conor; Ward, Bernadette; Kippen, Rebecca; Chapman, Kathy

    2015-04-01

    Several options are advocated by policy experts to mitigate alcohol-related harms, although the most effective strategies often have the least public support. While knowledge of tobacco-related health risks predicts support for relevant public health measures, it is not known whether knowledge of alcohol health risks is similarly associated with the acceptability of policies intended to reduce alcohol consumption and related harms. This study aims to gauge public support for a range of alcohol policies and to determine whether or not support is associated with knowledge of a long-term health risk of alcohol consumption, specifically cancer. 2482 adults in New South Wales (NSW), Australia, participated in an online survey. Logistic regression analysis was used to examine the association between demographic data, alcohol consumption, smoking status, knowledge of alcohol as a risk factor for cancer and support for alcohol-related policies. Most participants were supportive of health warnings, restricting access to internet alcohol advertising to young people, and requiring information on national drinking guidelines on alcohol containers. Almost half of participants supported a ban on sport sponsorship, while less than 41% supported price increases, volumetric taxation, or reducing the number of retail outlets. Only 47% of participants identified drinking too much alcohol as a risk factor for cancer. Knowledge of alcohol as a risk factor for cancer was a significant predictor of support for all policies, while level of alcohol consumption had a significant inverse relationship with policy support. The finding that support for alcohol management policies is associated with awareness that drinking too much alcohol may contribute to cancer could assist in the planning of future public health interventions. Improving awareness of the long term health risks of alcohol consumption may be one avenue to increasing public support for effective alcohol harm-reduction policies

  14. Nutrients and Risk of Colon Cancer

    Directory of Open Access Journals (Sweden)

    Les Mery

    2010-02-01

    Full Text Available Dietary fats are thought to be important in the etiology of colon cancer. However, the evidence linking them is inconclusive. Studies on dietary protein, cholesterol and carbohydrate and the risk of colon cancer are also inconsistent. This study examined the association between dietary intake of protein, fats, cholesterol and carbohydrates, and the risk of colon cancer. Mailed questionnaires were completed by 1731 individuals with histologically confirmed cases of colon cancer and 3097 population controls between 1994 and 1997 in seven Canadian provinces. Measurements included socio-economic status, lifestyle habits and diet. A 69-item food frequency questionnaire was used to provide data on eating habits from two years before the study. Odds ratios (OR and 95% confidence intervals (CI were computed using unconditional logistic regression. The nutrients were categorized by quartiles based on the distributions among the controls. Intake of polyunsaturated fat, trans-fat and cholesterol were significantly associated with the risk of colon cancer; the ORs for the highest quartiles were 1.36 (95% CI, 1.02–1.80, 1.37 (95% CI, 1.10–1.71 and 1.42 (95% CI, 1.10–1.84, respectively. The association was stronger with proximal colon cancer (PCC. An increased risk was also observed with increasing intake of sucrose for both proximal and distal colon cancers; the ORs for the highest quartiles were 1.67 (95% CI, 1.22–2.29 for PCC and 1.58 (95% CI, 1.18–2.10 for distal colon cancer (DCC. An elevated risk of PCC was also found with increased lactose intake. Our findings provide evidence that a diet low in fat and sucrose could reduce the risk of various colon cancers.

  15. Nutrients and Risk of Colon Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Jinfu, E-mail: Jinfu.hu@phac-aspc.gc.ca [Evidence and Risk Assessment Division, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, 785 Carling Avenue, AL: 6807B, Ottawa, Ontario K1A 0K9 (Canada); La Vecchia, Carlo [Istituto di Ricerche Farmacologiche “Mario Negri,” Via La Masa, 19-20156 Milan (Italy); Istituto di Statistica Medica e Biometria, Università degli Studi di Milano, Via Venezian, 1, 20133 Milan (Italy); Negri, Eva [Istituto di Ricerche Farmacologiche “Mario Negri,” Via La Masa, 19-20156 Milan (Italy); Mery, Les [Evidence and Risk Assessment Division, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, 785 Carling Avenue, AL: 6807B, Ottawa, Ontario K1A 0K9 (Canada)

    2010-02-10

    Dietary fats are thought to be important in the etiology of colon cancer. However, the evidence linking them is inconclusive. Studies on dietary protein, cholesterol and carbohydrate and the risk of colon cancer are also inconsistent. This study examined the association between dietary intake of protein, fats, cholesterol and carbohydrates, and the risk of colon cancer. Mailed questionnaires were completed by 1731 individuals with histologically confirmed cases of colon cancer and 3097 population controls between 1994 and 1997 in seven Canadian provinces. Measurements included socio-economic status, lifestyle habits and diet. A 69-item food frequency questionnaire was used to provide data on eating habits from two years before the study. Odds ratios (OR) and 95% confidence intervals (CI) were computed using unconditional logistic regression. The nutrients were categorized by quartiles based on the distributions among the controls. Intake of polyunsaturated fat, trans-fat and cholesterol were significantly associated with the risk of colon cancer; the ORs for the highest quartiles were 1.36 (95% CI, 1.02–1.80), 1.37 (95% CI, 1.10–1.71) and 1.42 (95% CI, 1.10–1.84), respectively. The association was stronger with proximal colon cancer (PCC). An increased risk was also observed with increasing intake of sucrose for both proximal and distal colon cancers; the ORs for the highest quartiles were 1.67 (95% CI, 1.22–2.29) for PCC and 1.58 (95% CI, 1.18–2.10) for distal colon cancer (DCC). An elevated risk of PCC was also found with increased lactose intake. Our findings provide evidence that a diet low in fat and sucrose could reduce the risk of various colon cancers.

  16. Nutrients and Risk of Colon Cancer

    International Nuclear Information System (INIS)

    Hu, Jinfu; La Vecchia, Carlo; Negri, Eva; Mery, Les

    2010-01-01

    Dietary fats are thought to be important in the etiology of colon cancer. However, the evidence linking them is inconclusive. Studies on dietary protein, cholesterol and carbohydrate and the risk of colon cancer are also inconsistent. This study examined the association between dietary intake of protein, fats, cholesterol and carbohydrates, and the risk of colon cancer. Mailed questionnaires were completed by 1731 individuals with histologically confirmed cases of colon cancer and 3097 population controls between 1994 and 1997 in seven Canadian provinces. Measurements included socio-economic status, lifestyle habits and diet. A 69-item food frequency questionnaire was used to provide data on eating habits from two years before the study. Odds ratios (OR) and 95% confidence intervals (CI) were computed using unconditional logistic regression. The nutrients were categorized by quartiles based on the distributions among the controls. Intake of polyunsaturated fat, trans-fat and cholesterol were significantly associated with the risk of colon cancer; the ORs for the highest quartiles were 1.36 (95% CI, 1.02–1.80), 1.37 (95% CI, 1.10–1.71) and 1.42 (95% CI, 1.10–1.84), respectively. The association was stronger with proximal colon cancer (PCC). An increased risk was also observed with increasing intake of sucrose for both proximal and distal colon cancers; the ORs for the highest quartiles were 1.67 (95% CI, 1.22–2.29) for PCC and 1.58 (95% CI, 1.18–2.10) for distal colon cancer (DCC). An elevated risk of PCC was also found with increased lactose intake. Our findings provide evidence that a diet low in fat and sucrose could reduce the risk of various colon cancers

  17. Height, selected genetic markers and prostate cancer risk

    DEFF Research Database (Denmark)

    Lophatananon, Artitaya; Stewart-Brown, Sarah; Kote-Jarai, Zsofia

    2017-01-01

    Background:Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer.Methods:We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases...... and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions.Results:The results suggest that height is associated with high-grade prostate cancer risk. Men with height >180 cm...... are at a 22% increased risk as compared to men with height prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer...

  18. Quantifying prognosis with risk predictions.

    Science.gov (United States)

    Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R

    2012-01-01

    Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.

  19. The risk of cancer as a result of elevated levels of nitrate in drinking water and vegetables in Central India.

    Science.gov (United States)

    Taneja, Pinky; Labhasetwar, Pawan; Nagarnaik, Pranav; Ensink, Jeroen H J

    2017-08-01

    The objective of the present study was to determine the effect of nitrates on the incidence of gastrointestinal (GI) cancer development. Nitrate converted to nitrite under reducing conditions of gut results in the formation of N-nitrosamines which are linked to an increased gastric cancer risk. A population of 234 individuals with 78 cases of GI cancer and 156 controls residing at urban and rural settings in Nagpur and Bhandara districts of India were studied for 2 years using a case-control study. A detailed survey of 16 predictor variables using Formhub software was carried out. Nitrate concentrations in vegetables and primary drinking water supplies were measured. The logistic regression model showed that nitrate was statistically significant in predicting increasing risk of cancer when potential confounders were kept at base level (P value of 0.001 nitrate in drinking water; 0.003 for nitrate in vegetable) at P nitrate in drinking water at >45 mg/L level of nitrate was associated with a higher risk of GI cancers. Analysis suggests that nitrate concentration in drinking water was found statistically significant in predicting cancer risk with an odds ratio of 1.20.

  20. Colon Cancer Risk Assessment - Gauss Program

    Science.gov (United States)

    An executable file (in GAUSS) that projects absolute colon cancer risk (with confidence intervals) according to NCI’s Colorectal Cancer Risk Assessment Tool (CCRAT) algorithm. GAUSS is not needed to run the program.

  1. Plasma testosterone in the general population, cancer prognosis and cancer risk

    DEFF Research Database (Denmark)

    Orsted, D D; Nordestgaard, B G; Bojesen, S E

    2014-01-01

    BACKGROUND: Testosterone is an important anabolic hormone in humans and in vitro testosterone stimulates growth of lung and colon cancer cells. We tested the hypothesis that plasma testosterone associate with increased risk of cancer and with increased risk of early death after cancer. MATERIALS...

  2. Diet and breast cancer: understanding risks and benefits.

    Science.gov (United States)

    Thomson, Cynthia A

    2012-10-01

    Breast cancer is the most commonly diagnosed cancer among women in the United States. Extensive research has been completed to evaluate the relationship between dietary factors and breast cancer risk and survival after breast cancer; however, a summary report with clinical inference is needed. Materials and This review summarizes the current epidemiological and clinical trial evidence relating diet to breast cancer incidence, recurrence, survival, and mortality. The review includes emerging epidemiological studies that assess risk within breast cancer subtypes as well as a summary of previous and ongoing dietary intervention trials designed to modify breast cancer risk. The available literature suggests that both low-fat and high-fiber diets may be weakly protective against breast cancer, whereas total energy intake and alcohol appear to be positively associated. Fiber may be weakly protective possibly through modulation of estrogen, whereas fruit and vegetable intake is not clearly associated with risk. Obesity is a risk factor for postmenopausal disease, and adult weight gain should be avoided to reduce risk. In survivors, diet has the greatest potential influence on overall mortality rather than breast cancer-specific events. Diet is modestly associated with breast cancer risk; associations appear more pronounced for postmenopausal disease, and healthy choices after diagnosis and treatment likely support longevity more so than reduced risk for recurrent disease.

  3. Male pattern baldness and the risk of prostate cancer.

    Science.gov (United States)

    Yassa, M; Saliou, M; De Rycke, Y; Hemery, C; Henni, M; Bachaud, J M; Thiounn, N; Cosset, J M; Giraud, P

    2011-08-01

    Androgens play a role in the development of both androgenic alopecia, commonly known as male pattern baldness, and prostate cancer. We set out to study if early-onset androgenic alopecia was associated with an increased risk of prostate cancer later in life. A total of 669 subjects (388 with a history of prostate cancer and 281 without) were enrolled in this study. All subjects were asked to score their balding pattern at ages 20, 30 and 40. Statistical comparison was subsequently done between both groups of patients. Our study revealed that patients with prostate cancer were twice as likely to have androgenic alopecia at age 20 [odds ratio (OR) 2.01, P = 0.0285]. The pattern of hair loss was not a predictive factor for the development of cancer. There was no association between early-onset alopecia and an earlier diagnosis of prostate cancer or with the development of more aggressive tumors. This study shows an association between early-onset androgenic alopecia and the development of prostate cancer. Whether this population can benefit from routine prostate cancer screening or systematic use of 5-alpha reductase inhibitors as primary prevention remains to be determined.

  4. Estimated risks and optimistic self-perception of breast cancer risk in Korean women.

    Science.gov (United States)

    Chung, ChaeWeon; Lee, Suk Jeong

    2013-11-01

    To determine women's perceived personal and comparative risks of breast cancer, and to examine the relationships with risk factors. Despite the increasing incidence of breast cancer in younger women and the availability of screening, women's health behaviors have not advanced accordingly. A cross-sectional survey design utilized a convenience sample of 222 women in their 30s and 40s recruited from community settings in Seoul. Self-administered questionnaire data were analyzed by descriptive statistics, the chi-squared test, and ANOVA. Risk perception levels differed significantly by breast cancer risk factors. Half of the women were optimistic about their breast cancer risk, while perceived personal risk did not reflect women's own risk factors and comparative risk differed only by the practice of clinical breast exam. Women's knowledge and awareness of their breast cancer risk factors need to be improved for appropriate risk perception and health behaviors, and accurate risk estimation could be utilized to educate them in clinical settings. © 2013.

  5. Gene panel testing for inherited cancer risk.

    Science.gov (United States)

    Hall, Michael J; Forman, Andrea D; Pilarski, Robert; Wiesner, Georgia; Giri, Veda N

    2014-09-01

    Next-generation sequencing technologies have ushered in the capability to assess multiple genes in parallel for genetic alterations that may contribute to inherited risk for cancers in families. Thus, gene panel testing is now an option in the setting of genetic counseling and testing for cancer risk. This article describes the many gene panel testing options clinically available to assess inherited cancer susceptibility, the potential advantages and challenges associated with various types of panels, clinical scenarios in which gene panels may be particularly useful in cancer risk assessment, and testing and counseling considerations. Given the potential issues for patients and their families, gene panel testing for inherited cancer risk is recommended to be offered in conjunction or consultation with an experienced cancer genetic specialist, such as a certified genetic counselor or geneticist, as an integral part of the testing process. Copyright © 2014 by the National Comprehensive Cancer Network.

  6. Predictive model for survival in patients with gastric cancer.

    Science.gov (United States)

    Goshayeshi, Ladan; Hoseini, Benyamin; Yousefli, Zahra; Khooie, Alireza; Etminani, Kobra; Esmaeilzadeh, Abbas; Golabpour, Amin

    2017-12-01

    Gastric cancer is one of the most prevalent cancers in the world. Characterized by poor prognosis, it is a frequent cause of cancer in Iran. The aim of the study was to design a predictive model of survival time for patients suffering from gastric cancer. This was a historical cohort conducted between 2011 and 2016. Study population were 277 patients suffering from gastric cancer. Data were gathered from the Iranian Cancer Registry and the laboratory of Emam Reza Hospital in Mashhad, Iran. Patients or their relatives underwent interviews where it was needed. Missing values were imputed by data mining techniques. Fifteen factors were analyzed. Survival was addressed as a dependent variable. Then, the predictive model was designed by combining both genetic algorithm and logistic regression. Matlab 2014 software was used to combine them. Of the 277 patients, only survival of 80 patients was available whose data were used for designing the predictive model. Mean ?SD of missing values for each patient was 4.43?.41 combined predictive model achieved 72.57% accuracy. Sex, birth year, age at diagnosis time, age at diagnosis time of patients' family, family history of gastric cancer, and family history of other gastrointestinal cancers were six parameters associated with patient survival. The study revealed that imputing missing values by data mining techniques have a good accuracy. And it also revealed six parameters extracted by genetic algorithm effect on the survival of patients with gastric cancer. Our combined predictive model, with a good accuracy, is appropriate to forecast the survival of patients suffering from Gastric cancer. So, we suggest policy makers and specialists to apply it for prediction of patients' survival.

  7. Common ataxia telangiectasia mutated haplotypes and risk of breast cancer: a nested case–control study

    International Nuclear Information System (INIS)

    Tamimi, Rulla M; Hankinson, Susan E; Spiegelman, Donna; Kraft, Peter; Colditz, Graham A; Hunter, David J

    2004-01-01

    The ataxia telangiectasia mutated (ATM) gene is a tumor suppressor gene with functions in cell cycle arrest, apoptosis, and repair of DNA double-strand breaks. Based on family studies, women heterozygous for mutations in the ATM gene are reported to have a fourfold to fivefold increased risk of breast cancer compared with noncarriers of the mutations, although not all studies have confirmed this association. Haplotype analysis has been suggested as an efficient method for investigating the role of common variation in the ATM gene and breast cancer. Five biallelic haplotype tagging single nucleotide polymorphisms are estimated to capture 99% of the haplotype diversity in Caucasian populations. We conducted a nested case–control study of breast cancer within the Nurses' Health Study cohort to address the role of common ATM haplotypes and breast cancer. Cases and controls were genotyped for five haplotype tagging single nucleotide polymorphisms. Haplotypes were predicted for 1309 cases and 1761 controls for which genotype information was available. Six unique haplotypes were predicted in this study, five of which occur at a frequency of 5% or greater. The overall distribution of haplotypes was not significantly different between cases and controls (χ 2 = 3.43, five degrees of freedom, P = 0.63). There was no evidence that common haplotypes of ATM are associated with breast cancer risk. Extensive single nucleotide polymorphism detection using the entire genomic sequence of ATM will be necessary to rule out less common variation in ATM and sporadic breast cancer risk

  8. Haptoglobin phenotype is not a predictor of recurrence free survival in high-risk primary breast cancer patients

    NARCIS (Netherlands)

    Gast, M.C.; van Tinteren, H.; Bontenbal, M.; van Hoesel, R.Q.; Nooij, M.A.; Rodenhuis, S.; Span, P.N.; Tjan-Heijnen, V.C.; de Vries, E.G.; Harris, N.; Twisk, J.W.R.; Schellens, J.H.; Beijnen, J.H.

    2008-01-01

    Background: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective follow-up study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence free survival. Methods: Two

  9. Haptoglobin phenotype is not a predictor of recurrence free survival in high-risk primary breast cancer patients

    NARCIS (Netherlands)

    M.C.W. Gast; H. van Tinteren (Harm); M. Bontenbal (Marijke); R.Q.G.C.M. van Hoesel (René); M.A. Nooij; S. Rodenhuis (Sjoerd); P.N. Span (Paul); V.C.G. Tjan-Heijnen (Vivianne); E. de Vries (Esther); N. Harris (Nathan); J.W.R. Twisk (Jos); J.H.M. Schellens (Jan); J.H. Beijnen (Jos)

    2008-01-01

    textabstractBackground: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective follow-up study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence free survival.

  10. Haptoglobin phenotype is not a predictor of recurrence free survival in high-risk primary breast cancer patients

    NARCIS (Netherlands)

    Gast, Marie-Christine W.; van Tinteren, Harm; Bontenbal, Marijke; van Hoesel, Rene Q. G. C. M.; Nooij, Marianne A.; Rodenhuis, Sjoerd; Span, Paul N.; Tjan-Heijnen, Vivianne C. G.; de Vries, Elisabeth G. E.; Harris, Nathan; Twisk, Jos W. R.; Schellens, Jan H. M.; Beijnen, Jos H.

    2008-01-01

    ABSTRACT: BACKGROUND: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective follow-up study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence free survival.

  11. Haptoglobin phenotype is not a predictor of recurrence free survival in high-risk primary breast cancer patients.

    NARCIS (Netherlands)

    Gast, M.C.; Tinteren, H. van; Bontenbal, M.; Hoesel, R.Q. van; Nooij, M.A.; Rodenhuis, S.; Span, P.N.; Tjan-Heijnen, V.C.; Vries, E.G.F. de; Harris, N.; Twisk, J.W.R.; Schellens, J.H.; Beijnen, J.H.

    2008-01-01

    BACKGROUND: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective follow-up study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence free survival. METHODS: Two

  12. Predictive test for chemotherapy response in resectable gastric cancer: a multi-cohort, retrospective analysis.

    Science.gov (United States)

    Cheong, Jae-Ho; Yang, Han-Kwang; Kim, Hyunki; Kim, Woo Ho; Kim, Young-Woo; Kook, Myeong-Cherl; Park, Young-Kyu; Kim, Hyung-Ho; Lee, Hye Seung; Lee, Kyung Hee; Gu, Mi Jin; Kim, Ha Yan; Lee, Jinae; Choi, Seung Ho; Hong, Soonwon; Kim, Jong Won; Choi, Yoon Young; Hyung, Woo Jin; Jang, Eunji; Kim, Hyeseon; Huh, Yong-Min; Noh, Sung Hoon

    2018-05-01

    patients as low risk, 296 (47%) as intermediate risk, and 250 (40%) as high risk, and 5-year overall survival for these groups was 83·2% (95% CI 75·2-92·0), 74·8% (69·9-80·1), and 66·0% (60·1-72·4), respectively (p=0·012). The predictive single patient classifier (based on the expression of GZMB, WARS, and CDX1) assigned 281 (45%) of 625 patients in the validation cohort to the chemotherapy-benefit group and 344 (55%) to the no-benefit group. In the predicted chemotherapy-benefit group, 5-year overall survival was significantly improved in those patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (80% [95% CI 73·5-87·1] vs 64·5% [56·8-73·3]; univariate hazard ratio 0·47 [95% CI 0·30-0·75], p=0·0015), whereas no such improvement in 5-year overall survival was observed in the no-benefit group (72·9% [66·5-79·9] in patients who received chemotherapy plus surgery vs 72·5% [65·8-79·9] in patients who only had surgery; 0·93 [0·62-1·38], p=0·71). The predictive single patient classifier groups (chemotherapy benefit vs no-benefit) could predict adjuvant chemotherapy benefit in terms of 5-year overall survival in the validation cohort (p interaction =0·036 in univariate analysis). Similar results were obtained in the internal evaluation cohort. The single patient classifiers validated in this study provide clinically important prognostic information independent of standard risk-stratification methods and predicted chemotherapy response after surgery in two independent cohorts of patients with resectable, stage II-III gastric cancer. The single patient classifiers could complement TNM staging to optimise decision making in patients with resectable gastric cancer who are eligible for adjuvant chemotherapy after surgery. Further validation of these results in prospective studies is warranted. Ministry of ICT and Future Planning; Ministry of Trade, Industry, and Energy; and Ministry of Health and

  13. Predictors of Fracture Risk and Bone Mineral Density in Men with Prostate Cancer on Androgen Deprivation Therapy

    Directory of Open Access Journals (Sweden)

    Katherine Neubecker

    2011-01-01

    Full Text Available Decrease of bone mineral density (BMD and fracture risk is increased in men with prostate cancer receiving androgen deprivation therapy (ADT. We looked at possible predictors of decreased BMD and increased fracture risk in men with prostate cancer; most of whom were on ADT. In a retrospective study, we analyzed serum, BMD, and clinical risk factors used in the Fracture Risk Assessment (FRAX tool and others in 78 men with prostate cancer with reported height loss. The subjects were divided in two groups: 22 men with and 56 without vertebral fractures. 17 of the 22 men with vertebral fractures on spine X-rays did not know they had a vertebral fracture. Of those 17 men, 9 had not previously qualified for treatment based on preradiograph FRAX score calculated with BMD, and 6 based on FRAX calculated without BMD. Performing spine films increased the predictive ability of FRAX for vertebral fracture. Vertebral fracture was better predicted by FRAX for other osteoporotic fractures than FRAX for hip fractures. The inclusion of BMD in FRAX calculations did not affect the predictive ability of FRAX. The PSA level showed a positive correlation with lumbar spine BMD and accounted for about 9% of spine BMD.

  14. Serum protein profiling using an aptamer array predicts clinical outcomes of stage IIA colon cancer: A leave-one-out crossvalidation

    Science.gov (United States)

    Huh, Jung Wook; Kim, Sung Chun; Sohn, Insuk; Jung, Sin-Ho; Kim, Hee Cheol

    2016-01-01

    Background In this study, we established and validated a model for predicting prognosis of stage IIA colon cancer patients based on expression profiles of aptamers in serum. Methods Bloods samples were collected from 227 consecutive patients with pathologic T3N0M0 (stage IIA) colon cancer. We incubated 1,149 serum molecule-binding aptamer pools of clinical significance with serum from patients to obtain aptamers bound to serum molecules, which were then amplified and marked. Oligonucleotide arrays were constructed with the base sequences of the 1,149 aptamers, and the marked products identified above were reacted with one another to produce profiles of the aptamers bound to serum molecules. These profiles were organized into low- and high-risk groups of colon cancer patients based on clinical information for the serum samples. Cox proportional hazards model and leave-one-out cross-validation (LOOCV) were used to evaluate predictive performance. Results During a median follow-up period of 5 years, 29 of the 227 patients (11.9%) experienced recurrence. There were 212 patients (93.4%) in the low-risk group and 15 patients (6.6%) in the high-risk group in our aptamer prognosis model. Postoperative recurrence significantly correlated with age and aptamer risk stratification (p = 0.046 and p = 0.001, respectively). In multivariate analysis, aptamer risk stratification (p recurrence. Disease-free survival curves calculated according to aptamer risk level predicted through a LOOCV procedure and age showed significant differences (p < 0.001 from permutations). Conclusion Aptamer risk stratification can be a valuable prognostic factor in stage II colon cancer patients. PMID:26908450

  15. Genetic polymorphisms in the microRNA binding-sites of the thymidylate synthase gene predict risk and survival in gastric cancer.

    Science.gov (United States)

    Shen, Rong; Liu, Hongliang; Wen, Juyi; Liu, Zhensheng; Wang, Li-E; Wang, Qiming; Tan, Dongfeng; Ajani, Jaffer A; Wei, Qingyi

    2015-09-01

    Thymidylate synthase (TYMS) plays a crucial role in folate metabolism as well as DNA synthesis and repair. We hypothesized that functional polymorphisms in the 3' UTR of TYMS are associated with gastric cancer risk and survival. In the present study, we tested our hypothesis by genotyping three potentially functional (at miRNA binding sites) TYMS SNPs (rs16430 6bp del/ins, rs2790 A>G and rs1059394 C>T) in 379 gastric cancer patients and 431 cancer-free controls. Compared with the rs16430 6bp/6bp + 6bp/0bp genotypes, the 0bp/0bp genotype was associated with significantly increased gastric cancer risk (adjusted OR = 1.72, 95% CI = 1.15-2.58). Similarly, rs2790 GG and rs1059394 TT genotypes were also associated with significantly increased risk (adjusted OR = 2.52, 95% CI = 1.25-5.10 and adjusted OR = 1.57, 95% CI = 1.04-2.35, respectively), compared with AA + AG and CC + CT genotypes, respectively. In the haplotype analysis, the T-G-0bp haplotype was associated with significantly increased gastric cancer risk, compared with the C-A-6bp haplotype (adjusted OR = 1.34, 95% CI = 1.05-1.72). Survival analysis revealed that rs16430 0bp/0bp and rs1059394 TT genotypes were also associated with poor survival in gastric cancer patients who received chemotherapy treatment (adjusted HR = 1.61, 95% CI = 1.05-2.48 and adjusted HR = 1.59, 95% CI = 1.02-2.48, respectively). These results suggest that these three variants in the miRNA binding sites of TYMS may be associated with cancer risk and survival of gastric cancer patients. Larger population studies are warranted to verify these findings. © 2014 Wiley Periodicals, Inc.

  16. A comparison of machine learning techniques for survival prediction in breast cancer.

    Science.gov (United States)

    Vanneschi, Leonardo; Farinaccio, Antonella; Mauri, Giancarlo; Antoniotti, Mauro; Provero, Paolo; Giacobini, Mario

    2011-05-11

    The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.

  17. A comparison of machine learning techniques for survival prediction in breast cancer

    Directory of Open Access Journals (Sweden)

    Vanneschi Leonardo

    2011-05-01

    Full Text Available Abstract Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.

  18. Familial risks in testicular cancer as aetiological clues.

    Science.gov (United States)

    Hemminki, Kari; Chen, Bowang

    2006-02-01

    We used the nationwide Swedish Family-Cancer Database to analyse the risk for testicular cancer in offspring through parental and sibling probands. Among 0 to 70-year-old offspring, 4,586 patients had testicular cancer. Standardized incidence ratios for familial risk were 3.8-fold when a father and 7.6-fold when a brother had testicular cancer. Testicular cancer was associated with leukaemia, distal colon and kidney cancer, melanoma, connective tissue tumours and lung cancer in families. Non-seminoma was associated with maternal lung cancer but the risk was highest for the late-onset cases, providing no support to the theory of the in utero effect of maternal smoking on the son's risk of testicular cancer. However, the theory cannot be excluded but should be taken up for study when further data are available on maternal smoking. The high familial risk may be the product of shared childhood environment and heritable causes.

  19. Prediction of bleeding and prophylactic platelet transfusions in cancer patients with thrombocytopenia

    DEFF Research Database (Denmark)

    Vinholt, Pernille J; Alnor, Anne; Nybo, Mads

    2016-01-01

    Studies on markers for bleeding risk among thrombocytopenic cancer patients are lacking. This prospective observational cohort study investigated whether platelet parameters and a standardised bleeding questionnaire predicted bleeding or prophylactic platelet transfusions in patients with cancer ...... platelet transfusion but not bleeding. Bleeding risk factors were previous haematuria or gastrointestinal bleeding, infection, antiplatelet or anticoagulant treatment, high urea nitrogen, low haemoglobin or high creatinine....... or warfarin OR = 2.34, 95% CI 1.23–4.48; urea nitrogen OR = 1.15, 95% CI 1.07–1.25; creatinine OR = 1.01, 95% CI 1.01–1.01; and haemoglobin OR = 0.62, 95% CI 0.41–0.93. Specific information regarding previous gastrointestinal bleeding OR = 3.33, 95% CI 1.19–9.34 and haematuria OR = 3.00, 95% CI 1...

  20. Establishing a family risk assessment clinic for breast cancer.

    LENUS (Irish Health Repository)

    Mulsow, Jurgen

    2012-02-01

    Breast cancer is the most common cancer affecting European women and the leading cause of cancer-related death. A total of 15-20% of women who develop breast cancer have a family history and 5-10% a true genetic predisposition. The identification and screening of women at increased risk may allow early detection of breast cancer and improve prognosis. We established a family risk assessment clinic in May 2005 to assess and counsel women with a family history of breast cancer, to initiate surveillance, and to offer risk-reducing strategies for selected high-risk patients. Patients at medium or high risk of developing breast cancer according to NICE guidelines were accepted. Family history was determined by structured questionnaire and interview. Lifetime risk of developing breast cancer was calculated using Claus and Tyrer-Cuzick scoring. Risk of carrying a breast cancer-related gene mutation was calculated using the Manchester system. One thousand two hundred and forty-three patients have been referred. Ninety-two percent were at medium or high risk of developing breast cancer. Formal assessment of risk has been performed in 368 patients, 73% have a high lifetime risk of developing breast cancer, and 72% a Manchester score >or=16. BRCA1\\/2 mutations have been identified in 14 patients and breast cancer diagnosed in two. Our initial experience of family risk assessment has shown there to be a significant demand for this service. Identification of patients at increased risk of developing breast cancer allows us to provide individuals with accurate risk profiles, and enables patients to make informed choices regarding their follow-up and management.

  1. A Validated Clinical Risk Prediction Model for Lung Cancer in Smokers of All Ages and Exposure Types

    DEFF Research Database (Denmark)

    Markaki, Maria; Tsamardinos, Ioannis; Langhammer, Arnulf

    2018-01-01

    Lung cancer causes >1·6 million deaths annually, with early diagnosis being paramount to effective treatment. Here we present a validated risk assessment model for lung cancer screening. The prospective HUNT2 population study in Norway examined 65,237 people aged >20years in 1995-97. After a median...

  2. Low-risk factor profile, estrogen levels, and breast cancer risk among postmenopausal women

    DEFF Research Database (Denmark)

    Rod, Naja Hulvej; Hansen, Ase Marie; Nielsen, Jens

    2008-01-01

    Obesity, alcohol consumption, physical inactivity and postmenopausal hormone use are known modifiable risk factors for breast cancer. We aim to measure incidence rates of breast cancer for women with favorable levels on all 4 risk factors (BMI......Obesity, alcohol consumption, physical inactivity and postmenopausal hormone use are known modifiable risk factors for breast cancer. We aim to measure incidence rates of breast cancer for women with favorable levels on all 4 risk factors (BMI...

  3. Does Metformin Reduce Cancer Risks? Methodologic Considerations.

    Science.gov (United States)

    Golozar, Asieh; Liu, Shuiqing; Lin, Joeseph A; Peairs, Kimberly; Yeh, Hsin-Chieh

    2016-01-01

    The substantial burden of cancer and diabetes and the association between the two conditions has been a motivation for researchers to look for targeted strategies that can simultaneously affect both diseases and reduce their overlapping burden. In the absence of randomized clinical trials, researchers have taken advantage of the availability and richness of administrative databases and electronic medical records to investigate the effects of drugs on cancer risk among diabetic individuals. The majority of these studies suggest that metformin could potentially reduce cancer risk. However, the validity of this purported reduction in cancer risk is limited by several methodological flaws either in the study design or in the analysis. Whether metformin use decreases cancer risk relies heavily on the availability of valid data sources with complete information on confounders, accurate assessment of drug use, appropriate study design, and robust analytical techniques. The majority of the observational studies assessing the association between metformin and cancer risk suffer from methodological shortcomings and efforts to address these issues have been incomplete. Future investigations on the association between metformin and cancer risk should clearly address the methodological issues due to confounding by indication, prevalent user bias, and time-related biases. Although the proposed strategies do not guarantee a bias-free estimate for the association between metformin and cancer, they will reduce synthesis of and reporting of erroneous results.

  4. Predicting 6- and 12-Month Risk of Mortality in Patients With Platinum-Resistant Advanced-Stage Ovarian Cancer: Prognostic Model to Guide Palliative Care Referrals.

    Science.gov (United States)

    Foote, Jonathan; Lopez-Acevedo, Micael; Samsa, Gregory; Lee, Paula S; Kamal, Arif H; Alvarez Secord, Angeles; Havrilesky, Laura J

    2018-02-01

    Predictive models are increasingly being used in clinical practice. The aim of the study was to develop a predictive model to identify patients with platinum-resistant ovarian cancer with a prognosis of less than 6 to 12 months who may benefit from immediate referral to hospice care. A retrospective chart review identified patients with platinum-resistant epithelial ovarian cancer who were treated at our institution between 2000 and 2011. A predictive model for survival was constructed based on the time from development of platinum resistance to death. Multivariate logistic regression modeling was used to identify significant survival predictors and to develop a predictive model. The following variables were included: time from diagnosis to platinum resistance, initial stage, debulking status, number of relapses, comorbidity score, albumin, hemoglobin, CA-125 levels, liver/lung metastasis, and the presence of a significant clinical event (SCE). An SCE was defined as a malignant bowel obstruction, pleural effusion, or ascites occurring on or before the diagnosis of platinum resistance. One hundred sixty-four patients met inclusion criteria. In the regression analysis, only an SCE and the presence of liver or lung metastasis were associated with poorer short-term survival (P < 0.001). Nine percent of patients with an SCE or liver or lung metastasis survived 6 months or greater and 0% survived 12 months or greater, compared with 85% and 67% of patients without an SCE or liver or lung metastasis, respectively. Patients with platinum-resistant ovarian cancer who have experienced an SCE or liver or lung metastasis have a high risk of death within 6 months and should be considered for immediate referral to hospice care.

  5. Radiation risk from CT: implications for cancer screening.

    Science.gov (United States)

    Albert, Jeffrey M

    2013-07-01

    The cancer risks associated with patient exposure to radiation from medical imaging have become a major topic of debate. The higher doses necessary for technologies such as CT and the increasing utilization of these technologies further increase medical radiation exposure to the population. Furthermore, the use of CT for population-based cancer screening continues to be explored for common malignancies such as lung cancer and colorectal cancer. Given the known carcinogenic effects of ionizing radiation, this warrants evaluation of the balance between the benefit of early cancer detection and the risk of screening-induced malignancy. This report provides a brief review of the process of radiation carcino-genesis and the literature evaluating the risk of malignancy from CT, with a focus on the risks and benefits of CT for cancer screening. The available data suggest a small but real risk of radiation-induced malignancy from CT that could become significant at the population level with widespread use of CT-based screening. However, a growing body of literature suggests that the benefits of CT screening for lung cancer in high-risk patients and CT colonography for colorectal cancer may significantly outweigh the radiation risk. Future studies evaluating the benefits of CT screening should continue to consider potential radiation risks.

  6. Making sense of cancer risk calculators on the web.

    Science.gov (United States)

    Levy, Andrea Gurmankin; Sonnad, Seema S; Kurichi, Jibby E; Sherman, Melani; Armstrong, Katrina

    2008-03-01

    Cancer risk calculators on the internet have the potential to provide users with valuable information about their individual cancer risk. However, the lack of oversight of these sites raises concerns about low quality and inconsistent information. These concerns led us to evaluate internet cancer risk calculators. After a systematic search to find all cancer risk calculators on the internet, we reviewed the content of each site for information that users should seek to evaluate the quality of a website. We then examined the consistency of the breast cancer risk calculators by having 27 women complete 10 of the breast cancer risk calculators for themselves. We also completed the breast cancer risk calculators for a hypothetical high- and low-risk woman, and compared the output to Surveillance Epidemiology and End Results estimates for the average same-age and same-race woman. Nineteen sites were found, 13 of which calculate breast cancer risk. Most sites do not provide the information users need to evaluate the legitimacy of a website. The breast cancer calculator sites vary in the risk factors they assess to calculate breast cancer risk, how they operationalize each risk factor and in the risk estimate they provide for the same individual. Internet cancer risk calculators have the potential to provide a public health benefit by educating individuals about their risks and potentially encouraging preventive health behaviors. However, our evaluation of internet calculators revealed several problems that call into question the accuracy of the information that they provide. This may lead the users of these sites to make inappropriate medical decisions on the basis of misinformation.

  7. Chronic and episodic stress predict physical symptom bother following breast cancer diagnosis.

    Science.gov (United States)

    Harris, Lauren N; Bauer, Margaret R; Wiley, Joshua F; Hammen, Constance; Krull, Jennifer L; Crespi, Catherine M; Weihs, Karen L; Stanton, Annette L

    2017-12-01

    Breast cancer patients often experience adverse physical side effects of medical treatments. According to the biobehavioral model of cancer stress and disease, life stress during diagnosis and treatment may negatively influence the trajectory of women's physical health-related adjustment to breast cancer. This longitudinal study examined chronic and episodic stress as predictors of bothersome physical symptoms during the year after breast cancer diagnosis. Women diagnosed with breast cancer in the previous 4 months (N = 460) completed a life stress interview for contextual assessment of chronic and episodic stress severity at study entry and 9 months later. Physical symptom bother (e.g., pain, fatigue) was measured at study entry, every 6 weeks through 6 months, and at nine and 12 months. In multilevel structural equation modeling (MSEM) analyses, both chronic stress and episodic stress occurring shortly after diagnosis predicted greater physical symptom bother over the study period. Episodic stress reported to have occurred prior to diagnosis did not predict symptom bother in MSEM analyses, and the interaction between chronic and episodic stress on symptom bother was not significant. Results suggest that ongoing chronic stress and episodic stress occurring shortly after breast cancer diagnosis are important predictors of bothersome symptoms during and after cancer treatment. Screening for chronic stress and recent stressful life events in the months following diagnosis may help to identify breast cancer patients at risk for persistent and bothersome physical symptoms. Interventions to prevent or ameliorate treatment-related physical symptoms may confer added benefit by addressing ongoing non-cancer-related stress in women's lives.

  8. Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study

    International Nuclear Information System (INIS)

    Wu, Jia; Gensheimer, Michael F.; Dong, Xinzhe; Rubin, Daniel L.; Napel, Sandy; Diehn, Maximilian; Loo, Billy W.; Li, Ruijiang

    2016-01-01

    Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from "1"8F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust intratumor

  9. Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Jia; Gensheimer, Michael F.; Dong, Xinzhe [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Rubin, Daniel L. [Department of Radiology, Stanford University School of Medicine, Stanford, California (United States); Department of Medicine (Biomedical Informatics Research), Stanford University School of Medicine, Stanford, California (United States); Napel, Sandy [Department of Radiology, Stanford University School of Medicine, Stanford, California (United States); Diehn, Maximilian [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California (United States); Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California (United States); Loo, Billy W. [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California (United States); Li, Ruijiang, E-mail: rli2@stanford.edu [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California (United States)

    2016-08-01

    Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust

  10. Mobile application-based Seoul National University Prostate Cancer Risk Calculator: development, validation, and comparative analysis with two Western risk calculators in Korean men.

    Directory of Open Access Journals (Sweden)

    Chang Wook Jeong

    Full Text Available OBJECTIVES: We developed a mobile application-based Seoul National University Prostate Cancer Risk Calculator (SNUPC-RC that predicts the probability of prostate cancer (PC at the initial prostate biopsy in a Korean cohort. Additionally, the application was validated and subjected to head-to-head comparisons with internet-based Western risk calculators in a validation cohort. Here, we describe its development and validation. PATIENTS AND METHODS: As a retrospective study, consecutive men who underwent initial prostate biopsy with more than 12 cores at a tertiary center were included. In the development stage, 3,482 cases from May 2003 through November 2010 were analyzed. Clinical variables were evaluated, and the final prediction model was developed using the logistic regression model. In the validation stage, 1,112 cases from December 2010 through June 2012 were used. SNUPC-RC was compared with the European Randomized Study of Screening for PC Risk Calculator (ERSPC-RC and the Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC. The predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC. The clinical value was evaluated using decision curve analysis. RESULTS: PC was diagnosed in 1,240 (35.6% and 417 (37.5% men in the development and validation cohorts, respectively. Age, prostate-specific antigen level, prostate size, and abnormality on digital rectal examination or transrectal ultrasonography were significant factors of PC and were included in the final model. The predictive accuracy in the development cohort was 0.786. In the validation cohort, AUC was significantly higher for the SNUPC-RC (0.811 than for ERSPC-RC (0.768, p<0.001 and PCPT-RC (0.704, p<0.001. Decision curve analysis also showed higher net benefits with SNUPC-RC than with the other calculators. CONCLUSIONS: SNUPC-RC has a higher predictive accuracy and clinical benefit than Western risk calculators. Furthermore, it is easy

  11. ATM variants and cancer risk in breast cancer patients from Southern Finland

    Directory of Open Access Journals (Sweden)

    Aittomäki Kristiina

    2006-08-01

    Full Text Available Abstract Background Individuals heterozygous for germline ATM mutations have been reported to have an increased risk for breast cancer but the role for ATM genetic variants for breast cancer risk has remained unclear. Recently, a common ATM variant, ATMivs38 -8T>C in cis with the ATMex39 5557G>A (D1853N variant, was suggested to associate with bilateral breast cancer among familial breast cancer patients from Northern Finland. We have here evaluated the 5557G>A and ivs38-8T>C variants in an extensive case-control association analysis. We also aimed to investigate whether there are other ATM mutations or variants contributing to breast cancer risk in our population. Methods Two common ATM variants, 5557G>A and ivs38-8T>C, previously suggested to associate with bilateral breast cancer, were genotyped in an extensive set of 786 familial and 884 unselected breast cancer cases as well as 708 healthy controls. We also screened the entire coding region and exon-intron boundaries of the ATM gene in 47 familial breast cancer patients and constructed haplotypes of the patients. The identified variants were also evaluated for increased breast cancer risk among additional breast cancer cases and controls. Results Neither of the two common variants, 5557G>A and ivs38-8T>C, nor any haplotype containing them, was significantly associated with breast cancer risk, bilateral breast cancer or multiple primary cancers in any of the patient groups or subgoups. Three rare missense alterations and one intronic change were each found in only one patient of over 250 familial patients studied and not among controls. The fourth missense alteration studied further was found with closely similar frequencies in over 600 familial cases and controls. Conclusion Altogether, our results suggest very minor effect, if any, of ATM genetic variants on familial breast cancer in Southern Finland. Our results do not support association of the 5557G>A or ivs38-8T>C variant with

  12. Review of radon and lung cancer risk

    International Nuclear Information System (INIS)

    Samet, J.M.; Hornung, R.W.

    1990-01-01

    Radon, a long-established cause of lung cancer in uranium and other underground miners, has recently emerged as a potentially important cause of lung cancer in the general population. The evidence for widespread exposure of the population to radon and the well-documented excess of lung cancer among underground miners exposed to radon decay products have raised concern that exposure to radon progeny might also be a cause of lung cancer in the general population. To date, epidemiological data on the lung cancer risk associated with environmental exposure to radon have been limited. Consequently, the lung cancer hazard posed by radon exposure in indoor air has been addressed primarily through risk estimation procedures. The quantitative risks of lung cancer have been estimated using exposure-response relations derived from the epidemiological investigations of uranium and other underground miners. We review five of the more informative studies of miners and recent risk projection models for excess lung cancer associated with radon. The principal models differ substantially in their underlying assumptions and consequently in the resulting risk projections. The resulting diversity illustrates the substantial uncertainty that remains concerning the most appropriate model of the temporal pattern of radon-related lung cancer. Animal experiments, further follow-up of the miner cohorts, and well-designed epidemiological studies of indoor exposure should reduce this uncertainty. 18 references

  13. Parity and risk of lung cancer in women.

    Science.gov (United States)

    Paulus, Jessica K; Asomaning, Kofi; Kraft, Peter; Johnson, Bruce E; Lin, Xihong; Christiani, David C

    2010-03-01

    Patterns of lung cancer incidence suggest that gender-associated factors may influence lung cancer risk. Given the association of parity with risk of some women's cancers, the authors hypothesized that childbearing history may also be associated with lung cancer. Women enrolled in the Lung Cancer Susceptibility Study at Massachusetts General Hospital (Boston, Massachusetts) between 1992 and 2004 (1,004 cases, 848 controls) were available for analysis of the association between parity and lung cancer risk. Multivariate logistic regression was used to estimate adjusted odds ratios and 95% confidence intervals. After results were controlled for age and smoking history, women with at least 1 child had 0.71 times the odds of lung cancer as women without children (odds ratio = 0.71, 95% confidence interval: 0.52, 0.97). A significant linear trend was found: Lung cancer risk decreased with increasing numbers of children (P < 0.001). This inverse association was stronger in never smokers (P = 0.12) and was limited to women over age 50 years at diagnosis (P = 0.17). Age at first birth was not associated with risk. The authors observed a protective association between childbearing and lung cancer, adding to existing evidence that reproductive factors may moderate lung cancer risk in women.

  14. Increased pancreatic cancer risk following radiotherapy for testicular cancer.

    Science.gov (United States)

    Hauptmann, Michael; Børge Johannesen, Tom; Gilbert, Ethel S; Stovall, Marilyn; van Leeuwen, Flora E; Rajaraman, Preetha; Smith, Susan A; Weathers, Rita E; Aleman, Berthe M P; Andersson, Michael; Curtis, Rochelle E; Dores, Graça M; Fraumeni, Joseph F; Hall, Per; Holowaty, Eric J; Joensuu, Heikki; Kaijser, Magnus; Kleinerman, Ruth A; Langmark, Frøydis; Lynch, Charles F; Pukkala, Eero; Storm, Hans H; Vaalavirta, Leila; van den Belt-Dusebout, Alexandra W; Morton, Lindsay M; Fossa, Sophie D; Travis, Lois B

    2016-09-27

    Pancreatic cancer risk is elevated among testicular cancer (TC) survivors. However, the roles of specific treatments are unclear. Among 23 982 5-year TC survivors diagnosed during 1947-1991, doses from radiotherapy to the pancreas were estimated for 80 pancreatic cancer patients and 145 matched controls. Chemotherapy details were recorded. Logistic regression was used to estimate odds ratios (ORs). Cumulative incidence of second primary pancreatic cancer was 1.1% at 30 years after TC diagnosis. Radiotherapy (72 (90%) cases and 115 (80%) controls) was associated with a 2.9-fold (95% confidence interval (CI) 1.0-7.8) increased risk. The OR increased linearly by 0.12 per Gy to the pancreas (P-trendcancer risk, and persists for over 20 years. These excesses, although small, should be considered when radiotherapy with exposure to the pancreas is considered for newly diagnosed patients. Additional data are needed on the role of chemotherapy.

  15. Persistence of type-specific human papillomavirus infection and increased long-term risk of cervical cancer.

    Science.gov (United States)

    Chen, Hui-Chi; Schiffman, Mark; Lin, Ching-Yu; Pan, Mei-Hung; You, San-Lin; Chuang, Li-Chung; Hsieh, Chang-Yao; Liaw, Kai-Li; Hsing, Ann W; Chen, Chien-Jen

    2011-09-21

    Human papillomavirus (HPV) persistence is the pivotal event in cervical carcinogenesis. We followed a large-scale community-based cohort for 16 years to investigate the role of genotype-specific HPV persistence in predicting cervical cancer including invasive and in situ carcinoma. At the baseline examination in 1991-1992, 11,923 participants (aged 30-65 years) consented to HPV testing and cytology; 6923 participants were reexamined in 1993-1995. For HPV testing, we used a polymerase chain reaction-based assay that detected 39 HPV types. Women who developed cervical cancer were identified from cancer and death registries. Cumulative risks for developing cervical cancer among infected and persistently infected women were calculated by the Kaplan-Meier method. Of 10,123 women who were initially cytologically normal, 68 developed cervical cancer. The 16-year cumulative risks of subsequent cervical cancer for women with HPV16, HPV58 (without HPV16), or other carcinogenic HPV types (without HPV16 or HPV58) were 13.5%, 10.3%, and 4.0%, respectively, compared with 0.26% for HPV-negative women. Women with type-specific persistence of any carcinogenic HPV had greatly increased risk compared with women who were HPV-negative at both visits (hazard ratio = 75.4, 95% confidence interval = 31.8 to 178.9). The cumulative cervical cancer risks following persistent carcinogenic HPV infections increased with age: The risks were 5.5%, 14.4%, and 18.1% for women aged 30-44 years, 45-54 years, and 55 years and older, respectively. However, newly acquired infections were associated with a low risk of cervical cancer regardless of age. HPV negativity was associated with a very low long-term risk of cervical cancer. Persistent detection of HPV among cytologically normal women greatly increased risk. Thus, it is useful to perform repeated HPV testing following an initial positive test.

  16. Chronic obstructive pulmonary disease and cancer risk

    DEFF Research Database (Denmark)

    Kornum, Jette Brommann; Sværke, Claus; Thomsen, Reimar Wernich

    2012-01-01

    Little is known about the risk of cancer in patients with chronic obstructive pulmonary disease (COPD), including which cancer sites are most affected. We examined the short- and long-term risk of lung and extrapulmonary cancer in a nationwide cohort of COPD patients....

  17. Network information improves cancer outcome prediction.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

    2014-07-01

    Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  18. Risk of prostate cancer among cancer survivors in the Netherlands

    NARCIS (Netherlands)

    Kok, D.E.G.; Schans, van de S.A.; Liu, L.; Kampman, E.; Coebergh, J.W.; Kiemeney, L.A.; Soerjomataram, I.; Aben, K.K.

    2013-01-01

    In parallel with increasing numbers of cancer patients and improving cancer survival, the occurrence of second primary cancers becomes a relevant issue. The aim of our study was to evaluate risk of prostate cancer as second primary cancer in a population-based setting. Methods Data from the

  19. Evaluation of sestamibi scanning as a predictor of risk of development of breast cancer and as a non-invasive biomarker for breast cancer chemoprevention trials

    International Nuclear Information System (INIS)

    Kimler, B.F.; Preston, D.; McMillin, C.H.; Dusing, R.; Zalles, C.M.; Fabian, C.J.

    2003-01-01

    Sestamibi scintimammography is becoming increasingly accepted as an adjunct to conventional breast imaging by mammography and ultrasound. We sought to determine whether it might serve to detect/quantify pre-cancerous breast lesions, specifically hyperplasia with atypia which, when detected by random periareolar fine needle aspiration (FNA), is known to be associated with increased risk for subsequent development of breast cancer. If a parameter derived from sestamibi scanning could be shown to correlate with and predict for atypia, then this could serve 1) to refine estimates of risk of development of breast cancer; and 2) as a surrogate endpoint biomarker in clinical breast cancer chemoprevention trials. To this end, we performed sestamibi scanning on both breasts of 65 women at high risk for development of breast cancer who also underwent FNA. Seventeen women (26%) exhibited non-proliferative cytology; 30 (46%) had hyperplasia; and 18 (28%) had hyperplasia with atypia in the FNA specimen. Since the fine needle aspiration specimens from both breasts are pooled to provide a single result, we likewise pooled the sestamibi results from both breasts so as to consider the most abnormal finding. Twenty-five women (39%) were characterized as having an abnormal sestamibi scan with heterogenous, focal, intense uptake. There was no correlation between an abnormal scan and cytologic evidence of hyperplasia with atypia. Neither was there a correlation between any of a variety of quantitative measures of the sestamibi scans and the cytological classification. At this time, there is no indication for the use of sestamibi scanning for the prediction of risk of subsequent development of breast cancer, or as a surrogate endpoint biomarker in clinical breast cancer chemoprevention trials

  20. Preoperative Metabolic Syndrome Is Predictive of Significant Gastric Cancer Mortality after Gastrectomy: The Fujian Prospective Investigation of Cancer (FIESTA Study

    Directory of Open Access Journals (Sweden)

    Dan Hu

    2017-02-01

    Full Text Available Metabolic syndrome (MetS has been shown to be associated with an increased risk of gastric cancer. However, the impact of MetS on gastric cancer mortality remains largely unknown. Here, we prospectively examined the prediction of preoperative MetS for gastric cancer mortality by analyzing a subset of data from the ongoing Fujian prospective investigation of cancer (FIESTA study. This study was conducted among 3012 patients with gastric cancer who received radical gastrectomy between 2000 and 2010. The latest follow-up was completed in 2015. Blood/tissue specimens, demographic and clinicopathologic characteristics were collected at baseline. During 15-year follow-up, 1331 of 3012 patients died of gastric cancer. The median survival time (MST of patients with MetS was 31.3 months, which was significantly shorter than that of MetS-free patients (157.1 months. The coexistence of MetS before surgery was associated with a 2.3-fold increased risk for gastric cancer mortality (P < 0.001. The multivariate-adjusted hazard ratios (HRs were increased with invasion depth T1/T2 (HR = 2.78, P < 0.001, regional lymph node metastasis N0 (HR = 2.65, P < 0.001, positive distant metastasis (HR = 2.53, P < 0.001, TNM stage I/II (HR = 3.00, P < 0.001, intestinal type (HR = 2.96, P < 0.001, negative tumor embolus (HR = 2.34, P < 0.001, and tumor size ≤4.5 cm (HR = 2.49, P < 0.001. Further survival tree analysis confirmed the top splitting role of TNM stage, followed by MetS or hyperglycemia with remarkable discrimination ability. In this large cohort study, preoperative MetS, especially hyperglycemia, was predictive of significant gastric cancer mortality in patients with radical gastrectomy, especially for early stage of gastric cancer.

  1. A Risk Prediction Model for Sporadic CRC Based on Routine Lab Results.

    Science.gov (United States)

    Boursi, Ben; Mamtani, Ronac; Hwang, Wei-Ting; Haynes, Kevin; Yang, Yu-Xiao

    2016-07-01

    Current risk scores for colorectal cancer (CRC) are based on demographic and behavioral factors and have limited predictive values. To develop a novel risk prediction model for sporadic CRC using clinical and laboratory data in electronic medical records. We conducted a nested case-control study in a UK primary care database. Cases included those with a diagnostic code of CRC, aged 50-85. Each case was matched with four controls using incidence density sampling. CRC predictors were examined using univariate conditional logistic regression. Variables with p value CRC prediction models which included age, sex, height, obesity, ever smoking, alcohol dependence, and previous screening colonoscopy had an AUC of 0.58 (0.57-0.59) with poor goodness of fit. A laboratory-based model including hematocrit, MCV, lymphocytes, and neutrophil-lymphocyte ratio (NLR) had an AUC of 0.76 (0.76-0.77) and a McFadden's R2 of 0.21 with a NRI of 47.6 %. A combined model including sex, hemoglobin, MCV, white blood cells, platelets, NLR, and oral hypoglycemic use had an AUC of 0.80 (0.79-0.81) with a McFadden's R2 of 0.27 and a NRI of 60.7 %. Similar results were shown in an internal validation set. A laboratory-based risk model had good predictive power for sporadic CRC risk.

  2. Computed tomography for pulmonary embolism - Assessment of a 1-year cohort and estimated cancer risk associated with diagnostic irradiation

    International Nuclear Information System (INIS)

    Niemann, T.; Zbinden, I.; Bremerich, J.; Bongartz, G.; Roser, H. W.; Remy-Jardin, M.

    2013-01-01

    Background: The principal concern of any radiation exposure in computed tomography (CT) is the induction of stochastic risks of developing a radiation-induced cancer. The results given in this manuscript will allow to (re-)calculate yield of chest CT. Purpose: To demonstrate a method to evaluate the lifetime attributable risk (LAR) of cancer incidence/mortality due to a single diagnostic investigation in a 1-year cohort of consecutive chest CT for suspected pulmonary embolism (PE). Material and Methods: A 1-year cohort of consecutive chest CT for suspected PE using a standard scan protocol was analyzed retrospectively (691 patients, 352 men, 339 women). Normalized patient-specific estimations of the radiation doses received by individual organs were correlated with age- and sex-specific mean predicted cancer incidence and age- and sex-specific predicted cancer mortality based on the BEIR VII results. Additional correlation was provided for natural occurring risks. Results: LAR of cancer incidence/mortality following one chest CT was calculated for cancer of the stomach, colon, liver, lung, breast, uterus, ovaries, bladder, thyroid, and for leukemia. LAR remains very low for all age and sex categories, being highest for cancer of the lungs and breasts in 20-year-old women (0.61% and 0.4%, respectively). Summation of all cancer sites analyzed raised the cumulative relative LAR up to 2.76% in 20-year-old women. Conclusion: Using the method presented in this work, LAR of cancer incidence and cancer mortality for a single chest CT for PE seems very low for all age groups and both sexes, but being highest for young patients. Hence the risk for radiation-induced organ cancers must be outweighed with the potential benefit or a treatment and the potential risks of a missed and therefore untreated PE

  3. Computed tomography for pulmonary embolism - Assessment of a 1-year cohort and estimated cancer risk associated with diagnostic irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Niemann, T. [Dept. of Radiology and Nuclear Medicine, Univ. Hospital, Basel (Switzerland); Dept. of Thoracic Imaging, Univ. Lille Nord de France, Hospital Calmette, Lille (France)], e-mail: tilo.niemann@usb.ch; Zbinden, I.; Bremerich, J.; Bongartz, G. [Dept. of Radiology and Nuclear Medicine, Univ. Hospital, Basel (Switzerland); Roser, H. W. [Dept. of Radiology and Nuclear Medicine, Univ. Hospital, Radiological Physics, Basel (Switzerland); Remy-Jardin, M. [Dept. of Thoracic Imaging, Univ. Lille Nord de France, Hospital Calmette, Lille (France)

    2013-09-15

    Background: The principal concern of any radiation exposure in computed tomography (CT) is the induction of stochastic risks of developing a radiation-induced cancer. The results given in this manuscript will allow to (re-)calculate yield of chest CT. Purpose: To demonstrate a method to evaluate the lifetime attributable risk (LAR) of cancer incidence/mortality due to a single diagnostic investigation in a 1-year cohort of consecutive chest CT for suspected pulmonary embolism (PE). Material and Methods: A 1-year cohort of consecutive chest CT for suspected PE using a standard scan protocol was analyzed retrospectively (691 patients, 352 men, 339 women). Normalized patient-specific estimations of the radiation doses received by individual organs were correlated with age- and sex-specific mean predicted cancer incidence and age- and sex-specific predicted cancer mortality based on the BEIR VII results. Additional correlation was provided for natural occurring risks. Results: LAR of cancer incidence/mortality following one chest CT was calculated for cancer of the stomach, colon, liver, lung, breast, uterus, ovaries, bladder, thyroid, and for leukemia. LAR remains very low for all age and sex categories, being highest for cancer of the lungs and breasts in 20-year-old women (0.61% and 0.4%, respectively). Summation of all cancer sites analyzed raised the cumulative relative LAR up to 2.76% in 20-year-old women. Conclusion: Using the method presented in this work, LAR of cancer incidence and cancer mortality for a single chest CT for PE seems very low for all age groups and both sexes, but being highest for young patients. Hence the risk for radiation-induced organ cancers must be outweighed with the potential benefit or a treatment and the potential risks of a missed and therefore untreated PE.

  4. Analysis of competing risk parameters in irradiated prostate cancer patients

    International Nuclear Information System (INIS)

    Mayer, R.; Mayer, E.; Langsenlehner, U.; Hackl, A.; Pummer, K.; Quehenberger, F.; Feigl, G.

    2003-01-01

    Purpose: Retrospective competing risk analysis of prognostic factors in definitive-irradiated prostate cancer patients. Patients and Methods: Data of 652 patients were analyzed according to three age subgroups ( 75 years; Table 1). Pre-RT PSA values (median 13.4 ng/ml) were available for 340 patients. Adjuvant hormone therapy (n = 261) consisted either of orchiectomy (n = 151) or LHRH agonist with/without antiandrogen therapy or, in the early years, diethystilbestrol. Neoadjuvant hormone therapy (n = 31) using LHRH agonists was given 6 months before and during radiotherapy. Results: Biochemical failure was observed in 69/.340 patients, 5 years after biochemical failure, 64.9% of them also had failed clinically. The cumulative incidence of local failure (LF) and distant metastases (DM) was 9.4% and 37.2%, respectively; LF and DM at the same time were seen in 18.2%. On multivariate analysis (Tables 2 and 3), advanced stage (relative risk [RR] 4.54), pre-RT PSA > 20 ng/ml (RR 2.79) and poorly differentiated tumors (RR 2.96) were significant predictors of biochemical failure. Advanced stage increased the risk of LF (RR 2.18), DM (RR 3.66), and prostate cancer death (PCD; RR 4.30). Hormone therapy decreased the risk of biochemical failure (RR 0.67), DM (RR 0.59), and PCD (RR 0.60) without reaching statistical significance. Median follow-up was 7.6 years. Conclusion: Risk of biochemical failure was predicted by pre-RT PSA, stage, and grade; in patients with biochemical failure, the cumulative incidence of death from intercurrent diseases and PCD was 25.0% and 29.2% after 5 years, respectively. The risk of DM and PCD was predicted by stage and grade. Higher age (> 75 years) decreased the relative risk of LF, DM, and PCD significantly. (orig.)

  5. Management of low (favourable)-risk prostate cancer.

    Science.gov (United States)

    Carter, H Ballentine

    2011-12-01

    What's known on the subject? and What does the study add? Most men who are diagnosed with favourable-risk prostate cancer undergo some form of active intervention, despite evidence that treatment will not improve health outcomes for many. The decision to undergo treatment after diagnosis is, in part, related to the inability to precisely determine the long-term risk of harm without treatment. Nevertheless, physicians should consider patient age, overall health, and preferences for living with cancer and the potential side effects of curative treatments, before recommending a management option. This is especially important for older men, given the high level of evidence that those with low-risk disease are unlikely to accrue any benefit from curative intervention. What is known on the subject: Over treatment of favourable-risk prostate cancer is common, especially among older men. What does the study add: A review of the natural history of favourable-risk prostate cancer in the context of choices for management of the disease. • The management of favourable-risk prostate cancer is controversial, and in the absence of controlled trials to inform best practice, choices are driven by personal beliefs with resultant wide variation in practice patterns. • Men with favourable-risk prostate cancer diagnosed today often undergo treatments that will not improve overall health outcomes. • A shared-decision approach for selecting optimal management of favourable-risk disease should account for patient age, overall health, and preferences for living with cancer and the potential side effects of curative treatments. © 2011 THE AUTHOR. BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.

  6. Fertility drugs, reproductive strategies and ovarian cancer risk.

    Science.gov (United States)

    Tomao, Federica; Lo Russo, Giuseppe; Spinelli, Gian Paolo; Stati, Valeria; Prete, Alessandra Anna; Prinzi, Natalie; Sinjari, Marsela; Vici, Patrizia; Papa, Anselmo; Chiotti, Maria Stefania; Benedetti Panici, Pierluigi; Tomao, Silverio

    2014-01-01

    Several adverse effects have been related to infertility treatments, such as cancer development. In particular, the relationship between infertility, reproductive strategies, and risk of gynecological cancers has aroused much interest in recent years. The evaluation of cancer risk among women treated for infertility is very complex, mainly because of many factors that can contribute to occurrence of cancer in these patients (including parity status). This article addresses the possible association between the use of fertility treatments and the risk of ovarian cancer, through a scrupulous search of the literature published thus far in this field. Our principal objective was to give more conclusive answers on the question whether the use of fertility drug significantly increases ovarian cancer risk. Our analysis focused on the different types of drugs and different treatment schedules used. This study provides additional insights regarding the long-term relationships between fertility drugs and risk of ovarian cancer.

  7. Racial/Ethnic Differences in Cancer Risk After Kidney Transplantation

    Science.gov (United States)

    Hall, EC; Segev, DL; Engels, EA

    2014-01-01

    Transplant recipients have elevated cancer risk, but it is unknown if cancer risk differs across race and ethnicity as in the general population. U.S. kidney recipients (N=87,895) in the Transplant Cancer Match Study between 1992 and 2008 were evaluated for racial/ethnic differences in risk for six common cancers after transplantation. Compared to white recipients, black recipients had lower incidence of non-Hodgkin lymphoma (NHL) (adjusted incidence rate ratio [aIRR] 0.60, pkidney (aIRR 2.09, pcancer (aIRR 2.14, pcancer (aIRR 0.72, p=0.05). Colorectal cancer incidence was similar across groups. Standardized incidence ratios (SIRs) measured the effect of transplantation on cancer risk and were similar for most cancers (p≥0.1). However, black and Hispanic recipients had larger increases in kidney cancer risk with transplantation (SIRs: 8.96 in blacks, 5.95 in Hispanics vs. 4.44 in whites), and only blacks had elevated prostate cancer risk following transplantation (SIR: 1.21). Racial/ethnic differences in cancer risk after transplantation mirror general population patterns, except for kidney and prostate cancers where differences reflect the effects of end-stage renal disease or transplantation. PMID:23331953

  8. Can Predictive Modeling Identify Head and Neck Oncology Patients at Risk for Readmission?

    Science.gov (United States)

    Manning, Amy M; Casper, Keith A; Peter, Kay St; Wilson, Keith M; Mark, Jonathan R; Collar, Ryan M

    2018-05-01

    Objective Unplanned readmission within 30 days is a contributor to health care costs in the United States. The use of predictive modeling during hospitalization to identify patients at risk for readmission offers a novel approach to quality improvement and cost reduction. Study Design Two-phase study including retrospective analysis of prospectively collected data followed by prospective longitudinal study. Setting Tertiary academic medical center. Subjects and Methods Prospectively collected data for patients undergoing surgical treatment for head and neck cancer from January 2013 to January 2015 were used to build predictive models for readmission within 30 days of discharge using logistic regression, classification and regression tree (CART) analysis, and random forests. One model (logistic regression) was then placed prospectively into the discharge workflow from March 2016 to May 2016 to determine the model's ability to predict which patients would be readmitted within 30 days. Results In total, 174 admissions had descriptive data. Thirty-two were excluded due to incomplete data. Logistic regression, CART, and random forest predictive models were constructed using the remaining 142 admissions. When applied to 106 consecutive prospective head and neck oncology patients at the time of discharge, the logistic regression model predicted readmissions with a specificity of 94%, a sensitivity of 47%, a negative predictive value of 90%, and a positive predictive value of 62% (odds ratio, 14.9; 95% confidence interval, 4.02-55.45). Conclusion Prospectively collected head and neck cancer databases can be used to develop predictive models that can accurately predict which patients will be readmitted. This offers valuable support for quality improvement initiatives and readmission-related cost reduction in head and neck cancer care.

  9. Urinary tract cancer and hereditary nonpolyposis colorectal cancer : Risks and screening options

    NARCIS (Netherlands)

    Sijmons, RH; Kiemeney, LALM; Witjes, JA; Vasen, HFA

    Purpose: We investigate the risk of the different types of urinary tract cancer in hereditary nonpolyposis colorectal cancer families and review screening options. Materials and Methods: We retrospectively calculated the relative and cumulative risks of developing urinary tract cancer by comparing

  10. Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

    Science.gov (United States)

    Tut, Thein Ga

    Colorectal cancer (CRC) is the third most common cancer in the world. Australia, New Zealand, Canada, the United States, and parts of Europe have the highest incidence rates of CRC. China, India, South America and parts of Africa have the lowest risk of CRC. CRC is the second most common cancer in both sexes in Australia. Even though the death rates from CRC involving the colon have diminished, those arising from the rectum have revealed no improvement. The greatest obstacle in attaining a complete surgical resection of large rectal cancers is the close anatomical relation to surrounding structures, as opposed to the free serosal surfaces enfolding the colon. To assist complete resection, pre-operative radiotherapy (DXT) can be applied, but the efficacy of ionising radiation (IR) is extremely variable between individual tumours. Reliable predictive marker/s that enable patient stratification in the application of this otherwise toxic therapy is still not available. Current therapeutic management of rectal cancer can be improved with the availability of better predictive and prognostic biomarkers. Proteins such as Plk1, gammaH2AX and MMR proteins (MSH2, MSH6, MLH1 and PMS2), involved in DNA damage response (DDR) pathway may be possible biomarkers for radiation response prediction and prognostication of rectal cancer. Serine/threonine protein kinase Plk1 is overexpressed in most of cancers including CRC. Plk1 functional activity is essential in the restoration of DNA damage following IR, which causes DNA double strand break (DSB). The earliest manifestation of this reparative process is histone H2AX phosphorylation at serine 139, leading to gammaH2AX. Colorectal normal mucosa showed the lowest level of gammaH2AX with gradually increasing levels in early adenoma and then in advanced malignant colorectal tissues, leading to the possibility that gammaH2AX may be a prospective biomarker in rectal cancer management. There are numerous publications regarding DNA mismatch

  11. Cancer risk among atomic bomb survivors

    International Nuclear Information System (INIS)

    Schull, W.J.

    1992-01-01

    Continued mortality surveillance and incidence studies have revealed the risk of cancer among the survivors of the atomic bombings of Hiroshima and Nagasaki to increase with increasing dose. Among the sites where the frequency of cancer can be clearly shown to be dose-related are the following: female breast, colon, esophagus, lung, ovary, stomach, thyroid, urinary bladder and leukemia. Although the evidence is less compelling, cancers of the liver, salivary glands, and skin as well as multiple myeloma appear increased too. This increase generally manifests itself when the survivors reach those ages where the natural incidence of cancer begins to rise. Risk is, however, related to the age of the individual at the time of the bombing; the highest risks are associated with individuals who were exposed in the first two decades of life. Current evidence suggests these higher risks decline with increasing time since exposure

  12. Discrepancies between estimated and perceived risk of cancer among individuals with hereditary nonpolyposis colorectal cancer

    DEFF Research Database (Denmark)

    Domanska, K; Nilbert, Mef; Soller, M

    2007-01-01

    to individual characteristics. A perceived risk of colorectal cancer above 60% was reported by 22/45 individuals, and only one out of five mutation carriers reported a perceived risk > 80%. Female mutation carriers, individuals below age 50, and individuals who received their oncogenetic counseling within 1......Communicating cancer risk and recommending adequate control programs is central for genetic counseling. Individuals affected by hereditary nonpolyposis colorectal cancer (HNPCC) are at about 80% life-time risk of colorectal cancer and for female carriers 40-60% risk of endometrial cancer and 10...... year prior to the study reported higher, albeit not significantly, perceived risks of colorectal cancer. Higher perceived risks were also reported by individuals who had lost a parent to HNPCC-related cancer at early age, whereas individuals with a personal history of cancer did not report a higher...

  13. Discrepancies between estimated and perceived risk of cancer among individuals with hereditary nonpolyposis colorectal cancer

    DEFF Research Database (Denmark)

    Domanska, K; Nilbert, Mef; Soller, M

    2007-01-01

    Communicating cancer risk and recommending adequate control programs is central for genetic counseling. Individuals affected by hereditary nonpolyposis colorectal cancer (HNPCC) are at about 80% life-time risk of colorectal cancer and for female carriers 40-60% risk of endometrial cancer and 10...... to individual characteristics. A perceived risk of colorectal cancer above 60% was reported by 22/45 individuals, and only one out of five mutation carriers reported a perceived risk > 80%. Female mutation carriers, individuals below age 50, and individuals who received their oncogenetic counseling within 1...... year prior to the study reported higher, albeit not significantly, perceived risks of colorectal cancer. Higher perceived risks were also reported by individuals who had lost a parent to HNPCC-related cancer at early age, whereas individuals with a personal history of cancer did not report a higher...

  14. Risk of ovarian cancer in women with first-degree relatives with cancer

    DEFF Research Database (Denmark)

    Soegaard, Marie; Frederiksen, Kirsten; Jensen, Allan

    2009-01-01

    OBJECTIVE: To assess the risk of ovarian cancer in women with first-degree relatives with cancer at one of the four most frequent hereditary sites based on validated cancer diagnoses and to examine the association according to age at diagnosis of ovarian cancer and histology. DESIGN: Case......-control study. SETTING AND POPULATION: First-degree relatives of 554 women with invasive epithelial ovarian cancer and 1,564 controls were included. METHODS: Analyses were performed using multiple logistic regression models. RESULTS: Ovarian cancer in a first-degree relative was significantly associated...... with increased risk of ovarian cancer (OR, 2.4; 95% CI, 1.4-4.1 (mother or sister)). Ovarian cancer in a first-degree relative appeared to be a stronger risk factor for early-onset (cancer than late-onset (OR, 5.3; 95% CI, 2.0-14.1 vs. OR, 1.8; 95% CI, 1.0-3.4). The positive association...

  15. Immunosuppression and risk of cervical cancer

    DEFF Research Database (Denmark)

    Dugué, Pierre-Antoine; Rebolj, Matejka; Garred, Peter

    2013-01-01

    -stage renal disease seem to be at an increased risk of cervical cancer. A higher risk of cervical precancerous lesions was found in patients with some autoimmune diseases; particularly if treated with immunosuppressants. Among behavioral factors weakening the immune system, smoking appeared to strongly...... increase the risk of cervical cancer, while poor diet only moderately increased the risk. It is difficult to determine whether sexually transmitted infections other than human papillomavirus infection are independent risk factors. Identifying those groups of women likely to fail in clearing persistent...

  16. Age-dependent associations between androgenetic alopecia and prostate cancer risk.

    Science.gov (United States)

    Muller, David C; Giles, Graham G; Sinclair, Rod; Hopper, John L; English, Dallas R; Severi, Gianluca

    2013-02-01

    Both prostate cancer and androgenetic alopecia are strongly age-related conditions that are considered to be androgen dependent, but studies of the relationship between them have yielded inconsistent results. We aimed to assess whether androgenetic alopecia at ages 20 and 40 years are associated with risk of prostate cancer. At a follow-up of the Melbourne Collaborative Cohort Study, men were asked to assess their hair pattern at ages 20 and 40 years relative to eight categories in showcards. Cases were men notified to the Victorian Cancer Registry with prostate cancer diagnosed between cohort enrollment (1990-1994) and follow-up attendance (2003-2009). Flexible parametric survival models were used to estimate age-varying HRs and predicted cumulative probabilities of prostate cancer by androgenetic alopecia categories. Of 9,448 men that attended follow-up and provided data on androgenetic alopecia, we identified 476 prostate cancer cases during a median follow-up of 11 years four months. Cumulative probability of prostate cancer was greater at all ages up to 76 years, for men with vertex versus no androgenetic alopecia at age of 40 years. At age of 76 years, the estimated probabilities converged to 0.15. Vertex androgenetic alopecia at 40 years was also associated with younger age of diagnosis for prostate cancer cases. Vertex androgenetic alopecia at age of 40 years might be a marker of increased risk of early-onset prostate cancer. If confirmed, these results suggest that the apparently conflicting findings of previous studies might be explained by failure to adequately model the age-varying nature of the association between androgenetic alopecia and prostate cancer.

  17. Clinical utility of the percentage of positive prostate biopsies in predicting prostate cancer-specific and overall survival after radiotherapy for patients with localized prostate cancer

    International Nuclear Information System (INIS)

    D'Amico, Anthony V.; Keshaviah, Aparna; Manola, Judith; Cote, Kerri; Loffredo, Marian; Iskrzytzky, Olga; Renshaw, Andrew A.

    2002-01-01

    Purpose: To determine whether the percentage of positive prostate biopsies provides clinically relevant information to a previously established risk stratification system with respect to the end points of prostate cancer-specific survival (PCSS) and overall survival after radiotherapy for patients with clinically localized prostate cancer. Methods and Materials: A Cox regression multivariable analysis was used to evaluate the ability of the percentage of positive prostate biopsies to predict PCSS and overall survival for 381 men who underwent radiotherapy for localized prostate cancer during the prostate-specific antigen era. Results: At a median follow-up of 4.3 years (range 0.8-13.3), the presence of ≤50% positive biopsies vs. >50% positive biopsies provided a clinically relevant stratification of the 7-year estimates of PCSS (100% vs. 57%, p=0.004) in intermediate-risk patients. Moreover, all patients could be stratified into a minimal or high-risk cohort on the basis of the 10-year estimates of PCSS (100% vs. 55%, p 50%] intermediate-risk + high-risk) cohort for prostate cancer-specific death after conventional dose radiotherapy. Additional follow-up and independent validation are needed to confirm these findings

  18. Risk of thyroid cancer, brain cancer, and non-Hodgkin lymphoma after adult leukemia

    DEFF Research Database (Denmark)

    Nielsen, Sune F; Bojesen, Stig E; Birgens, Henrik S

    2011-01-01

    .2-3.1) for brain cancer, and 3.3 (95% CI, 2.5-4.4) for NHL. Corresponding hazard ratios after childhood leukemia were 10.4 (95% CI, 0.4-223) for thyroid cancer, 7.2 (95% CI, 2.0-26) for brain cancer, and 6.5 (95% CI, 0.4-110) for NHL. Patients with adult leukemia have excess risk of thyroid cancer, brain cancer......Patients with childhood leukemia surviving into adulthood have elevated risk of developing thyroid cancer, brain cancer, and non-Hodgkin lymphoma (NHL); these risks cannot automatically be extrapolated to patients surviving adult leukemia. We tested whether survivors of adult leukemia...... are at increased risk of developing thyroid cancer, brain cancer, and NHL. We included the entire adult Danish population (14 years of age or older), in a 28-year follow-up period from 1980 through 2007, composed of 6 542 639 persons; during this period, 18 834 developed adult leukemia, 4561 developed thyroid...

  19. Establishment of a 12-gene expression signature to predict colon cancer prognosis

    Directory of Open Access Journals (Sweden)

    Dalong Sun

    2018-06-01

    Full Text Available A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA. The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS: Kaplan Meier (KM Log Rank p = 0.0034; overall survival (OS: KM Log Rank p = 0.0336 in GSE17538. For patients with proficient mismatch repair system (pMMR in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS: KM Log Rank p = 0.022. Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003. After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01 and stage II & III (Log Rank p = 0.017 in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041. Among stage II/III pMMR patients

  20. Does risk for ovarian malignancy algorithm excel human epididymis protein 4 and ca125 in predicting epithelial ovarian cancer: A meta-analysis

    International Nuclear Information System (INIS)

    Li, Fake; Tie, Ruxiu; Chang, Kai; Wang, Feng; Deng, Shaoli; Lu, Weiping; Yu, Lili; Chen, Ming

    2012-01-01

    Risk for Ovarian Malignancy Algorithm (ROMA) and Human epididymis protein 4 (HE4) appear to be promising predictors for epithelial ovarian cancer (EOC), however, conflicting results exist in the diagnostic performance comparison among ROMA, HE4 and CA125. Remote databases (MEDLINE/PUBMED, EMBASE, Web of Science, Google Scholar, the Cochrane Library and ClinicalTrials.gov) and full texts bibliography were searched for relevant abstracts. All studies included were closely assessed with the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2). EOC predictive value of ROMA was systematically evaluated, and comparison among the predictive performances of ROMA, HE4 and CA125 were conducted within the same population. Sensitivity, specificity, DOR (diagnostic odds ratio), LR ± (positive and negative likelihood ratio) and AUC (area under receiver operating characteristic-curve) were summarized with a bivariate model. Subgroup analysis and sensitivity analysis were used to explore the heterogeneity. Data of 7792 tests were retrieved from 11 studies. The overall estimates of ROMA for EOC predicting were: sensitivity (0.89, 95% CI 0.84-0.93), specificity (0.83, 95% CI 0.77-0.88), and AUC (0.93, 95% CI 0.90-0.95). Comparison of EOC predictive value between HE4 and CA125 found, specificity: HE4 (0.93, 95% CI 0.87-0.96) > CA125 (0.84, 95% CI 0.76-0.90); AUC: CA125 (0.88, 95% CI 0.85-0.91) > HE4 (0.82, 95% CI 0.78-0.85). Comparison of OC predictive value between HE4 and CA125 found, AUC: CA125 (0.89, 95% CI 0.85-0.91) > HE4 (0.79, 95% CI 0.76-0.83). Comparison among the three tests for EOC prediction found, sensitivity: ROMA (0.86, 95%CI 0.81-0.91) > HE4 (0.80, 95% CI 0.73-0.85); specificity: HE4 (0.94, 95% CI 0.90-0.96) > ROMA (0.84, 95% CI 0.79-0.88) > CA125 (0.78, 95%CI 0.73-0.83). ROMA is helpful for distinguishing epithelial ovarian cancer from benign pelvic mass. HE4 is not better than CA125 either for EOC or OC prediction. ROMA is promising predictors of

  1. Canadian Cancer Risk Management Model: evaluation of cancer control.

    Science.gov (United States)

    Evans, William K; Wolfson, Michael C; Flanagan, William M; Shin, Janey; Goffin, John; Miller, Anthony B; Asakawa, Keiko; Earle, Craig; Mittmann, Nicole; Fairclough, Lee; Oderkirk, Jillian; Finès, Philippe; Gribble, Stephen; Hoch, Jeffrey; Hicks, Chantal; Omariba, D Walter R; Ng, Edward

    2013-04-01

    The aim of this study was to develop a decision support tool to assess the potential benefits and costs of new healthcare interventions. The Canadian Partnership Against Cancer (CPAC) commissioned the development of a Cancer Risk Management Model (CRMM)--a computer microsimulation model that simulates individual lives one at a time, from birth to death, taking account of Canadian demographic and labor force characteristics, risk factor exposures, and health histories. Information from all the simulated lives is combined to produce aggregate measures of health outcomes for the population or for particular subpopulations. The CRMM can project the population health and economic impacts of cancer control programs in Canada and the impacts of major risk factors, cancer prevention, and screening programs and new cancer treatments on population health and costs to the healthcare system. It estimates both the direct costs of medical care, as well as lost earnings and impacts on tax revenues. The lung and colorectal modules are available through the CPAC Web site (www.cancerview.ca/cancerrriskmanagement) to registered users where structured scenarios can be explored for their projected impacts. Advanced users will be able to specify new scenarios or change existing modules by varying input parameters or by accessing open source code. Model development is now being extended to cervical and breast cancers.

  2. Hormonal contraception and risk of cancer

    DEFF Research Database (Denmark)

    Cibula, D.; Gompel, A.; Mueck, A.O.

    2011-01-01

    Fear from increased cancer risk is one of the most significant reasons for low acceptance of reliable contraceptive methods and low compliance.......Fear from increased cancer risk is one of the most significant reasons for low acceptance of reliable contraceptive methods and low compliance....

  3. Hormonal contraception and risk of cancer

    DEFF Research Database (Denmark)

    Cibula, D; Gompel, A; Mueck, A O

    2010-01-01

    Fear from increased cancer risk is one of the most significant reasons for low acceptance of reliable contraceptive methods and low compliance.......Fear from increased cancer risk is one of the most significant reasons for low acceptance of reliable contraceptive methods and low compliance....

  4. Breast cancer epidemiology and risk factors

    International Nuclear Information System (INIS)

    Broeders, M. J. M.; Verbeek, A. L. M.

    1997-01-01

    Breast cancer is the most common malignancy among women in the Western society. Over the past decades it has become apparent that breast cancer incidence rates are increasing steadily, whereas the mortality rates for breast cancer have remained relatively constant. Information through the media on this rising number of cases has increased breast health awareness but has also introduced anxiety in the female population. This combination of factors has made the need for prevention of breast cancer an urgent matter. Breast cancer does not seem to be a single disease entity. A specific etiologic factor may therefore have more influence on one form may therefore have more influence on one form of breast cancer than another. So far though, as shown in their summary of current knowledge on established and dubious risk factors, no risk factors have been identified that can explain a major part of the incidence. Efforts to identify other ways for primary prevention have also been discouraging, even though breast cancer is one of the most investigated tumours world-wide. Thus, at this point i time, the most important strategy to reduce breast cancer mortality is early detection through individual counselling and organised breast screening programs. The recent isolation of breast cancer susceptibility genes may introduce new ways to reduce the risk of breast cancer in a small subset of women

  5. Helicobacter pylori Diversity and Gastric Cancer Risk

    Directory of Open Access Journals (Sweden)

    Timothy L. Cover

    2016-03-01

    Full Text Available Gastric cancer is a leading cause of cancer-related death worldwide. Helicobacter pylori infection is the strongest known risk factor for this malignancy. An important goal is to identify H. pylori-infected persons at high risk for gastric cancer, so that these individuals can be targeted for therapeutic intervention. H. pylori exhibits a high level of intraspecies genetic diversity, and over the past two decades, many studies have endeavored to identify strain-specific features of H. pylori that are linked to development of gastric cancer. One of the most prominent differences among H. pylori strains is the presence or absence of a 40-kb chromosomal region known as the cag pathogenicity island (PAI. Current evidence suggests that the risk of gastric cancer is very low among persons harboring H. pylori strains that lack the cag PAI. Among persons harboring strains that contain the cag PAI, the risk of gastric cancer is shaped by a complex interplay among multiple strain-specific bacterial factors as well as host factors. This review discusses the strain-specific properties of H. pylori that correlate with increased gastric cancer risk, focusing in particular on secreted proteins and surface-exposed proteins, and describes evidence from cell culture and animal models linking these factors to gastric cancer pathogenesis. Strain-specific features of H. pylori that may account for geographic variation in gastric cancer incidence are also discussed.

  6. Increased colon cancer risk after severe Salmonella infection.

    Directory of Open Access Journals (Sweden)

    Lapo Mughini-Gras

    Full Text Available Colon cancer constitutes one of the most frequent malignancies. Previous studies showed that Salmonella manipulates host cell signaling pathways and that Salmonella Typhimurium infection facilitates colon cancer development in genetically predisposed mice. This epidemiological study examined whether severe Salmonella infection, usually acquired from contaminated food, is associated with increased colon cancer risk in humans.We performed a nationwide registry-based study to assess colon cancer risk after diagnosed Salmonella infection. National infectious disease surveillance records (1999-2015 for Dutch residents aged ≥20 years when diagnosed with salmonellosis (n = 14,264 were linked to the Netherlands Cancer Registry. Salmonella-infected patients were laboratory-confirmed under medical consultation after 1-2 weeks of illness. These datasets also contained information on Salmonella serovar and type of infection. Colon cancer risk (overall and per colon subsite among patients with a diagnosed Salmonella infection was compared with expected colon cancer risk in the general population. Data from the nationwide registry of histo- and cytopathology (PALGA and Statistics Netherlands (CBS allowed assessing potential effects of age, gender, latency, socioeconomic status, genetic predisposition, inflammatory bowel disease (IBD, and tumor features. We found that compared to the general population, colon cancer risk was significantly increased (standardized incidence ratio [SIR] 1.54; 95%CI 1.09-2.10 among patients with Salmonella infection diagnosed <60 years of age. Such increased risk concerned specifically the ascending/transverse colon (SIR 2.12; 95%CI 1.38-3.09 after S. Enteritidis infection (SIR 2.97; 95%CI 1.73-4.76. Salmonellosis occurred more frequently among colon cancer patients with pre-infectious IBD, a known risk factor for colon cancer. Colon tumors of patients with a history of Salmonella infection were mostly of low grade

  7. Familial Risk and Heritability of Colorectal Cancer in the Nordic Twin Study of Cancer

    DEFF Research Database (Denmark)

    Graff, Rebecca E; Möller, Sören; Passarelli, Michael N

    2017-01-01

    included 39,990 monozygotic and 61,443 same-sex dizygotic twins from the Nordic Twin Study of Cancer. We compared each cancer's risk in twins of affected co-twins relative to the cohort risk (familial risk ratio; FRR). We then estimated the proportion of variation in risk that could be attributed......BACKGROUND & AIMS: We analyzed data from twins to determine how much the familial risk of colorectal cancer can be attributed to genetic factors vs environment. We also examined whether heritability is distinct for colon vs rectal cancer, given evidence of distinct etiologies. METHODS: Our data set...... to genetic factors (heritability). RESULTS: From earliest registration in 1943 through 2010, 1861 individuals were diagnosed with colon cancer and 1268 with rectal cancer. Monozygotic twins of affected co-twins had an FRR for colorectal cancer of 3.1 (95% CI, 2.4-3.8) relative to the cohort risk. Dizygotic...

  8. Lay Awareness of the Relationship between Age and Cancer Risk.

    Science.gov (United States)

    Taber, Jennifer M; Klein, William M P; Suls, Jerry M; Ferrer, Rebecca A

    2017-04-01

    Cross-sectional studies suggest many people are unaware that cancer risk increases with age, but this misbelief has rarely been studied prospectively, nor are its moderators known. To assess whether people recognize that cancer risk increases with age and whether beliefs differ according to gender, education, smoking status, and family history of cancer. First, items from the cross-sectional Health Information National Trends Survey (n = 2069) were analyzed to examine the association of age and perceived cancer risk. Second, the prospective National Survey of Midlife Development in the United States (n = 3896) was used to assess whether perceived cancer risk changes over a decade. Third, beliefs about the age at which cancer occurs were analyzed using the US Awareness and Beliefs about Cancer survey (n = 1080). As a comparator, perceived risk of heart disease was also examined. Cross-sectionally, older age was associated with lower perceived cancer risk but higher perceived heart disease risk. Prospectively, perceived cancer risk remained stable, whereas perceived heart attack risk increased. Seventy percent of participants reported a belief that cancer is equally likely to affect people of any age. Across three surveys, women and former smokers/smokers who recently quit tended to misunderstand the relationship between age and cancer risk and also expressed relatively higher perceived cancer risk overall. Data from three national surveys indicated that people are unaware that age is a risk factor for cancer. Moreover, those who were least aware perceived the highest risk of cancer regardless of age.

  9. Breast cancer biomarkers predict weight loss after gastric bypass surgery

    Directory of Open Access Journals (Sweden)

    Sauter Edward R

    2012-01-01

    Full Text Available Abstract Background Obesity has long been associated with postmenopausal breast cancer risk and more recently with premenopausal breast cancer risk. We previously observed that nipple aspirate fluid (n levels of prostate specific antigen (PSA were associated with obesity. Serum (s levels of adiponectin are lower in women with higher body mass index (BMI and with breast cancer. We conducted a prospective study of obese women who underwent gastric bypass surgery to determine: 1 change in n- and s-adiponectin and nPSA after surgery and 2 if biomarker change is related to change in BMI. Samples (30-s, 28-n and BMI were obtained from women 0, 3, 6 and 12 months after surgery. Findings There was a significant increase after surgery in pre- but not postmenopausal women at all time points in s-adiponectin and at 3 and 6 months in n-adiponectin. Low n-PSA and high s-adiponectin values were highly correlated with decrease in BMI from baseline. Conclusions Adiponectin increases locally in the breast and systemically in premenopausal women after gastric bypass. s-adiponectin in pre- and nPSA in postmenopausal women correlated with greater weight loss. This study provides preliminary evidence for biologic markers to predict weight loss after gastric bypass surgery.

  10. Scoring system development for prediction of extravesical bladder cancer

    Directory of Open Access Journals (Sweden)

    Prelević Rade

    2014-01-01

    Full Text Available Background/Aim. Staging of bladder cancer is crucial for optimal management of the disease. However, clinical staging is not perfectly accurate. The aim of this study was to derive a simple scoring system in prediction of pathological advanced muscle-invasive bladder cancer (MIBC. Methods. Logistic regression and bootstrap methods were used to create an integer score for estimating the risk in prediction of pathological advanced MIBC using precystectomy clinicopathological data: demographic, initial transurethral resection (TUR [grade, stage, multiplicity of tumors, lymphovascular invasion (LVI], hydronephrosis, abdominal and pelvic CT radiography (size of the tumor, tumor base width, and pathological stage after radical cystectomy (RC. Advanced MIBC in surgical specimen was defined as pT3-4 tumor. Receiving operating characteristic (ROC curve quantified the area under curve (AUC as predictive accuracy. Clinical usefulness was assessed by using decision curve analysis. Results. This single-center retrospective study included 233 adult patients with BC undergoing RC at the Military Medical Academy, Belgrade. Organ confined disease was observed in 101 (43.3% patients, and 132 (56.7% had advanced MIBC. In multivariable analysis, 3 risk factors most strongly associated with advanced MIBC: grade of initial TUR [odds ratio (OR = 4.7], LVI (OR = 2, and hydronephrosis (OR = 3.9. The resultant total possible score ranged from 0 to 15, with the cut-off value of > 8 points, the AUC was 0.795, showing good discriminatory ability. The model showed excellent calibration. Decision curve analysis showed a net benefit across all threshold probabilities and clinical usefulness of the model. Conclusion. We developed a unique scoring system which could assist in predicting advanced MIBC in patients before RC. The scoring system showed good performance characteristics and introducing of such a tool into daily clinical decision-making may lead to more appropriate

  11. Identification of cancer risk and associated behaviour: implications for social marketing campaigns for cancer prevention.

    Science.gov (United States)

    Kippen, Rebecca; James, Erica; Ward, Bernadette; Buykx, Penny; Shamsullah, Ardel; Watson, Wendy; Chapman, Kathy

    2017-08-17

    Community misconception of what causes cancer is an important consideration when devising communication strategies around cancer prevention, while those initiating social marketing campaigns must decide whether to target the general population or to tailor messages for different audiences. This paper investigates the relationships between demographic characteristics, identification of selected cancer risk factors, and associated protective behaviours, to inform audience segmentation for cancer prevention social marketing. Data for this cross-sectional study (n = 3301) are derived from Cancer Council New South Wales' 2013 Cancer Prevention Survey. Descriptive statistics and logistic regression models were used to investigate the relationship between respondent demographic characteristics and identification of each of seven cancer risk factors; demographic characteristics and practice of the seven 'protective' behaviours associated with the seven cancer risk factors; and identification of cancer risk factors and practising the associated protective behaviours, controlling for demographic characteristics. More than 90% of respondents across demographic groups identified sun exposure and smoking cigarettes as moderate or large cancer risk factors. Around 80% identified passive smoking as a moderate/large risk factor, and 40-60% identified being overweight or obese, drinking alcohol, not eating enough vegetables and not eating enough fruit. Women and older respondents were more likely to identify most cancer risk factors as moderate/large, and to practise associated protective behaviours. Education was correlated with identification of smoking as a moderate/large cancer risk factor, and with four of the seven protective behaviours. Location (metropolitan/regional) and country of birth (Australia/other) were weak predictors of identification and of protective behaviours. Identification of a cancer risk factor as moderate/large was a significant predictor for five out

  12. Use of advanced treatment technologies among men at low risk of dying from prostate cancer.

    Science.gov (United States)

    Jacobs, Bruce L; Zhang, Yun; Schroeck, Florian R; Skolarus, Ted A; Wei, John T; Montie, James E; Gilbert, Scott M; Strope, Seth A; Dunn, Rodney L; Miller, David C; Hollenbeck, Brent K

    2013-06-26

    The use of advanced treatment technologies (ie, intensity-modulated radiotherapy [IMRT] and robotic prostatectomy) for prostate cancer is increasing. The extent to which these advanced treatment technologies have disseminated among patients at low risk of dying from prostate cancer is uncertain. To assess the use of advanced treatment technologies, compared with prior standards (ie, traditional external beam radiation treatment [EBRT] and open radical prostatectomy) and observation, among men with a low risk of dying from prostate cancer. Using Surveillance, Epidemiology, and End Results (SEER)-Medicare data, we identified a retrospective cohort of men diagnosed with prostate cancer between 2004 and 2009 who underwent IMRT (n = 23,633), EBRT (n = 3926), robotic prostatectomy (n = 5881), open radical prostatectomy (n = 6123), or observation (n = 16,384). Follow-up data were available through December 31, 2010. The use of advanced treatment technologies among men unlikely to die from prostate cancer, as assessed by low-risk disease (clinical stage ≤T2a, biopsy Gleason score ≤6, and prostate-specific antigen level ≤10 ng/mL), high risk of noncancer mortality (based on the predicted probability of death within 10 years in the absence of a cancer diagnosis), or both. In our cohort, the use of advanced treatment technologies increased from 32% (95% CI, 30%-33%) to 44% (95% CI, 43%-46%) among men with low-risk disease (P risk of noncancer mortality (P use of these advanced treatment technologies among men with both low-risk disease and high risk of noncancer mortality increased from 25% (95% CI, 23%-28%) to 34% (95% CI, 31%-37%) (P use of advanced treatment technologies for men unlikely to die from prostate cancer increased from 13% (95% CI, 12%-14%), or 129.2 per 1000 patients diagnosed with prostate cancer, to 24% (95% CI, 24%-25%), or 244.2 per 1000 patients diagnosed with prostate cancer (P risk disease, high risk of noncancer mortality, or both, the use of

  13. A non-synonymous polymorphism in IRS1 modifies risk of developing breast and ovarian cancers in BRCA1 and ovarian cancer in BRCA2 mutation carriers

    Science.gov (United States)

    Ding, Yuan C.; McGuffog, Lesley; Healey, Sue; Friedman, Eitan; Laitman, Yael; Shani-Shimon–Paluch; Kaufman, Bella; Liljegren, Annelie; Lindblom, Annika; Olsson, Håkan; Kristoffersson, Ulf; Stenmark-Askmalm, Marie; Melin, Beatrice; Domchek, Susan M.; Nathanson, Katherine L.; Rebbeck, Timothy R.; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Gronwald, Jacek; Huzarski, Tomasz; Cybulski, Cezary; Byrski, Tomasz; Osorio, Ana; Cajal, Teresa Ramóny; Stavropoulou, Alexandra V; Benítez, Javier; Hamann, Ute; Rookus, Matti; Aalfs, Cora M.; de Lange, Judith L.; Meijers-Heijboer, Hanne E.J.; Oosterwijk, Jan C.; van Asperen, Christi J.; García, Encarna B. Gómez; Hoogerbrugge, Nicoline; Jager, Agnes; van der Luijt, Rob B.; Easton, Douglas F.; Peock, Susan; Frost, Debra; Ellis, Steve D.; Platte, Radka; Fineberg, Elena; Evans, D. Gareth; Lalloo, Fiona; Izatt, Louise; Eeles, Ros; Adlard, Julian; Davidson, Rosemarie; Eccles, Diana; Cole, Trevor; Cook, Jackie; Brewer, Carole; Tischkowitz, Marc; Godwin, Andrew K.; Pathak, Harsh; Stoppa-Lyonnet, Dominique; Sinilnikova, Olga M.; Mazoyer, Sylvie; Barjhoux, Laure; Léoné, Mélanie; Gauthier-Villars, Marion; Caux-Moncoutier, Virginie; de Pauw, Antoine; Hardouin, Agnès; Berthet, Pascaline; Dreyfus, Hélène; Ferrer, Sandra Fert; Collonge-Rame, Marie-Agnès; Sokolowska, Johanna; Buys, Saundra; Daly, Mary; Miron, Alex; Terry, Mary Beth; Chung, Wendy; John, Esther M; Southey, Melissa; Goldgar, David; Singer, Christian F; Maria, Muy-Kheng Tea; Gschwantler-Kaulich, Daphne; Fink-Retter, Anneliese; Hansen, Thomas v. O.; Ejlertsen, Bent; Johannsson, Oskar Th.; Offit, Kenneth; Sarrel, Kara; Gaudet, Mia M.; Vijai, Joseph; Robson, Mark; Piedmonte, Marion R; Andrews, Lesley; Cohn, David; DeMars, Leslie R.; DiSilvestro, Paul; Rodriguez, Gustavo; Toland, Amanda Ewart; Montagna, Marco; Agata, Simona; Imyanitov, Evgeny; Isaacs, Claudine; Janavicius, Ramunas; Lazaro, Conxi; Blanco, Ignacio; Ramus, Susan J; Sucheston, Lara; Karlan, Beth Y.; Gross, Jenny; Ganz, Patricia A.; Beattie, Mary S.; Schmutzler, Rita K.; Wappenschmidt, Barbara; Meindl, Alfons; Arnold, Norbert; Niederacher, Dieter; Preisler-Adams, Sabine; Gadzicki, Dorotehea; Varon-Mateeva, Raymonda; Deissler, Helmut; Gehrig, Andrea; Sutter, Christian; Kast, Karin; Nevanlinna, Heli; Aittomäki, Kristiina; Simard, Jacques; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Tomlinson, Gail E.; Weitzel, Jeffrey; Garber, Judy E.; Olopade, Olufunmilayo I.; Rubinstein, Wendy S.; Tung, Nadine; Blum, Joanne L.; Narod, Steven A.; Brummel, Sean; Gillen, Daniel L.; Lindor, Noralane; Fredericksen, Zachary; Pankratz, Vernon S.; Couch, Fergus J.; Radice, Paolo; Peterlongo, Paolo; Greene, Mark H.; Loud, Jennifer T.; Mai, Phuong L.; Andrulis, Irene L.; Glendon, Gord; Ozcelik, Hilmi; Gerdes, Anne-Marie; Thomassen, Mads; Jensen, Uffe Birk; Skytte, Anne-Bine; Caligo, Maria A.; Lee, Andrew; Chenevix-Trench, Georgia; Antoniou, Antonis C; Neuhausen, Susan L.

    2012-01-01

    Background We previously reported significant associations between genetic variants in insulin receptor substrate 1 (IRS1) and breast cancer risk in women carrying BRCA1 mutations. The objectives of this study were to investigate whether the IRS1 variants modified ovarian cancer risk and were associated with breast cancer risk in a larger cohort of BRCA1 and BRCA2 mutation carriers. Methods IRS1 rs1801123, rs1330645, and rs1801278 were genotyped in samples from 36 centers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Data were analyzed by a retrospective cohort approach modeling the associations with breast and ovarian cancer risks simultaneously. Analyses were stratified by BRCA1 and BRCA2 status and mutation class in BRCA1 carriers. Results Rs1801278 (Gly972Arg) was associated with ovarian cancer risk for both BRCA1 [Hazard ratio (HR) = 1.43; 95% CI: 1.06–1.92; p = 0.019] and BRCA2 mutation carriers (HR=2.21; 95% CI: 1.39–3.52, p=0.0008). For BRCA1 mutation carriers, the breast cancer risk was higher in carriers with class 2 mutations than class 1 (mutations (class 2 HR=1.86, 95% CI: 1.28–2.70; class 1 HR=0.86, 95%CI:0.69–1.09; p-for difference=0.0006). Rs13306465 was associated with ovarian cancer risk in BRCA1 class 2 mutation carriers (HR = 2.42; p = 0.03). Conclusion The IRS1 Gly972Arg SNP, which affects insulin-like growth factor and insulin signaling, modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers and breast cancer risk in BRCA1 class 2 mutation carriers. Impact These findings may prove useful for risk prediction for breast and ovarian cancers in BRCA1 and BRCA2 mutation carriers. PMID:22729394

  14. Epidemiologic review of marijuana use and cancer risk.

    Science.gov (United States)

    Hashibe, Mia; Straif, Kurt; Tashkin, Donald P; Morgenstern, Hal; Greenland, Sander; Zhang, Zuo-Feng

    2005-04-01

    Marijuana is the most commonly used illegal drug in the United States and is considered by young adults to be the illicit drug with the least risk. On the other hand, marijuana smoke contains several of the same carcinogens and co-carcinogens as the tar from tobacco, raising concerns that smoking of marijuana may be a risk factor for tobacco-related cancers. We reviewed two cohort studies and 14 case-control studies with assessment of the association of marijuana use and cancer risk. In the cohort studies, increased risks of lung or colorectal cancer due to marijuana smoking were not observed, but increased risks of prostate and cervical cancers among non-tobacco smokers, as well as adult-onset glioma among tobacco and non-tobacco smokers, were observed. The 14 case-control studies included four studies on head and neck cancers, two studies on lung cancer, two studies on non-Hodgkin's lymphoma, one study on anal cancer, one study on penile cancer, and four studies on childhood cancers with assessment of parental exposures. Zhang and colleagues reported that marijuana use may increase risk of head and neck cancers in a hospital-based case-control study in the United States, with dose-response relations for both frequency and duration of use. However, Rosenblatt and co-workers reported no association between oral cancer and marijuana use in a population-based case-control study. An eightfold increase in risk among marijuana users was observed in a lung cancer study in Tunisia. However, there was no assessment of the dose response, and marijuana may have been mixed with tobacco. Parental marijuana use during gestation was associated with increased risks of childhood leukemia, astrocytoma, and rhabdomyosarcoma, but dose-response relations were not assessed. In summary, sufficient studies are not available to adequately evaluate marijuana impact on cancer risk. Several limitations of previous studies include possible underreporting where marijuana use is illegal, small

  15. Mitochondrial dysfunction and risk of cancer

    DEFF Research Database (Denmark)

    Lund, M; Melbye, M; Diaz, L J

    2015-01-01

    matrilineal relatives to a cohort member with a genetically confirmed maternally inherited mDNA mutation. Information on cancer was obtained by linkage to the Danish Cancer Register. Standardised incidence ratios (SIRs) were used to assess the relative risk of cancer. RESULTS: During 7334 person......-years of follow-up, 19 subjects developed a primary cancer. The corresponding SIR for any primary cancer was 1.06 (95% confidence interval 0.68-1.63). Subgroup analyses according to mutational subtype yielded similar results, for example, a SIR of 0.94 (95% CI 0.53 to 1.67) for the m.3243A>G maternally inherited...... mDNA mutation, cases=13. CONCLUSIONS: Patients with mitochondrial dysfunction do not appear to be at increased risk of cancer compared with the general population....

  16. Screening for breast cancer in a high-risk series

    International Nuclear Information System (INIS)

    Woodard, E.D.; Hempelmann, L.H.; Janus, J.; Logan, W.; Dean, P.

    1982-01-01

    A unique cohort of women at increased risk of breast cancer because of prior X-ray treatment of acute mastitis and their selected high-risk siblings were offered periodic breast cancer screening including physical examination of the breasts, mammography, and thermography. Twelve breast cancers were detected when fewer than four would have been expected based on age-specific breast cancer detection rates from the National Cancer institute/American Cancer Society Breast Cancer Demonstration Detection Projects. Mammograpy was positive in all cases but physical examination was positive in only three cases. Thermography was an unreliable indicator of disease. Given the concern over radiation-induced risk, use of low-dose technique and of criteria for participation that select women at high risk of breast cancer will maximize the benefit/risk ratio for mammography screening

  17. Lipoprotein metabolism indicators improve cardiovascular risk prediction.

    Directory of Open Access Journals (Sweden)

    Daniël B van Schalkwijk

    Full Text Available BACKGROUND: Cardiovascular disease risk increases when lipoprotein metabolism is dysfunctional. We have developed a computational model able to derive indicators of lipoprotein production, lipolysis, and uptake processes from a single lipoprotein profile measurement. This is the first study to investigate whether lipoprotein metabolism indicators can improve cardiovascular risk prediction and therapy management. METHODS AND RESULTS: We calculated lipoprotein metabolism indicators for 1981 subjects (145 cases, 1836 controls from the Framingham Heart Study offspring cohort in which NMR lipoprotein profiles were measured. We applied a statistical learning algorithm using a support vector machine to select conventional risk factors and lipoprotein metabolism indicators that contributed to predicting risk for general cardiovascular disease. Risk prediction was quantified by the change in the Area-Under-the-ROC-Curve (ΔAUC and by risk reclassification (Net Reclassification Improvement (NRI and Integrated Discrimination Improvement (IDI. Two VLDL lipoprotein metabolism indicators (VLDLE and VLDLH improved cardiovascular risk prediction. We added these indicators to a multivariate model with the best performing conventional risk markers. Our method significantly improved both CVD prediction and risk reclassification. CONCLUSIONS: Two calculated VLDL metabolism indicators significantly improved cardiovascular risk prediction. These indicators may help to reduce prescription of unnecessary cholesterol-lowering medication, reducing costs and possible side-effects. For clinical application, further validation is required.

  18. Mammographic Density Phenotypes and Risk of Breast Cancer: A Meta-analysis

    Science.gov (United States)

    Graff, Rebecca E.; Ursin, Giske; dos Santos Silva, Isabel; McCormack, Valerie; Baglietto, Laura; Vachon, Celine; Bakker, Marije F.; Giles, Graham G.; Chia, Kee Seng; Czene, Kamila; Eriksson, Louise; Hall, Per; Hartman, Mikael; Warren, Ruth M. L.; Hislop, Greg; Chiarelli, Anna M.; Hopper, John L.; Krishnan, Kavitha; Li, Jingmei; Li, Qing; Pagano, Ian; Rosner, Bernard A.; Wong, Chia Siong; Scott, Christopher; Stone, Jennifer; Maskarinec, Gertraud; Boyd, Norman F.; van Gils, Carla H.

    2014-01-01

    Background Fibroglandular breast tissue appears dense on mammogram, whereas fat appears nondense. It is unclear whether absolute or percentage dense area more strongly predicts breast cancer risk and whether absolute nondense area is independently associated with risk. Methods We conducted a meta-analysis of 13 case–control studies providing results from logistic regressions for associations between one standard deviation (SD) increments in mammographic density phenotypes and breast cancer risk. We used random-effects models to calculate pooled odds ratios and 95% confidence intervals (CIs). All tests were two-sided with P less than .05 considered to be statistically significant. Results Among premenopausal women (n = 1776 case patients; n = 2834 control subjects), summary odds ratios were 1.37 (95% CI = 1.29 to 1.47) for absolute dense area, 0.78 (95% CI = 0.71 to 0.86) for absolute nondense area, and 1.52 (95% CI = 1.39 to 1.66) for percentage dense area when pooling estimates adjusted for age, body mass index, and parity. Corresponding odds ratios among postmenopausal women (n = 6643 case patients; n = 11187 control subjects) were 1.38 (95% CI = 1.31 to 1.44), 0.79 (95% CI = 0.73 to 0.85), and 1.53 (95% CI = 1.44 to 1.64). After additional adjustment for absolute dense area, associations between absolute nondense area and breast cancer became attenuated or null in several studies and summary odds ratios became 0.82 (95% CI = 0.71 to 0.94; P heterogeneity = .02) for premenopausal and 0.85 (95% CI = 0.75 to 0.96; P heterogeneity women. Conclusions The results suggest that percentage dense area is a stronger breast cancer risk factor than absolute dense area. Absolute nondense area was inversely associated with breast cancer risk, but it is unclear whether the association is independent of absolute dense area. PMID:24816206

  19. Epidemiology of Lung Cancer.

    Science.gov (United States)

    Schwartz, Ann G; Cote, Michele L

    2016-01-01

    Lung cancer continues to be one of the most common causes of cancer death despite understanding the major cause of the disease: cigarette smoking. Smoking increases lung cancer risk 5- to 10-fold with a clear dose-response relationship. Exposure to environmental tobacco smoke among nonsmokers increases lung cancer risk about 20%. Risks for marijuana and hookah use, and the new e-cigarettes, are yet to be consistently defined and will be important areas for continued research as use of these products increases. Other known environmental risk factors include exposures to radon, asbestos, diesel, and ionizing radiation. Host factors have also been associated with lung cancer risk, including family history of lung cancer, history of chronic obstructive pulmonary disease and infections. Studies to identify genes associated with lung cancer susceptibility have consistently identified chromosomal regions on 15q25, 6p21 and 5p15 associated with lung cancer risk. Risk prediction models for lung cancer typically include age, sex, cigarette smoking intensity and/or duration, medical history, and occupational exposures, however there is not yet a risk prediction model currently recommended for general use. As lung cancer screening becomes more widespread, a validated model will be needed to better define risk groups to inform screening guidelines.

  20. Antioxidant vitamins and cancer risk: is oxidative damage to DNA a relevant biomarker?

    DEFF Research Database (Denmark)

    Loft, Steffen; Møller, Peter; Cooke, Marcus S

    2008-01-01

    -dihydroguanine (8-oxodG) are increasingly being regarded as reliable biomarkers of oxidative stress and they may have a predictive value of cancer risk, although this needs to be established independently in several cohort studies. A survey of intervention studies of the ingestion of antioxidant-containing foods...

  1. Identification and Validation of a New Set of Five Genes for Prediction of Risk in Early Breast Cancer

    Directory of Open Access Journals (Sweden)

    Giorgio Mustacchi

    2013-05-01

    Full Text Available Molecular tests predicting the outcome of breast cancer patients based on gene expression levels can be used to assist in making treatment decisions after consideration of conventional markers. In this study we identified a subset of 20 mRNA differentially regulated in breast cancer analyzing several publicly available array gene expression data using R/Bioconductor package. Using RTqPCR we evaluate 261 consecutive invasive breast cancer cases not selected for age, adjuvant treatment, nodal and estrogen receptor status from paraffin embedded sections. The biological samples dataset was split into a training (137 cases and a validation set (124 cases. The gene signature was developed on the training set and a multivariate stepwise Cox analysis selected five genes independently associated with DFS: FGF18 (HR = 1.13, p = 0.05, BCL2 (HR = 0.57, p = 0.001, PRC1 (HR = 1.51, p = 0.001, MMP9 (HR = 1.11, p = 0.08, SERF1a (HR = 0.83, p = 0.007. These five genes were combined into a linear score (signature weighted according to the coefficients of the Cox model, as: 0.125FGF18 − 0.560BCL2 + 0.409PRC1 + 0.104MMP9 − 0.188SERF1A (HR = 2.7, 95% CI = 1.9–4.0, p < 0.001. The signature was then evaluated on the validation set assessing the discrimination ability by a Kaplan Meier analysis, using the same cut offs classifying patients at low, intermediate or high risk of disease relapse as defined on the training set (p < 0.001. Our signature, after a further clinical validation, could be proposed as prognostic signature for disease free survival in breast cancer patients where the indication for adjuvant chemotherapy added to endocrine treatment is uncertain.

  2. Risk perception after genetic counseling in patients with increased risk of cancer

    Directory of Open Access Journals (Sweden)

    Rantala Johanna

    2009-08-01

    Full Text Available Abstract Background Counselees are more aware of genetics and seek information, reassurance, screening and genetic testing. Risk counseling is a key component of genetic counseling process helping patients to achieve a realistic view for their own personal risk and therefore adapt to the medical, psychological and familial implications of disease and to encourage the patient to make informed choices 12. The aim of this study was to conceptualize risk perception and anxiety about cancer in individuals attending to genetic counseling. Methods The questionnaire study measured risk perception and anxiety about cancer at three time points: before and one week after initial genetic counseling and one year after completed genetic investigations. Eligibility criteria were designed to include only index patients without a previous genetic consultation in the family. A total of 215 individuals were included. Data was collected during three years period. Results Before genetic counseling all of the unaffected participants subjectively estimated their risk as higher than their objective risk. Participants with a similar risk as the population overestimated their risk most. All risk groups estimated the risk for children's/siblings to be lower than their own. The benefits of preventive surveillance program were well understood among unaffected participants. The difference in subjective risk perception before and directly after genetic counseling was statistically significantly lower in all risk groups. Difference in risk perception for children as well as for population was also statistically significant. Experienced anxiety about developing cancer in the unaffected subjects was lower after genetic counseling compared to baseline in all groups. Anxiety about cancer had clear correlation to perceived risk of cancer before and one year after genetic investigations. The affected participants overestimated their children's risk as well as risk for anyone in

  3. Understanding personal risk of oropharyngeal cancer: risk-groups for oncogenic oral HPV infection and oropharyngeal cancer.

    Science.gov (United States)

    D'Souza, G; McNeel, T S; Fakhry, C

    2017-12-01

    Incidence of human papillomavirus (HPV)-related oropharyngeal cancer is increasing. There is interest in identifying healthy individuals most at risk for development of oropharyngeal cancer to inform screening strategies. All data are from 2009 to 2014, including 13 089 people ages 20-69 in the National Health and Nutrition Examination Survey (NHANES), oropharyngeal cancer cases from the Surveillance, Epidemiology, and End Results (SEER 18) registries (representing ∼28% of the US population), and oropharyngeal cancer mortality from National Center for Health Statistics (NCHS). Primary study outcomes are (i) prevalence of oncogenic HPV DNA in an oral rinse and gargle sample, and (ii) incident oropharyngeal squamous cell cancer. Oncogenic oral HPV DNA is detected in 3.5% of all adults age 20-69 years; however, the lifetime risk of oropharyngeal cancer is low (37 per 10 000). Among men 50-59 years old, 8.1% have an oncogenic oral HPV infection, 2.1% have an oral HPV16 infection, yet only 0.7% will 'ever' develop oropharyngeal cancer in their lifetime. Oncogenic oral HPV prevalence was higher in men than women, and increased with number of lifetime oral sexual partners and tobacco use. Men who currently smoked and had ≥5 lifetime oral sexual partners had 'elevated risk' (prevalence = 14.9%). Men with only one of these risk factors (i.e. either smoked and had 2-4 partners or did not smoke and had ≥5 partners) had 'medium risk' (7.3%). Regardless of what other risk factors participants had, oncogenic oral HPV prevalence was 'low' among those with only ≤1 lifetime oral sexual partner (women = 0.7% and men = 1.7%). Screening based upon oncogenic oral HPV detection would be challenging. Most groups have low oncogenic oral HPV prevalence. In addition to the large numbers of individuals who would need to be screened to identify prevalent oncogenic oral HPV, the lifetime risk of developing oropharyngeal caner among those with infection remains

  4. Fear of cancer recurrence and its predictive factors among Iranian cancer patients

    Directory of Open Access Journals (Sweden)

    Alireza Mohajjel Aghdam

    2014-01-01

    Full Text Available Context: Fear of cancer recurrence (FOCR is one of the most important psychological problems among cancer patients. In extensive review of related literature there were no articles on FOCR among Iranian cancer patients. Aim: The aim of present study was to investigation FOCR and its predictive factors among Iranian cancer patients. Materials and Methods: In this descriptive-correlational study 129 cancer patients participated. For data collection, the demographic checklist and short form of fear of progression questionnaire was used. Logistic regression was used to determine predictive factors of FOCR. Result: Mean score of FOCR among participants was 44.8 and about 50% of them had high level of FOCR. The most important worries of participants were about their family and the future of their children and their lesser worries were about the physical symptoms and fear of physical damage because of cancer treatments. Also, women, breast cancer patient, and patients with lower level of education have more FOCR. Discussion: There is immediate need for supportive care program designed for Iranian cancer patients aimed at decreasing their FOCR. Especially, breast cancer patients and the patient with low educational level need more attention.

  5. Depressive symptoms predict head and neck cancer survival: Examining plausible behavioral and biological pathways.

    Science.gov (United States)

    Zimmaro, Lauren A; Sephton, Sandra E; Siwik, Chelsea J; Phillips, Kala M; Rebholz, Whitney N; Kraemer, Helena C; Giese-Davis, Janine; Wilson, Liz; Bumpous, Jeffrey M; Cash, Elizabeth D

    2018-03-01

    Head and neck cancers are associated with high rates of depression, which may increase the risk for poorer immediate and long-term outcomes. Here it was hypothesized that greater depressive symptoms would predict earlier mortality, and behavioral (treatment interruption) and biological (treatment response) mediators were examined. Patients (n = 134) reported depressive symptomatology at treatment planning. Clinical data were reviewed at the 2-year follow-up. Greater depressive symptoms were associated with significantly shorter survival (hazard ratio, 0.868; 95% confidence interval [CI], 0.819-0.921; P ratio, 0.865; 95% CI, 0.774-0.966; P = .010), and poorer treatment response (odds ratio, 0.879; 95% CI, 0.803-0.963; P = .005). The poorer treatment response partially explained the depression-survival relation. Other known prognostic indicators did not challenge these results. Depressive symptoms at the time of treatment planning predict overall 2-year mortality. Effects are partly influenced by the treatment response. Depression screening and intervention may be beneficial. Future studies should examine parallel biological pathways linking depression to cancer survival, including endocrine disruption and inflammation. Cancer 2018;124:1053-60. © 2018 American Cancer Society. © 2018 American Cancer Society.

  6. Concentrations, input prediction and probabilistic biological risk assessment of polycyclic aromatic hydrocarbons (PAHs) along Gujarat coastline.

    Science.gov (United States)

    Gosai, Haren B; Sachaniya, Bhumi K; Dudhagara, Dushyant R; Rajpara, Rahul K; Dave, Bharti P

    2018-04-01

    A comprehensive investigation was conducted in order to assess the levels of PAHs, their input prediction and potential risks to bacterial abundance and human health along Gujarat coastline. A total of 40 sediment samples were collected at quarterly intervals within a year from two contaminated sites-Alang-Sosiya Shipbreaking Yard (ASSBRY) and Navlakhi Port (NAV), situated at Gulf of Khambhat and Gulf of Kutch, respectively. The concentration of ΣPAHs ranged from 408.00 to 54240.45 ng g -1  dw, indicating heavy pollution of PAHs at both the contaminated sites. Furthermore, isomeric ratios and principal component analysis have revealed that inputs of PAHs at both contaminated sites were mixed-pyrogenic and petrogenic. Pearson co-relation test and regression analysis have disclosed Nap, Acel and Phe as major predictors for bacterial abundance at both contaminated sites. Significantly, cancer risk assessment of the PAHs has been exercised based on incremental lifetime cancer risks. Overall, index of cancer risk of PAHs for ASSBRY and NAV ranged from 4.11 × 10 -6 -2.11 × 10 -5 and 9.08 × 10 -6 -4.50 × 10 -3 indicating higher cancer risk at NAV compared to ASSBRY. The present findings provide baseline information that may help in developing advanced bioremediation and bioleaching strategies to minimize biological risk.

  7. Uncertainties in fatal cancer risk estimates used in radiation protection

    International Nuclear Information System (INIS)

    Kai, Michiaki

    1999-01-01

    Although ICRP and NCRP had not described the details of uncertainties in cancer risk estimates in radiation protection, NCRP, in 1997, firstly reported the results of uncertainty analysis (NCRP No.126) and which is summarized in this paper. The NCRP report pointed out that there are following five factors which uncertainty possessing: uncertainty in epidemiological studies, in dose assessment, in transforming the estimates to risk assessment, in risk prediction and in extrapolation to the low dose/dose rate. These individual factors were analyzed statistically to obtain the relationship between the probability of cancer death in the US population and life time risk coefficient (% per Sv), which showed that, for the latter, the mean value was 3.99 x 10 -2 /Sv, median, 3.38 x 10 -2 /Sv, GSD (geometrical standard deviation), 1.83 x 10 -2 /Sv and 95% confidential limit, 1.2-8.84 x 10 -2 /Sv. The mean value was smaller than that of ICRP recommendation (5 x 10 -2 /Sv), indicating that the value has the uncertainty factor of 2.5-3. Moreover, the most important factor was shown to be the uncertainty in DDREF (dose/dose rate reduction factor). (K.H.)

  8. Mammographic density and risk of breast cancer by tumor characteristics: a case-control study.

    Science.gov (United States)

    Krishnan, Kavitha; Baglietto, Laura; Stone, Jennifer; McLean, Catriona; Southey, Melissa C; English, Dallas R; Giles, Graham G; Hopper, John L

    2017-12-16

    In a previous paper, we had assumed that the risk of screen-detected breast cancer mostly reflects inherent risk, and the risk of whether a breast cancer is interval versus screen-detected mostly reflects risk of masking. We found that inherent risk was predicted by body mass index (BMI) and dense area (DA) or percent dense area (PDA), but not by non-dense area (NDA). Masking, however, was best predicted by PDA but not BMI. In this study, we aimed to investigate if these associations vary by tumor characteristics and mode of detection. We conducted a case-control study nested within the Melbourne Collaborative Cohort Study of 244 screen-detected cases matched to 700 controls and 148 interval cases matched to 446 controls. DA, NDA and PDA were measured using the Cumulus software. Tumor characteristics included size, grade, lymph node involvement, and ER, PR, and HER2 status. Conditional and unconditional logistic regression were applied as appropriate to estimate the Odds per Adjusted Standard Deviation (OPERA) adjusted for age and BMI, allowing the association with BMI to be a function of age at diagnosis. For screen-detected cancer, both DA and PDA were associated to an increased risk of tumors of large size (OPERA ~ 1.6) and positive lymph node involvement (OPERA ~ 1.8); no association was observed for BMI and NDA. For risk of interval versus screen-detected breast cancer, the association with risk for any of the three mammographic measures did not vary by tumor characteristics; an association was observed for BMI for positive lymph nodes (OPERA ~ 0.6). No associations were observed for tumor grade and ER, PR and HER2 status of tumor. Both DA and PDA were predictors of inherent risk of larger breast tumors and positive nodal status, whereas for each of the three mammographic density measures the association with risk of masking did not vary by tumor characteristics. This might raise the hypothesis that the risk of breast tumours with poorer prognosis

  9. Increased colon cancer risk after severe Salmonella infection

    Science.gov (United States)

    Mooij, Sofie; Neefjes-Borst, E. Andra; van Pelt, Wilfrid; Neefjes, Jacques

    2018-01-01

    Background Colon cancer constitutes one of the most frequent malignancies. Previous studies showed that Salmonella manipulates host cell signaling pathways and that Salmonella Typhimurium infection facilitates colon cancer development in genetically predisposed mice. This epidemiological study examined whether severe Salmonella infection, usually acquired from contaminated food, is associated with increased colon cancer risk in humans. Methods and findings We performed a nationwide registry-based study to assess colon cancer risk after diagnosed Salmonella infection. National infectious disease surveillance records (1999–2015) for Dutch residents aged ≥20 years when diagnosed with salmonellosis (n = 14,264) were linked to the Netherlands Cancer Registry. Salmonella-infected patients were laboratory-confirmed under medical consultation after 1–2 weeks of illness. These datasets also contained information on Salmonella serovar and type of infection. Colon cancer risk (overall and per colon subsite) among patients with a diagnosed Salmonella infection was compared with expected colon cancer risk in the general population. Data from the nationwide registry of histo- and cytopathology (PALGA) and Statistics Netherlands (CBS) allowed assessing potential effects of age, gender, latency, socioeconomic status, genetic predisposition, inflammatory bowel disease (IBD), and tumor features. We found that compared to the general population, colon cancer risk was significantly increased (standardized incidence ratio [SIR] 1.54; 95%CI 1.09–2.10) among patients with Salmonella infection diagnosed transverse colon (SIR 2.12; 95%CI 1.38–3.09) after S. Enteritidis infection (SIR 2.97; 95%CI 1.73–4.76). Salmonellosis occurred more frequently among colon cancer patients with pre-infectious IBD, a known risk factor for colon cancer. Colon tumors of patients with a history of Salmonella infection were mostly of low grade. Conclusions Patients diagnosed with severe

  10. SVM and SVM Ensembles in Breast Cancer Prediction

    OpenAIRE

    Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

    2017-01-01

    Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction per...

  11. Anthropometric characteristics and ovarian cancer risk and survival.

    Science.gov (United States)

    Minlikeeva, Albina N; Moysich, Kirsten B; Mayor, Paul C; Etter, John L; Cannioto, Rikki A; Ness, Roberta B; Starbuck, Kristen; Edwards, Robert P; Segal, Brahm H; Lele, Sashikant; Odunsi, Kunle; Diergaarde, Brenda; Modugno, Francesmary

    2018-02-01

    Multiple studies have examined the role of anthropometric characteristics in ovarian cancer risk and survival; however, their results have been conflicting. We investigated the associations between weight change, height and height change and risk and outcome of ovarian cancer using data from a large population-based case-control study. Data from 699 ovarian cancer cases and 1,802 controls who participated in the HOPE study were included. We used unconditional logistic regression adjusted for age, race, number of pregnancies, use of oral contraceptives, and family history of breast or ovarian cancer to examine the associations between self-reported height and weight and height change with ovarian cancer risk. Cox proportional hazards regression models adjusted for age and stage were used to examine the association between the exposure variables and overall and progression-free survival among ovarian cancer cases. We observed an increased risk of ovarian cancer mortality and progression for gaining more than 20 pounds between ages 18-30, HR 1.36; 95% CI 1.05-1.76, and HR 1.31; 95% CI 1.04-1.66, respectively. Losing weight and gaining it back multiple times was inversely associated with both ovarian cancer risk, OR 0.78; 95% CI 0.63-0.97 for 1-4 times and OR 0.73; 95% CI 0.54-0.99 for 5-9 times, and mortality, HR 0.63; 95% CI 0.40-0.99 for 10-14 times. Finally, being taller during adolescence and adulthood was associated with increased risk of mortality. Taller stature and weight gain over lifetime were not related to ovarian cancer risk. Our results suggest that height and weight and their change over time may influence ovarian cancer risk and survival. These findings suggest that biological mechanisms underlying these associations may be hormone driven and may play an important role in relation to ovarian carcinogenesis and tumor progression.

  12. Long working hours and cancer risk: a multi-cohort study.

    Science.gov (United States)

    Heikkila, Katriina; Nyberg, Solja T; Madsen, Ida E H; de Vroome, Ernest; Alfredsson, Lars; Bjorner, Jacob J; Borritz, Marianne; Burr, Hermann; Erbel, Raimund; Ferrie, Jane E; Fransson, Eleonor I; Geuskens, Goedele A; Hooftman, Wendela E; Houtman, Irene L; Jöckel, Karl-Heinz; Knutsson, Anders; Koskenvuo, Markku; Lunau, Thorsten; Nielsen, Martin L; Nordin, Maria; Oksanen, Tuula; Pejtersen, Jan H; Pentti, Jaana; Shipley, Martin J; Steptoe, Andrew; Suominen, Sakari B; Theorell, Töres; Vahtera, Jussi; Westerholm, Peter J M; Westerlund, Hugo; Dragano, Nico; Rugulies, Reiner; Kawachi, Ichiro; Batty, G David; Singh-Manoux, Archana; Virtanen, Marianna; Kivimäki, Mika

    2016-03-29

    Working longer than the maximum recommended hours is associated with an increased risk of cardiovascular disease, but the relationship of excess working hours with incident cancer is unclear. This multi-cohort study examined the association between working hours and cancer risk in 116 462 men and women who were free of cancer at baseline. Incident cancers were ascertained from national cancer, hospitalisation and death registers; weekly working hours were self-reported. During median follow-up of 10.8 years, 4371 participants developed cancer (n colorectal cancer: 393; n lung cancer: 247; n breast cancer: 833; and n prostate cancer: 534). We found no clear evidence for an association between working hours and the overall cancer risk. Working hours were also unrelated the risk of incident colorectal, lung or prostate cancers. Working ⩾55 h per week was associated with 1.60-fold (95% confidence interval 1.12-2.29) increase in female breast cancer risk independently of age, socioeconomic position, shift- and night-time work and lifestyle factors, but this observation may have been influenced by residual confounding from parity. Our findings suggest that working long hours is unrelated to the overall cancer risk or the risk of lung, colorectal or prostate cancers. The observed association with breast cancer would warrant further research.

  13. ABO blood group and risk of cancer

    DEFF Research Database (Denmark)

    Vasan, Senthil K; Hwang, Jinseub; Rostgaard, Klaus

    2016-01-01

    groups and site-specific cancer risk in a large cohort of healthy blood donors from Sweden and Denmark. RESULTS: A total of 1.6 million donors were followed over 27 million person-years (20 million in Sweden and 7 million in Denmark). We observed 119,584 cancer cases. Blood groups A, AB and B were......INTRODUCTION: The associations between ABO blood group and cancer risk have been studied repeatedly, but results have been variable. Consistent associations have only been reported for pancreatic and gastric cancers. MATERIALS AND METHODS: We estimated associations between different ABO blood...... associated either with increased or decreased risk of cancer at 13 anatomical sites (p≤0.05), compared to blood group O. Consistent with assessment using a false discovery rate approach, significant associations with ABO blood group were observed for cancer of the pancreas, breast, and upper gastrointestinal...

  14. PCOS and cancer risk.

    Directory of Open Access Journals (Sweden)

    Tadeusz Issat

    2010-01-01

    Full Text Available Polycystic ovary syndrome (PCOS affects approximately 5 to 10% of women of reproductive age. It is the most common reason of anovulation in infertile women. PCOS is accompanied by such conditions as oligo- or anovulation, hipertestosteronism, lower cell sensitivity to insulin, type II diabetes, hyperlipidemia and obesity. Each of the above-mentioned conditions is an approved risk factor proved to predispose towards cancer. However, PCOS is also a disease entity which differs in its clinical manifestation. For example not all patients suffer from obesity or hipertestosteronism related symptoms. From the analysis of literature it is possible to draw conclusions, that there is a possible correlation between PCOS and endometrial cancer, which emerges from clinical trials or research focused on molecular changes in endometrium patients with PCOS. On the other hand, correlation between PCOS and breast or ovary cancer is not so strong, in spite of single papers which are showing the link. The main problem in researching the correlation between PCOS and any cancer risk, is there is a very small group of women or the trial is imperfect (e.g. no control group. There is no meta-analysis focused on this correlation in literature. The change of criteria of PCOS in the past is also a big problem, because there was a number of definitions of PCOS, which results in inconsistent PCOS diagnoses over time. In this paper we would like to provide a description of studies that aimed at showing correlation between PCOS and cancer risk and underlying theoretical assumptions.

  15. Polymorphisms associated with the risk of lung cancer in a healthy Mexican Mestizo population: application of the additive model for cancer

    Directory of Open Access Journals (Sweden)

    Rebeca Pérez-Morales

    2011-01-01

    Full Text Available Lung cancer is the leading cause of cancer mortality in Mexico and worldwide. In the past decade, there has been an increase in the number of lung cancer cases in young people, which suggests an important role for genetic background in the etiology of this disease. In this study, we genetically characterized 16 polymorphisms in 12 low penetrance genes (AhR, CYP1A1, CYP2E1, EPHX1, GSTM1, GSTT1, GSTPI, XRCC1, ERCC2, MGMT, CCND1 and TP53 in 382 healthy Mexican Mestizos as the first step in elucidating the genetic structure of this population and identifying high risk individuals. All of the genotypes analyzed were in Hardy-Weinberg equilibrium, but different degrees of linkage were observed for polymorphisms in the CYP1A1 and EPHX1 genes. The genetic variability of this population was distributed in six clusters that were defined based on their genetic characteristics. The use of a polygenic model to assess the additive effect of low penetrance risk alleles identified combinations of risk genotypes that could be useful in predicting a predisposition to lung cancer. Estimation of the level of genetic susceptibility showed that the individual calculated risk value (iCRV ranged from 1 to 16, with a higher iCRV indicating a greater genetic susceptibility to lung cancer.

  16. Association between allergies and risk of pancreatic cancer.

    Science.gov (United States)

    Cotterchio, Michelle; Lowcock, Elizabeth; Hudson, Thomas J; Greenwood, Celia; Gallinger, Steven

    2014-03-01

    Less than 10% of pancreatic cancer cases survive 5 years, yet its etiology is not well understood. Studies suggest allergies are associated with reduced pancreatic cancer risk. Our study collected additional information on allergies (including skin prick test results and differentiation of allergic/nonallergic asthma), and is the first to assess possible confounding by allergy medications. A population-based case-control study was designed to comprehensively assess the association between allergy and pancreatic cancer risk. Pancreas cancer cases were diagnosed during 2011 to 2012, and identified through the Ontario Cancer Registry (345 cases). Population-based controls were identified using random digit dialing and age/sex frequency matched to cases (1,285 controls). Questionnaires collected lifetime allergy history (type of allergy, age at onset, skin prick testing results), allergy medications, and established pancreas cancer risk factors. Logistic regression was used to estimate odd ratios and test potential confounders, including allergy medications. Hay fever was associated with a significant reduction in pancreatic cancer risk [AOR = 0.68; 95% confidence intervals (CI), 0.52-0.89], and reduction was greatest for those whose skin prick test was positive for hay fever allergens. No particular patterns were observed as regards age at onset and duration of allergy. Positive dust/mold allergy skin prick test and animal allergies were associated with a statistically significant reduced pancreatic cancer risk; AOR = 0.49; 95% CI, 0.31-0.78 and AOR = 0.68; 95% CI, 0.46-0.99, respectively. Asthma was not associated with pancreatic cancer risk. These findings support the growing body of evidence that suggests certain allergies are associated with reduced pancreatic cancer risk. ©2014 AACR.

  17. Stage-specific predictive models for breast cancer survivability.

    Science.gov (United States)

    Kate, Rohit J; Nadig, Ramya

    2017-01-01

    Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. Relative Risks for Lethal Prostate Cancer Based on Complete Family History of Prostate Cancer Death.

    Science.gov (United States)

    Albright, Frederick S; Stephenson, Robert A; Agarwal, Neeraj; Cannon-Albright, Lisa A

    2017-01-01

    There are few published familial relative risks (RR) for lethal prostate cancer. This study estimates RRs for lethal prostate cancer based on comprehensive family history data, with the goal of improving identification of those men at highest risk of dying from prostate cancer. We used a population-based genealogical resource linked to a statewide electronic SEER cancer registry and death certificates to estimate relative risks (RR) for death from prostate cancer based upon family history. Over 600,000 male probands were analyzed, representing a variety of family history constellations of lethal prostate cancer. RR estimates were based on the ratio of the observed to the expected number of lethal prostate cancer cases using internal rates. RRs for lethal prostate cancer based on the number of affected first-degree relatives (FDR) ranged from 2.49 (95% CI: 2.27, 2.73) for exactly 1 FDR to 5.30 (2.13, 10.93) for ≥3 affected FDRs. In an absence of affected FDRs, increased risk was also significant for increasing numbers of affected second-degree or third degree relatives. Equivalent risks were observed for similar maternal and paternal family history. This study provides population-based estimates of lethal prostate cancer risk based on lethal prostate cancer family history. Many family history constellations associated with two to greater than five times increased risk for lethal prostate cancer were identified. These lethal prostate cancer risk estimates hold potential for use in identification, screening, early diagnosis, and treatment of men at high risk for death from prostate cancer. Prostate77:41-48, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Prediction of cancer incidence in Tyrol/Austria for year of diagnosis 2020.

    Science.gov (United States)

    Oberaigner, Willi; Geiger-Gritsch, Sabine

    2014-10-01

    Prediction of the number of incident cancer cases is very relevant for health planning purposes and allocation of resources. The shift towards elder age groups in central European populations in the next decades is likely to contribute to an increase in cancer incidence for many cancer sites. In Tyrol, cancer incidence data have been registered on a high level of completeness for more than 20 years. We therefore aimed to compute well-founded predictions of cancer incidence for Tyrol for the year 2020 for all frequent cancer sites and for all cancer sites combined. After defining a prediction base range for every cancer site, we extrapolated the age-specific time trends in the prediction base range following a linear model for increasing and a log-linear model for decreasing time trends. The extrapolated time trends were evaluated for the year 2020 applying population figures supplied by Statistics Austria. Compared with the number of annual incident cases for the year 2009 for all cancer sites combined except non-melanoma skin cancer, we predicted an increase of 235 (15 %) and 362 (21 %) for females and males, respectively. For both sexes, more than 90 % of the increase is attributable to the shift toward older age groups in the next decade. The biggest increase in absolute numbers is seen for females in breast cancer (92, 21 %), lung cancer (64, 52 %), colorectal cancer (40, 24 %), melanoma (38, 30 %) and the haematopoietic system (37, 35 %) and for males in prostate cancer (105, 25 %), colorectal cancer (91, 45 %), the haematopoietic system (71, 55 %), bladder cancer (69, 100 %) and melanoma (64, 52 %). The increase in the number of incident cancer cases of 15 % in females and 21 % in males in the next decade is very relevant for planning purposes. However, external factors cause uncertainty in the prediction of some cancer sites (mainly prostate cancer and colorectal cancer) and the prediction intervals are still broad. Therefore

  20. Development of a web-based liver cancer prediction model for type II diabetes patients by using an artificial neural network.

    Science.gov (United States)

    Rau, Hsiao-Hsien; Hsu, Chien-Yeh; Lin, Yu-An; Atique, Suleman; Fuad, Anis; Wei, Li-Ming; Hsu, Ming-Huei

    2016-03-01

    Diabetes mellitus is associated with an increased risk of liver cancer, and these two diseases are among the most common and important causes of morbidity and mortality in Taiwan. To use data mining techniques to develop a model for predicting the development of liver cancer within 6 years of diagnosis with type II diabetes. Data were obtained from the National Health Insurance Research Database (NHIRD) of Taiwan, which covers approximately 22 million people. In this study, we selected patients who were newly diagnosed with type II diabetes during the 2000-2003 periods, with no prior cancer diagnosis. We then used encrypted personal ID to perform data linkage with the cancer registry database to identify whether these patients were diagnosed with liver cancer. Finally, we identified 2060 cases and assigned them to a case group (patients diagnosed with liver cancer after diabetes) and a control group (patients with diabetes but no liver cancer). The risk factors were identified from the literature review and physicians' suggestion, then, chi-square test was conducted on each independent variable (or potential risk factor) for a comparison between patients with liver cancer and those without, those found to be significant were selected as the factors. We subsequently performed data training and testing to construct artificial neural network (ANN) and logistic regression (LR) prediction models. The dataset was randomly divided into 2 groups: a training group and a test group. The training group consisted of 1442 cases (70% of the entire dataset), and the prediction model was developed on the basis of the training group. The remaining 30% (618 cases) were assigned to the test group for model validation. The following 10 variables were used to develop the ANN and LR models: sex, age, alcoholic cirrhosis, nonalcoholic cirrhosis, alcoholic hepatitis, viral hepatitis, other types of chronic hepatitis, alcoholic fatty liver disease, other types of fatty liver disease, and

  1. Modulating Cancer Risk: The Gut Takes Control | Center for Cancer Research

    Science.gov (United States)

    Cancer risk is influenced by a number of factors, including exposure to chemicals in food and drugs and other molecules in the environment. Some of these chemicals may increase risk of developing cancer, while others, including many chemicals in vegetables, may confer protection.

  2. Impact of preventive therapy on the risk of breast cancer among women with benign breast disease.

    Science.gov (United States)

    Cuzick, Jack; Sestak, Ivana; Thorat, Mangesh A

    2015-11-01

    There are three main ways in which women can be identified as being at high risk of breast cancer i) family history of breast and/or ovarian cancer, which includes genetic factors ii) mammographically identified high breast density, and iii) certain types of benign breast disease. The last category is the least common, but in some ways the easiest one for which treatment can be offered, because these women have already entered into the treatment system. The highest risk is seen in women with lobular carcinoma in situ (LCIS), but this is very rare. More common is atypical hyperplasia (AH), which carries a 4-5-fold risk of breast cancer as compared to general population. Even more common is hyperplasia of the usual type and carries a roughly two-fold increased risk. Women with aspirated cysts are also at increased risk of subsequent breast cancer. Tamoxifen has been shown to be particularly effective in preventing subsequent breast cancer in women with AH, with a more than 70% reduction in the P1 trial and a 60% reduction in IBIS-I. The aromatase inhibitors (AIs) also are highly effective for AH and LCIS. There are no published data on the effectiveness of tamoxifen or the AIs for breast cancer prevention in women with hyperplasia of the usual type, or for women with aspirated cysts. Improving diagnostic consistency, breast cancer risk prediction and education of physicians and patients regarding therapeutic prevention in women with benign breast disease may strengthen breast cancer prevention efforts. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Obesity and colorectal cancer risk

    International Nuclear Information System (INIS)

    Hano Garcia, Olga Marina; Wood Rodriguez, Lisette; Villa Jimenez, Oscar Manuel

    2011-01-01

    Obesity is a chronic and multifactor disease characterized by presence of excess body fat harmful for health. Several studies have been conducted to assess the possible risk character of different factors for colorectal cancer including the following modifying factors: a diet rich in saturated fats, a diet low in vegetables, physical inactivity, alcohol consumption and obesity. A case-control study was conducted to include 276 adult patients (93 cases and 184 controls) consecutively seen from May, 2008 to May, 2009 in the Institute of Gastroenterology determining a possible association between obesity as risk factor and colorectal cancer. Variables measures included: sex, age, skin color, body mass index, hip-waist circumference and endoscopic location of cancer. We conclude that the colorectal cancer with predominance in female sex and in white people in both groups. Obesity according to a great relation hip-waist had an strong relation with colorectal cancer, which had predominance towards distal colon in both sexes

  4. Applying a CAD-generated imaging marker to assess short-term breast cancer risk

    Science.gov (United States)

    Mirniaharikandehei, Seyedehnafiseh; Zarafshani, Ali; Heidari, Morteza; Wang, Yunzhi; Aghaei, Faranak; Zheng, Bin

    2018-02-01

    Although whether using computer-aided detection (CAD) helps improve radiologists' performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all "prior" negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65+/-0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (pbreast cancer risk.

  5. Predicting the risk of perioperative transfusion for patients undergoing elective hepatectomy.

    Science.gov (United States)

    Sima, Camelia S; Jarnagin, William R; Fong, Yuman; Elkin, Elena; Fischer, Mary; Wuest, David; D'Angelica, Michael; DeMatteo, Ronald P; Blumgart, Leslie H; Gönen, Mithat

    2009-12-01

    To develop 2 instruments that predict the probability of perioperative red blood cell transfusion in patients undergoing elective liver resection for primary and secondary tumors. Hepatic resection is the most effective treatment for several benign and malign conditions, but may be accompanied by substantial blood loss and the need for perioperative transfusions. While blood conservation strategies such as autologous blood donation, acute normovolemic hemodilution, or cell saver systems are available, they are economically efficient only if directed toward patients with a high risk of transfusion. Using preoperative data from 1204 consecutive patients who underwent liver resection between 1995 and 2000 at Memorial Sloan- Kettering Cancer Center, we modeled the probability of perioperative red blood cell transfusion. We used the resulting model, validated on an independent dataset (n = 555 patients), to develop 2 prediction instruments, a nomogram and a transfusion score, which can be easily implemented into clinical practice. The planned number of liver segments resected, concomitant extrahepatic organ resection, a diagnosis of primary liver malignancy, as well as preoperative hemoglobin and platelets levels predicted the probability of perioperative red blood cell transfusion. The predictions of the model appeared accurate and with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.71. Preoperative factors can be combined into risk profiles to predict the likelihood of transfusion during or after elective liver resection. These predictions, easy to calculate in the frame of a nomogram or of a transfusion score, can be used to identify patients who are at high risk for red cell transfusions and therefore most likely to benefit from blood conservation techniques.

  6. Improvement of the projection models for radiogenic cancer risk

    International Nuclear Information System (INIS)

    Tong Jian

    2005-01-01

    Calculations of radiogenic cancer risk are based on the risk projection models for specific cancer sites. Improvement has been made for the parameters used in the previous models including introductions of mortality and morbidity risk coefficients, and age-/ gender-specific risk coefficients. These coefficients have been applied to calculate the radiogenic cancer risks for specific organs and radionuclides under different exposure scenarios. (authors)

  7. Cancer risks and prevention

    International Nuclear Information System (INIS)

    Vessey, M.P.; Gray, M.

    1985-01-01

    A series of essays in honour of Sir Richard Doll is presented. Chapters cover the preventability of cancer, geography, smoking, diet, occupation, radiation, infections and immune impairment, exogenous and endogenous hormones, other drugs, prevention through legislation and by education and cancer risks and prevention in the Third World. The chapter on radiation has been indexed separately. (UK)

  8. Multisite external validation of a risk prediction model for the diagnosis of blood stream infections in febrile pediatric oncology patients without severe neutropenia.

    Science.gov (United States)

    Esbenshade, Adam J; Zhao, Zhiguo; Aftandilian, Catherine; Saab, Raya; Wattier, Rachel L; Beauchemin, Melissa; Miller, Tamara P; Wilkes, Jennifer J; Kelly, Michael J; Fernbach, Alison; Jeng, Michael; Schwartz, Cindy L; Dvorak, Christopher C; Shyr, Yu; Moons, Karl G M; Sulis, Maria-Luisa; Friedman, Debra L

    2017-10-01

    Pediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/μL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness. A 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables. From the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI. The results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017;123:3781-3790. © 2017 American Cancer Society. © 2017 American Cancer Society.

  9. Radiation dose and second cancer risk in patients treated for cancer of the cervix

    International Nuclear Information System (INIS)

    Boice, J.D. Jr.; Engholm, G.; Kleinerman, R.A.

    1988-01-01

    The risk of cancer associated with a broad range of organ doses was estimated in an international study of women with cervical cancer. Among 150,000 patients reported to one of 19 population-based cancer registries or treated in any of 20 oncology clinics, 4188 women with second cancers and 6880 matched controls were selected for detailed study. Radiation doses for selected organs were reconstructed for each patient on the basis of her original radiotherapy records. Very high doses, on the order of several hundred gray, were found to increase the risk of cancers of the bladder [relative risk (RR) = 4.0], rectum (RR = 1.8), vagina (RR = 2.7), and possibly bone (RR = 1.3), uterine corpus (RR = 1.3), cecum (RR = 1.5), and non-Hodgkin's lymphoma (RR = 2.5). For all female genital cancers taken together, a sharp dose-response gradient was observed, reaching fivefold for doses more than 150 Gy. Several gray increased the risk of stomach cancer (RR = 2.1) and leukemia (RR = 2.0). Although cancer of the pancreas was elevated, there was no evidence of a dose-dependent risk. Cancer of the kidney was significantly increased among 15-year survivors. A nonsignificant twofold risk of radiogenic thyroid cancer was observed following an average dose of only 0.11 Gy. Breast cancer was not increased overall, despite an average dose of 0.31 Gy and 953 cases available for evaluation (RR = 0.9); there was, however, a weak suggestion of a dose response among women whose ovaries had been surgically removed. Doses greater than 6 Gy to the ovaries reduced breast cancer risk by 44%. A significant deficit of ovarian cancer was observed within 5 years of radiotherapy; in contrast, a dose response was suggested among 10-year survivors

  10. Risk of Salivary Gland Cancer After Childhood Cancer: A Report From the Childhood Cancer Survivor Study

    Energy Technology Data Exchange (ETDEWEB)

    Boukheris, Houda [Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Stovall, Marilyn [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Gilbert, Ethel S. [Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States); Stratton, Kayla L. [Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington (United States); Smith, Susan A.; Weathers, Rita [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Hammond, Sue [Department of Pathology, Ohio State University School of Medicine, Columbus, Ohio (United States); Mertens, Ann C. [Department of Pediatrics, Emory University, Atlanta, Georgia (United States); Donaldson, Sarah S. [Department of Radiation Oncology, Stanford University Medical Center, Stanford, California (United States); Armstrong, Gregory T.; Robison, Leslie L. [Department of Epidemiology and Cancer Control, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Neglia, Joseph P. [Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota (United States); Inskip, Peter D., E-mail: inskippe@mail.nih.gov [Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland (United States)

    2013-03-01

    Purpose: To evaluate effects of radiation therapy, chemotherapy, cigarette smoking, and alcohol consumption on the risk of second primary salivary gland cancer (SGC) in the Childhood Cancer Survivor Study (CCSS). Methods and Materials: Standardized incidence ratios (SIR) and excess absolute risks (EAR) of SGC in the CCSS were calculated using incidence rates from Surveillance, Epidemiology, and End Results population-based cancer registries. Radiation dose to the salivary glands was estimated based on medical records. Poisson regression was used to assess risks with respect to radiation dose, chemotherapy, smoking, and alcohol consumption. Results: During the time period of the study, 23 cases of SGC were diagnosed among 14,135 childhood cancer survivors. The mean age at diagnosis of the first primary cancer was 8.3 years, and the mean age at SGC diagnosis was 24.8 years. The incidence of SGC was 39-fold higher in the cohort than in the general population (SIR = 39.4; 95% CI = 25.4-57.8). The EAR was 9.8 per 100,000 person-years. Risk increased linearly with radiation dose (excess relative risk = 0.36/Gy; 95% CI = 0.06-2.5) and remained elevated after 20 years. There was no significant trend of increasing risk with increasing dose of chemotherapeutic agents, pack-years of cigarette smoking, or alcohol intake. Conclusion: Although the cumulative incidence of SGC was low, childhood cancer survivors treated with radiation experienced significantly increased risk for at least 2 decades after exposure, and risk was positively associated with radiation dose. Results underscore the importance of long-term follow up of childhood cancer survivors for the development of new malignancies.

  11. Risk of Salivary Gland Cancer After Childhood Cancer: A Report From the Childhood Cancer Survivor Study

    International Nuclear Information System (INIS)

    Boukheris, Houda; Stovall, Marilyn; Gilbert, Ethel S.; Stratton, Kayla L.; Smith, Susan A.; Weathers, Rita; Hammond, Sue; Mertens, Ann C.; Donaldson, Sarah S.; Armstrong, Gregory T.; Robison, Leslie L.; Neglia, Joseph P.; Inskip, Peter D.

    2013-01-01

    Purpose: To evaluate effects of radiation therapy, chemotherapy, cigarette smoking, and alcohol consumption on the risk of second primary salivary gland cancer (SGC) in the Childhood Cancer Survivor Study (CCSS). Methods and Materials: Standardized incidence ratios (SIR) and excess absolute risks (EAR) of SGC in the CCSS were calculated using incidence rates from Surveillance, Epidemiology, and End Results population-based cancer registries. Radiation dose to the salivary glands was estimated based on medical records. Poisson regression was used to assess risks with respect to radiation dose, chemotherapy, smoking, and alcohol consumption. Results: During the time period of the study, 23 cases of SGC were diagnosed among 14,135 childhood cancer survivors. The mean age at diagnosis of the first primary cancer was 8.3 years, and the mean age at SGC diagnosis was 24.8 years. The incidence of SGC was 39-fold higher in the cohort than in the general population (SIR = 39.4; 95% CI = 25.4-57.8). The EAR was 9.8 per 100,000 person-years. Risk increased linearly with radiation dose (excess relative risk = 0.36/Gy; 95% CI = 0.06-2.5) and remained elevated after 20 years. There was no significant trend of increasing risk with increasing dose of chemotherapeutic agents, pack-years of cigarette smoking, or alcohol intake. Conclusion: Although the cumulative incidence of SGC was low, childhood cancer survivors treated with radiation experienced significantly increased risk for at least 2 decades after exposure, and risk was positively associated with radiation dose. Results underscore the importance of long-term follow up of childhood cancer survivors for the development of new malignancies

  12. Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study.

    Science.gov (United States)

    Wu, Jia; Gensheimer, Michael F; Dong, Xinzhe; Rubin, Daniel L; Napel, Sandy; Diehn, Maximilian; Loo, Billy W; Li, Ruijiang

    2016-08-01

    To develop an intratumor partitioning framework for identifying high-risk subregions from (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. In this institutional review board-approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). We propose a robust intratumor partitioning method to identify clinically relevant, high-risk

  13. Factors Predictive of Sentinel Lymph Node Involvement in Primary Breast Cancer.

    Science.gov (United States)

    Malter, Wolfram; Hellmich, Martin; Badian, Mayhar; Kirn, Verena; Mallmann, Peter; Krämer, Stefan

    2018-06-01

    Sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) for axillary staging in patients with early-stage breast cancer. The need for therapeutic ALND is the subject of ongoing debate especially after the publication of the ACOSOG Z0011 trial. In a retrospective trial with univariate and multivariate analyses, factors predictive of sentinel lymph node involvement should be analyzed in order to define tumor characteristics of breast cancer patients, where SLNB should not be spared to receive important indicators for adjuvant treatment decisions (e.g. thoracic wall irradiation after mastectomy with or without reconstruction). Between 2006 and 2010, 1,360 patients with primary breast cancer underwent SLNB with/without ALND with evaluation of tumor localization, multicentricity and multifocality, histological subtype, tumor size, grading, lymphovascular invasion (LVI), and estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status. These characteristics were retrospectively analyzed in univariate and multivariate logistic regression models to define significant predictive factors for sentinel lymph node involvement. The multivariate analysis demonstrated that tumor size and LVI (pbreast cancer. Because of the increased risk for metastatic involvement of axillary sentinel nodes in cases with larger breast cancer or diagnosis of LVI, patients with these breast cancer characteristics should not be spared from SLNB in a clinically node-negative situation in order to avoid false-negative results with a high potential for wrong indication of primary breast reconstruction or wrong non-indication of necessary post-mastectomy radiation therapy. The prognostic impact of avoidance of axillary staging with SLNB is analyzed in the ongoing prospective INSEMA trial. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  14. Obesity-associated Breast Cancer: Analysis of risk factors.

    Science.gov (United States)

    Engin, Atilla

    2017-01-01

    Several studies show that a significantly stronger association is obvious between increased body mass index (BMI) and higher breast cancer incidence. Furthermore, obese women are at higher risk of all-cause and breast cancer specific mortality when compared to non-obese women with breast cancer. In this context, increased levels of estrogens due to excessive aromatization activity of the adipose tissue, overexpression of pro-inflammatory cytokines, insulin resistance, hyperactivation of insulin-like growth factors (IGFs) pathways, adipocyte-derived adipokines, hypercholesterolemia and excessive oxidative stress contribute to the development of breast cancer in obese women. While higher breast cancer risk with hormone replacement therapy is particularly evident among lean women, in postmenopausal women who are not taking exogenous hormones, general obesity is a significant predictor for breast cancer. Moreover, increased plasma cholesterol leads to accelerated tumor formation and exacerbates their aggressiveness. In contrast to postmenopausal women, premenopausal women with high BMI are inversely associated with breast cancer risk. Nevertheless, life-style of women for breast cancer risk is regulated by avoiding the overweight and a high-fat diet. Estrogen-plus-progestin hormone therapy users for more than 5 years have elevated risks of both invasive ductal and lobular breast cancer. Additionally, these cases are more commonly node-positive and have a higher cancer-related mortality. Collectively, in this chapter, the impacts of obesity-related estrogen, cholesterol, saturated fatty acid, leptin and adiponectin concentrations, aromatase activity, leptin and insulin resistance on breast cancer patients are evaluated. Obesity-related prognostic factors of breast cancer also are discussed at molecular basis.

  15. Cancer risk awareness and screening uptake in individuals at higher risk for colon cancer: a cross-sectional study.

    Science.gov (United States)

    Salimzadeh, Hamideh; Bishehsari, Faraz; Delavari, Alireza; Barzin, Gilda; Amani, Mohammad; Majidi, Azam; Sadjadi, Alireza; Malekzadeh, Reza

    2016-12-20

    We aimed to measure cancer knowledge and feasibility of a screening colonoscopy among a cohort of individuals at higher risk of colon cancer. This study was conducted as part of an ongoing screening cohort, in which first degree relatives (FDRs) of patients with colon cancer are invited to participate in a free of charge screening colonoscopy. We enrolled 1017 FDRs in the study between 2013 and 2014 measuring their data on demographics, cancer knowledge and colonoscopy uptake. A p value of aware of their increased risk for cancer, near 35.0% had ever heard about colonoscopy with 22% aware of the correct age to start screening. Comparing cancer knowledge of FDRs at high risk versus those at moderate risk, we recorded non-significant differences (p>0.05). Almost two-thirds of FDRs expressed willingness to undergo a colonoscopy and 49.2% completed the procedure, of which 12.8% had advanced neoplasm. Our data indicated that remarkable numbers of FDRs were not still informed of their cancer risk or never received a physician recommendation for screening. The desirable uptake at first invitation, which would be higher over successive invitations, supports the feasibility of a family-based recruitment approach for early screening. This has promising implications to introduce targeted screening colonoscopy into the healthcare system in Iran and other developing nations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  16. Second cancer incidence risk estimates using BEIR VII models for standard and complex external beam radiotherapy for early breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Donovan, E. M.; James, H.; Bonora, M.; Yarnold, J. R.; Evans, P. M. [Joint Department of Physics, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton SM2 5PT (United Kingdom); Physics Department, Ipswich Hospital NHS Foundation Trust, Ipswich IP4 5PD (United Kingdom); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT, United Kingdom and School of Radiotherapy, University of Milan, Milan 20122 (Italy); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT (United Kingdom); Centre for Vision Speech and Signal Processing, University of Surrey, Guildford GU2 7XH (United Kingdom)

    2012-10-15

    contralateral breast doses and LAR were comparable to WBRT, despite their added complexity. The smaller irradiated volume of the ABPI plan contributed to a halving of LAR for contralateral breast compared with the other plan types. Daily image guided radiotherapy (IGRT) for a left breast protocol using kilovoltage CBCT contributed <10% to LAR for the majority of organs, and did not exceed 22% of total organ dose. Conclusions: Phantom measurements and calculations of LAR from the BEIR VII models predict that complex breast radiotherapy techniques do not increase the theoretical risk of second cancer incidence for organs distant from the treated breast, or the contralateral breast where appropriate plan constraints are applied. Complex SIB treatments are predicted to increase the risk of second cancer incidence in the lungs compared to standard whole breast radiotherapy; this is outweighed by the threefold reduction in 5 yr local recurrence risk for patients of high risk of recurrence, and young age, from the use of radiotherapy. APBI may have a favorable impact on risk of second cancer in the contralateral breast and lung for older patients at low risk of recurrence. Intensive use of IGRTincreased the estimated values of LAR but these are dominated by the effect of the dose from the radiotherapy, and any increase in LAR from IGRT is much lower than the models' uncertainties.

  17. Second cancer incidence risk estimates using BEIR VII models for standard and complex external beam radiotherapy for early breast cancer

    International Nuclear Information System (INIS)

    Donovan, E. M.; James, H.; Bonora, M.; Yarnold, J. R.; Evans, P. M.

    2012-01-01

    contralateral breast doses and LAR were comparable to WBRT, despite their added complexity. The smaller irradiated volume of the ABPI plan contributed to a halving of LAR for contralateral breast compared with the other plan types. Daily image guided radiotherapy (IGRT) for a left breast protocol using kilovoltage CBCT contributed <10% to LAR for the majority of organs, and did not exceed 22% of total organ dose. Conclusions: Phantom measurements and calculations of LAR from the BEIR VII models predict that complex breast radiotherapy techniques do not increase the theoretical risk of second cancer incidence for organs distant from the treated breast, or the contralateral breast where appropriate plan constraints are applied. Complex SIB treatments are predicted to increase the risk of second cancer incidence in the lungs compared to standard whole breast radiotherapy; this is outweighed by the threefold reduction in 5 yr local recurrence risk for patients of high risk of recurrence, and young age, from the use of radiotherapy. APBI may have a favorable impact on risk of second cancer in the contralateral breast and lung for older patients at low risk of recurrence. Intensive use of IGRTincreased the estimated values of LAR but these are dominated by the effect of the dose from the radiotherapy, and any increase in LAR from IGRT is much lower than the models’ uncertainties.

  18. Geographical variance in the risk of gastric stump cancer: no increased risk in Japan?

    NARCIS (Netherlands)

    Tersmette, A. C.; Giardiello, F. M.; Offerhaus, G. J.; Tersmette, K. W.; Ohara, K.; Vandenbroucke, J. P.; Tytgat, G. N.

    1991-01-01

    Geographical differences may exist in the risk of gastric stump cancer. Therefore, we performed meta-analysis of literature reports in Japan (n = 3), the USA (n = 4), and Europe (n = 20) on the risk of postgastrectomy cancer. The weighted mean relative risk of stump cancer in Japan was 0.28, 95%

  19. Graphs to estimate an individualized risk of breast cancer.

    Science.gov (United States)

    Benichou, J; Gail, M H; Mulvihill, J J

    1996-01-01

    Clinicians who counsel women about their risk for developing breast cancer need a rapid method to estimate individualized risk (absolute risk), as well as the confidence limits around that point. The Breast Cancer Detection Demonstration Project (BCDDP) model (sometimes called the Gail model) assumes no genetic model and simultaneously incorporates five risk factors, but involves cumbersome calculations and interpolations. This report provides graphs to estimate the absolute risk of breast cancer from the BCDDP model. The BCDDP recruited 280,000 women from 1973 to 1980 who were monitored for 5 years. From this cohort, 2,852 white women developed breast cancer and 3,146 controls were selected, all with complete risk-factor information. The BCDDP model, previously developed from these data, was used to prepare graphs that relate a specific summary relative-risk estimate to the absolute risk of developing breast cancer over intervals of 10, 20, and 30 years. Once a summary relative risk is calculated, the appropriate graph is chosen that shows the 10-, 20-, or 30-year absolute risk of developing breast cancer. A separate graph gives the 95% confidence limits around the point estimate of absolute risk. Once a clinician rules out a single gene trait that predisposes to breast cancer and elicits information on age and four risk factors, the tables and figures permit an estimation of a women's absolute risk of developing breast cancer in the next three decades. These results are intended to be applied to women who undergo regular screening. They should be used only in a formal counseling program to maximize a woman's understanding of the estimates and the proper use of them.

  20. Calibration plots for risk prediction models in the presence of competing risks

    DEFF Research Database (Denmark)

    Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

    2014-01-01

    A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks...... prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves...