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Sample records for regression survival analyses

  1. Survival analysis II: Cox regression

    NARCIS (Netherlands)

    Stel, Vianda S.; Dekker, Friedo W.; Tripepi, Giovanni; Zoccali, Carmine; Jager, Kitty J.

    2011-01-01

    In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the

  2. Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

    Science.gov (United States)

    Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

    2017-06-01

    We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  3. Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

  4. Support vector methods for survival analysis: a comparison between ranking and regression approaches.

    Science.gov (United States)

    Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

    2011-10-01

    To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods

  5. Quantifying Fire Cycle from Dendroecological Records Using Survival Analyses

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    Dominic Cyr

    2016-06-01

    Full Text Available Quantifying fire regimes in the boreal forest ecosystem is crucial for understanding the past and present dynamics, as well as for predicting its future dynamics. Survival analyses have often been used to estimate the fire cycle in eastern Canada because they make it possible to take into account the censored information that is made prevalent by the typically long fire return intervals and the limited scope of the dendroecological methods that are used to quantify them. Here, we assess how the true length of the fire cycle, the short-term temporal variations in fire activity, and the sampling effort affect the accuracy and precision of estimates obtained from two types of parametric survival models, the Weibull and the exponential models, and one non-parametric model obtained with the Cox regression. Then, we apply those results in a case area located in eastern Canada. Our simulation experiment confirms some documented concerns regarding the detrimental effects of temporal variations in fire activity on parametric estimation of the fire cycle. Cox regressions appear to provide the most accurate and robust estimator, being by far the least affected by temporal variations in fire activity. The Cox-based estimate of the fire cycle for the last 300 years in the case study area is 229 years (CI95: 162–407, compared with the likely overestimated 319 years obtained with the commonly used exponential model.

  6. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  7. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

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    Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

    2009-11-01

    G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

  8. The analysis of survival data in nephrology: basic concepts and methods of Cox regression

    NARCIS (Netherlands)

    van Dijk, Paul C.; Jager, Kitty J.; Zwinderman, Aeilko H.; Zoccali, Carmine; Dekker, Friedo W.

    2008-01-01

    How much does the survival of one group differ from the survival of another group? How do differences in age in these two groups affect such a comparison? To obtain a quantity to compare the survival of different patient groups and to account for confounding effects, a multiple regression technique

  9. Regression models for interval censored survival data: Application to HIV infection in Danish homosexual men

    DEFF Research Database (Denmark)

    Carstensen, Bendix

    1996-01-01

    This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men.......This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men....

  10. Meta-regression analysis of commensal and pathogenic Escherichia coli survival in soil and water.

    Science.gov (United States)

    Franz, Eelco; Schijven, Jack; de Roda Husman, Ana Maria; Blaak, Hetty

    2014-06-17

    The extent to which pathogenic and commensal E. coli (respectively PEC and CEC) can survive, and which factors predominantly determine the rate of decline, are crucial issues from a public health point of view. The goal of this study was to provide a quantitative summary of the variability in E. coli survival in soil and water over a broad range of individual studies and to identify the most important sources of variability. To that end, a meta-regression analysis on available literature data was conducted. The considerable variation in reported decline rates indicated that the persistence of E. coli is not easily predictable. The meta-analysis demonstrated that for soil and water, the type of experiment (laboratory or field), the matrix subtype (type of water and soil), and temperature were the main factors included in the regression analysis. A higher average decline rate in soil of PEC compared with CEC was observed. The regression models explained at best 57% of the variation in decline rate in soil and 41% of the variation in decline rate in water. This indicates that additional factors, not included in the current meta-regression analysis, are of importance but rarely reported. More complete reporting of experimental conditions may allow future inference on the global effects of these variables on the decline rate of E. coli.

  11. USE OF THE SIMPLE LINEAR REGRESSION MODEL IN MACRO-ECONOMICAL ANALYSES

    Directory of Open Access Journals (Sweden)

    Constantin ANGHELACHE

    2011-10-01

    Full Text Available The article presents the fundamental aspects of the linear regression, as a toolbox which can be used in macroeconomic analyses. The article describes the estimation of the parameters, the statistical tests used, the homoscesasticity and heteroskedasticity. The use of econometrics instrument in macroeconomics is an important factor that guarantees the quality of the models, analyses, results and possible interpretation that can be drawn at this level.

  12. Prediction of survival to discharge following cardiopulmonary resuscitation using classification and regression trees.

    Science.gov (United States)

    Ebell, Mark H; Afonso, Anna M; Geocadin, Romergryko G

    2013-12-01

    To predict the likelihood that an inpatient who experiences cardiopulmonary arrest and undergoes cardiopulmonary resuscitation survives to discharge with good neurologic function or with mild deficits (Cerebral Performance Category score = 1). Classification and Regression Trees were used to develop branching algorithms that optimize the ability of a series of tests to correctly classify patients into two or more groups. Data from 2007 to 2008 (n = 38,092) were used to develop candidate Classification and Regression Trees models to predict the outcome of inpatient cardiopulmonary resuscitation episodes and data from 2009 (n = 14,435) to evaluate the accuracy of the models and judge the degree of over fitting. Both supervised and unsupervised approaches to model development were used. 366 hospitals participating in the Get With the Guidelines-Resuscitation registry. Adult inpatients experiencing an index episode of cardiopulmonary arrest and undergoing cardiopulmonary resuscitation in the hospital. The five candidate models had between 8 and 21 nodes and an area under the receiver operating characteristic curve from 0.718 to 0.766 in the derivation group and from 0.683 to 0.746 in the validation group. One of the supervised models had 14 nodes and classified 27.9% of patients as very unlikely to survive neurologically intact or with mild deficits (Tree models that predict survival to discharge with good neurologic function or with mild deficits following in-hospital cardiopulmonary arrest. Models like this can assist physicians and patients who are considering do-not-resuscitate orders.

  13. 77 FR 6548 - Notice of Availability of Ballistic Survivability, Lethality and Vulnerability Analyses

    Science.gov (United States)

    2012-02-08

    ... DEPARTMENT OF DEFENSE Department of the Army Notice of Availability of Ballistic Survivability, Lethality and Vulnerability Analyses AGENCY: Department of the Army, DoD. ACTION: Notice of availability. SUMMARY: The US Army Research Laboratory's (ARL's), Survivability, Lethality Analysis Directorate (SLAD...

  14. Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

    Science.gov (United States)

    Hasyim, M.; Prastyo, D. D.

    2018-03-01

    Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

  15. Applications of MIDAS regression in analysing trends in water quality

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    Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

    2014-04-01

    We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

  16. Enhanced left ventricular mass regression after aortic valve replacement in patients with aortic stenosis is associated with improved long-term survival.

    Science.gov (United States)

    Ali, Ayyaz; Patel, Amit; Ali, Ziad; Abu-Omar, Yasir; Saeed, Amber; Athanasiou, Thanos; Pepper, John

    2011-08-01

    Aortic valve replacement in patients with aortic stenosis is usually followed by regression of left ventricular hypertrophy. More complete resolution of left ventricular hypertrophy is suggested to be associated with superior clinical outcomes; however, its translational impact on long-term survival after aortic valve replacement has not been investigated. Demographic, operative, and clinical data were obtained retrospectively through case note review. Transthoracic echocardiography was used to measure left ventricular mass preoperatively and at annual follow-up visits. Patients were classified according to their reduction in left ventricular mass at 1 year after the operation: group 1, less than 25 g; group 2, 25 to 150 g; and group 3, more than 150 g. Kaplan-Meier and multivariable Cox regression were used. A total of 147 patients were discharged from the hospital after aortic valve replacement for aortic stenosis between 1991 and 2001. Preoperative left ventricular mass was 279 ± 98 g in group 1 (n = 47), 347 ± 104 g in group 2 (n = 62), and 491 ± 183 g in group 3 (n = 38) (P regression such as ischemic heart disease or hypertension, valve type, or valve size used. Ten-year actuarial survival was not statistically different in patients with enhanced left ventricular mass regression when compared with the log-rank test (group 1, 51% ± 9%; group 2, 54% ± 8%; and group 3, 72% ± 10%) (P = .26). After adjustment, left ventricular mass reduction of more than 150 g was demonstrated as an independent predictor of improved long-term survival on multivariate analysis (P = .02). Our study is the first to suggest that enhanced postoperative left ventricular mass regression, specifically in patients undergoing aortic valve replacement for aortic stenosis, may be associated with improved long-term survival. In view of these findings, strategies purported to be associated with superior left ventricular mass regression should be considered when undertaking

  17. New insights into survival trend analyses in cancer population-based studies: the SUDCAN methodology.

    Science.gov (United States)

    Uhry, Zoé; Bossard, Nadine; Remontet, Laurent; Iwaz, Jean; Roche, Laurent

    2017-01-01

    The main objective of the SUDCAN study was to compare, for 15 cancer sites, the trends in net survival and excess mortality rates from cancer 5 years after diagnosis between six European Latin countries (Belgium, France, Italy, Portugal, Spain and Switzerland). The data were extracted from the EUROCARE-5 database. The study period ranged from 6 (Portugal, 2000-2005) to 18 years (Switzerland, 1989-2007). Trend analyses were carried out separately for each country and cancer site; the number of cases ranged from 1500 to 104 000 cases. We developed an original flexible excess rate modelling strategy that accounts for the continuous effects of age, year of diagnosis, time since diagnosis and their interactions. Nineteen models were constructed; they differed in the modelling of the effect of the year of diagnosis in terms of linearity, proportionality and interaction with age. The final model was chosen according to the Akaike Information Criterion. The fit was assessed graphically by comparing model estimates versus nonparametric (Pohar-Perme) net survival estimates. Out of the 90 analyses carried out, the effect of the year of diagnosis on the excess mortality rate depended on age in 61 and was nonproportional in 64; it was nonlinear in 27 out of the 75 analyses where this effect was considered. The model fit was overall satisfactory. We analysed successfully 15 cancer sites in six countries. The refined methodology proved necessary for detailed trend analyses. It is hoped that three-dimensional parametric modelling will be used more widely in net survival trend studies as it has major advantages over stratified analyses.

  18. Physical activity increases survival after heart valve surgery

    DEFF Research Database (Denmark)

    Lund, K.; Sibilitz, Kirstine Lærum; Kikkenborg Berg, Selina

    2016-01-01

    physical activity levels 6-12 months after heart valve surgery and (1) survival, (2) hospital readmission 18-24 months after surgery and (3) participation in exercise-based cardiac rehabilitation. METHODS: Prospective cohort study with registry data from The CopenHeart survey, The Danish National Patient......OBJECTIVES: Increased physical activity predicts survival and reduces risk of readmission in patients with coronary heart disease. However, few data show how physical activity is associated with survival and readmission after heart valve surgery. Objective were to assess the association between...... Register and The Danish Civil Registration System of 742 eligible patients. Physical activity was quantified with the International Physical Activity Questionnaire and analysed using Kaplan-Meier analysis and Cox regression and logistic regression methods. RESULTS: Patients with a moderate to high physical...

  19. Bayesian linear regression with skew-symmetric error distributions with applications to survival analysis

    KAUST Repository

    Rubio, Francisco J.

    2016-02-09

    We study Bayesian linear regression models with skew-symmetric scale mixtures of normal error distributions. These kinds of models can be used to capture departures from the usual assumption of normality of the errors in terms of heavy tails and asymmetry. We propose a general noninformative prior structure for these regression models and show that the corresponding posterior distribution is proper under mild conditions. We extend these propriety results to cases where the response variables are censored. The latter scenario is of interest in the context of accelerated failure time models, which are relevant in survival analysis. We present a simulation study that demonstrates good frequentist properties of the posterior credible intervals associated with the proposed priors. This study also sheds some light on the trade-off between increased model flexibility and the risk of over-fitting. We illustrate the performance of the proposed models with real data. Although we focus on models with univariate response variables, we also present some extensions to the multivariate case in the Supporting Information.

  20. An Additive-Multiplicative Cox-Aalen Regression Model

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects...

  1. A generalized additive regression model for survival times

    DEFF Research Database (Denmark)

    Scheike, Thomas H.

    2001-01-01

    Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...

  2. Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Shahrbanoo Goli

    2016-01-01

    Full Text Available The Support Vector Regression (SVR model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

  3. Exponential Decay Nonlinear Regression Analysis of Patient Survival Curves: Preliminary Assessment in Non-Small Cell Lung Cancer

    Science.gov (United States)

    Stewart, David J.; Behrens, Carmen; Roth, Jack; Wistuba, Ignacio I.

    2010-01-01

    Background For processes that follow first order kinetics, exponential decay nonlinear regression analysis (EDNRA) may delineate curve characteristics and suggest processes affecting curve shape. We conducted a preliminary feasibility assessment of EDNRA of patient survival curves. Methods EDNRA was performed on Kaplan-Meier overall survival (OS) and time-to-relapse (TTR) curves for 323 patients with resected NSCLC and on OS and progression-free survival (PFS) curves from selected publications. Results and Conclusions In our resected patients, TTR curves were triphasic with a “cured” fraction of 60.7% (half-life [t1/2] >100,000 months), a rapidly-relapsing group (7.4%, t1/2=5.9 months) and a slowly-relapsing group (31.9%, t1/2=23.6 months). OS was uniphasic (t1/2=74.3 months), suggesting an impact of co-morbidities; hence, tumor molecular characteristics would more likely predict TTR than OS. Of 172 published curves analyzed, 72 (42%) were uniphasic, 92 (53%) were biphasic, 8 (5%) were triphasic. With first-line chemotherapy in advanced NSCLC, 87.5% of curves from 2-3 drug regimens were uniphasic vs only 20% of those with best supportive care or 1 drug (p<0.001). 54% of curves from 2-3 drug regimens had convex rapid-decay phases vs 0% with fewer agents (p<0.001). Curve convexities suggest that discontinuing chemotherapy after 3-6 cycles “synchronizes” patient progression and death. With postoperative adjuvant chemotherapy, the PFS rapid-decay phase accounted for a smaller proportion of the population than in controls (p=0.02) with no significant difference in rapid-decay t1/2, suggesting adjuvant chemotherapy may move a subpopulation of patients with sensitive tumors from the relapsing group to the cured group, with minimal impact on time to relapse for a larger group of patients with resistant tumors. In untreated patients, the proportion of patients in the rapid-decay phase increased (p=0.04) while rapid-decay t1/2 decreased (p=0.0004) with increasing

  4. Development of a likelihood of survival scoring system for hospitalized equine neonates using generalized boosted regression modeling.

    Directory of Open Access Journals (Sweden)

    Katarzyna A Dembek

    Full Text Available BACKGROUND: Medical management of critically ill equine neonates (foals can be expensive and labor intensive. Predicting the odds of foal survival using clinical information could facilitate the decision-making process for owners and clinicians. Numerous prognostic indicators and mathematical models to predict outcome in foals have been published; however, a validated scoring method to predict survival in sick foals has not been reported. The goal of this study was to develop and validate a scoring system that can be used by clinicians to predict likelihood of survival of equine neonates based on clinical data obtained on admission. METHODS AND RESULTS: Data from 339 hospitalized foals of less than four days of age admitted to three equine hospitals were included to develop the model. Thirty seven variables including historical information, physical examination and laboratory findings were analyzed by generalized boosted regression modeling (GBM to determine which ones would be included in the survival score. Of these, six variables were retained in the final model. The weight for each variable was calculated using a generalized linear model and the probability of survival for each total score was determined. The highest (7 and the lowest (0 scores represented 97% and 3% probability of survival, respectively. Accuracy of this survival score was validated in a prospective study on data from 283 hospitalized foals from the same three hospitals. Sensitivity, specificity, positive and negative predictive values for the survival score in the prospective population were 96%, 71%, 91%, and 85%, respectively. CONCLUSIONS: The survival score developed in our study was validated in a large number of foals with a wide range of diseases and can be easily implemented using data available in most equine hospitals. GBM was a useful tool to develop the survival score. Further evaluations of this scoring system in field conditions are needed.

  5. Association of tRNA methyltransferase NSUN2/IGF-II molecular signature with ovarian cancer survival.

    Science.gov (United States)

    Yang, Jia-Cheng; Risch, Eric; Zhang, Meiqin; Huang, Chan; Huang, Huatian; Lu, Lingeng

    2017-09-01

    To investigate the association between NSUN2/IGF-II signature and ovarian cancer survival. Using a publicly accessible dataset of RNA sequencing and clinical follow-up data, we performed Classification and Regression Tree and survival analyses. Patients with NSUN2 high IGF-II low had significantly superior overall and disease progression-free survival, followed by NSUN2 low IGF-II low , NSUN2 high IGF-II high and NSUN2 low IGF-II high (p IGF-II signature with the risks of death and relapse remained significant in multivariate Cox regression models. Random-effects meta-analyses show the upregulated NSUN2 and IGF-II expression in ovarian cancer versus normal tissues. The NSUN2/IGF-II signature associates with heterogeneous outcome and may have clinical implications in managing ovarian cancer.

  6. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

    Science.gov (United States)

    Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

    2016-04-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

  7. How to deal with continuous and dichotomic outcomes in epidemiological research: linear and logistic regression analyses

    NARCIS (Netherlands)

    Tripepi, Giovanni; Jager, Kitty J.; Stel, Vianda S.; Dekker, Friedo W.; Zoccali, Carmine

    2011-01-01

    Because of some limitations of stratification methods, epidemiologists frequently use multiple linear and logistic regression analyses to address specific epidemiological questions. If the dependent variable is a continuous one (for example, systolic pressure and serum creatinine), the researcher

  8. Modeling time-to-event (survival) data using classification tree analysis.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2017-12-01

    Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

  9. Survival analysis of dialysis patients in selected hospitals of lahore city

    International Nuclear Information System (INIS)

    Ahmad, Z.; Shahzad, I.

    2015-01-01

    There are several reasons which are directly or indirectly relate to affect the survival time of End Stage Renal Disease (ESRD) patients. This study was done to analyse the survival rate of ESRD patients in Lahore city, and to evaluate the influence of various risk factors and prognostic factors on survival of these patients. Methods: A sample of 40 patients was taken from the Jinnah Hospital Lahore and Lahore General Hospital by using the convenience sampling technique. The Log Rank Test was used to determine the significant difference between the categories of qualitative variables of ESRD patients. Multivariate Cox Regression Analysis was used to analyse the effect of different clinical and socio-economic variables on the survival time of these patients. Results: Different qualitative variables like: age, marital status, BMI, comorbid factors, diabetes type, gender, income level, place, risk factor like diabetes, ischemic heart disease, hypertension and Hepatitis status were analysed on the basis of Log Rank Test. While age and comorbid factors were found to be statistically significant which showed that the distribution of age and comorbid factors were different. By using the Cox Regression analysis the coefficient of Mass, serum albumin and family history of diabetes were found to be significant. Conclusions: There were some of the factors which had been taken for the analysis came out less or more significant in patients of ESRD. So it was concluded that mostly clinical factors which were Mass of the Patient, Serum Albumin and Family History of Diabetes made significant contribution towards the survival status of patients. (author)

  10. Body mass index and breast cancer survival

    DEFF Research Database (Denmark)

    Guo, Qi; Burgess, Stephen; Turman, Constance

    2017-01-01

    Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival...... from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between...... the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER...

  11. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...

  12. Effect of bystander CPR initiation prior to the emergency call on ROSC and 30day survival

    DEFF Research Database (Denmark)

    Viereck, Søren; Palsgaard Møller, Thea; Kjær Ersbøll, Annette

    2017-01-01

    BACKGROUND: This study aimed at evaluating if time for initiation of bystander cardiopulmonary resuscitation (CPR) - prior to the emergency call (CPRprior) versus during the emergency call following dispatcher-assisted CPR (CPRduring) - was associated with return of spontaneous circulation (ROSC...... and corresponding emergency calls were evaluated. Multivariable logistic regression analyses were applied to evaluate the association between time for initiation of bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of CPRprior. RESULTS: The study...... included 548 emergency calls for OHCA patients receiving bystander CPR, 34.9% (n=191) in the CPRpriorgroup and 65.1% (n=357) in the CPRduringgroup. Multivariable analyses showed no difference in ROSC (OR=0.88, 95% CI: 0.56-1.38) or 30-day survival (OR=1.14, 95% CI: 0.68-1.92) between CPRpriorand CPRduring...

  13. From basic survival analytic theory to a non-standard application

    CERN Document Server

    Zimmermann, Georg

    2017-01-01

    Georg Zimmermann provides a mathematically rigorous treatment of basic survival analytic methods. His emphasis is also placed on various questions and problems, especially with regard to life expectancy calculations arising from a particular real-life dataset on patients with epilepsy. The author shows both the step-by-step analyses of that dataset and the theory the analyses are based on. He demonstrates that one may face serious and sometimes unexpected problems, even when conducting very basic analyses. Moreover, the reader learns that a practically relevant research question may look rather simple at first sight. Nevertheless, compared to standard textbooks, a more detailed account of the theory underlying life expectancy calculations is needed in order to provide a mathematically rigorous framework. Contents Regression Models for Survival Data Model Checking Procedures Life Expectancy Target Groups Researchers, lecturers, and students in the fields of mathematics and statistics Academics and experts work...

  14. Prognostic value of biochemical variables for survival after surgery for metastatic bone disease of the extremities.

    Science.gov (United States)

    Sørensen, Michala Skovlund; Hovgaard, Thea Bechman; Hindsø, Klaus; Petersen, Michael Mørk

    2017-03-01

    Prediction of survival in patients having surgery for metastatic bone disease in the extremities (MBDex) has been of interest in more than two decades. Hitherto no consensus on the value of biochemical variables has been achieved. Our purpose was (1) to investigate if standard biochemical variables have independent prognostic value for survival after surgery for MBDex and (2) to identify optimal prognostic cut off values for survival of biochemical variables. In a consecutive cohort of 270 patients having surgery for MBDex, we measured preoperative biochemical variables: hemoglobin, alkaline phosphatase, C-reactive protein and absolute, neutrophil and lymphocyte count. ROC curve analyses were performed to identify optimal cut off levels. Independent prognostic factors for variables were addressed with multiple Cox regression analyses. Optimal cut off levels were identified as: hemoglobin 7.45 mmol/L, absolute lymphocyte count 8.5 × 10 9 /L, neutrophil 5.68 × 10 9 /L, lymphocyte 1.37 × 10 9 /L, C-reactive protein 22.5 mg/L, and alkaline phosphatase 129 U/L. Regression analyses found alkaline phosphatase (HR 2.49) and neutrophil count (HR 2.49) to be independent prognostic factors. We found neutrophil count and alkaline phosphatase to be independent prognostic variables in predicting survival in patients after surgery for MBDex. © 2016 Wiley Periodicals, Inc.

  15. The number of subjects per variable required in linear regression analyses.

    Science.gov (United States)

    Austin, Peter C; Steyerberg, Ewout W

    2015-06-01

    To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  16. A chip-level modeling approach for rail span collapse and survivability analyses

    International Nuclear Information System (INIS)

    Marvis, D.G.; Alexander, D.R.; Dinger, G.L.

    1989-01-01

    A general semiautomated analysis technique has been developed for analyzing rail span collapse and survivability of VLSI microcircuits in high ionizing dose rate radiation environments. Hierarchical macrocell modeling permits analyses at the chip level and interactive graphical postprocessing provides a rapid visualization of voltage, current and power distributions over an entire VLSIC. The technique is demonstrated for a 16k C MOS/SOI SRAM and a CMOS/SOS 8-bit multiplier. The authors also present an efficient method to treat memory arrays as well as a three-dimensional integration technique to compute sapphire photoconduction from the design layout

  17. Statistical and regression analyses of detected extrasolar systems

    Czech Academy of Sciences Publication Activity Database

    Pintr, Pavel; Peřinová, V.; Lukš, A.; Pathak, A.

    2013-01-01

    Roč. 75, č. 1 (2013), s. 37-45 ISSN 0032-0633 Institutional support: RVO:61389021 Keywords : Exoplanets * Kepler candidates * Regression analysis Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.630, year: 2013 http://www.sciencedirect.com/science/article/pii/S0032063312003066

  18. 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

  19. Reducing Inter-Laboratory Differences between Semen Analyses Using Z Score and Regression Transformations

    Directory of Open Access Journals (Sweden)

    Esther Leushuis

    2016-12-01

    Full Text Available Background: Standardization of the semen analysis may improve reproducibility. We assessed variability between laboratories in semen analyses and evaluated whether a transformation using Z scores and regression statistics was able to reduce this variability. Materials and Methods: We performed a retrospective cohort study. We calculated between-laboratory coefficients of variation (CVB for sperm concentration and for morphology. Subsequently, we standardized the semen analysis results by calculating laboratory specific Z scores, and by using regression. We used analysis of variance for four semen parameters to assess systematic differences between laboratories before and after the transformations, both in the circulation samples and in the samples obtained in the prospective cohort study in the Netherlands between January 2002 and February 2004. Results: The mean CVB was 7% for sperm concentration (range 3 to 13% and 32% for sperm morphology (range 18 to 51%. The differences between the laboratories were statistically significant for all semen parameters (all P<0.001. Standardization using Z scores did not reduce the differences in semen analysis results between the laboratories (all P<0.001. Conclusion: There exists large between-laboratory variability for sperm morphology and small, but statistically significant, between-laboratory variation for sperm concentration. Standardization using Z scores does not eliminate between-laboratory variability.

  20. Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images

    DEFF Research Database (Denmark)

    van Timmeren, Janna E; Leijenaar, Ralph T H; van Elmpt, Wouter

    2017-01-01

    was validated. MATERIAL AND METHODS: One training dataset of 132 and two validation datasets of 62 and 94stage I-IV NSCLC patients were included. Interchangeability was assessed by performing a linear regression on CT and CBCT extracted features. A two-step correction was applied prior to model validation...... different between groups with high and low prognostic value for both modalities. Harrell's concordance index was 0.69 for CT and 0.66 for CBCT models for dataset 1. Conclusions The results show that a subset of radiomic features extracted from CT and CBCT images are interchangeable using simple linear...... regression. Moreover, a previously developed radiomics signature has prognostic value for overall survival in three CBCT cohorts, showing the potential of CBCT radiomics to be used as prognostic imaging biomarker....

  1. Survival after Out-of-Hospital Cardiac Arrest in Nursing Homes

    DEFF Research Database (Denmark)

    Pape, Marianne; Rajan, Shahzleen; Hansen, Steen Møller

    2018-01-01

    BACKGROUND: Survival among nursing home residents who suffers out-of-hospital cardiac arrest (OHCA) is sparsely studied. Deployment of automated external defibrillators (AEDs) in nursing home facilities in Denmark is unknown. We examined 30-day survival following OHCA in nursing and private home...... residents. METHODS: This register-based, nationwide, follow-up study identified OHCA-patients ≥18 years of age with a resuscitation attempt in nursing homes and private homes using Danish Cardiac Arrest Register data from June 1, 2001 to December 31, 2014. The primary outcome measure was 30-day survival....... Multiple logistic regression analyses were used to assess factors potentially associated with survival among nursing and private home residents separately. RESULTS: Of 26,999 OCHAs, 2516 (9.3%) occurred in nursing homes, and 24,483 (90.7%) in private homes. Nursing home residents were older (median 83 (Q1...

  2. On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model

    International Nuclear Information System (INIS)

    Unkel, Steffen; Belka, Claus; Lauber, Kirsten

    2016-01-01

    the extraction of scores of radioresistance, which displayed significant correlations with the estimated parameters of the regression models. Undoubtedly, LQ regression is a robust method for the analysis of clonogenic survival data. Nevertheless, alternative approaches including non-linear regression and multivariate techniques such as cluster analysis and principal component analysis represent versatile tools for the extraction of parameters and/or scores of the cellular response towards ionizing irradiation with a more intuitive biological interpretation. The latter are highly informative for correlation analyses with other types of data, including functional genomics data that are increasingly beinggenerated

  3. Correlation and regression analyses of genetic effects for different types of cells in mammals under radiation and chemical treatment

    International Nuclear Information System (INIS)

    Slutskaya, N.G.; Mosseh, I.B.

    2006-01-01

    Data about genetic mutations under radiation and chemical treatment for different types of cells have been analyzed with correlation and regression analyses. Linear correlation between different genetic effects in sex cells and somatic cells have found. The results may be extrapolated on sex cells of human and mammals. (authors)

  4. Recognising out-of-hospital cardiac arrest during emergency calls increases bystander cardiopulmonary resuscitation and survival.

    Science.gov (United States)

    Viereck, Søren; Møller, Thea Palsgaard; Ersbøll, Annette Kjær; Bækgaard, Josefine Stokholm; Claesson, Andreas; Hollenberg, Jacob; Folke, Fredrik; Lippert, Freddy K

    2017-06-01

    Initiation of early bystander cardiopulmonary resuscitation (CPR) depends on bystanders' or medical dispatchers' recognition of out-of-hospital cardiac arrest (OHCA). The primary aim of our study was to investigate if OHCA recognition during the emergency call was associated with bystander CPR, return of spontaneous circulation (ROSC), and 30-day survival. Our secondary aim was to identify patient-, setting-, and dispatcher-related predictors of OHCA recognition. We performed an observational study of all OHCA patients' emergency calls in the Capital Region of Denmark from 01/01/2013-31/12/2013. OHCAs were collected from the Danish Cardiac Arrest Registry and the Mobile Critical Care Unit database. Emergency call recordings were identified and evaluated. Multivariable logistic regression analyses were applied to all OHCAs and witnessed OHCAs only to analyse the association between OHCA recognition and bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of OHCA recognition. We included 779 emergency calls in the analyses. During the emergency calls, 70.1% (n=534) of OHCAs were recognised; OHCA recognition was positively associated with bystander CPR (odds ratio [OR]=7.84, 95% confidence interval [CI]: 5.10-12.05) in all OHCAs; and ROSC (OR=1.86, 95% CI: 1.13-3.06) and 30-day survival (OR=2.80, 95% CI: 1.58-4.96) in witnessed OHCA. Predictors of OHCA recognition were addressing breathing (OR=1.76, 95% CI: 1.17-2.66) and callers located by the patient's side (OR=2.16, 95% CI: 1.46-3.19). Recognition of OHCA during emergency calls was positively associated with the provision of bystander CPR, ROSC, and 30-day survival in witnessed OHCA. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  5. The number of subjects per variable required in linear regression analyses

    NARCIS (Netherlands)

    P.C. Austin (Peter); E.W. Steyerberg (Ewout)

    2015-01-01

    textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

  6. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

    OpenAIRE

    Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

    2016-01-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epide...

  7. Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

    Science.gov (United States)

    Onder, Seyhan; Mutlu, Mert

    2017-09-01

    Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

  8. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Science.gov (United States)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  9. Correlation, Regression and Path Analyses of Seed Yield Components in Crambe abyssinica, a Promising Industrial Oil Crop

    OpenAIRE

    Huang, Banglian; Yang, Yiming; Luo, Tingting; Wu, S.; Du, Xuezhu; Cai, Detian; Loo, van, E.N.; Huang Bangquan

    2013-01-01

    In the present study correlation, regression and path analyses were carried out to decide correlations among the agro- nomic traits and their contributions to seed yield per plant in Crambe abyssinica. Partial correlation analysis indicated that plant height (X1) was significantly correlated with branching height and the number of first branches (P <0.01); Branching height (X2) was significantly correlated with pod number of primary inflorescence (P <0.01) and number of secondary branch...

  10. Men and women show similar survival outcome in stage IV breast cancer.

    Science.gov (United States)

    Wu, San-Gang; Zhang, Wen-Wen; Liao, Xu-Lin; Sun, Jia-Yuan; Li, Feng-Yan; Su, Jing-Jun; He, Zhen-Yu

    2017-08-01

    To evaluate the clinicopathological features, patterns of distant metastases, and survival outcome between stage IV male breast cancer (MBC) and female breast cancer (FBC). Patients diagnosed with stage IV MBC and FBC between 2010 and 2013 were included using the Surveillance, Epidemiology, and End Results program. Univariate and multivariate Cox regression analyses were used to analyze risk factors for overall survival (OS). A total of 4997 patients were identified, including 60 MBC and 4937 FBC. Compared with FBC, patients with MBC were associated with a significantly higher rate of estrogen receptor-positive, progesterone receptor-positive, unmarried, lung metastases, and a lower frequency of liver metastases. Univariate and multivariate analyses showed no significant difference in OS between MBC and FBC. In the propensity score-matched population, there was also no difference in survival between MBC and FBC. Multivariate analysis of MBC showed that OS was longer for patients aged 50-69 years and with estrogen receptor-positive disease. There was no significant difference in survival outcome between stage IV MBC and FBC, but significant differences in clinicopathological features and patterns of metastases between the genders. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Directory of Open Access Journals (Sweden)

    M. Guns

    2012-06-01

    Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  12. ASURV: Astronomical SURVival Statistics

    Science.gov (United States)

    Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.

    2014-06-01

    ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

  13. Predictors of adalimumab drug survival in psoriasis differ by reason for discontinuation: long-term results from the Bio-CAPTURE registry.

    Science.gov (United States)

    van den Reek, J M P A; Tummers, M; Zweegers, J; Seyger, M M B; van Lümig, P P M; Driessen, R J B; van de Kerkhof, P C M; Kievit, W; de Jong, E M G J

    2015-03-01

    Drug survival is an indicator for treatment success; insight in predictors associated with drug survival is important. To analyse the long-term drug survival for adalimumab in patients with psoriasis treated in daily practice and (II) to identify predictors of prolonged drug survival for adalimumab split for different reasons of discontinuation. Data were extracted from a prospective psoriasis cohort and analysed using Kaplan-Meier survival curves split for reasons of discontinuation. Baseline predictors associated with longer drug survival were identified using multivariate Cox-regression analysis. One hundred and sixteen patients were included with a total of 208 patient-years. Overall drug survival was 76% after 1 year and 52% after 4.5 years. In patients who stopped due to ineffectiveness, longer drug survival was associated with the absence of specific comorbidities (P = 0.03). In patients who stopped due to side-effects, longer drug survival was associated with male gender (P = 0.02). Predictors of adalimumab drug survival in psoriasis differ by reason for discontinuation. Strong, specific predictors can lead to patient-tailored treatment. © 2014 European Academy of Dermatology and Venereology.

  14. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  15. Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

    Science.gov (United States)

    Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

    2017-12-01

    1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

  16. Testing homogeneity in Weibull-regression models.

    Science.gov (United States)

    Bolfarine, Heleno; Valença, Dione M

    2005-10-01

    In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.

  17. Recognising out-of-hospital cardiac arrest during emergency calls increases bystander cardiopulmonary resuscitation and survival

    DEFF Research Database (Denmark)

    Viereck, Søren; Møller, Thea Palsgaard; Ersbøll, Annette Kjær

    2017-01-01

    BACKGROUND: Initiation of early bystander cardiopulmonary resuscitation (CPR) depends on bystanders' or medical dispatchers' recognition of out-of-hospital cardiac arrest (OHCA). The primary aim of our study was to investigate if OHCA recognition during the emergency call was associated...... with bystander CPR, return of spontaneous circulation (ROSC), and 30-day survival. Our secondary aim was to identify patient-, setting-, and dispatcher-related predictors of OHCA recognition. METHODS: We performed an observational study of all OHCA patients' emergency calls in the Capital Region of Denmark from...... the association between OHCA recognition and bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of OHCA recognition. RESULTS: We included 779 emergency calls in the analyses. During the emergency calls, 70.1% (n=534) of OHCAs were recognised...

  18. Regression models for the restricted residual mean life for right-censored and left-truncated data

    DEFF Research Database (Denmark)

    Cortese, Giuliana; Holmboe, Stine A.; Scheike, Thomas H.

    2017-01-01

    The hazard ratios resulting from a Cox's regression hazards model are hard to interpret and to be converted into prolonged survival time. As the main goal is often to study survival functions, there is increasing interest in summary measures based on the survival function that are easier to inter......The hazard ratios resulting from a Cox's regression hazards model are hard to interpret and to be converted into prolonged survival time. As the main goal is often to study survival functions, there is increasing interest in summary measures based on the survival function that are easier...... to interpret than the hazard ratio; the residual mean time is an important example of those measures. However, because of the presence of right censoring, the tail of the survival distribution is often difficult to estimate correctly. Therefore, we consider the restricted residual mean time, which represents...... a partial area under the survival function, given any time horizon τ, and is interpreted as the residual life expectancy up to τ of a subject surviving up to time t. We present a class of regression models for this measure, based on weighted estimating equations and inverse probability of censoring weighted...

  19. The Poor Survival among Pulmonary Tuberculosis Patients in Chiapas, Mexico: The Case of Los Altos Region

    Science.gov (United States)

    Nájera-Ortiz, J. C.; Sánchez-Pérez, H. J.; Ochoa-Díaz-López, H.; Leal-Fernández, G.; Navarro-Giné, A.

    2012-01-01

    Objective. To analyse survival in patients with pulmonary tuberculosis (PTB) and factors associated with such survival. Design. Study of a cohort of patients aged over 14 years diagnosed with PTB from January 1, 1998 to July 31, 2005. During 2004–2006 a home visit was made to each patient and, during 2008-2009, they were visited again. During these visits a follow-up interview was administered; when the patient had died, a verbal autopsy was conducted with family members. Statistical analysis consisted of survival tests, Kaplan-Meier log-rank test and Cox regression. Results. Of 305 studied patients, 68 had died due to PTB by the time of the first evaluation, 237 were followed-up for a second evaluation, and 10 of them had died of PTB. According to the Cox regression, age (over 45 years) and treatment duration (under six months) were associated with a poorer survival. When treatment duration was excluded, the association between poorer survival with age persisted, whereas with having been treated via DOTS strategy, was barely significant. Conclusions. In the studied area it is necessary that patients receive a complete treatment scheme, and to give priority to patients aged over 45 years. PMID:22701170

  20. The Poor Survival among Pulmonary Tuberculosis Patients in Chiapas, Mexico: The Case of Los Altos Region

    Directory of Open Access Journals (Sweden)

    J. C. Nájera-Ortiz

    2012-01-01

    Full Text Available Objective. To analyse survival in patients with pulmonary tuberculosis (PTB and factors associated with such survival. Design. Study of a cohort of patients aged over 14 years diagnosed with PTB from January 1, 1998 to July 31, 2005. During 2004–2006 a home visit was made to each patient and, during 2008-2009, they were visited again. During these visits a follow-up interview was administered; when the patient had died, a verbal autopsy was conducted with family members. Statistical analysis consisted of survival tests, Kaplan-Meier log-rank test and Cox regression. Results. Of 305 studied patients, 68 had died due to PTB by the time of the first evaluation, 237 were followed-up for a second evaluation, and 10 of them had died of PTB. According to the Cox regression, age (over 45 years and treatment duration (under six months were associated with a poorer survival. When treatment duration was excluded, the association between poorer survival with age persisted, whereas with having been treated via DOTS strategy, was barely significant. Conclusions. In the studied area it is necessary that patients receive a complete treatment scheme, and to give priority to patients aged over 45 years.

  1. Survival after early-stage breast cancer of women previously treated for depression

    DEFF Research Database (Denmark)

    Suppli, Nis Frederik Palm; Johansen, Christoffer; Kessing, Lars Vedel

    2017-01-01

    treatment of depression and risk of receiving nonguideline treatment of breast cancer were assessed in multivariable logistic regression analyses. We compared the overall survival, breast cancer-specific survival, and risk of death by suicide of women who were and were not treated for depression before......Purpose The aim of this nationwide, register-based cohort study was to determine whether women treated for depression before primary early-stage breast cancer are at increased risk for receiving treatment that is not in accordance with national guidelines and for poorer survival. Material...... and Methods We identified 45,325 women with early breast cancer diagnosed in Denmark from 1998 to 2011. Of these, 744 women (2%) had had a previous hospital contact (as an inpatient or outpatient) for depression and another 6,068 (13%) had been treated with antidepressants. Associations between previous...

  2. Survival of Sami cancer patients

    Directory of Open Access Journals (Sweden)

    Leena Soininen

    2012-07-01

    Full Text Available Objectives. The incidence of cancer among the indigenous Sami people of Northern Finland is lower than among the Finnish general population. The survival of Sami cancer patients is not known, and therefore it is the object of this study. Study design. The cohort consisted of 2,091 Sami and 4,161 non-Sami who lived on 31 December 1978 in the two Sami municipalities of Inari and Utsjoki, which are located in Northern Finland and are 300–500 km away from the nearest central hospital. The survival experience of Sami and non-Sami cancer patients diagnosed in this cohort during 1979–2009 was compared with that of the Finnish patients outside the cohort. Methods. The Sami and non-Sami cancer patients were matched to other Finnish cancer patients for gender, age and year of diagnosis and for the site of cancer. An additional matching was done for the stage at diagnosis. Cancer-specific survival analyses were made using the Kaplan–Meier method and Cox regression modelling. Results. There were 204 Sami and 391 non-Sami cancer cases in the cohort, 20,181 matched controls without matching with stage, and 7,874 stage-matched controls. In the cancer-specific analysis without stage variable, the hazard ratio for Sami was 1.05 (95% confidence interval 0.85–1.30 and for non-Sami 1.02 (0.86–1.20, indicating no difference between the survival of those groups and other patients in Finland. Likewise, when the same was done by also matching the stage, there was no difference in cancer survival. Conclusion. Long distances to medical care or Sami ethnicity have no influence on the cancer patient survival in Northern Finland.

  3. Instrumental variable estimation in a survival context

    DEFF Research Database (Denmark)

    Tchetgen Tchetgen, Eric J; Walter, Stefan; Vansteelandt, Stijn

    2015-01-01

    for regression analysis in a survival context, primarily under an additive hazards model, for which we describe 2 simple methods for estimating causal effects. The first method is a straightforward 2-stage regression approach analogous to 2-stage least squares commonly used for IV analysis in linear regression....... The IV approach is very well developed in the context of linear regression and also for certain generalized linear models with a nonlinear link function. However, IV methods are not as well developed for regression analysis with a censored survival outcome. In this article, we develop the IV approach....... In this approach, the fitted value from a first-stage regression of the exposure on the IV is entered in place of the exposure in the second-stage hazard model to recover a valid estimate of the treatment effect of interest. The second method is a so-called control function approach, which entails adding...

  4. Lung cancer incidence and survival among HIV-infected and uninfected women and men.

    Science.gov (United States)

    Hessol, Nancy A; Martínez-Maza, Otoniel; Levine, Alexandra M; Morris, Alison; Margolick, Joseph B; Cohen, Mardge H; Jacobson, Lisa P; Seaberg, Eric C

    2015-06-19

    To determine the lung cancer incidence and survival time among HIV-infected and uninfected women and men. Two longitudinal studies of HIV infection in the United States. Data from 2549 women in the Women's Interagency HIV Study (WIHS) and 4274 men in the Multicenter AIDS Cohort Study (MACS), all with a history of cigarette smoking, were analyzed. Lung cancer incidence rates and incidence rate ratios were calculated using Poisson regression analyses. Survival time was assessed using Kaplan-Meier and Cox proportional-hazard analyses. Thirty-seven women and 23 men developed lung cancer (46 HIV-infected and 14 HIV-uninfected) during study follow-up. In multivariable analyses, the factors that were found to be independently associated with a higher lung cancer incidence rate ratios were older age, less education, 10 or more pack-years of smoking, and a prior diagnosis of AIDS pneumonia (vs. HIV-uninfected women). In an adjusted Cox model that allowed different hazard functions for each cohort, a history of injection drug use was associated with shorter survival, and a lung cancer diagnosis after 2001 was associated with longer survival. In an adjusted Cox model restricted to HIV-infected participants, nadir CD4 lymphocyte cell count less than 200 was associated with shorter survival time. Our data suggest that pulmonary damage and inflammation associated with HIV infection may be causative for the increased risk of lung cancer. Encouraging and assisting younger HIV-infected smokers to quit and to sustain cessation of smoking is imperative to reduce the lung cancer burden in this population.

  5. Geographical variations in the use of cancer treatments are associated with survival of lung cancer patients

    DEFF Research Database (Denmark)

    Møller, Henrik; Coupland, Victoria H; Tataru, Daniela

    2018-01-01

    INTRODUCTION: Lung cancer outcomes in England are inferior to comparable countries. Patient or disease characteristics, healthcare-seeking behaviour, diagnostic pathways, and oncology service provision may contribute. We aimed to quantify associations between geographic variations in treatment...... and survival of patients in England. METHODS: We retrieved detailed cancer registration data to analyse the variation in survival of 176,225 lung cancer patients, diagnosed 2010-2014. We used Kaplan-Meier analysis and Cox proportional hazards regression to investigate survival in the two-year period following...... diagnosis. RESULTS: Survival improved over the period studied. The use of active treatment varied between geographical areas, with inter-quintile ranges of 9%-17% for surgical resection, 4%-13% for radical radiotherapy, and 22%-35% for chemotherapy. At 2 years, there were 188 potentially avoidable deaths...

  6. A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

    Science.gov (United States)

    Anderson, Carl A; McRae, Allan F; Visscher, Peter M

    2006-07-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

  7. Survival Patterns Among Newcomers To Franchising

    OpenAIRE

    Timothy Bates

    1997-01-01

    This study analyzes survival patterns among franchisee firms and establishments that began operations in 1986 and 1987. Differing methodologies and data bases are utilized to demonstrate that 1) franchises have higher survival rates than independents, and 2) franchises have lower survival rates than independent business formations. Analyses of corporate establishment data generate high franchisee survival rates relative to independents, while analyses of young firm data generate the opposite ...

  8. High serum uric acid concentration predicts poor survival in patients with breast cancer.

    Science.gov (United States)

    Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

    2017-10-01

    Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Comparison of Adjuvant Radiation Therapy Alone and Chemotherapy Alone in Surgically Resected Low-Grade Gliomas: Survival Analyses of 2253 Cases from the National Cancer Data Base.

    Science.gov (United States)

    Wu, Jing; Neale, Natalie; Huang, Yuqian; Bai, Harrison X; Li, Xuejun; Zhang, Zishu; Karakousis, Giorgos; Huang, Raymond; Zhang, Paul J; Tang, Lei; Xiao, Bo; Yang, Li

    2018-04-01

    It is becoming increasingly common to incorporate chemotherapy (CT) with radiotherapy (RT) in the treatment of low-grade gliomas (LGGs) after surgical resection. However, there is a lack of literature comparing survival of patients who underwent RT or CT alone. The U.S. National Cancer Data Base was used to identify patients with histologically confirmed, World Health Organization grade 2 gliomas who received either RT alone or CT alone after surgery from 2004 to 2013. Overall survival (OS) was evaluated by Kaplan-Meier analysis, multivariable Cox proportional hazard regression, and propensity-score-matched analysis. In total, 2253 patients with World Health Organization grade 2 gliomas were included, of whom 1466 (65.1%) received RT alone and 787 (34.9%) CT alone. The median OS was 98.9 months for the RT alone group and 125.8 months for the CT alone group. On multivariable analysis, CT alone was associated with a significant OS benefit compared with RT alone (hazard ratio [HR], 0.405; 95% confidence interval, 0.277-0.592; P < 0.001). On subgroup analyses, the survival advantage of CT alone over RT alone persisted across all age groups, and for the subtotal resection and biopsy groups, but not in the gross total resection group. In propensity-score-matched analysis, CT alone still showed significantly improved OS compared with RT alone (HR, 0.612; 95% confidence interval, 0.506-0.741; P < 0.001). Our results suggest that CT alone was independently associated with longer OS compared with RT alone in patients with LGGs who underwent surgery. Copyright © 2018 Elsevier Inc. All rights reserved.

  10. Mesothelin-specific Immune Responses Predict Survival of Patients With Brain Metastasis

    DEFF Research Database (Denmark)

    Zhenjiang, Liu; Rao, Martin; Luo, Xiaohua

    2017-01-01

    BACKGROUND: Patients with advanced malignancies, e.g. lung cancer, ovarian cancer or melanoma, frequently present with brain metastases. Clinical presentation and disease progression of cancer is in part shaped by the interaction of the immune system with malignant cells. Antigen-targeted immune ...... of the primary tumor origin. Analyses of immunological markers could potentially serve as prognostic markers in patients with brain metastases and help to select patients in need for adjunct, immunological, treatment strategies....... were tested for interferon gamma (IFN-γ) production, after which univariate and multivariate analyses (Cox stepwise regression model) were performed to identify independent clinical and immunological factors associated with patient survival. Patients were followed-up for at least 500days after surgery...

  11. The influence of sarcopenia on survival and surgical complications in ovarian cancer patients undergoing primary debulking surgery.

    Science.gov (United States)

    Rutten, I J G; Ubachs, J; Kruitwagen, R F P M; van Dijk, D P J; Beets-Tan, R G H; Massuger, L F A G; Olde Damink, S W M; Van Gorp, T

    2017-04-01

    Sarcopenia, severe skeletal muscle loss, has been identified as a prognostic factor in various malignancies. This study aims to investigate whether sarcopenia is associated with overall survival (OS) and surgical complications in patients with advanced ovarian cancer undergoing primary debulking surgery (PDS). Ovarian cancer patients (n = 216) treated with PDS were enrolled retrospectively. Total skeletal muscle surface area was measured on axial computed tomography at the level of the third lumbar vertebra. Optimum stratification was used to find the optimal skeletal muscle index cut-off to define sarcopenia (≤38.73 cm 2 /m 2 ). Cox-regression and Kaplan-Meier analysis were used to analyse the relationship between sarcopenia and OS. The effect of sarcopenia on the development of major surgical complications was studied with logistic regression. Kaplan-Meier analysis showed a significant survival disadvantage for patients with sarcopenia compared to patients without sarcopenia (p = 0.010). Sarcopenia univariably predicted OS (HR 1.536 (95% CI 1.105-2.134), p = 0.011) but was not significant in multivariable Cox-regression analysis (HR 1.362 (95% CI 0.968-1.916), p = 0.076). Significant predictors for OS in multivariable Cox-regression analysis were complete PDS, treatment in a specialised centre and the development of major complications. Sarcopenia was not predictive of major complications. Sarcopenia was not predictive of OS or major complications in ovarian cancer patients undergoing primary debulking surgery. However a strong trend towards a survival disadvantage for patients with sarcopenia was seen. Future prospective studies should focus on interventions to prevent or reverse sarcopenia and possibly increase ovarian cancer survival. Complete cytoreduction remains the strongest predictor of ovarian cancer survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights

  12. Analyses of potential factors affecting survival of juvenile salmonids volitionally passing through turbines at McNary and John Day Dams, Columbia River

    Science.gov (United States)

    Beeman, John; Hansel, Hal; Perry, Russell; Hockersmith, Eric; Sandford, Ben

    2011-01-01

    This report describes analyses of data from radio- or acoustic-tagged juvenile salmonids passing through hydro-dam turbines to determine factors affecting fish survival. The data were collected during a series of studies designed to estimate passage and survival probabilities at McNary (2002-09) and John Day (2002-03) Dams on the Columbia River during controlled experiments of structures or operations at spillways. Relatively few tagged fish passed turbines in any single study, but sample sizes generally were adequate for our analyses when data were combined from studies using common methods over a series of years. We used information-theoretic methods to evaluate biological, operational, and group covariates by creating models fitting linear (all covariates) or curvilinear (operational covariates only) functions to the data. Biological covariates included tag burden, weight, and water temperature; operational covariates included spill percentage, total discharge, hydraulic head, and turbine unit discharge; and group covariates included year, treatment, and photoperiod. Several interactions between the variables also were considered. Support of covariates by the data was assessed by comparing the Akaike Information Criterion of competing models. The analyses were conducted because there was a lack of information about factors affecting survival of fish passing turbines volitionally and the data were available from past studies. The depth of acclimation, tag size relative to fish size (tag burden), turbine unit discharge, and area of entry into the turbine intake have been shown to affect turbine passage survival of juvenile salmonids in other studies. This study indicates that turbine passage survival of the study fish was primarily affected by biological covariates rather than operational covariates. A negative effect of tag burden was strongly supported in data from yearling Chinook salmon at John Day and McNary dams, but not for subyearling Chinook salmon or

  13. Geographical variations in the use of cancer treatments are associated with survival of lung cancer patients

    DEFF Research Database (Denmark)

    Møller, Henrik; Coupland, Victoria H; Tataru, Daniela

    2018-01-01

    INTRODUCTION: Lung cancer outcomes in England are inferior to comparable countries. Patient or disease characteristics, healthcare-seeking behaviour, diagnostic pathways, and oncology service provision may contribute. We aimed to quantify associations between geographic variations in treatment...... and survival of patients in England. METHODS: We retrieved detailed cancer registration data to analyse the variation in survival of 176,225 lung cancer patients, diagnosed 2010-2014. We used Kaplan-Meier analysis and Cox proportional hazards regression to investigate survival in the two-year period following...... to statistical adjustments for age, sex, socio-economic status, performance status and co-morbidity. CONCLUSION: The extent of use of different treatment modalities varies between geographical areas in England. These variations are not attributable to measurable patient and tumour characteristics, and more...

  14. Disparities in survival after Hodgkin lymphoma: a population-based study

    Science.gov (United States)

    Keegan, Theresa H.M.; Clarke, Christina A.; Chang, Ellen T.; Shema, Sarah J.; Glaser, Sally L.

    2009-01-01

    Survival after Hodgkin lymphoma (HL) is generally favorable, but may vary by patient demographic characteristics. The authors examined HL survival according to race/ethnicity and neighborhood socioeconomic status (SES), determined from residential census block group at diagnosis. For 12,492 classical HL patients ≥15 years diagnosed in California during 1988-2006 and followed through 2007, we determined risk of overall and HL-specific death using Cox proportional hazards regression; analyses were stratified by age and Ann Arbor stage. Irrespective of disease stage, patients with lower neighborhood SES had worse overall and HL-specific survival than patients with higher SES. Patients with the lowest quintile of neighborhood SES had a 64% (patients aged 15-44 years) and 36% (≥45 years) increased risk of HL-death compared to patients with the highest quintile of SES; SES results were similar for overall survival. Even after adjustment for neighborhood SES, blacks and Hispanics had increased risks of HL-death 74% and 43% (15-44 years) and 40% and 17% (≥45 years), respectively, higher than white patients. The racial/ethnic differences in survival were evident for all stages of disease. These data provide evidence for substantial, and probably remediable, racial/ethnic and neighborhood SES disparities in HL outcomes. PMID:19557531

  15. Is there a difference in survival between men and women suffering in-hospital cardiac arrest?

    Science.gov (United States)

    Israelsson, Johan; Persson, Carina; Strömberg, Anna; Arestedt, Kristofer

    2014-01-01

    To describe in-hospital cardiac arrest (CA) events with regard to sex and to investigate if sex is associated with survival. Previous studies exploring differences between sexes are incongruent with regard to clinical outcomes. In order to provide equality and improve care, further investigations into these aspects are warranted. This registry study included 286 CAs. To investigate if sex was associated with survival, logistic regression analyses were performed. The proportion of CA with a resuscitation attempt compared to CA without resuscitation was higher among men. There were no associations between sex and survival when controlling for previously known predictors and interaction effects. Sex does not appear to be a predictor for survival among patients suffering CA where resuscitation is attempted. The difference regarding proportion of resuscitation attempts requires more attention. It is important to consider possible interaction effects when studying the sex perspective. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Primary tumor regression speed after radiotherapy and its prognostic significance in nasopharyngeal carcinoma: a retrospective study

    International Nuclear Information System (INIS)

    Zhang, Ning; Liu, Dong-Sheng; Chen, Yong; Liang, Shao-Bo; Deng, Yan-Ming; Lu, Rui-Liang; Chen, Hai-Yang; Zhao, Hai; Lv, Zhi-Qian; Liang, Shao-Qiang; Yang, Lin

    2014-01-01

    To observe the primary tumor (PT) regression speed after radiotherapy (RT) in nasopharyngeal carcinoma (NPC) and evaluate its prognostic significance. One hundred and eighty-eight consecutive newly diagnosed NPC patients were reviewed retrospectively. All patients underwent magnetic resonance imaging and fiberscope examination of the nasopharynx before RT, during RT when the accumulated dose was 46–50 Gy, at the end of RT, and 3–4 months after RT. Of 188 patients, 40.4% had complete response of PT (CRPT), 44.7% had partial response of PT (PRPT), and 14.9% had stable disease of PT (SDPT) at the end of RT. The 5-year overall survival (OS) rates for patients with CRPT, PRPT, and SDPT at the end of RT were 84.0%, 70.7%, and 44.3%, respectively (P < 0.001, hazard ratio [HR] = 2.177, 95% confidence interval [CI] = 1.480-3.202). The 5-year failure-free survival (FFS) and distant metastasis-free survival (DMFS) rates also differed significantly (87.8% vs. 74.3% vs. 52.7%, P = 0.001, HR = 2.148, 95% CI, 1.384-3.333; 91.7% vs. 84.7% vs. 66.1%, P = 0.004, HR = 2.252, 95% CI = 1.296-3.912). The 5-year local relapse–free survival (LRFS) rates were not significantly different (95.8% vs. 86.0% vs. 81.8%, P = 0.137, HR = 1.975, 95% CI, 0.976-3.995). By multivariate analyses, the PT regression speed at the end of RT was the only independent prognostic factor of OS, FFS, and DMFS (P < 0.001, P = 0.001, and P = 0.004, respectively). The 5-year FFS rates for patients with CRPT during RT and CRPT only at the end of RT were 80.2% and 97.1%, respectively (P = 0.033). For patients with persistent PT at the end of RT, the 5-year LRFS rates of patients without and with boost irradiation were 87.1% and 84.6%, respectively (P = 0.812). PT regression speed at the end of RT was an independent prognostic factor of OS, FFS, and DMFS in NPC patients. Immediate strengthening treatment may be provided to patients with poor tumor regression at the end of RT

  17. PROGNOSTIC FACTORS FOR SURVIVAL IN PATIENTS WITH METASTATIC COLORECTAL CANCER TREATED WITH FIRST - LINE CHEMOTHERAPY

    Directory of Open Access Journals (Sweden)

    Deyan Davidov

    2017-05-01

    Full Text Available Objective: The aim of this study was to investigate the prognostic significance for survival of certain clinical and pathological factors in patients with advanced or metastatic colorectal carcinoma (CRC treated with first- line chemotherapy. Methods: From 2002 to 2011 seventy- four consecutive patients with advanced or metastatic CRC, treated in UMHAT- Dr. G. Stranski, Department of Medical Oncology entered the study. Some patient’s characteristics, hematological and pathological parameters, were evaluated for their role as predictors of overall survival. The therapeutic regimens included FOLFOX or FOlFIRI. Survival analysis was evaluated by Kaplan- Meier test. The influence of pretreatment characteristics as prognostic factor for survival was analyzed using multivariate stepwise Cox regression analyses. Results: In multivariate analysis a significant correlation was exhibited between survival, poor performance status and multiple sites of metastasis. Variables significantly associated with overall survival in univariate analysis were performance status>1, thrombocytosis, anemia and number of metastatic sites >1. Conclusion: These results indicated that poor performance status, anemia, thrombocytosis as well as multiple site of metastasis could be useful prognostic factors in patients with metastatic CRC.

  18. Clustered survival data with left-truncation

    DEFF Research Database (Denmark)

    Eriksson, Frank; Martinussen, Torben; Scheike, Thomas H.

    2015-01-01

    Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry....... Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties...

  19. Biostatistics series module 9: Survival analysis

    Directory of Open Access Journals (Sweden)

    Avijit Hazra

    2017-01-01

    Full Text Available Survival analysis is concerned with “time to event“ data. Conventionally, it dealt with cancer death as the event in question, but it can handle any event occurring over a time frame, and this need not be always adverse in nature. When the outcome of a study is the time to an event, it is often not possible to wait until the event in question has happened to all the subjects, for example, until all are dead. In addition, subjects may leave the study prematurely. Such situations lead to what is called censored observations as complete information is not available for these subjects. The data set is thus an assemblage of times to the event in question and times after which no more information on the individual is available. Survival analysis methods are the only techniques capable of handling censored observations without treating them as missing data. They also make no assumption regarding normal distribution of time to event data. Descriptive methods for exploring survival times in a sample include life table and Kaplan–Meier techniques as well as various kinds of distribution fitting as advanced modeling techniques. The Kaplan–Meier cumulative survival probability over time plot has become the signature plot for biomedical survival analysis. Several techniques are available for comparing the survival experience in two or more groups – the log-rank test is popularly used. This test can also be used to produce an odds ratio as an estimate of risk of the event in the test group; this is called hazard ratio (HR. Limitations of the traditional log-rank test have led to various modifications and enhancements. Finally, survival analysis offers different regression models for estimating the impact of multiple predictors on survival. Cox's proportional hazard model is the most general of the regression methods that allows the hazard function to be modeled on a set of explanatory variables without making restrictive assumptions concerning the

  20. Accelerated failure time regression for backward recurrence times and current durations

    DEFF Research Database (Denmark)

    Keiding, N; Fine, J P; Hansen, O H

    2011-01-01

    Backward recurrence times in stationary renewal processes and current durations in dynamic populations observed at a cross-section may yield estimates of underlying interarrival times or survival distributions under suitable stationarity assumptions. Regression models have been proposed for these......Backward recurrence times in stationary renewal processes and current durations in dynamic populations observed at a cross-section may yield estimates of underlying interarrival times or survival distributions under suitable stationarity assumptions. Regression models have been proposed...... for these situations, but accelerated failure time models have the particularly attractive feature that they are preserved when going from the backward recurrence times to the underlying survival distribution of interest. This simple fact has recently been noticed in a sociological context and is here illustrated...... by a study of current duration of time to pregnancy...

  1. Applied survival analysis using R

    CERN Document Server

    Moore, Dirk F

    2016-01-01

    Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics...

  2. Does exclusion of cancers registered only from death-certificate information diminish socio-demographic disparities in recorded survival?

    Science.gov (United States)

    Tervonen, Hanna E; Roder, David; Morrell, Stephen; You, Hui; Currow, David C

    2017-06-01

    Death Certificate Only (DCO) cancer cases are commonly excluded from survival analyses due to unknown survival time. This study examines whether socio-demographic factors are associated with DCO diagnosis, and the potential effects of excluding DCO cases on socio-demographic cancer survival disparities in NSW, Australia. NSW Cancer Registry data for cases diagnosed in 2000-2008 were used in this study. Logistic regression was used to estimate the odds of DCO registration by socio-demographic sub-group (socio-economic disadvantage, residential remoteness, country of birth, age at diagnosis). Cox proportional hazard regression was used to estimate the probability of death from cancer by socio-demographic subgroup when DCO cases were included and excluded from analyses. DCO cases consisted of 1.5% (n=4336) of all cases (n=299,651). DCO diagnosis was associated with living in socio-economically disadvantaged areas (most disadvantaged compared with least disadvantaged quintile: odds ratio OR 1.25, 95%CI 1.12-1.40), living in inner regional (OR 1.16, 95%CI 1.08-1.25) or remote areas (OR 1.48, 95%CI 1.01-2.19), having an unknown country of birth (OR 1.63, 95%CI 1.47-1.81) and older age. Including or excluding DCO cases had no significant impact on hazard ratios for cancer death by socio-economic disadvantage quintile or remoteness category, and only a minor impact on hazard ratios by age. Socio-demographic factors were associated with DCO diagnosis in NSW. However, socio-demographic cancer survival disparities remained unchanged or varied only slightly irrespective of including/excluding DCO cases. Further research could examine the upper limits of DCO proportions that significantly alter estimated cancer survival differentials if DCOs are excluded. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

  3. Analyses of Developmental Rate Isomorphy in Ectotherms: Introducing the Dirichlet Regression.

    Directory of Open Access Journals (Sweden)

    David S Boukal

    Full Text Available Temperature drives development in insects and other ectotherms because their metabolic rate and growth depends directly on thermal conditions. However, relative durations of successive ontogenetic stages often remain nearly constant across a substantial range of temperatures. This pattern, termed 'developmental rate isomorphy' (DRI in insects, appears to be widespread and reported departures from DRI are generally very small. We show that these conclusions may be due to the caveats hidden in the statistical methods currently used to study DRI. Because the DRI concept is inherently based on proportional data, we propose that Dirichlet regression applied to individual-level data is an appropriate statistical method to critically assess DRI. As a case study we analyze data on five aquatic and four terrestrial insect species. We find that results obtained by Dirichlet regression are consistent with DRI violation in at least eight of the studied species, although standard analysis detects significant departure from DRI in only four of them. Moreover, the departures from DRI detected by Dirichlet regression are consistently much larger than previously reported. The proposed framework can also be used to infer whether observed departures from DRI reflect life history adaptations to size- or stage-dependent effects of varying temperature. Our results indicate that the concept of DRI in insects and other ectotherms should be critically re-evaluated and put in a wider context, including the concept of 'equiproportional development' developed for copepods.

  4. Survival and clinical outcome of dogs with ischaemic stroke

    DEFF Research Database (Denmark)

    Gredal, Hanne Birgit; Toft, Nils; Westrup, Ulrik

    2013-01-01

    The objectives of the present study were to investigate survival time, possible predictors of survival and clinical outcome in dogs with ischaemic stroke. A retrospective study of dogs with a previous diagnosis of ischaemic stroke diagnosed by magnetic resonance imaging (MRI) was performed....... The association between survival and the hypothesised risk factors was examined using univariable exact logistic regression. Survival was examined using Kaplan-Meier and Cox regression. Twenty-two dogs were identified. Five dogs (23%) died within the first 30days of the stroke event. Median survival in 30-day...... survivors was 505days. Four dogs (18%) were still alive by the end of the study. Right-sided lesions posed a significantly increased risk of mortality with a median survival time in dogs with right-sided lesions of 24days vs. 602days in dogs with left sided lesions (P=0.006). Clinical outcome was considered...

  5. ER and PR expression and survival after endometrial cancer.

    Science.gov (United States)

    Smith, Deborah; Stewart, Colin J R; Clarke, Edward M; Lose, Felicity; Davies, Claire; Armes, Jane; Obermair, Andreas; Brennan, Donal; Webb, Penelope M; Nagle, Christina M; Spurdle, Amanda B

    2018-02-01

    To measure association between endometrial carcinoma ER and PR status and endometrial cancer (EC) survival, accounting for inter-observer variation. The intensity and proportion of tumor cell expression of ER and PR in ECs were assessed independently and semi-quantitatively by two pathologists using digital images of duplicate tumor tissue microarrays (TMAs). Cases with inconsistent initial assessment were reviewed and final scoring agreed. The association between overall and EC-specific survival and hormone receptor expression (intensity, proportion and combined) was assessed using Cox regression analysis. The C-index was used to evaluate model discrimination with addition of ER and PR status. Tumor ER and PR analysis was possible in 659 TMAs from 255 patients, and in 459 TMAs from 243 patients, respectively. Initial ER and PR scoring was consistent in 82% and 80% of cases, respectively. In multivariate analyses decreased ER and PR expression was associated with increased tumor-related mortality. Associations reached statistical significance for ER proportion score (P=0.05), ER intensity score (P=0.003), and PR combined score (P=0.04). Decreased expression of combined ER/PR expression was associated with poorer EC-specific survival than decreased expression of either hormone receptor alone (P=0.005). However, hormone receptor status did not significantly improve mortality prediction in individual cases. ER and PR expression combined, using cut-points that capture variation in scoring and across cores, is significantly associated with EC-specific survival in analyses adjusting for known prognostic factors. However, at the individual level, ER and PR expression does not improve mortality prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Outcome of cardiopulmonary resuscitation - predictors of survival

    International Nuclear Information System (INIS)

    Ishtiaq, O.; Iqbal, M.; Zubair, M.; Qayyum, R.; Adil, M.

    2008-01-01

    To assess the outcomes of patients undergoing cardiopulmonary resuscitation (CPR). Data were collected retrospectively of all adult patients who underwent CPR. Clinical outcomes of interest were survival at the end of CPR and survival at discharge from hospital. Factors associated with survival were evaluated using logistic regression analysis. Of the 159 patients included, 55 (35%) were alive at the end of CPR and 17 (11%) were discharged alive from the hospital. At the end of CPR, univariate logistic regression analysis found the following factors associated with survival: cardiac arrest within hospital as compared to outside the hospital (odds ratio = 2.8, 95% CI = 1.27-6.20, p-value = 0.01), both cardiac and pulmonary arrest as compared to either cardiac or pulmonary arrest (odds ratio = 0.37, 95% CI = 0.19- 0.73, p-value = 0.004), asystole as cardiac rhythm at presentation (odds ratio = 0.47, 95% CI = 0.24-0.93, p-value = 0.03), and total atropine dose given during CPR (odds ratio = 0.78, 95% CI = 0.62-0.97, p-value = 0.02). In multivariate logistic regression, cardiac arrest within hospital (odds ratio = 2.52, 95% CI = 1.06-5.99, p-value = 0.04) and both cardiac and pulmonary arrest as compared to cardiac or pulmonary arrest (odds ratio = 0.44, 95% CI = 0.21-0.91, p-value = 0.03) were associated with survival at the end of CPR. At the time of discharge from hospital, univariate logistic regression analysis found following factors that were associated with survival: cardiac arrest within hospital (odds ratio = 8.4, 95% CI = 1.09-65.64, p-value = 0.04), duration of CPR (odds ratio = 0.91, 95% CI = 0.85-0.96, p-value = 0.001), and total atropine dose given during CPR (odds ratio = 0.68, 95% CI = 0.47-0.99, p-value = 0.05). In multivariate logistic regression analysis cardiac arrest within hospital (odds ratio 8.69, 95% CI = 1.01-74.6, p-value = 0.05) and duration of CPR (odds ratio 0.92, 95% CI = 0.87-0.98, p-value = 0.01) were associated with survival at

  7. Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

    OpenAIRE

    KELEŞ, Taliha; ALTUN, Murat

    2016-01-01

    Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

  8. Factors affecting survival of women diagnosed with breast cancer in El-Minia Governorate, Egypt.

    Science.gov (United States)

    Seedhom, Amany Edward; Kamal, Nashwa Nabil

    2011-07-01

    This study was conducted to determine breast cancer survival time and the association between breast cancer survival and socio-demographic and pathologic factors among women, in El-Minia, Egypt. While there has been much researches regarding prognostic factors for breast cancer but the majority of these studies were from developed countries. El-Minia has a population of approximately 4 million. To date, no research has been performed to determine breast cancer survival and the factors affecting it in El-minia. This retrospective study used data obtained from the cancer registry in the National Institute of Oncology in El-Minia and included 1207 women diagnosed with first primary breast cancer between 1(st) January 2005 and 31(st) December 2009 and followed to 30(th) June 2010. The association between survival and sociodemographic and pathological factors and distant metastasis at diagnosis, and treatment options was investigated using unifactorial chi-square test and multi-factorial (Cox regression) analyses. Kaplan-Meier analysis was used to compare survival time among different groups. Median survival time was 83.8 ± 3.2. Cox regression showed that high vs low educational level (Hazard ratio (HR)= 0.35, 95% CI; 0.27-0.46), metastases to bone (HR = 3.22, 95% CI: 1.71-6.05), metastases to lung (HR= 2.314, 95% CI: 1.225-4.373), tumor size (≤ 2 cm vs ≥ 5 cm: HR = 1.4, 95% CI: 1.1-1.8) and number of involved nodes (1 vs > 10 HR = 5.21, 95%CI: 3.1-9.01) were significantly related to survival. The results showed the need to develop screening programs and standardized treatment regimens in a tax-funded health care system.

  9. Prognostic value of tumor regression evaluated after first course of radiotherapy for anal canal cancer

    International Nuclear Information System (INIS)

    Chapet, Olivier; Gerard, Jean-Pierre; Riche, Benjamin; Alessio, Annunziato; Mornex, Francoise; Romestaing, Pascale

    2005-01-01

    Purpose: To evaluate whether the tumor response after an initial course of irradiation predicts for colostomy-free survival and overall survival in patients with anal canal cancer. Methods and Materials: Between 1980 and 1998, 252 patients were treated by pelvic external-beam radiotherapy (EBRT) followed by a brachytherapy boost in 218 or EBRT in 34. EBRT was combined with chemotherapy in 168 patients. An evaluation of tumor regression, before the boost, was available for 221 patients. They were divided into four groups according to the tumor response: 80% but 80% vs. ≤80%. The group with a T3-T4 lesion and tumor regression ≤80% had the poorest overall (52.8% ± 12.3%), disease-free (19.9% ± 9.9%), and colostomy-free survival (24.8% ± 11.2%) rates. Conclusion: The amount of tumor regression before EBRT or brachytherapy boost is a strong prognostic factor of disease control without colostomy. When regression is ≤80% in patients with an initial T3-T4 lesion, the use of conservative RT should be carefully evaluated because of the very poor disease-free and colostomy-free survival

  10. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD)-Level Meta-Regression Analyses

    Science.gov (United States)

    Cashman, Kevin D.; Ritz, Christian; Kiely, Mairead

    2017-01-01

    Dietary Reference Values (DRVs) for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs) are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD)-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years) of the vitamin D intake–serum 25-hydroxyvitamin D (25(OH)D) dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OH)D concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years) from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OH)D >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OH)D to vitamin D intake. PMID:28481259

  11. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD-Level Meta-Regression Analyses

    Directory of Open Access Journals (Sweden)

    Kevin D. Cashman

    2017-05-01

    Full Text Available Dietary Reference Values (DRVs for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years of the vitamin D intake–serum 25-hydroxyvitamin D (25(OHD dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OHD concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OHD >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OHD to vitamin D intake.

  12. Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses.

    Directory of Open Access Journals (Sweden)

    Christopher Rentsch

    Full Text Available BACKGROUND: Variable selection is an important step in building a multivariate regression model for which several methods and statistical packages are available. A comprehensive approach for variable selection in complex multivariate regression analyses within HIV cohorts is explored by utilizing both epidemiological and biostatistical procedures. METHODS: Three different methods for variable selection were illustrated in a study comparing survival time between subjects in the Department of Defense's National History Study and the Atlanta Veterans Affairs Medical Center's HIV Atlanta VA Cohort Study. The first two methods were stepwise selection procedures, based either on significance tests (Score test, or on information theory (Akaike Information Criterion, while the third method employed a Bayesian argument (Bayesian Model Averaging. RESULTS: All three methods resulted in a similar parsimonious survival model. Three of the covariates previously used in the multivariate model were not included in the final model suggested by the three approaches. When comparing the parsimonious model to the previously published model, there was evidence of less variance in the main survival estimates. CONCLUSIONS: The variable selection approaches considered in this study allowed building a model based on significance tests, on an information criterion, and on averaging models using their posterior probabilities. A parsimonious model that balanced these three approaches was found to provide a better fit than the previously reported model.

  13. Survival Analysis of Factors Influencing Cyclic Fatigue of Nickel-Titanium Endodontic Instruments

    Directory of Open Access Journals (Sweden)

    Eva Fišerová

    2015-01-01

    Full Text Available Objective. The aim of this study was to validate a survival analysis assessing the effect of type of rotary system, canal curvature, and instrument size on cyclic resistance. Materials and Methods. Cyclic fatigue testing was carried out in stainless steel artificial canals with radii of curvature of 3 or 5 mm and the angle of curvature of 60 degrees. All the instruments were new and 25 mm in working length, and ISO colour coding indicated the instrument size (yellow for size 20; red for size 25. Wizard Navigator instruments, Mtwo instruments, ProTaper instruments, and Revo-S instruments were passively rotated at 250 rotations per minute, and the time fracture was being recorded. Subsequently, fractographic analysis of broken tips was performed by scanning electron microscope. The data were then analysed by the Kaplan-Meier estimator of the survival function, the Cox proportional hazards model, the Wald test for regression covariates, and the Wald test for significance of regression model. Conclusion. The lifespan registered for the tested instruments was Mtwo > Wizard Navigator > Revo-S > ProTaper; 5 mm radius > 3 mm radius; and yellow > red in ISO colour coding system.

  14. Treatment algorithm based on the multivariate survival analyses in patients with advanced hepatocellular carcinoma treated with trans-arterial chemoembolization.

    Directory of Open Access Journals (Sweden)

    Hasmukh J Prajapati

    Full Text Available To develop the treatment algorithm from multivariate survival analyses (MVA in patients with Barcelona clinic liver cancer (BCLC C (advanced Hepatocellular carcinoma (HCC patients treated with Trans-arterial Chemoembolization (TACE.Consecutive unresectable and non-tranplantable patients with advanced HCC, who received DEB TACE were studied. A total of 238 patients (mean age, 62.4yrs was included in the study. Survivals were analyzed according to different parameters from the time of the 1st DEB TACE. Kaplan Meier and Cox Proportional Hazard model were used for survival analysis. The SS was constructed from MVA and named BCLC C HCC Prognostic (BCHP staging system (SS.Overall median survival (OS was 16.2 months. In HCC patients with venous thrombosis (VT of large vein [main portal vein (PV, right or left PV, hepatic vein, inferior vena cava] (22.7% versus small vein (segmental/subsegmental PV (9.7% versus no VT had OSs of 6.4 months versus 20 months versus 22.8 months respectively (p<0.001. On MVA, the significant independent prognostic factors (PFs of survival were CP class, eastern cooperative oncology group (ECOG performance status (PS, single HCC<5 cm, site of VT, metastases, serum creatinine and serum alpha-feto protein. Based on these PFs, the BCHP staging system was constructed. The OSs of stages I, II and III were 28.4 months, 11.8 months and 2.4 months accordingly (p<0.001. The treatment plan was proposed according to the different stages.On MVA of patients with advanced HCC treated with TACE, significant independent prognostic factors (PFs of survival were CP class, ECOG PS, single HCC<5 cm or others, site of VT, metastases, serum creatinine and serum alpha-feto protein. New BCHP SS was proposed based on MVA data to identify the suitable advanced HCC patients for TACE treatments.

  15. Better midterm survival in women after transcatheter aortic valve implantation.

    Science.gov (United States)

    Takagi, Hisato; Umemoto, Takuya

    2017-08-01

    In previous meta-analyses demonstrating better midterm overall survival in women undergoing transcatheter aortic valve implantation (TAVI), unadjusted risk and odds ratios were combined. To determine whether female gender is independently associated with better survival after TAVI, we performed a meta-analysis pooling adjusted hazard ratios (HRs) based on multivariate Cox proportional hazard regression. MEDLINE and EMBASE were searched through September 2015 using PubMed and OVID. Studies considered for inclusion met the following criteria: the study population was patients undergoing TAVI; and main outcomes included midterm (mean or median ≥6 months) overall survival or all-cause mortality in women and men. An unadjusted and/or adjusted HR of all-cause mortality for women versus men was abstracted from each individual study. Of 1347 potentially relevant articles screened initially, 16 reports of eligible studies were identified and included. A primary meta-analysis of the 9 adjusted HRs demonstrated a significantly better midterm overall survival in women than men (N.=6891; HR=0.80; 95% confidence interval [CI]: 0.65 to 0.97; P=0.03). A secondary meta-analysis adding 5 statistically non-significant unadjusted HR also indicated better survival in women (N.=8645; HR=0.83; 95% CI: 0.72 to 0.96; P=0.01). Although statistical tests for the primary meta-analysis revealed funnel plot asymmetry in favor of women, the secondary meta-analysis produced a symmetrical funnel plot. Female gender may be independently associated with better midterm overall survival after TAVI.

  16. Analysing inequalities in Germany a structured additive distributional regression approach

    CERN Document Server

    Silbersdorff, Alexander

    2017-01-01

    This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals’ realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.

  17. Age of blood and survival after massive transfusion.

    Science.gov (United States)

    Sanz, C C; Pereira, A

    2017-11-01

    Massive transfusion is the clinical scenario where the presumed adverse effects of stored blood are expected to be more evident because the whole patient's blood volume is replaced by stored blood. To analyse the association between age of transfused red blood cells (RBC) and survival in massively transfused patients. In this retrospective study, clinical and transfusion data of all consecutive patients massively transfused between 2008 and 2014 in a large, tertiary-care hospital were electronically extracted from the Transfusion Service database and the patients' electronic medical records. Prognostic factors for in-hospital mortality were investigated by multivariate logistic regression. A total of 689 consecutive patients were analysed (median age: 61 years; 65% males) and 272 died in-hospital. Projected mortality at 2, 30, and 90 days was 21%, 35% and 45%, respectively. The odds ratio (OR) for in-hospital mortality among patients who survived after the 2nd day increased with patient age (OR: 1.037, 95% CI: 1.021-1.054; per year Ptransfused in the first 48hours (OR: 1.060; 95% CI: 1.038-1.020 per unit; Ptransfusion was associated with a higher proportion of old RBCs transfused in the first 48hours. Other factors associated with poor prognosis were older patient's age and larger volumes of transfused RBCs. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  18. Population-based study of survival for women with serous cancer of the ovary, fallopian tube, peritoneum or undesignated origin - on behalf of the Swedish gynecological cancer group (SweGCG).

    Science.gov (United States)

    Dahm-Kähler, Pernilla; Borgfeldt, Christer; Holmberg, Erik; Staf, Christian; Falconer, Henrik; Bjurberg, Maria; Kjölhede, Preben; Rosenberg, Per; Stålberg, Karin; Högberg, Thomas; Åvall-Lundqvist, Elisabeth

    2017-01-01

    The aim of the study was to determine survival outcome in patients with serous cancer in the ovary, fallopian tube, peritoneum and of undesignated origin. Nation-wide population-based study of women≥18years with histologically verified non-uterine serous cancer, included in the Swedish Quality Registry for primary cancer of the ovary, fallopian tube and peritoneum diagnosed 2009-2013. Relative survival (RS) was estimated using the Ederer II method. Simple and multivariable analyses were estimated by Poisson regression models. Of 5627 women identified, 1246 (22%) had borderline tumors and 4381 had malignant tumors. In total, 2359 women had serous cancer; 71% originated in the ovary (OC), 9% in the fallopian tube (FTC), 9% in the peritoneum (PPC) and 11% at an undesignated primary site (UPS). Estimated RS at 5-years was 37%; for FTC 54%, 40% for OC, 34% for PPC and 13% for UPS. In multivariable regression analyses restricted to women who had undergone primary or interval debulking surgery for OC, FTC and PPC, site of origin was not independently associated with survival. Significant associations with worse survival were found for advanced stages (RR 2.63, Pcancer at UPS than for ovarian, fallopian tube and peritoneal cancer. Serous cancer at UPS needs to be addressed when reporting and comparing survival rates of ovarian cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. The influence of marital status on the stage at diagnosis, treatment, and survival of adult patients with gastric cancer: a population-based study.

    Science.gov (United States)

    Zhang, Jieyun; Gan, Lu; Wu, Zhenhua; Yan, Shican; Liu, Xiyu; Guo, Weijian

    2017-04-04

    Marital status was reported as a prognostic factor in many cancers. However, its role in gastric cancer (GC) hasn't been thoroughly explored. In this study, we aimed to investigate the effect of marital status on survival, stage, treatment, and survival in subgroups. We used the Surveillance, Epidemiology and End Results (SEER) database and identified 16910 GC patients. These patients were categorized into married (58.44%) and unmarred (41.56%) groups. Pearson chi-square, Wilcoxon-Mann-Whitney, Log-rank, multivariate Cox regression, univariate and multivariate binomial or multinomial logistic regression analysis were used in our analysis. Subgroup analyses of married versus unmarried patients were summarized in a forest plot. Married patients had better 5-year overall survival (OS) (32.09% VS 24.61%, PVS 32.79%, Punmarried ones. Then we studied several underlying mechanisms. Firstly, married patients weren't in earlier stage at diagnosis (P=0.159). Secondly, married patients were more likely to receive surgery (P unmarried. Thirdly, in subgroup analyses, married patients still had survival advantage in subgroups with stage II-IV and no radiotherapy. These results showed that marital status was an independently prognostic factor for both OS and CSS in GC patients. Undertreatment and lack of social support in unmarried patients were potential explanations. With the knowledge of heterogeneous effects of marriage in subgroups, we can target unmarried patients with better social support, especially who are diagnosed at late stage and undergo no treatment.

  20. Time dependent ethnic convergence in colorectal cancer survival in hawaii

    Directory of Open Access Journals (Sweden)

    Hundahl Scott A

    2003-02-01

    Full Text Available Abstract Background Although colorectal cancer death rates have been declining, this trend is not consistent across all ethnic groups. Biological, environmental, behavioral and socioeconomic explanations exist, but the reason for this discrepancy remains inconclusive. We examined the hypothesis that improved cancer screening across all ethnic groups will reduce ethnic differences in colorectal cancer survival. Methods Through the Hawaii Tumor Registry 16,424 patients diagnosed with colorectal cancer were identified during the years 1960–2000. Cox regression analyses were performed for each of three cohorts stratified by ethnicity (Caucasian, Japanese, Hawaiian, Filipino, and Chinese. The models included stage of diagnosis, year of diagnosis, age, and sex as predictors of survival. Results Mortality rates improved significantly for all ethnic groups. Moreover, with the exception of Hawaiians, rates for all ethnic groups converged over time. Persistently lower survival for Hawaiians appeared linked with more cancer treatment. Conclusion Ethnic disparities in colorectal cancer mortality rates appear primarily the result of differential utilization of health care. If modern screening procedures can be provided equally to all ethnic groups, ethnic outcome differences can be virtually eliminated.

  1. Outcome and histopathologic regression in oral squamous cell carcinoma after preoperative radiochemotherapy

    International Nuclear Information System (INIS)

    Driemel, Oliver; Ettl, Tobias; Reichert, Torsten E.; Koelbl, Oliver; Dresp, Bernd V.; Reuther, Juergen; Pistner, Hans

    2009-01-01

    Background and purpose: preoperative radiochemotherapy has been reported to enhance tumor response and to improve long-term survival in advanced squamous cell carcinoma of the head and neck. This retrospective study evaluates regression rate and long-term survival in 228 patients with primary oral squamous cell carcinoma treated by neoadjuvant radiochemotherapy and radical surgery. Patients and methods: all patients with biopsy-proven, resectable oral squamous cell carcinoma - TNM stages II-IV without distant metastasis - received preoperative treatment consisting of fractioned irradiation of the primary and the regional lymph nodes with a total dose of 40 Gy and additional cisplatin (n = 160) or carboplatin (n = 68) during the 1st week of treatment. Radical surgery and neck dissection followed after a delay of 10-14 days. The study only included cases with histologically negative resection margins. Results: after a median follow-up of 5.2 years, 53 patients (23.2%) had experienced local-regional recurrence. The median 2-year disease-specific survival (DSS) rate was 86.2%. 5-year DSS and 10-year DSS were 76.3% and 66.7%, respectively. Complete histological local tumor regression after surgery (ypTO) was observed in 50 patients (21.9%) and was independent of pretreatment tumor classification. Uni- and multivariate survival analysis revealed that ypT- and ypN-stage were the most decisive predictors for DSS. Conclusion: preoperative radiochemotherapy with cisplatin/carboplatin followed by radical surgery attains favorable long-term survival rates. This applies especially to cases with complete histological tumor regression after radiochemotherapy, which can be assumed for one of five patients. (orig.)

  2. Total Laryngectomy Versus Larynx Preservation for T4a Larynx Cancer: Patterns of Care and Survival Outcomes

    International Nuclear Information System (INIS)

    Grover, Surbhi; Swisher-McClure, Samuel; Mitra, Nandita; Li, Jiaqi; Cohen, Roger B.; Ahn, Peter H.; Lukens, John N.; Chalian, Ara A.; Weinstein, Gregory S.; O'Malley, Bert W.; Lin, Alexander

    2015-01-01

    Purpose: To examine practice patterns and compare survival outcomes between total laryngectomy (TL) and larynx preservation chemoradiation (LP-CRT) in the setting of T4a larynx cancer, using a large national cancer registry. Methods and Materials: Using the National Cancer Database, we identified 969 patients from 2003 to 2006 with T4a squamous cell larynx cancer receiving definitive treatment with either initial TL plus adjuvant therapy or LP-CRT. Univariate and multivariable logistic regression were used to assess predictors of undergoing surgery. Survival outcomes were compared using Kaplan-Meier and propensity score–adjusted and inverse probability of treatment–weighted Cox proportional hazards methods. Sensitivity analyses were performed to account for unmeasured confounders. Results: A total of 616 patients (64%) received LP-CRT, and 353 (36%) received TL. On multivariable logistic regression, patients with advanced nodal disease were less likely to receive TL (N2 vs N0, 26.6% vs 43.4%, odds ratio [OR] 0.52, 95% confidence interval [CI] 0.37-0.73; N3 vs N0, 19.1% vs 43.4%, OR 0.23, 95% CI 0.07-0.77), whereas patients treated in high case-volume facilities were more likely to receive TL (46.1% vs 31.5%, OR 1.78, 95% CI 1.27-2.48). Median survival for TL versus LP was 61 versus 39 months (P<.001). After controlling for potential confounders, LP-CRT had inferior overall survival compared with TL (hazard ratio 1.31, 95% CI 1.10-1.57), and with the inverse probability of treatment–weighted model (hazard ratio 1.25, 95% CI 1.05-1.49). This survival difference was shown to be robust on additional sensitivity analyses. Conclusions: Most patients with T4a larynx cancer receive LP-CRT, despite guidelines suggesting TL as the preferred initial approach. Patients receiving LP-CRT had more advanced nodal disease and worse overall survival. Previous studies of (non-T4a) locally advanced larynx cancer showing no difference in survival between LP-CRT and TL may not

  3. A Simulation Investigation of Principal Component Regression.

    Science.gov (United States)

    Allen, David E.

    Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

  4. Overall survival and disease-free survival in endometrial cancer: prognostic factors in 276 patients

    Directory of Open Access Journals (Sweden)

    Tejerizo-García A

    2013-09-01

    Full Text Available Álvaro Tejerizo-García,1 Jesús S Jiménez-López,1 José L Muñoz-González,1 Sara Bartolomé-Sotillos,1 Laura Marqueta-Marqués,1 Gregorio López-González,1 José F Pérez-Regadera Gómez21Service of Obstetrics and Gynecology, 2Radiation Oncology Service, Hospital Universitario 12 de Octubre, Madrid, SpainObjective: The aim of the study reported here was to assess the disease-free survival and overall survival of patients with endometrial cancer and to determine independent factors affecting the prognosis.Materials and methods: This was a retrospective study of a single-center clinical series of 276 patients (mean age 64 years with histologically confirmed cancer of the corpus uteri. The standard treatments were extrafascial total hysterectomy and bilateral salpingo-oophorectomy with selective pelvic/para-aortic node dissection, according to risk for recurrence. Actuarial overall survival and disease-free survival were estimated according to the Kaplan–Meier method. Univariate and multivariate Cox proportional hazards analyses were used to assess the prognostic significance of the different variables.Results: The estimated median follow-up, determined using the inverse Kaplan–Meier method, was 45 months (95% confidence interval [CI] 41.2–48.8 for disease-free survival and 46 months (95% CI 43.0–49.0 for overall survival. The statistically significant variables affecting disease-free survival and overall survival were age, serous-papillary and clear-cell histological types, outer-half myometrial invasion, advanced International Federation of Gynecology and Obstetrics (FIGO stage, tumor grades G2 and G3, incomplete surgical resection, positive lymph nodes, lymphovascular space invasion, tumor remnants of >1 cm after surgery, and high-risk group. In the multivariate Cox regression model, predictors of tumor recurrence included advanced FIGO stage (hazard ratio [HR] 4.90, 95% CI 2.57–9.36, P < 0.001 and tumor grades G2 (HR 4.79, 95

  5. Effect of bystander CPR initiation prior to the emergency call on ROSC and 30day survival-An evaluation of 548 emergency calls.

    Science.gov (United States)

    Viereck, Søren; Palsgaard Møller, Thea; Kjær Ersbøll, Annette; Folke, Fredrik; Lippert, Freddy

    2017-02-01

    This study aimed at evaluating if time for initiation of bystander cardiopulmonary resuscitation (CPR) - prior to the emergency call (CPR prior ) versus during the emergency call following dispatcher-assisted CPR (CPR during ) - was associated with return of spontaneous circulation (ROSC) and 30-day survival. The secondary aim was to identify predictors of CPR prior . This observational study evaluated out-of-hospital cardiac arrests (OHCA) occurring in the Capital Region of Denmark from 01.01.2013 to 31.12.2013. OHCAs were linked to emergency medical dispatch centre records and corresponding emergency calls were evaluated. Multivariable logistic regression analyses were applied to evaluate the association between time for initiation of bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of CPR prior . The study included 548 emergency calls for OHCA patients receiving bystander CPR, 34.9% (n=191) in the CPR prior group and 65.1% (n=357) in the CPR during group. Multivariable analyses showed no difference in ROSC (OR=0.88, 95% CI: 0.56-1.38) or 30-day survival (OR=1.14, 95% CI: 0.68-1.92) between CPR prior and CPR during . Predictors positively associated with CPR prior included witnessed OHCA and healthcare professional bystanders. Predictors negatively associated with CPR prior included residential location, solitary bystanders, and bystanders related to the patient. The majority of bystander CPR (65%) was initiated during the emergency call, following dispatcher-assisted CPR instructions. Whether bystander CPR was initiated prior to emergency call versus during the emergency call following dispatcher-assisted CPR was not associated with ROSC or 30-day survival. Dispatcher-assisted CPR was especially beneficial for the initiation of bystander CPR in residential areas. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  6. Check-all-that-apply data analysed by Partial Least Squares regression

    DEFF Research Database (Denmark)

    Rinnan, Åsmund; Giacalone, Davide; Frøst, Michael Bom

    2015-01-01

    are analysed by multivariate techniques. CATA data can be analysed both by setting the CATA as the X and the Y. The former is the PLS-Discriminant Analysis (PLS-DA) version, while the latter is the ANOVA-PLS (A-PLS) version. We investigated the difference between these two approaches, concluding...

  7. The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard

    and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

  8. Incidence, treatment, and survival patterns for sacral chordoma in the United States, 1974-2011

    Directory of Open Access Journals (Sweden)

    Esther Yu

    2016-09-01

    Full Text Available IntroductionSacral chordomas represent one half of all chordomas, a rare neoplasm of notochordal remnants. Current NCCN guidelines recommend surgical resection with or without adjuvant radiotherapy, or definitive radiation for unresectable cases. Recent advances in radiation for chordomas include conformal photon and proton beam radiation. We investigated incidence, treatment, and survival outcomes to observe any trends in response to improvements in surgical and radiation techniques over a near 40 year time period.Materials and Methods345 microscopically confirmed cases of sacral chordoma were identified between 1974 and 2011 from the Surveillance, Epidemiology, and End Results (SEER program of the National Cancer Institute. Cases were divided into three cohorts by calendar year, 1974-1989, 1990-1999, and 2000-2011, as well as into two groups by age less than or equal to 65 versus greater than 65 to investigate trends over time and age via Chi-square analysis. Kaplan-Meier analyses were performed to determine effects of treatment on survival. Multivariate Cox regression analysis was performed to determine predictors of overall survival.Results5-year overall survival for the entire cohort was 60.0%. Overall survival correlated significantly with treatment modality, with 44% surviving at 5 years with no treatment, 52% with radiation alone, 82% surgery alone, and 78% surgery and radiation (p<.001. Age greater than 65 was significantly associated with non-surgical management with radiation alone or no treatment (p<.001. Relatively fewer patients received radiation between 2000 and 2011 compared to prior time periods (p=.03 versus surgery, for which rates which did not vary significantly over time (p=.55. However, 5-year overall survival was not significantly different by time period. Age group and treatment modality were predictive for overall survival on multivariate analysis (p<.001. ConclusionSurgery remains an important component in the

  9. Identification of subgroups by risk of graft failure after paediatric renal transplantation: application of survival tree models on the ESPN/ERA-EDTA Registry.

    Science.gov (United States)

    Lofaro, Danilo; Jager, Kitty J; Abu-Hanna, Ameen; Groothoff, Jaap W; Arikoski, Pekka; Hoecker, Britta; Roussey-Kesler, Gwenaelle; Spasojević, Brankica; Verrina, Enrico; Schaefer, Franz; van Stralen, Karlijn J

    2016-02-01

    Identification of patient groups by risk of renal graft loss might be helpful for accurate patient counselling and clinical decision-making. Survival tree models are an alternative statistical approach to identify subgroups, offering cut-off points for covariates and an easy-to-interpret representation. Within the European Society of Pediatric Nephrology/European Renal Association-European Dialysis and Transplant Association (ESPN/ERA-EDTA) Registry data we identified paediatric patient groups with specific profiles for 5-year renal graft survival. Two analyses were performed, including (i) parameters known at time of transplantation and (ii) additional clinical measurements obtained early after transplantation. The identified subgroups were added as covariates in two survival models. The prognostic performance of the models was tested and compared with conventional Cox regression analyses. The first analysis included 5275 paediatric renal transplants. The best 5-year graft survival (90.4%) was found among patients who received a renal graft as a pre-emptive transplantation or after short-term dialysis (2.2 years). The Cox model including both pre-transplant factors and tree subgroups had a significantly better predictive performance than conventional Cox regression (P 30 mL/min/1.73 m(2) and dialysis 20 months). Also in this case combining tree findings and clinical factors improved the predictive performance as compared with conventional Cox model models (P tree model to be an accurate and attractive tool to predict graft failure for patients with specific characteristics. This may aid the evaluation of individual graft prognosis and thereby the design of measures to improve graft survival in the poor prognosis groups. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  10. Detecting overdispersion in count data: A zero-inflated Poisson regression analysis

    Science.gov (United States)

    Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah

    2017-09-01

    This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.

  11. Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

    Science.gov (United States)

    Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

    2015-01-01

    We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson--Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package PRIMsrc (Patient Rule Induction Method in Survival, Regression and Classification settings) is available on CRAN (Comprehensive R Archive Network) and GitHub. PMID:27034730

  12. Association of MTHFR gene polymorphisms with breast cancer survival

    International Nuclear Information System (INIS)

    Martin, Damali N; Boersma, Brenda J; Howe, Tiffany M; Goodman, Julie E; Mechanic, Leah E; Chanock, Stephen J; Ambs, Stefan

    2006-01-01

    Two functional single nucleotide polymorphisms (SNPs) in the 5,10-methylenetetrahydrofolate reductase (MTHFR) gene, C677T and A1298C, lead to decreased enzyme activity and affect chemosensitivity of tumor cells. We investigated whether these MTHFR SNPs were associated with breast cancer survival in African-American and Caucasian women. African-American (n = 143) and Caucasian (n = 105) women, who had incident breast cancer with surgery, were recruited between 1993 and 2003 from the greater Baltimore area, Maryland, USA. Kaplan-Meier survival and multivariate Cox proportional hazards regression analyses were used to examine the relationship between MTHFR SNPs and disease-specific survival. We observed opposite effects of the MTHFR polymorphisms A1298C and C677T on breast cancer survival. Carriers of the variant allele at codon 1298 (A/C or C/C) had reduced survival when compared to homozygous carriers of the common A allele [Hazard ratio (HR) = 2.05; 95% confidence interval (CI), 1.05–4.00]. In contrast, breast cancer patients with the variant allele at codon 677 (C/T or T/T) had improved survival, albeit not statistically significant, when compared to individuals with the common C/C genotype (HR = 0.65; 95% CI, 0.31–1.35). The effects were stronger in patients with estrogen receptor-negative tumors (HR = 2.70; 95% CI, 1.17–6.23 for A/C or C/C versus A/A at codon 1298; HR = 0.36; 95% CI, 0.12–1.04 for C/T or T/T versus C/C at codon 677). Interactions between the two MTHFR genotypes and race/ethnicity on breast cancer survival were also observed (A1298C, p interaction = 0.088; C677T, p interaction = 0.026). We found that the MTHFR SNPs, C677T and A1298C, were associated with breast cancer survival. The variant alleles had opposite effects on disease outcome in the study population. Race/ethnicity modified the association between the two SNPs and breast cancer survival

  13. Bayesian linear regression with skew-symmetric error distributions with applications to survival analysis

    KAUST Repository

    Rubio, Francisco J.; Genton, Marc G.

    2016-01-01

    are censored. The latter scenario is of interest in the context of accelerated failure time models, which are relevant in survival analysis. We present a simulation study that demonstrates good frequentist properties of the posterior credible intervals

  14. Exposure-survival analyses of pazopanib in renal cell carcinoma and soft tissue sarcoma patients: opportunities for dose optimization.

    Science.gov (United States)

    Verheijen, R B; Swart, L E; Beijnen, J H; Schellens, J H M; Huitema, A D R; Steeghs, N

    2017-12-01

    Pazopanib is an angiogenesis inhibitor approved for the treatment of renal cell carcinoma and soft tissue sarcoma. Post hoc analysis of a clinical trial demonstrated a relationship between pazopanib trough concentrations (C min ) and treatment efficacy. The aim of this study was to explore the pharmacokinetics and exposure-survival relationships of pazopanib in a real-world patient cohort. Renal cell cancer and soft tissue sarcoma patients who had at least one pazopanib plasma concentration available were included. Using calculated C min values and a threshold of > 20 mg/L, univariate and multivariate exposure-survival analyses were performed. Sixty-one patients were included, of which 16.4% were underexposed (mean C min   20 mg/L was related to longer progression free survival in renal cell cancer patients (34.1 vs. 12.5 weeks, n = 35, p = 0.027) and the overall population (25.0 vs. 8.8 weeks, n = 61, p = 0.012), but not in the sarcoma subgroup (18.7 vs. 8.8 weeks, n = 26, p = 0.142). In multivariate analysis C min  > 20 mg/L was associated with hazard ratios of 0.25 (p = 0.021) in renal cancer, 0.12 (p = 0.011) in sarcoma and 0.38 (p = 0.017) in a pooled analysis. This study confirms that pazopanib C min  > 20 mg/L relates to better progression free survival in renal cancer and points towards a similar trend in sarcoma patients. C min monitoring of pazopanib can help identify patients with low C min for whom individualized treatment at a higher dose may be appropriate.

  15. Alpins and thibos vectorial astigmatism analyses: proposal of a linear regression model between methods

    Directory of Open Access Journals (Sweden)

    Giuliano de Oliveira Freitas

    2013-10-01

    Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.

  16. Survival rates and predictors of survival among colorectal cancer patients in a Malaysian tertiary hospital.

    Science.gov (United States)

    Magaji, Bello Arkilla; Moy, Foong Ming; Roslani, April Camilla; Law, Chee Wei

    2017-05-18

    Colorectal cancer is the third most commonly diagnosed malignancy and the fourth leading cause of cancer-related death globally. It is the second most common cancer among both males and females in Malaysia. The economic burden of colorectal cancer is likely to increase over time owing to its current trend and aging population. Cancer survival analysis is an essential indicator for early detection and improvement in cancer treatment. However, there was a scarcity of studies concerning survival of colorectal cancer patients as well as its predictors. Therefore, we aimed to determine the 1-, 3- and 5-year survival rates, compare survival rates among ethnic groups and determine the predictors of survival among colorectal cancer patients. This was an ambidirectional cohort study conducted at the University Malaya Medical Centre (UMMC) in Kuala Lumpur, Malaysia. All Malaysian citizens or permanent residents with histologically confirmed diagnosis of colorectal cancer seen at UMMC from 1 January 2001 to 31 December 2010 were included in the study. Demographic and clinical characteristics were extracted from the medical records. Patients were followed-up until death or censored at the end of the study (31st December 2010). Censored patients' vital status (whether alive or dead) were cross checked with the National Registration Department. Survival analyses at 1-, 3- and 5-year intervals were performed using the Kaplan-Meier method. Log-rank test was used to compare the survival rates, while Cox proportional hazard regression analysis was carried out to determine the predictors of 5-year colorectal cancer survival. Among 1212 patients, the median survival for colorectal, colon and rectal cancers were 42.0, 42.0 and 41.0 months respectively; while the 1-, 3-, and 5-year relative survival rates ranged from 73.8 to 76.0%, 52.1 to 53.7% and 40.4 to 45.4% respectively. The Chinese patients had the lowest 5-year survival compared to Malay and Indian patients. Based on the 814

  17. [Medulloblastoma: improved survival in recent decades. Unicentric experience].

    Science.gov (United States)

    Igual Estellés, Lucía; Berlanga Charriel, Pablo; Cañete Nieto, Adela

    2017-01-01

    The aim of the study is to analyse variations in the treatment of medulloblastoma, the most common childhood brain tumour, and its impact on survival over the past two decades, as well as its clinical and pathological features. Survival analysis of all patients under 14 years old diagnosed with medulloblastoma between January 1990 and December 2013 in a Paediatric Oncology Unit. Sixty-three patients were diagnosed and treated for medulloblastoma, with a median follow-up of 5.1 years (range 0.65-21.7 years). The overall survival (OS) at 3 and 5 years was 66±13% and 55±14%, respectively. The OS at 5 years was 44%±25% in patients diagnosed in the 1990's, showing an increase to 70%±23% (p=0.032) since 2000. Clinical prognosis factors were included in the logistic regression model: age (p=0.008), presence of metastases and/or residual tumour (p=0.007), and receiving chemotherapy with radiotherapy after surgery (p=0.008). Statistically significant differences were observed for all of them. In our institution there has been a significant increase in medulloblastoma survival in the last decades. Multivariate analysis showed that this improvement was not related to the date of diagnosis, but with the introduction of chemotherapy in adjuvant treatment. This study confirmed that clinical factors significantly associated with worse outcome were age and presence of metastases at diagnosis. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

  18. Linear regression metamodeling as a tool to summarize and present simulation model results.

    Science.gov (United States)

    Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

    2013-10-01

    Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

  19. Quantifying discrimination of Framingham risk functions with different survival C statistics.

    Science.gov (United States)

    Pencina, Michael J; D'Agostino, Ralph B; Song, Linye

    2012-07-10

    Cardiovascular risk prediction functions offer an important diagnostic tool for clinicians and patients themselves. They are usually constructed with the use of parametric or semi-parametric survival regression models. It is essential to be able to evaluate the performance of these models, preferably with summaries that offer natural and intuitive interpretations. The concept of discrimination, popular in the logistic regression context, has been extended to survival analysis. However, the extension is not unique. In this paper, we define discrimination in survival analysis as the model's ability to separate those with longer event-free survival from those with shorter event-free survival within some time horizon of interest. This definition remains consistent with that used in logistic regression, in the sense that it assesses how well the model-based predictions match the observed data. Practical and conceptual examples and numerical simulations are employed to examine four C statistics proposed in the literature to evaluate the performance of survival models. We observe that they differ in the numerical values and aspects of discrimination that they capture. We conclude that the index proposed by Harrell is the most appropriate to capture discrimination described by the above definition. We suggest researchers report which C statistic they are using, provide a rationale for their selection, and be aware that comparing different indices across studies may not be meaningful. Copyright © 2012 John Wiley & Sons, Ltd.

  20. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    International Nuclear Information System (INIS)

    Taktak, Azzam F G; Fisher, Anthony C; Damato, Bertil E

    2004-01-01

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate

  1. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    Energy Technology Data Exchange (ETDEWEB)

    Taktak, Azzam F G [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Fisher, Anthony C [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Damato, Bertil E [Department of Ophthalmology, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom)

    2004-01-07

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate.

  2. COX-2 activation is associated with Akt phosphorylation and poor survival in ER-negative, HER2-positive breast cancer

    International Nuclear Information System (INIS)

    Glynn, Sharon A; Ambs, Stefan; Prueitt, Robyn L; Ridnour, Lisa A; Boersma, Brenda J; Dorsey, Tiffany M; Wink, David A; Goodman, Julie E; Yfantis, Harris G; Lee, Dong H

    2010-01-01

    Inducible cyclooxgenase-2 (COX-2) is commonly overexpressed in breast tumors and is a target for cancer therapy. Here, we studied the association of COX-2 with breast cancer survival and how this association is influenced by tumor estrogen and HER2 receptor status and Akt pathway activation. Tumor COX-2, HER2 and estrogen receptor α (ER) expression and phosphorylation of Akt, BAD, and caspase-9 were analyzed immunohistochemically in 248 cases of breast cancer. Spearman's correlation and multivariable logistic regression analyses were used to examine the relationship between COX-2 and tumor characteristics. Kaplan-Meier survival and multivariable Cox proportional hazards regression analyses were used to examine the relationship between COX-2 and disease-specific survival. COX-2 was significantly associated with breast cancer outcome in ER-negative [Hazard ratio (HR) = 2.72; 95% confidence interval (CI), 1.36-5.41; comparing high versus low COX-2] and HER2 overexpressing breast cancer (HR = 2.84; 95% CI, 1.07-7.52). However, the hazard of poor survival associated with increased COX-2 was highest among patients who were both ER-negative and HER2-positive (HR = 5.95; 95% CI, 1.01-34.9). Notably, COX-2 expression in the ER-negative and HER2-positive tumors correlated significantly with increased phosphorylation of Akt and of the two Akt targets, BAD at Ser136 and caspase-9 at Ser196. Up-regulation of COX-2 in ER-negative and HER2-positive breast tumors is associated with Akt pathway activation and is a marker of poor outcome. The findings suggest that COX-2-specific inhibitors and inhibitors of the Akt pathway may act synergistically as anticancer drugs in the ER-negative and HER2-positive breast cancer subtype

  3. Progression-free survival as a potential surrogate for overall survival in metastatic breast cancer

    Directory of Open Access Journals (Sweden)

    Beauchemin C

    2014-06-01

    Full Text Available Catherine Beauchemin,1 Dan Cooper,2 Marie-Ève Lapierre,1 Louise Yelle,3 Jean Lachaine11Université de Montréal, Faculté de pharmacie, Montreal, 2Institut national d'excellence en santé et en services sociaux (INESSS, 3Centre Hospitalier de l'Université de Montréal – Hôpital Notre-Dame, Département de médecine, Université de Montréal, Montreal, QC, CanadaBackground: Progression-free survival (PFS and time to progression (TTP are frequently used to establish the clinical efficacy of anti-cancer drugs. However, the surrogacy of PFS/TTP for overall survival (OS remains a matter of uncertainty in metastatic breast cancer (mBC. This study assessed the relationship between PFS/TTP and OS in mBC using a trial-based approach.Methods: We conducted a systematic literature review according to the PICO method: 'Population' consisted of women with mBC; 'Interventions' and 'Comparators' were standard treatments for mBC or best supportive care; 'Outcomes' of interest were median PFS/TTP and OS. We first performed a correlation analysis between median PFS/TTP and OS, and then conducted subgroup analyses to explore possible reasons for heterogeneity. Then, we assessed the relationship between the treatment effect on PFS/TTP and OS. The treatment effect on PFS/TTP and OS was quantified by the absolute difference of median values. We also conducted linear regression analysis to predict the effects of a new anti-cancer drug on OS on the basis of its effects on PFS/TTP.Results: A total of 5,041 studies were identified, and 144 fulfilled the eligibility criteria. There was a statistically significant relationship between median PFS/TTP and OS across included trials (r=0.428; P<0.01. Correlation coefficient for the treatment effect on PFS/TTP and OS was estimated at 0.427 (P<0.01. The obtained linear regression equation was ΔOS =−0.088 (95% confidence interval [CI] −1.347–1.172 + 1.753 (95% CI 1.307–2.198 × ΔPFS (R2=0.86.Conclusion: Results of

  4. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

    Science.gov (United States)

    Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

    2016-12-01

    : MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We

  5. Survival after out-of-hospital cardiac arrest in relation to sex: a nationwide registry-based study.

    Science.gov (United States)

    Wissenberg, Mads; Hansen, Carolina Malta; Folke, Fredrik; Lippert, Freddy K; Weeke, Peter; Karlsson, Lena; Rajan, Shahzleen; Søndergaard, Kathrine Bach; Kragholm, Kristian; Christensen, Erika Frischknecht; Nielsen, Søren L; Køber, Lars; Gislason, Gunnar H; Torp-Pedersen, Christian

    2014-09-01

    Crude survival has increased following an out-of-hospital cardiac arrest (OHCA). We aimed to study sex-related differences in patient characteristics and survival during a 10-year study period. Patients≥12 years old with OHCA of a presumed cardiac cause, and in whom resuscitation was attempted, were identified through the Danish Cardiac Arrest Registry 2001-2010. A total of 19,372 patients were included. One-third were female, with a median age of 75 years (IQR 65-83). Compared to females, males were five years younger; and less likely to have severe comorbidities, e.g., chronic obstructive pulmonary disease (12.8% vs. 16.5%); but more likely to have arrest outside of the home (29.4% vs. 18.7%), receive bystander CPR (32.9% vs. 25.9%), and have a shockable rhythm (32.6% vs. 17.2%), all p<0.001. Thirty-day crude survival increased in males (3.0% in 2001 to 12.9% in 2010); and in females (4.8% in 2001 to 6.7% in 2010), p<0.001. Multivariable logistic regression analyses adjusted for patient characteristics including comorbidities, showed no survival difference between sexes in patients with a non-shockable rhythm (OR 1.00; CI 0.72-1.40), while female sex was positively associated with survival in patients with a shockable rhythm (OR 1.31; CI 1.07-1.59). Analyses were rhythm-stratified due to interaction between sex and heart rhythm; there was no interaction between sex and calendar-year. Temporal increase in crude survival was more marked in males due to poorer prognostic characteristics in females with a lower proportion of shockable rhythm. In an adjusted model, female sex was positively associated with survival in patients with a shockable rhythm. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  6. The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

    Science.gov (United States)

    Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

    2017-01-01

    Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

  7. Translating Response During Therapy into Ultimate Treatment Outcome: A Personalized 4-Dimensional MRI Tumor Volumetric Regression Approach in Cervical Cancer

    International Nuclear Information System (INIS)

    Mayr, Nina A.; Wang, Jian Z.; Lo, Simon S.; Zhang Dongqing; Grecula, John C.; Lu Lanchun; Montebello, Joseph F.; Fowler, Jeffrey M.; Yuh, William T.C.

    2010-01-01

    Purpose: To assess individual volumetric tumor regression pattern in cervical cancer during therapy using serial four-dimensional MRI and to define the regression parameters' prognostic value validated with local control and survival correlation. Methods and Materials: One hundred and fifteen patients with Stage IB 2 -IVA cervical cancer treated with radiation therapy (RT) underwent serial MRI before (MRI 1) and during RT, at 2-2.5 weeks (MRI 2, at 20-25 Gy), and at 4-5 weeks (MRI 3, at 40-50 Gy). Eighty patients had a fourth MRI 1-2 months post-RT. Mean follow-up was 5.3 years. Tumor volume was measured by MRI-based three-dimensional volumetry, and plotted as dose(time)/volume regression curves. Volume regression parameters were correlated with local control, disease-specific, and overall survival. Results: Residual tumor volume, slope, and area under the regression curve correlated significantly with local control and survival. Residual volumes ≥20% at 40-50 Gy were independently associated with inferior 5-year local control (53% vs. 97%, p <0.001) and disease-specific survival rates (50% vs. 72%, p = 0.009) than smaller volumes. Patients with post-RT residual volumes ≥10% had 0% local control and 17% disease-specific survival, compared with 91% and 72% for <10% volume (p <0.001). Conclusion: Using more accurate four-dimensional volumetric regression analysis, tumor response can now be directly translated into individual patients' outcome for clinical application. Our results define two temporal thresholds critically influencing local control and survival. In patients with ≥20% residual volume at 40-50 Gy and ≥10% post-RT, the risk for local failure and death are so high that aggressive intervention may be warranted.

  8. Predicting Word Reading Ability: A Quantile Regression Study

    Science.gov (United States)

    McIlraith, Autumn L.

    2018-01-01

    Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

  9. Quality of life as predictor of survival: A prospective study on patients treated with combined surgery and radiotherapy for advanced oral and oropharyngeal cancer

    International Nuclear Information System (INIS)

    Oskam, Inge M.; Verdonck-de Leeuw, Irma M.; Aaronson, Neil K.; Kuik, Dirk J.; Bree, Remco de; Doornaert, Patricia; Langendijk, Johannes A.; Leemans, Rene C.

    2010-01-01

    Background and purpose: The relation between health-related quality of life (HRQOL) and survival was investigated at baseline and 6 months in 80 patients with advanced oral or oropharyngeal cancer after microvascular reconstructive surgery and (almost all) adjuvant radiotherapy. Materials and methods: Multivariate Cox regression analyses of overall and disease-specific survival were performed including sociodemographic (age, gender, marital status, comorbidity), and clinical (tumor stage and site, radical surgical, metastasis, radiotherapy) parameters, and HRQOL (EORTC QLQ-C30 global quality of life scale). Results: Before treatment, younger age and having a partner were predictors of disease-specific survival; younger age predicted overall survival. At 6 months post-treatment, disease-specific and overall survival was predicted by (deterioration of) global quality of life solely. Global health-related quality of life after treatment was mainly influenced by emotional functioning. Conclusion: Deterioration of global quality of life after treatment is an independent predictor of survival in patients with advanced oral or oropharyngeal cancer.

  10. Structural vascular disease in Africans: performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: the SABPA study

    OpenAIRE

    Botha, J.; De Ridder, J.H.; Potgieter, J.C.; Steyn, H.S.; Malan, L.

    2013-01-01

    A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fa...

  11. A Simple Linear Regression Method for Quantitative Trait Loci Linkage Analysis With Censored Observations

    OpenAIRE

    Anderson, Carl A.; McRae, Allan F.; Visscher, Peter M.

    2006-01-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using...

  12. Combined high-field intraoperative magnetic resonance imaging and endoscopy increase extent of resection and progression-free survival for pituitary adenomas

    Science.gov (United States)

    Sylvester, Peter T.; Evans, John A.; Zipfel, Gregory J.; Chole, Richard A.; Uppaluri, Ravindra; Haughey, Bruce H.; Getz, Anne E.; Silverstein, Julie; Rich, Keith M.; Kim, Albert H.; Dacey, Ralph G.

    2014-01-01

    Purpose The clinical benefit of combined intraoperative magnetic resonance imaging (iMRI) and endoscopy for transsphenoidal pituitary adenoma resection has not been completely characterized. This study assessed the impact of microscopy, endoscopy, and/or iMRI on progression-free survival, extent of resection status (gross-, near-, and subtotal resection), and operative complications. Methods Retrospective analyses were performed on 446 transsphenoidal pituitary adenoma surgeries at a single institution between 1998 and 2012. Multivariate analyses were used to control for baseline characteristics, differences during extent of resection status, and progression-free survival analysis. Results Additional surgery was performed after iMRI in 56/156 cases (35.9 %), which led to increased extent of resection status in 15/156 cases (9.6 %). Multivariate ordinal logistic regression revealed no increase in extent of resection status following iMRI or endoscopy alone; however, combining these modalities increased extent of resection status (odds ratio 2.05, 95 % CI 1.21–3.46) compared to conventional transsphenoidal microsurgery. Multivariate Cox regression revealed that reduced extent of resection status shortened progression-free survival for near- versus gross-total resection [hazard ratio (HR) 2.87, 95 % CI 1.24–6.65] and sub- versus near-total resection (HR 2.10; 95 % CI 1.00–4.40). Complication comparisons between microscopy, endoscopy, and iMRI revealed increased perioperative deaths for endoscopy versus microscopy (4/209 and 0/237, respectively), but this difference was non-significant considering multiple post hoc comparisons (Fisher exact, p = 0.24). Conclusions Combined use of endoscopy and iMRI increased pituitary adenoma extent of resection status compared to conventional transsphenoidal microsurgery, and increased extent of resection status was associated with longer progression-free survival. Treatment modality combination did not significantly impact

  13. ESC guidelines adherence is associated with improved survival in patients from the Norwegian Heart Failure Registry.

    Science.gov (United States)

    De Blois, Jonathan; Fagerland, Morten Wang; Grundtvig, Morten; Semb, Anne Grete; Gullestad, Lars; Westheim, Arne; Hole, Torstein; Atar, Dan; Agewall, Stefan

    2015-01-01

    To assess the adherence to heart failure (HF) guidelines for angiotensin-converting enzyme-I (ACE-I), angiotensin II receptor blockers (ARB), and β-blockers and the possible association of ACE-I or ARB, β-blockers, and statins with survival in the large contemporary Norwegian Heart Failure Registry. The study included 5761 outpatients who were diagnosed with HF of any aetiology (mean left ventricular ejection fraction 32% ± 11%) from January 2000 to January 2010 and followed up until death or February 2010. Adherence to treatment according to the guidelines was high. Cox regression analysis to identify risk factors for all-cause mortality, after adjustment for many factors, showed that ACE-I ≥ 50% of target dose, use of beta-blockers, and statins were significantly related to improved survival (P = 0.003, P < 0.001, and P < 0.001, respectively). Propensity scoring showed the same benefit for these variables. Both multivariable and propensity scoring analyses showed survival benefits with β-blockers, statins, and adequate doses of ACE-I in this contemporary HF cohort. This study stresses the importance of guidelines adherence, even in the context of high levels of adherence to guidelines. Moreover, respecting the recommended target doses of ACE-I appears to have a crucial role in survival improvement and, in the multivariate Cox regression analysis, ARB treatment was not significantly associated with a lower all-cause mortality. Published on behalf of the European Society of Cardiology. All rights reserved. ©The Author 2015. For permissions please email: journals.permissions@oup.com.

  14. The inflammation-based Glasgow Prognostic Score predicts survival in patients with cervical cancer.

    Science.gov (United States)

    Polterauer, Stephan; Grimm, Christoph; Seebacher, Veronika; Rahhal, Jasmin; Tempfer, Clemens; Reinthaller, Alexander; Hefler, Lukas

    2010-08-01

    The Glasgow Prognostic Score (GPS) is known to reflect the degree of tumor-associated cachexia and inflammation and is associated with survival in various malignancies. We investigated the value of the GPS in patients with cervical cancer. We included 244 consecutive patients with cervical cancer in our study. The pretherapeutic GPS was calculated as follows: patients with elevated C-reactive protein serum levels (>10 mg/L) and hypoalbuminemia (L) were allocated a score of 2, and patients with 1 or no abnormal value were allocated a score of 1 or 0, respectively. The association between GPS and survival was evaluated by univariate log-rank tests and multivariate Cox regression models. The GPS was correlated with clinicopathologic parameters as shown by performing chi2 tests. In univariate analyses, GPS (P GPS (P = 0.03, P = 0.04), FIGO stage (P = 0.006, P = 0.006), and lymph node involvement (P = 0.003, P = 0.002), but not patients' age (P = 0.5, P = 0.5), histological grade (P = 0.7, P = 0.6), and histological type (P = 0.4, P = 0.6) were associated with disease-free and overall survival, respectively. The GPS was associated with FIGO stage (P GPS can be used as an inflammation-based predictor for survival in patients with cervical cancer.

  15. Bisphenol-A exposures and behavioural aberrations: median and linear spline and meta-regression analyses of 12 toxicity studies in rodents.

    Science.gov (United States)

    Peluso, Marco E M; Munnia, Armelle; Ceppi, Marcello

    2014-11-05

    Exposures to bisphenol-A, a weak estrogenic chemical, largely used for the production of plastic containers, can affect the rodent behaviour. Thus, we examined the relationships between bisphenol-A and the anxiety-like behaviour, spatial skills, and aggressiveness, in 12 toxicity studies of rodent offspring from females orally exposed to bisphenol-A, while pregnant and/or lactating, by median and linear splines analyses. Subsequently, the meta-regression analysis was applied to quantify the behavioural changes. U-shaped, inverted U-shaped and J-shaped dose-response curves were found to describe the relationships between bisphenol-A with the behavioural outcomes. The occurrence of anxiogenic-like effects and spatial skill changes displayed U-shaped and inverted U-shaped curves, respectively, providing examples of effects that are observed at low-doses. Conversely, a J-dose-response relationship was observed for aggressiveness. When the proportion of rodents expressing certain traits or the time that they employed to manifest an attitude was analysed, the meta-regression indicated that a borderline significant increment of anxiogenic-like effects was present at low-doses regardless of sexes (β)=-0.8%, 95% C.I. -1.7/0.1, P=0.076, at ≤120 μg bisphenol-A. Whereas, only bisphenol-A-males exhibited a significant inhibition of spatial skills (β)=0.7%, 95% C.I. 0.2/1.2, P=0.004, at ≤100 μg/day. A significant increment of aggressiveness was observed in both the sexes (β)=67.9,C.I. 3.4, 172.5, P=0.038, at >4.0 μg. Then, bisphenol-A treatments significantly abrogated spatial learning and ability in males (Pbisphenol-A, e.g. ≤120 μg/day, were associated to behavioural aberrations in offspring. Copyright © 2014. Published by Elsevier Ireland Ltd.

  16. Serum level of soluble urokinase-type plasminogen activator receptor is a strong and independent predictor of survival in human immunodeficiency virus infection

    DEFF Research Database (Denmark)

    Sidenius, N; Sier, C.F.M.; Ullum, H

    2000-01-01

    levels of soluble uPAR (suPAR) in patients with advanced HIV-1 disease and whether the serum level of suPAR is predictive of clinical outcome. Using an enzyme-linked immunosorbent assay, the level of suPAR was measured retrospectively in serum samples from 314 patients with HIV-1 infection. By Kaplan......-Meier and Cox regression analyses, the serum suPAR levels were correlated to survival with AIDS-related death as the end point. High levels of serum suPAR (greater than median) were associated with poor overall survival, and Kaplan-Meier analysis on patients stratified by suPAR level demonstrated a continuous...

  17. Survival prognosis in plantations of Pinus caribaea Morelet var. caribaea Barrett & Golfari

    Directory of Open Access Journals (Sweden)

    Ouorou Ganni Mariel Guera

    2018-01-01

    Full Text Available The present study was carried out with the objective of obtaining regression equations and Artificial Neural Networks (ANNs for the prognosis of Pinus caribaea var. caribaea survival in Macurije Forest Company, province of Pinar del Río - Cuba. The data used in the modeling comes from the measurement of the variables age (years and survival (density in circular permanent plots of 500 m² established in P. caribaea var. caribaea plantations. The study was divided into three stages: i Adjustment of survival traditional regression models; ii Training of ANNs for survival prognosis, including categorical variables «site» and «Basic Units of Forest Production»; iii Comparison of regression equations performance with those of ANNs in survival prognosis. The best models and ANNs were selected based on: adjusted determination coefficient - R2aj (%, square root of the mean square error - RMSE (% and residue distribution analysis. The evaluation of the models goodness of fit also included the verification of the assumptions of normality, homocedasticity and absence of serial autocorrelation in the residues by Kolmogorov-Smirnov, White and Durbin-Watson tests, respectively. The model of Pienaar and Shiver (1981 turned out to be the best fit in survival prognosis. The ANN MLP 13-10-1 was the one with the best generalization capacity and presented a performance similar to that of Pienaar and Shiver equation.

  18. Survival in Malnourished Older Patients Receiving Post-Discharge Nutritional Support; Long-Term Results of a Randomized Controlled Trial.

    Science.gov (United States)

    Neelemaat, F; van Keeken, S; Langius, J A E; de van der Schueren, M A E; Thijs, A; Bosmans, J E

    2017-01-01

    Previous analyses have shown that a post-discharge individualized nutritional intervention had positive effects on body weight, lean body mass, functional limitations and fall incidents in malnourished older patients. However, the impact of this intervention on survival has not yet been studied. The objective of this randomized controlled study was to examine the effect of a post-discharge individualized nutritional intervention on survival in malnourished older patients. Malnourished older patients, aged ≥ 60 years, were randomized during hospitalization to a three-months post-discharge nutritional intervention group (protein and energy enriched diet, oral nutritional supplements, vitamin D3/calcium supplement and telephone counseling by a dietitian) or to a usual care regimen (control group). Survival data were collected 4 years after enrollment. Survival analyses were performed using intention-to-treat analysis by Log-rank tests and Cox regression adjusted for confounders. The study population consisted of 94 men (45%) and 116 women with a mean age of 74.5 (SD 9.5) years. There were no statistically significant differences in baseline characteristics. Survival data was available in 208 out of 210 patients. After 1 and 4 years of follow-up, survival rates were respectively 66% and 29% in the intervention group (n=104) and 73% and 30% in the control group (n=104). There were no statistically significant differences in survival between the two groups 1 year (HR= 0.933, 95% CI=0.675-1.289) and 4 years after enrollment (HR=0.928, 95% CI=0.671-1.283). The current study failed to show an effect of a three-months post-discharge multi-component nutritional intervention in malnourished older patients on long-term survival, despite the positive effects on short-term outcome such as functional limitations and falls.

  19. Influence of beta blockers on survival in dogs with severe subaortic stenosis.

    Science.gov (United States)

    Eason, B D; Fine, D M; Leeder, D; Stauthammer, C; Lamb, K; Tobias, A H

    2014-01-01

    Subaortic stenosis (SAS) is one of the most common congenital cardiac defects in dogs. Severe SAS frequently is treated with a beta adrenergic receptor blocker (beta blocker), but this approach largely is empirical. To determine the influence of beta blocker treatment on survival time in dogs with severe SAS. Retrospective review of medical records of dogs diagnosed with severe, uncomplicated SAS (pressure gradient [PG] ≥80 mmHg) between 1999 and 2011. Fifty dogs met the inclusion criteria. Twenty-seven dogs were treated with a beta blocker and 23 received no treatment. Median age at diagnosis was significantly greater in the untreated group (1.2 versus 0.6 years, respectively; P = .03). Median PG at diagnosis did not differ between the treated and untreated groups (127 versus 121 mmHg, respectively; P = .2). Cox proportional hazards regression was used to identify the influence of PG at diagnosis, age at diagnosis, and beta blocker treatment on survival. In the all-cause multivariate mortality analysis, only age at diagnosis (P = .02) and PG at diagnosis (P = .03) affected survival time. In the cardiac mortality analysis, only PG influenced survival time (P = .03). Treatment with a beta blocker did not influence survival time in either the all-cause (P = .93) or cardiac-cause (P = .97) mortality analyses. Beta blocker treatment did not influence survival in dogs with severe SAS in our study, and a higher PG at diagnosis was associated with increased risk of death. Copyright © 2014 by the American College of Veterinary Internal Medicine.

  20. Penalized estimation for competing risks regression with applications to high-dimensional covariates

    DEFF Research Database (Denmark)

    Ambrogi, Federico; Scheike, Thomas H.

    2016-01-01

    of competing events. The direct binomial regression model of Scheike and others (2008. Predicting cumulative incidence probability by direct binomial regression. Biometrika 95: (1), 205-220) is reformulated in a penalized framework to possibly fit a sparse regression model. The developed approach is easily...... Research 19: (1), 29-51), the research regarding competing risks is less developed (Binder and others, 2009. Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics 25: (7), 890-896). The aim of this work is to consider how to do penalized regression in the presence...... implementable using existing high-performance software to do penalized regression. Results from simulation studies are presented together with an application to genomic data when the endpoint is progression-free survival. An R function is provided to perform regularized competing risks regression according...

  1. Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves.

    Science.gov (United States)

    Guyot, Patricia; Ades, A E; Ouwens, Mario J N M; Welton, Nicky J

    2012-02-01

    The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated. We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios) with statistics based on repeated reconstructions by multiple observers. The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported. The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.

  2. Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

    Science.gov (United States)

    Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.

    2008-01-01

    Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results. PMID:19054742

  3. Stereotactic Radiosurgery in the Management of Brain Metastases: An Institutional Retrospective Analysis of Survival

    International Nuclear Information System (INIS)

    Frazier, James L.; Batra, Sachin; Kapor, Sumit; Vellimana, Ananth; Gandhi, Rahul; Carson, Kathryn A.; Shokek, Ori; Lim, Michael; Kleinberg, Lawrence; Rigamonti, Daniele

    2010-01-01

    Purpose: The objective of this study was to report our experience with stereotactic radiosurgery performed with the Gamma Knife (GK) in the treatment of patients with brain metastases and to compare survival for those treated with radiosurgery alone with survival for those treated with radiosurgery and whole-brain radiotherapy. Methods and Materials: Prospectively collected demographic and clinical characteristics and treatment and survival data on 237 patients with intracranial metastases who underwent radiosurgery with the GK between 2003 and 2007 were reviewed. Kaplan-Meier and Cox proportional hazards regression analyses were used to compare survival by demographic and clinical characteristics and treatment. Results: The mean age of the patient population was 56 years. The most common tumor histologies were non-small-cell lung carcinoma (34.2%) and breast cancer (13.9%). The median overall survival time was 8.5 months from the time of treatment. The median survival times for patients with one, two/three, and four or more brain metastases were 8.5, 9.4, and 6.7 months, respectively. Patients aged 65 years or greater and those aged less than 65 years had median survival times of 7.8 and 9 months, respectively (p = 0.008). The Karnofsky Performance Score (KPS) at the time of treatment was a significant predictor of survival: those patients with a KPS of 70 or less had a median survival of 2.9 months compared with 10.3 months (p = 0.034) for those with a KPS of 80 or greater. There was no statistically significant difference in survival between patients treated with radiosurgery alone and those treated with radiosurgery plus whole-brain radiotherapy. Conclusions: Radiosurgery with the GK is an efficacious treatment modality for brain metastases. A KPS greater than 70, histology of breast cancer, smaller tumor volume, and age less than 65 years were associated with a longer median survival in our study.

  4. Estimating haplotype effects for survival data

    DEFF Research Database (Denmark)

    Scheike, Thomas; Martinussen, Torben; Silver, J

    2010-01-01

    Genetic association studies often investigate the effect of haplotypes on an outcome of interest. Haplotypes are not observed directly, and this complicates the inclusion of such effects in survival models. We describe a new estimating equations approach for Cox's regression model to assess haplo...

  5. Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

    Science.gov (United States)

    Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

    2016-01-01

    Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

  6. Lamb survival analysis from birth to weaning in Iranian Kermani sheep.

    Science.gov (United States)

    Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Hossein-Zadeh, Navid Ghavi

    2012-04-01

    Survival records from 1,763 Kermani lambs born between 1996 and 2004 from 294 ewes and 81 rams were used to determine genetic and non-genetic factors affecting lamb survival. Traits included were lamb survival across five periods from birth to 7, 14, 56, 70, and 90 days of age. Traits were analyzed under Weibull proportional hazard sire models. Several binary analyses were also conducted using animal models. Statistical models included the fixed class effects of sex of lamb, month and year of birth, a covariate effect of birth weight, and random genetic effects of both sire (in survival analyses) and animal (in binary analyses). The average survival to 90 days of age was 94.8%. Hazard rates ranged from 1.00 (birth to 90 days of age) to 1.73 (birth to 7 days of age) between the two sexes indicating that male lambs were at higher risk of mortality than females (P lamb survival and lamb birth weight, suggesting that viability and birth weight could be considered simultaneously in the selection programs to obtain optimal birth weight in Kermani lambs. Estimates of heritabilities from survival analyses were medium and ranged from 0.23 to 0.29. In addition, heritability estimates obtained from binary analyses were low and varied from 0.04 to 0.09. The results of this study suggest that progress in survival traits could be possible through managerial strategies and genetic selection.

  7. Benefits of marriage on relative and conditional relative cancer survival differ between males and females in the USA.

    Science.gov (United States)

    Merrill, Ray M; Johnson, Erin

    2017-10-01

    The purpose of the paper is to assess the influence of marital status on conditional relative survival of cancer according to sex. Analyses involved 779,978 males and 1,032,868 females diagnosed with 1 of 13 cancer types between 2000 and 2008, and followed through 2013. Data are from the Surveillance, Epidemiology, and End Results (SEER) Program. Regression models were adjusted for age, sex, race, and tumor stage. Five-year relative survival conditional on years already survived is higher among married patients with less lethal cancers (oral cavity and pharynx, colon and rectum, breast, urinary bladder, kidney and renal pelvis, melanoma of the skin, thyroid, lymphoma). For more lethal cancers, married patients have similar (liver, lung and bronchus, pancreas, leukemia) or poorer (brain and other nervous system) cancer survival. Separated/divorced or widowed patients have the lowest conditional relative survival rates. For most cancers, 5-year cancer relative survival rates conditional on time already survived through 5 years approach 70 to 90% of that for the general population. The beneficial effect of marriage on survival decreases with years already survived. Superior conditional relative survival rates in females decrease with time already survived and are less pronounced in married patients. Five-year relative survival rates improve with time already survived. The benefits of marriage on conditional relative survival are greater for less lethal cancers. Greater 5-year conditional relative survival rates in females narrow with time already survived and are less pronounced in married patients. Conditional relative survival rates of cancer can lead to more informed decisions and understanding regarding treatment and prognosis.

  8. Isopropanolic black cohosh extract and recurrence-free survival after breast cancer.

    Science.gov (United States)

    Henneicke-von Zepelin, H H; Meden, H; Kostev, K; Schröder-Bernhardi, D; Stammwitz, U; Becher, H

    2007-03-01

    To investigate the influence of an isopropanolic Cimicifuga racemosa extract (iCR) on recurrence-free survival after breast cancer, including estrogen-dependent tumors. This pharmacoepidemiologic observational retrospective cohort study examined breast cancer patients treated at general, gynecological and internal facilities linked to a medical database in Germany. The main endpoint was disease-free survival following a diagnosis of breast cancer. The impact of treatment with iCR following diagnosis was analyzed by Cox-proportional hazards models, controlling for age and other confounders. Of 18,861 patients, a total of 1,102 had received an iCR therapy. The mean overall observation time was 3.6 years. Results showed that iCR was not associated with an increase in the risk of recurrence but associated with prolonged disease-free survival. After 2 years following initial diagnosis, 14% of the control group had developed a recurrence, while the iCR group reached this proportion after 6.5 years. The primary Cox regression model controlling for age, tamoxifen use and other confounders demonstrated a protractive effect of iCR on the rate of recurrence (hazard ratio 0.83, 95% confidence interval 0.69 0.99). This effect remained consistent throughout all variations of the statistical model, including subgroup analyses. TNM status was unknown but did not bias the iCR treatment decision as investigated separately. Hence, it was assumed to be equally distributed between treatment groups. Correlation analyses showed good internal and external validity of the database. An increase in the risk of breast cancer recurrence for women having had iCR treatment, compared to women not treated with iCR is unlikely.

  9. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    Science.gov (United States)

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  10. Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

    Science.gov (United States)

    Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

    2018-02-01

    A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  11. Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

    Directory of Open Access Journals (Sweden)

    Guyot Patricia

    2012-02-01

    Full Text Available Abstract Background The results of Randomized Controlled Trials (RCTs on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated. Methods We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios with statistics based on repeated reconstructions by multiple observers. Results The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported. Conclusion The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.

  12. Is there racial/ethnic variance in cervical cancer- specific survival of ...

    African Journals Online (AJOL)

    incident cervical carcinoma, between 1992 and 1999, in the Surveillance Epidemiology and End Results (SEER) Data was linked with Medicare to examine the impact of race/ethnicity on overall and cancer-specific survival, using Kaplan Meier survival estimates and multivariable Cox Regression model. Results: There was ...

  13. Augmenting Data with Published Results in Bayesian Linear Regression

    Science.gov (United States)

    de Leeuw, Christiaan; Klugkist, Irene

    2012-01-01

    In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

  14. Survival analysis of a treatment data for cancer of the larynx

    International Nuclear Information System (INIS)

    Khan, K.

    2002-01-01

    In this paper a survival analysis of the survival time is done. The Cox regression model is fitted to the survival time with the assumption of proportional hazard. A model is selected after inclusion and exclusion of factors and variables as explanatory variables. The assumption of proportional hazards is tested in the manner suggested by Harrell (1986). The assumption of proportional hazards is supported by these tests. However the plot of Schoenfeld residuals against dose gave a little evidence of non validity of the proportional hazard assumption. The assumption seems to be satisfied for variable time. The martingale residuals suggest no pattern for variable age. The functional form of dose is not linear. Hence the quadratic dose is used as an explanatory variable. A comparison of logistic regression analysis and survival analysis is also made in this paper. It can be concluded that Cox proportional hazards model is a better model than the logistic model as it is more parsimonious and utilizes more information. (author)

  15. Marital status and survival in patients with rectal cancer: A population-based STROBE cohort study.

    Science.gov (United States)

    Li, Zhuyue; Wang, Kang; Zhang, Xuemei; Wen, Jin

    2018-05-01

    To examine the impact of marital status on overall survival (OS) and rectal cancer-specific survival (RCSS) for aged patients.We used the Surveillance, Epidemiology and End Results database to identify aged patients (>65 years) with early stage rectal cancer (RC) (T1-T4, N0, M0) in the United States from 2004 to 2010. Propensity score matching was conducted to avoid potential confounding factors with ratio at 1:1. We used Kaplan-Meier to compare OS and RCSS between the married patients and the unmarried, respectively. We used cox proportion hazard regressions to obtain hazard rates for OS, and proportional subdistribution hazard model was performed to calculate hazard rates for RCSS.Totally, 5196 patients were included. The married (2598 [50%]) aged patients had better crude 5-year overall survival rate (64.2% vs 57.3%, P vs 75.9%, P unmarried (2598 (50%)), respectively. In multivariate analyses, married patients had significantly lower overall death than unmarried patients (HR = 0.77, 95% CI = 0.71-0.83, P married patients had no cancer-specific survival benefit versus the unmarried aged patients (HR = 0.92, 95% CI = 0.81-1.04, P = .17).Among old population, married patients with early stage RC had better OS than the unmarried, while current evidence showed that marital status might have no protective effect on cancer-specific survival.

  16. Survival and clinical outcome of dogs with ischaemic stroke.

    Science.gov (United States)

    Gredal, H; Toft, N; Westrup, U; Motta, L; Gideon, P; Arlien-Søborg, P; Skerritt, G C; Berendt, M

    2013-06-01

    The objectives of the present study were to investigate survival time, possible predictors of survival and clinical outcome in dogs with ischaemic stroke. A retrospective study of dogs with a previous diagnosis of ischaemic stroke diagnosed by magnetic resonance imaging (MRI) was performed. The association between survival and the hypothesised risk factors was examined using univariable exact logistic regression. Survival was examined using Kaplan-Meier and Cox regression. Twenty-two dogs were identified. Five dogs (23%) died within the first 30days of the stroke event. Median survival in 30-day survivors was 505days. Four dogs (18%) were still alive by the end of the study. Right-sided lesions posed a significantly increased risk of mortality with a median survival time in dogs with right-sided lesions of 24days vs. 602days in dogs with left sided lesions (P=0.006). Clinical outcome was considered excellent in seven of 17 (41%) 30-day survivors. Another seven 30-day survivors experienced new acute neurological signs within 6-17months of the initial stroke event; in two of those cases a new ischaemic stroke was confirmed by MRI. In conclusion, dogs with ischaemic stroke have a fair to good prognosis in terms of survival and clinical outcome. However, owners should be informed of the risk of acute death within 30days and of the possibility of new neurological events in survivors. Mortality was increased in dogs with right-sided lesions in this study. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. Delay of Treatment Initiation Does Not Adversely Affect Survival Outcome in Breast Cancer.

    Science.gov (United States)

    Yoo, Tae-Kyung; Han, Wonshik; Moon, Hyeong-Gon; Kim, Jisun; Lee, Jun Woo; Kim, Min Kyoon; Lee, Eunshin; Kim, Jongjin; Noh, Dong-Young

    2016-07-01

    Previous studies examining the relationship between time to treatment and survival outcome in breast cancer have shown inconsistent results. The aim of this study was to analyze the overall impact of delay of treatment initiation on patient survival and to determine whether certain subgroups require more prompt initiation of treatment. This study is a retrospective analysis of stage I-III patients who were treated in a single tertiary institution between 2005 and 2008. Kaplan-Meier survival analysis and Cox proportional hazards regression model were used to evaluate the impact of interval between diagnosis and treatment initiation in breast cancer and various subgroups. A total of 1,702 patients were included. Factors associated with longer delay of treatment initiation were diagnosis at another hospital, medical comorbidities, and procedures performed before admission for surgery. An interval between diagnosis and treatment initiation as a continuous variable or with a cutoff value of 15, 30, 45, and 60 days had no impact on disease-free survival (DFS). Subgroup analyses for hormone-responsiveness, triple-negative breast cancer, young age, clinical stage, and type of initial treatment showed no significant association between longer delay of treatment initiation and DFS. Our results show that an interval between diagnosis and treatment initiation of 60 days or shorter does not appear to adversely affect DFS in breast cancer.

  18. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  19. Predictors of survival in surgically treated patients of spinal metastasis

    Directory of Open Access Journals (Sweden)

    Pravin Padalkar

    2011-01-01

    Full Text Available Background: The spinal metastasis occurs in up to 40% of cancer patient. We compared the Tokuhashi and Tomita scoring systems, two commonly used scoring systems for prognosis in spinal metastases. We also assessed the different variables separately with respect to their value in predicting postsurgical life expectancy. Finally, we suggest criteria for selecting patients for surgery based on the postoperative survival pattern. Materials and Methods: We retrospectively analyzed 102 patients who had been operated for metastatic disease of the spine. Predictive scoring was done according to the scoring systems proposed by Tokuhashi and Tomita. Overall survival was assessed using Kaplan-Meier survival analysis. Using the log rank test and Cox regression model we assessed the value of the individual components of each scoring system for predicting survival in these patients. Result: The factors that were most significantly associated with survival were the general condition score (Karnofsky Performance Scale (P=.000, log rank test, metastasis to internal organs (P=.0002 log rank test, and number of extraspinal bone metastases (P=.0058. Type of primary tumor was not found to be significantly associated with survival according to the revised Tokuhashi scoring system (P=.9131, log rank test. Stepwise logistic regression revealed that the Tomita score correlated more closely with survival than the Tokuhashi score. Conclusion: The patient′s performance status, extent of visceral metastasis, and extent of bone metastases are significant predictors of survival in patients with metastatic disease. Both revised Tokuhashi and Tomita scores were significantly correlated with survival. A revised Tokuhashi score of 7 or more and a Tomita score of 6 or less indicated >50% chance of surviving 6 months postoperatively. We recommend that the Tomita score be used for prognostication in patients who are contemplating surgery, as it is simpler to score and has a higher

  20. Effect of Radiotherapy Planning Complexity on Survival of Elderly Patients With Unresected Localized Lung Cancer

    International Nuclear Information System (INIS)

    Park, Chang H.; Bonomi, Marcelo; Cesaretti, Jamie; Neugut, Alfred I.; Wisnivesky, Juan P.

    2011-01-01

    Purpose: To evaluate whether complex radiotherapy (RT) planning was associated with improved outcomes in a cohort of elderly patients with unresected Stage I-II non-small-cell lung cancer (NSCLC). Methods and Materials: Using the Surveillance, Epidemiology, and End Results registry linked to Medicare claims, we identified 1998 patients aged >65 years with histologically confirmed, unresected stage I-II NSCLC. Patients were classified into an intermediate or complex RT planning group using Medicare physician codes. To address potential selection bias, we used propensity score modeling. Survival of patients who received intermediate and complex simulation was compared using Cox regression models adjusting for propensity scores and in a stratified and matched analysis according to propensity scores. Results: Overall, 25% of patients received complex RT planning. Complex RT planning was associated with better overall (hazard ratio 0.84; 95% confidence interval, 0.75-0.95) and lung cancer-specific (hazard ratio 0.81; 95% confidence interval, 0.71-0.93) survival after controlling for propensity scores. Similarly, stratified and matched analyses showed better overall and lung cancer-specific survival of patients treated with complex RT planning. Conclusions: The use of complex RT planning is associated with improved survival among elderly patients with unresected Stage I-II NSCLC. These findings should be validated in prospective randomized controlled trials.

  1. Revascularization and cardioprotective drug treatment in myocardial infarction patients: how do they impact on patients' survival when delivered as usual care

    Directory of Open Access Journals (Sweden)

    Courteau Josiane

    2006-05-01

    Full Text Available Abstract Background Randomized clinical trials showed the benefit of pharmacological and revascularization treatments in secondary prevention of myocardial infarction (MI, in selected population with highly controlled interventions. The objective of this study is to measure these treatments' impact on the cardiovascular (CV mortality rate among patients receiving usual care in the province of Quebec. Methods The study population consisted of a "naturalistic" cohort of all patients ≥ 65 years old living in the Quebec province, who survived a MI (ICD-9: 410 in 1998. The studied dependant variable was time to death from a CV disease. Independent variables were revascularization procedure and cardioprotective drugs. Death from a non CV disease was also studied for comparison. Revascularization procedure was defined as percutaneous transluminal coronary angioplasty (PTCA or coronary artery bypass graft (CABG. The exposure to cardioprotective drugs was defined as the number of cardioprotective drug classes (Acetylsalicylic Acid (ASA, Beta-Blockers, Angiotensin-Converting Enzyme (ACE Inhibitors, Statins claimed within the index period (first 30 days after the index hospitalization. Age, gender and a comorbidity index were used as covariates. Kaplan-Meier survival curves, Cox proportional hazard models, logistic regressions and regression trees were used. Results The study population totaled 5596 patients (3206 men; 2390 women. We observed 1128 deaths (20% within two years following index hospitalization, of them 603 from CV disease. The CV survival rate at two years is much greater for patients with revascularization, regardless of pharmacological treatments. For patients without revascularization, the CV survival rate increases with the number of cardioprotective drug classes claimed. Finally, Cox proportional hazard models, regression tree and logistic regression analyses all revealed that the absence of revascularization and, to a lower extent

  2. Association between pre-transplant dialysis modality and patient and graft survival after kidney transplantation

    DEFF Research Database (Denmark)

    Kramer, Anneke; Jager, Kitty J; Fogarty, Damian G

    2012-01-01

    Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression.......Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression....

  3. Pre-therapeutic factors for predicting survival after radioembolization: a single-center experience in 389 patients

    International Nuclear Information System (INIS)

    Paprottka, K.J.; Schoeppe, F.; Ingrisch, M.; Ruebenthaler, J.; Sommer, N.N.; Paprottka, P.M.; Toni, E. de; Ilhan, H.; Zacherl, M.; Todica, A.

    2017-01-01

    To determine pre-therapeutic predictive factors for overall survival (OS) after yttrium (Y)-90 radioembolization (RE). We retrospectively analyzed the pre-therapeutic characteristics (sex, age, tumor entity, hepatic tumor burden, extrahepatic disease [EHD] and liver function [with focus on bilirubin and cholinesterase level]) of 389 consecutive patients with various refractory liver-dominant tumors (hepatocellular carcinoma [HCC], cholangiocarcinoma [CCC], neuroendocrine tumor [NET], colorectal cancer [CRC] and metastatic breast cancer [MBC]), who received Y-90 radioembolization for predicting survival. Predictive factors were selected by univariate Cox regression analysis and subsequently tested by multivariate analysis for predicting patient survival. The median OS was 356 days (95% CI 285-427 days). Stable disease was observed in 132 patients, an objective response in 71 (one of which was complete remission) and progressive disease in 122. The best survival rate was observed in patients with NET, and the worst in patients with MBC. In the univariate analyses, extrahepatic disease (P < 0.001), large tumor burden (P = 0.001), high bilirubin levels (>1.9 mg/dL, P < 0.001) and low cholinesterase levels (CHE <4.62 U/I, P < 0.001) at baseline were significantly associated with poor survival. Tumor entity, tumor burden, extrahepatic disease and CHE were confirmed in the multivariate analysis as independent predictors of survival. Sex, applied RE dose and age had no significant influence on OS. Pre-therapeutic baseline bilirubin and CHE levels, extrahepatic disease and hepatic tumor burden are associated with patient survival after RE. Such parameters may be used to improve patient selection for RE of primary or metastatic liver tumors. (orig.)

  4. Pre-therapeutic factors for predicting survival after radioembolization: a single-center experience in 389 patients

    Energy Technology Data Exchange (ETDEWEB)

    Paprottka, K.J.; Schoeppe, F.; Ingrisch, M.; Ruebenthaler, J.; Sommer, N.N.; Paprottka, P.M. [LMU - University of Munich, Department of Clinical Radiology, Munich (Germany); Toni, E. de [LMU - University of Munich, Department of Hepatology, Munich (Germany); Ilhan, H.; Zacherl, M.; Todica, A. [LMU - University of Munich, Department of Nuclear Medicine, Munich (Germany)

    2017-07-15

    To determine pre-therapeutic predictive factors for overall survival (OS) after yttrium (Y)-90 radioembolization (RE). We retrospectively analyzed the pre-therapeutic characteristics (sex, age, tumor entity, hepatic tumor burden, extrahepatic disease [EHD] and liver function [with focus on bilirubin and cholinesterase level]) of 389 consecutive patients with various refractory liver-dominant tumors (hepatocellular carcinoma [HCC], cholangiocarcinoma [CCC], neuroendocrine tumor [NET], colorectal cancer [CRC] and metastatic breast cancer [MBC]), who received Y-90 radioembolization for predicting survival. Predictive factors were selected by univariate Cox regression analysis and subsequently tested by multivariate analysis for predicting patient survival. The median OS was 356 days (95% CI 285-427 days). Stable disease was observed in 132 patients, an objective response in 71 (one of which was complete remission) and progressive disease in 122. The best survival rate was observed in patients with NET, and the worst in patients with MBC. In the univariate analyses, extrahepatic disease (P < 0.001), large tumor burden (P = 0.001), high bilirubin levels (>1.9 mg/dL, P < 0.001) and low cholinesterase levels (CHE <4.62 U/I, P < 0.001) at baseline were significantly associated with poor survival. Tumor entity, tumor burden, extrahepatic disease and CHE were confirmed in the multivariate analysis as independent predictors of survival. Sex, applied RE dose and age had no significant influence on OS. Pre-therapeutic baseline bilirubin and CHE levels, extrahepatic disease and hepatic tumor burden are associated with patient survival after RE. Such parameters may be used to improve patient selection for RE of primary or metastatic liver tumors. (orig.)

  5. THROMBOCYTOSIS AS PROGNOSTIC FACTOR FOR SURVIVAL IN PATIENTS WITH ADVANCED NON SMALL CELL LUNG CANCER TREATED WITH FIRST- LINE CHEMOTHERAPY.

    Directory of Open Access Journals (Sweden)

    Deyan Davidov

    2014-12-01

    Full Text Available Objective: The aim of this study was to evaluate elevated platelet count as a prognostic factor for survival in patients with advanced (stage IIIB/ IV non- small cell lung cancer (NSCLC receiving first- line chemotherapy. Methods: From 2005 to 2009 three hundreds forty seven consecutive patients with stage IIIB or IV NSCLC, treated in Department of Medical Oncology, UMHAT "Dr Georgi Stranski" entered the study. The therapeutic regimens included intravenous administration of platinum- based doublets. Survival analysis was evaluated by Kaplan- Meier test. The influence of pretreatment thrombocytosis as prognostic factor for survival was analyzed using multivariate stepwise Cox regression analyses. Results: Elevated platelet counts were found in 78 patients. The overall survival for patients without elevated platelet counts was 9,6 months versus 6,9 months for these with thrombocytosis. In multivariate analysis as independent poor prognostic factors were identified: stage, performance status and elevated platelet counts. Conclusions: These results indicated that platelet counts as well as some clinical pathologic characteristics could be useful prognostic factors in patients with unresectable NSCLC.

  6. Comparing parametric and nonparametric regression methods for panel data

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

  7. Obesity adversely affects survival in pancreatic cancer patients.

    Science.gov (United States)

    McWilliams, Robert R; Matsumoto, Martha E; Burch, Patrick A; Kim, George P; Halfdanarson, Thorvardur R; de Andrade, Mariza; Reid-Lombardo, Kaye; Bamlet, William R

    2010-11-01

    Higher body-mass index (BMI) has been implicated as a risk factor for developing pancreatic cancer, but its effect on survival has not been thoroughly investigated. The authors assessed the association of BMI with survival in a sample of pancreatic cancer patients and used epidemiologic and clinical information to understand the contribution of diabetes and hyperglycemia. A survival analysis using Cox proportional hazards by usual adult BMI was performed on 1861 unselected patients with pancreatic adenocarcinoma; analyses were adjusted for covariates that included clinical stage, age, and sex. Secondary analyses incorporated self-reported diabetes and fasting blood glucose in the survival model. BMI as a continuous variable was inversely associated with survival from pancreatic adenocarcinoma (hazard ratio [HR], 1.019 for each increased unit of BMI [kg/m2], PFasting blood glucose and diabetes did not affect the results. Higher BMI is associated with decreased survival in pancreatic cancer. Although the mechanism of this association remains undetermined, diabetes and hyperglycemia do not appear to account for the observed association. Copyright © 2010 American Cancer Society.

  8. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Adjuvant Sunitinib for High-risk Renal Cell Carcinoma After Nephrectomy: Subgroup Analyses and Updated Overall Survival Results.

    Science.gov (United States)

    Motzer, Robert J; Ravaud, Alain; Patard, Jean-Jacques; Pandha, Hardev S; George, Daniel J; Patel, Anup; Chang, Yen-Hwa; Escudier, Bernard; Donskov, Frede; Magheli, Ahmed; Carteni, Giacomo; Laguerre, Brigitte; Tomczak, Piotr; Breza, Jan; Gerletti, Paola; Lechuga, Mariajose; Lin, Xun; Casey, Michelle; Serfass, Lucile; Pantuck, Allan J; Staehler, Michael

    2018-01-01

    Adjuvant sunitinib significantly improved disease-free survival (DFS) versus placebo in patients with locoregional renal cell carcinoma (RCC) at high risk of recurrence after nephrectomy (hazard ratio [HR] 0.76, 95% confidence interval [CI] 0.59-0.98; p=0.03). To report the relationship between baseline factors and DFS, pattern of recurrence, and updated overall survival (OS). Data for 615 patients randomized to sunitinib (n=309) or placebo (n=306) in the S-TRAC trial. Subgroup DFS analyses by baseline risk factors were conducted using a Cox proportional hazards model. Baseline risk factors included: modified University of California Los Angeles integrated staging system criteria, age, gender, Eastern Cooperative Oncology Group performance status (ECOG PS), weight, neutrophil-to-lymphocyte ratio (NLR), and Fuhrman grade. Of 615 patients, 97 and 122 in the sunitinib and placebo arms developed metastatic disease, with the most common sites of distant recurrence being lung (40 and 49), lymph node (21 and 26), and liver (11 and 14), respectively. A benefit of adjuvant sunitinib over placebo was observed across subgroups, including: higher risk (T3, no or undetermined nodal involvement, Fuhrman grade ≥2, ECOG PS ≥1, T4 and/or nodal involvement; hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.55-0.99; p=0.04), NLR ≤3 (HR 0.72, 95% CI 0.54-0.95; p=0.02), and Fuhrman grade 3/4 (HR 0.73, 95% CI 0.55-0.98; p=0.04). All subgroup analyses were exploratory, and no adjustments for multiplicity were made. Median OS was not reached in either arm (HR 0.92, 95% CI 0.66-1.28; p=0.6); 67 and 74 patients died in the sunitinib and placebo arms, respectively. A benefit of adjuvant sunitinib over placebo was observed across subgroups. The results are consistent with the primary analysis, which showed a benefit for adjuvant sunitinib in patients at high risk of recurrent RCC after nephrectomy. Most subgroups of patients at high risk of recurrent renal cell carcinoma after

  10. Impact of Marital Status on Tumor Stage at Diagnosis and on Survival in Male Breast Cancer.

    Science.gov (United States)

    Adekolujo, Orimisan Samuel; Tadisina, Shourya; Koduru, Ujwala; Gernand, Jill; Smith, Susan Jane; Kakarala, Radhika Ramani

    2017-07-01

    The effect of marital status (MS) on survival varies according to cancer type and gender. There has been no report on the impact of MS on survival in male breast cancer (MBC). This study aims to determine the influence of MS on tumor stage at diagnosis and survival in MBC. Men with MBC ≥18 years of age in the SEER database from 1990 to 2011 were included in the study. MS was classified as married and unmarried (including single, divorced, separated, widowed). Kaplan-Meier method was used to estimate the 5-year cancer-specific survival. Multivariate regression analyses were done to determine the effect of MS on presence of Stage IV disease at diagnosis and on cancer-specific mortality. The study included 3,761 men; 2,647 (70.4%) were married. Unmarried men were more often diagnosed with Stage IV MBC compared with married (10.7% vs. 5.5%, p Unmarried men (compared with married) were significantly less likely to undergo surgery (92.4% vs. 96.7%, p unmarried males with Stages II, III, and IV MBC have significantly worse 5-year cancer-specific survival compared with married. On multivariate analysis, being unmarried was associated with increased hazard of death (HR = 1.43, p Unmarried males with breast cancer are at greater risk for Stage IV disease at diagnosis and poorer outcomes compared with married males.

  11. The relationship between survival of Columbia River fall chinook salmon and in-river environmental factors -- Analysis of historic data for juvenile and adult salmonid production: Phase 2. Final report

    International Nuclear Information System (INIS)

    Skalski, J.R.; Townsend, R.L.; Donnelly, R.F.; Hilborn, R.W.

    1996-12-01

    This project analyzes in greater detail the coded-wire-tag (CWT) returns of Priest Rapids Hatchery fall chinook for the years 1976--1989 initially begun by Hilborn et al. (1993a). These additional analyses were prompted by suggestions made by peer reviews of the initial draft report. The initial draft and the peer review comments are included in this final report (Appendices A and B). The statistical analyses paired Priest Rapids stock with potential downriver reference stocks to isolate in-river survival rates. Thirty-three potential reference stocks were initially examined for similar ocean recovery rates; the five stocks with the most similar recovery patterns (i.e., Bonneville Brights, Cowlitz, Gray's River, Tanner Creek, and Washougal) to the Priest Rapids stock were used in the subsequent analysis of in-river survival. Three alternate forms of multiple regression models were used to investigate the relationship between predicted in-river survival and ambient conditions. Analyses were conducted with and without attempts to adjust for smolt transportation at McNary Dam. Independent variables examined in the analysis included river flows, temperature, turbidity, and spill along with the total biomass of hatchery releases in the Columbia-Snake River Basin

  12. Fledgling survival increases with development time and adult survival across north and south temperate zones

    Science.gov (United States)

    Lloyd, Penn; Martin, Thomas E.

    2016-01-01

    Slow life histories are characterized by high adult survival and few offspring, which are thought to allow increased investment per offspring to increase juvenile survival. Consistent with this pattern, south temperate zone birds are commonly longer-lived and have fewer young than north temperate zone species. However, comparative analyses of juvenile survival, including during the first few weeks of the post-fledging period when most juvenile mortality occurs, are largely lacking. We combined our measurements of fledgling survival for eight passerines in South Africa with estimates from published studies of 57 north and south temperate zone songbird species to test three predictions: (1) fledgling survival increases with length of development time in the nest; (2) fledgling survival increases with adult survival and reduced brood size controlled for development time; and (3) south temperate zone species, with their higher adult survival and smaller brood sizes, exhibit higher fledgling survival than north temperate zone species controlled for development time. We found that fledgling survival was higher among south temperate zone species and generally increased with development time and adult survival within and between latitudinal regions. Clutch size did not explain additional variation, but was confounded with adult survival. Given the importance of age-specific mortality to life history evolution, understanding the causes of these geographical patterns of mortality is important.

  13. Causal Mediation Analysis of Survival Outcome with Multiple Mediators.

    Science.gov (United States)

    Huang, Yen-Tsung; Yang, Hwai-I

    2017-05-01

    Mediation analyses have been a popular approach to investigate the effect of an exposure on an outcome through a mediator. Mediation models with multiple mediators have been proposed for continuous and dichotomous outcomes. However, development of multimediator models for survival outcomes is still limited. We present methods for multimediator analyses using three survival models: Aalen additive hazard models, Cox proportional hazard models, and semiparametric probit models. Effects through mediators can be characterized by path-specific effects, for which definitions and identifiability assumptions are provided. We derive closed-form expressions for path-specific effects for the three models, which are intuitively interpreted using a causal diagram. Mediation analyses using Cox models under the rare-outcome assumption and Aalen additive hazard models consider effects on log hazard ratio and hazard difference, respectively; analyses using semiparametric probit models consider effects on difference in transformed survival time and survival probability. The three models were applied to a hepatitis study where we investigated effects of hepatitis C on liver cancer incidence mediated through baseline and/or follow-up hepatitis B viral load. The three methods show consistent results on respective effect scales, which suggest an adverse estimated effect of hepatitis C on liver cancer not mediated through hepatitis B, and a protective estimated effect mediated through the baseline (and possibly follow-up) of hepatitis B viral load. Causal mediation analyses of survival outcome with multiple mediators are developed for additive hazard and proportional hazard and probit models with utility demonstrated in a hepatitis study.

  14. Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

    Science.gov (United States)

    Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

    2014-01-01

    In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

  15. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  16. Multiple regression and beyond an introduction to multiple regression and structural equation modeling

    CERN Document Server

    Keith, Timothy Z

    2014-01-01

    Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

  17. PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

    Science.gov (United States)

    The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

  18. Edmondson-Steiner grade: A crucial predictor of recurrence and survival in hepatocellular carcinoma without microvascular invasio.

    Science.gov (United States)

    Zhou, Li; Rui, Jing-An; Zhou, Wei-Xun; Wang, Shao-Bin; Chen, Shu-Guang; Qu, Qiang

    2017-07-01

    Microvascular invasion (MVI), an important pathologic parameter, has been proven to be a powerful predictor of long-term prognosis in hepatocellular carcinoma (HCC). However, prognostic factors in HCC without MVI remain unknown. The present study aimed to identify the risk factors of recurrence and poor post-resectional survival in this type of HCC. A total of 109 patients with MVI-absent HCC underwent radical hepatectomy were enrolled. The influence of clinicopathologic variables on recurrence and patient survival was assessed using univariate and multivariate analyses. Chi-square test found that Edmondson-Steiner grade and satellite nodule were significantly associated with recurrence, while the former was the single marker for early recurrence. Stepwise logistic regression analysis demonstrated the independent predictive role of Edmondson-Steiner grade for recurrence. On the other hand, Edmondson-Steiner grade, serum AFP level and satellite nodule were significant for overall and disease-free survival in univariate analysis, whereas tumor size was linked to disease-free survival. Of the variables, Edmondson-Steiner grade, serum AFP level and satellite nodule were independent indicators. Edmondson-Steiner grade, a histological classification, carries robust prognostic implications for all the endpoints for prognosis, thus being potential to be a crucial prognosticator in HCC without MVI. Copyright © 2017 Elsevier GmbH. All rights reserved.

  19. Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models.

    Directory of Open Access Journals (Sweden)

    Luise A Seeker

    Full Text Available Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1 characterize the change in bovine relative leukocyte TL (RLTL across the lifetime in Holstein Friesian dairy cattle, 2 estimate genetic parameters of RLTL over time and 3 investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05-0.08 and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954.

  20. UK Renal Registry 15th annual report: Chapter 5 survival and causes of death of UK adult patients on renal replacement therapy in 2011: national and centre-specific analyses.

    Science.gov (United States)

    Steenkamp, Retha; Shaw, Catriona; Feest, Terry

    2013-01-01

    These analyses examine a) survival from the start of renal replacement therapy (RRT) based on the total incident UK RRT population reported to the UK Renal Registry, b) survival of prevalent patients. Changes in survival between 1997 and 2011 are also reported. Survival was calculated for both incident and prevalent patients on RRT and compared between the UK countries after adjustment for age. Survival of incident patients (starting RRT during 2010) was calculated both from the start of RRT and from 90 days after starting RRT, both with and without censoring at transplantation. Prevalent dialysis patients were censored at transplantation; this means that the patient is considered alive up to the point of transplantation, but the patient's status post-transplant is not considered. Both Kaplan-Meier and Cox adjusted models were used to calculate survival. Causes of death were analysed for both groups. The relative risk of death was calculated compared with the general UK population. The unadjusted 1 year after 90 day survival for patients starting RRT in 2010 was 87.3%, representing an increase from the previous year (86.6%). In incident patients aged 18-64 years, the unadjusted 1 year survival had risen from 86.0% in patients starting RRT in 1997 to 92.6% in patients starting RRT in 2010 and for those aged ≥65 it had increased from 63.9% to 77.0% over the same period. The age-adjusted one year survival (adjusted to age 60) of prevalent dialysis patients increased from 88.1% in the 2001 cohort to 89.8% in the 2010 cohort. Prevalent diabetic patient one year survival rose from 82.1% in the 2002 cohort to 84.7% in the 2010 cohort. The age-standardised mortality ratio for prevalent RRT patients compared with the general population was 18 for age group 30-34 and 2.5 at age 85+ years. In the prevalent RRT dialysis population, cardiovascular disease accounted for 22% of deaths, infection and treatment withdrawal 18% each and 25% were recorded as other causes of death

  1. Estimating haplotype effects for survival data.

    Science.gov (United States)

    Scheike, Thomas H; Martinussen, Torben; Silver, Jeremy D

    2010-09-01

    Genetic association studies often investigate the effect of haplotypes on an outcome of interest. Haplotypes are not observed directly, and this complicates the inclusion of such effects in survival models. We describe a new estimating equations approach for Cox's regression model to assess haplotype effects for survival data. These estimating equations are simple to implement and avoid the use of the EM algorithm, which may be slow in the context of the semiparametric Cox model with incomplete covariate information. These estimating equations also lead to easily computable, direct estimators of standard errors, and thus overcome some of the difficulty in obtaining variance estimators based on the EM algorithm in this setting. We also develop an easily implemented goodness-of-fit procedure for Cox's regression model including haplotype effects. Finally, we apply the procedures presented in this article to investigate possible haplotype effects of the PAF-receptor on cardiovascular events in patients with coronary artery disease, and compare our results to those based on the EM algorithm. © 2009, The International Biometric Society.

  2. Clinical characteristics and quality-of-life in patients surviving a decade of prostate cancer with bone metastases.

    Science.gov (United States)

    Klaff, Rami; Berglund, Anders; Varenhorst, Eberhard; Hedlund, Per Olov; Jǿnler, Morten; Sandblom, Gabriel

    2016-06-01

    To describe characteristics and quality-of-life (QoL), and to define factors associated with long-term survival in a subgroup of patients with prostate cancer with M1b disease. The study was based on 915 patients from a prospective randomised multicentre trial (No. 5) by the Scandinavian Prostate Cancer Group, comparing parenteral oestrogen with total androgen blockade. Long-term survival was defined as patients having an overall survival of ≥10 years, and logistic regression models were constructed to identity clinical predictors of survival. QoL during follow-up was assessed using the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaire - C30 version 1 (EORTC-C30) ratings. In all, 40 (4.4%) of the 915 men survived for >10 years. Factors significantly associated with increased likelihood of surviving for >10 years in the univariate analyses were: absence of cancer-related pain; Eastern Cooperative Oncology Group (ECOG) performance status of patients with short survival, but slowly declined over the decade. A subgroup of patients with prostate cancer with M1b disease and certain characteristics showed a positive long-term response to androgen-deprivation therapy with an acceptable QoL over a decade or more. Independent predictors of long-term survival were identified as ECOG performance status of <2, limited extent of bone metastases (Soloway score of 1), and a PSA level of <231 μg/L at the time of enrolment. © 2015 The Authors BJU International © 2015 BJU International Published by John Wiley & Sons Ltd.

  3. Pressure-Flow During Exercise Catheterization Predicts Survival in Pulmonary Hypertension.

    Science.gov (United States)

    Hasler, Elisabeth D; Müller-Mottet, Séverine; Furian, Michael; Saxer, Stéphanie; Huber, Lars C; Maggiorini, Marco; Speich, Rudolf; Bloch, Konrad E; Ulrich, Silvia

    2016-07-01

    Pulmonary hypertension manifests with impaired exercise capacity. Our aim was to investigate whether the mean pulmonary arterial pressure to cardiac output relationship (mPAP/CO) predicts transplant-free survival in patients with pulmonary arterial hypertension (PAH) and inoperable chronic thromboembolic pulmonary hypertension (CTEPH). Hemodynamic data according to right heart catheterization in patients with PAH and CTEPH at rest and during supine incremental cycle exercise were analyzed. Transplant-free survival and predictive value of hemodynamics were assessed by using Kaplan-Meier and Cox regression analyses. Seventy patients (43 female; 54 with PAH, 16 with CTEPH; median (quartiles) age, 65 [50; 73] years; mPAP, 34 [29; 44] mm Hg; cardiac index, 2.8 [2.3; 3.5] [L/min]/m(2)) were followed up for 610 (251; 1256) days. Survival at 1, 3, 5, and 7 years was 89%, 81%, 71%, and 59%. Age, World Health Organization-functional class, 6-min walk test, and mixed-venous oxygen saturation (but not resting hemodynamics) predicted transplant-free survival. Maximal workload (hazard ratio [HR], 0.94 [95% CI, 0.89-0.99]; P = .027), peak cardiac index (HR, 0.51 [95% CI, 0.27-0.95]; P = .034), change in cardiac index, 0.25 [95% CI, 0.06-0.94]; P = .040), and mPAP/CO (HR, 1.02 [95% CI, 1.01-1.03]; P = .003) during exercise predicted survival. Values for mPAP/CO predicted 3-year transplant-free survival with an area under the curve of 0.802 (95% CI, 0.66-0.95; P = .004). In this collective of patients with PAH or CTEPH, the pressure-flow relationship during exercise predicted transplant-free survival and correlated with established markers of disease severity and outcome. Right heart catheterization during exercise may provide important complementary prognostic information in the management of pulmonary hypertension. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  4. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies.

    NARCIS (Netherlands)

    Kromhout, D.

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements of the

  5. CASAS: Cancer Survival Analysis Suite, a web based application.

    Science.gov (United States)

    Rupji, Manali; Zhang, Xinyan; Kowalski, Jeanne

    2017-01-01

    We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/.

  6. Differential Survival for Men and Women with HIV/AIDS-Related Neurologic Diagnoses.

    Directory of Open Access Journals (Sweden)

    Martha L Carvour

    Full Text Available Neurologic complications of human immunodeficiency virus (HIV infection and acquired immune deficiency syndrome (AIDS frequently lead to disability or death in affected patients. The aim of this study was to determine whether survival patterns differ between men and women with HIV/AIDS-related neurologic disease (neuro-AIDS.Retrospective cohort data from a statewide surveillance database for HIV/AIDS were used to characterize survival following an HIV/AIDS-related neurologic diagnosis for men and women with one or more of the following conditions: cryptococcosis, toxoplasmosis, primary central nervous system lymphoma, progressive multifocal leukoencephalopathy, and HIV-associated dementia. A second, non-independent cohort was formed using university-based cases to confirm and extend the findings from the statewide data. Kaplan-Meier analysis was used to compare the survival experiences for men and women in the cohorts. Cox regression was employed to characterize survival while controlling for potential confounders in the study population.Women (n=27 had significantly poorer outcomes than men (n=198 in the statewide cohort (adjusted hazard ratio=2.31, 95% CI: 1.22 to 4.35, and a similar, non-significant trend was observed among university-based cases (n=17 women, 154 men. Secondary analyses suggested that this difference persisted over the course of the AIDS epidemic and was not attributable to differential antiretroviral therapy responses among men and women.The survival disadvantage of women compared to men should be confirmed and the mechanisms underlying this disparity elucidated. If this relationship is confirmed, targeted clinical and public health efforts might be directed towards screening, treatment, and support for women affected by neuro-AIDS.

  7. Socioeconomic disparity in survival after breast cancer in ireland: observational study.

    Directory of Open Access Journals (Sweden)

    Paul M Walsh

    Full Text Available We evaluated the relationship between breast cancer survival and deprivation using data from the Irish National Cancer Registry. Cause-specific survival was compared between five area-based socioeconomic deprivation strata using Cox regression. Patient and tumour characteristics and treatment were compared using modified Poisson regression with robust variance estimation. Based on 21356 patients diagnosed 1999-2008, age-standardized five-year survival averaged 80% in the least deprived and 75% in the most deprived stratum. Age-adjusted mortality risk was 33% higher in the most deprived group (hazard ratio 1.33, 95% CI 1.21-1.45, P<0.001. The most deprived groups were more likely to present with advanced stage, high grade or hormone receptor-negative cancer, symptomatically, or with significant comorbidity, and to be smokers or unmarried, and less likely to have breast-conserving surgery. Cox modelling suggested that the available data on patient, tumour and treatment factors could account for only about half of the survival disparity (adjusted hazard ratio 1.18, 95% CI 0.97-1.43, P = 0.093. Survival disparity did not diminish over time, compared with the period 1994-1998. Persistent survival disparities among Irish breast cancer patients suggest unequal use of or access to services and highlight the need for further research to understand and remove the behavioural or other barriers involved.

  8. Measurement Error in Education and Growth Regressions

    NARCIS (Netherlands)

    Portela, M.; Teulings, C.N.; Alessie, R.

    The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

  9. Measurement error in education and growth regressions

    NARCIS (Netherlands)

    Portela, Miguel; Teulings, Coen; Alessie, R.

    2004-01-01

    The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

  10. Regression analysis of censored data using pseudo-observations

    DEFF Research Database (Denmark)

    Parner, Erik T.; Andersen, Per Kragh

    2010-01-01

    We draw upon a series of articles in which a method based on pseu- dovalues is proposed for direct regression modeling of the survival function, the restricted mean, and the cumulative incidence function in competing risks with right-censored data. The models, once the pseudovalues have been...... computed, can be fit using standard generalized estimating equation software. Here we present Stata procedures for computing these pseudo-observations. An example from a bone marrow transplantation study is used to illustrate the method....

  11. Using threshold regression to analyze survival data from complex surveys: With application to mortality linked NHANES III Phase II genetic data.

    Science.gov (United States)

    Li, Yan; Xiao, Tao; Liao, Dandan; Lee, Mei-Ling Ting

    2018-03-30

    The Cox proportional hazards (PH) model is a common statistical technique used for analyzing time-to-event data. The assumption of PH, however, is not always appropriate in real applications. In cases where the assumption is not tenable, threshold regression (TR) and other survival methods, which do not require the PH assumption, are available and widely used. These alternative methods generally assume that the study data constitute simple random samples. In particular, TR has not been studied in the setting of complex surveys that involve (1) differential selection probabilities of study subjects and (2) intracluster correlations induced by multistage cluster sampling. In this paper, we extend TR procedures to account for complex sampling designs. The pseudo-maximum likelihood estimation technique is applied to estimate the TR model parameters. Computationally efficient Taylor linearization variance estimators that consider both the intracluster correlation and the differential selection probabilities are developed. The proposed methods are evaluated by using simulation experiments with various complex designs and illustrated empirically by using mortality-linked Third National Health and Nutrition Examination Survey Phase II genetic data. Copyright © 2017 John Wiley & Sons, Ltd.

  12. Predictors of Survival among Adult Ethiopian Patients in the National ART Program at Seven University Teaching Hospitals: A Prospective Cohort Study.

    Science.gov (United States)

    Fekade, Daniel; Weldegebreal, Teklu; Teklu, Alula M; Damen, Melake; Abdella, Saro; Baraki, Nega; Belayhun, Bekele; Berhan, Eyoel; Kebede, Amha; Assefa, Yibeltal

    2017-02-01

    In Ethiopia, the publicly funded antiretroviral treatment (ART) program was started in 2005. Two hundred seventy-five thousand patients were enrolled in the national ART program by 2012. However, there is limited data on mortality and predictors of death among adult patients in the ART program. The study aimed to estimate mortality and risk factors for death among adult, ART-naïve patients, started in the national ART program from January 2009 to July 2013. Multi-site, prospective, observational cohort study of adult, age > 18 years, ART-naïve patients, started in the national ART program at seven university-affiliated hospitals from January 2009 - July 2013. Kaplan-Meier and Cox regression analyses were used to estimate survival and determine risk factors for death. A total of 976 patients, 594 females (60.9 %), were enrolled into the study. Median age of the cohort was 33years. The median CD4 count at start of ART was 144 cells/µl (interquartile range (IQR) 78-205), and 34.2% (330/965) had CD4 ART. Cox regression analyses showed that the following measures independently predicted mortality: age >51 years, (Adjusted Hazard Ratio (AHR) 4.01, P=0.003), WHO stages III&IV, (AHR 1.76, p = 0.025), CD4 count, 5 log copies /ml (CHR 1.71, p = 0.037). There is high early on- ART mortality in patients presenting with advanced immunodeficiency. Detecting cases and initiating ART before onset of advanced immunodeficiency might improve survival.

  13. Vitamin K2 regression aortic calcification induced by warfarin via Gas6/Axl survival pathway in rats.

    Science.gov (United States)

    Jiang, Xiaoyu; Tao, Huiren; Qiu, Cuiting; Ma, Xiaolei; Li, Shan; Guo, Xian; Lv, Anlin; Li, Huan

    2016-09-05

    The aim of this study was to investigate the effect of vitamin K2 on aortic calcification induced by warfarin via Gas6/Axl survival pathway in rats. A calcification model was established by administering 3mg/g warfarin to rats. Rats were divided into 9 groups: control group (0W, 4W, 6W and 12W groups), 4W calcification group, 6W calcification group, 12W calcification group, 6W calcification+6W normal group and 6W calcification+6W vitamin K2 group. Alizarin red S staining measured aortic calcium depositions; alkaline phosphatase activity in serum was measured by a kit; apoptosis was evaluated by TUNEL assay; protein expression levels of Gas6, Axl, phosphorylated Akt (p-Akt), and Bcl-2 were determined by western blotting. The calcium content, calcium depositions, ALP activity and apoptosis were significantly higher in the calcification groups than control group. Gas6, Axl, p-Akt and Bcl-2 expression was lower in the calcification group than control group. 100μg/g vitamin K2 treatment decreased calcium depositions, ALP activity and apoptosis significantly, but increased Gas6, Axl, p-Akt and Bcl-2 expression. 100μg/g vitamin K2 reversed 44% calcification. Pearson correlation analysis showed a positive correlation between formation calcification and apoptosis (R(2)=0.8853, PK2 can inhibit warfarin-induced aortic calcification and apoptosis. The regression of aortic calcification by vitamin K2 involved the Gas6/Axl axis. This data may provide a theoretical basis for future clinical treatments for aortic calcification. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Timing of adjuvant chemotherapy and its relation to survival among patients with stage III colon cancer.

    Science.gov (United States)

    Bos, A C R K; van Erning, F N; van Gestel, Y R B M; Creemers, G J M; Punt, C J A; van Oijen, M G H; Lemmens, V E P P

    2015-11-01

    Currently available data suggest that delaying the start of adjuvant chemotherapy in colon cancer patients has a detrimental effect on survival. We analysed which factors impact on the timing of adjuvant chemotherapy and evaluated the influence on overall survival (OS). Stage III colon cancer patients who underwent resection and received adjuvant chemotherapy between 2008 and 2013 were selected from the Netherlands Cancer Registry. Timing of adjuvant chemotherapy was subdivided into: ⩽ 4, 5-6, 7-8, 9-10, 11-12 and 13-16 weeks post-surgery. Multivariable regressions were performed to assess the influence of several factors on the probability of starting treatment within 8 weeks post-surgery and to evaluate the association of timing of adjuvant chemotherapy with 5-year OS. 6620 patients received adjuvant chemotherapy, 14% commenced after 8 weeks. Factors associated with starting treatment after 8 weeks were older age (Odds ratio (OR) 65-74 versus colon cancer patients within 8 weeks post-surgery. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Elevated neutrophil and monocyte counts in peripheral blood are associated with poor survival in patients with metastatic melanoma: a prognostic model

    DEFF Research Database (Denmark)

    Schmidt, H; Bastholt, L; Geertsen, P

    2005-01-01

    factors in univariate analyses. Subsequently, a multivariate Cox's regression analysis identified elevated LDH (Pperformance status of 2 (P=0.008, hazard ratio 1.6) as independent prognostic factors for poor survival...... of several phase II protocols and the majority received treatment with intermediate dose subcutaneous IL-2 and interferon-alpha. Neutrophil and monocyte counts, lactate dehydrogenase (LDH), number of metastatic sites, location of metastases and performance status were all statistically significant prognostic...... survival of 12.6 months (95% confidence interval (CI), 11.4-13.8), 6.0 months (95% CI, 4.8-7.2) and 3.4 months (95% CI, 1.2-5.6), respectively. The low-risk group encompassed the majority of long-term survivors, whereas the patients in the high-risk group with a very poor prognosis should probably...

  16. Effect of Radiotherapy Interruptions on Survival in Medicare Enrollees With Local and Regional Head-and-Neck Cancer

    International Nuclear Information System (INIS)

    Fesinmeyer, Megan Dann; Mehta, Vivek; Blough, David; Tock, Lauri; Ramsey, Scott D.

    2010-01-01

    Purpose: To investigate whether interruptions in radiotherapy are associated with decreased survival in a population-based sample of head-and-neck cancer patients. Methods and Materials: Using the Surveillance, Epidemiology, and End Results-Medicare linked database we identified Medicare beneficiaries aged 66 years and older diagnosed with local-regional head-and-neck cancer during the period 1997-2003. We examined claims records of 3864 patients completing radiotherapy for the presence of one or more 5-30-day interruption(s) in therapy. We then performed Cox regression analyses to estimate the association between therapy interruptions and survival. Results: Patients with laryngeal tumors who experienced an interruption in radiotherapy had a 68% (95% confidence interval, 41-200%) increased risk of death, compared with patients with no interruptions. Patients with nasal cavity, nasopharynx, oral, salivary gland, and sinus tumors had similar associations between interruptions and increased risk of death, but these did not reach statistical significance because of small sample sizes. Conclusions: Treatment interruptions seem to influence survival time among patients with laryngeal tumors completing a full course of radiotherapy. At all head-and-neck sites, the association between interruptions and survival is sensitive to confounding by stage and other treatments. Further research is needed to develop methods to identify patients most susceptible to interruption-induced mortality.

  17. Quality of life assessment as a predictor of survival in non-small cell lung cancer

    Directory of Open Access Journals (Sweden)

    Staren Edgar D

    2011-08-01

    Full Text Available Abstract Background There are conflicting and inconsistent results in the literature on the prognostic role of quality of life (QoL in cancer. We investigated whether QoL at admission could predict survival in lung cancer patients. Methods The study population consisted of 1194 non-small cell lung cancer patients treated at our institution between Jan 2001 and Dec 2008. QoL was evaluated using EORTC-QLQ-C30 prior to initiation of treatment. Patient survival was defined as the time interval between the date of first patient visit and the date of death from any cause/date of last contact. Univariate and multivariate Cox regression evaluated the prognostic significance of QoL. Results Mean age at presentation was 58.3 years. There were 605 newly diagnosed and 589 previously treated patients; 601 males and 593 females. Stage of disease at diagnosis was I, 100; II, 63; III, 348; IV, 656; and 27 indeterminate. Upon multivariate analyses, global QoL as well as physical function predicted patient survival in the entire study population. Every 10-point increase in physical function was associated with a 10% increase in survival (95% CI = 6% to 14%, p Conclusions Baseline global QoL and physical function provide useful prognostic information in non-small cell lung cancer patients.

  18. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  19. Atrial fibrillation and survival in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Justin Timothy A

    2004-11-01

    Full Text Available Abstract Background Survival in colorectal cancer may correlate with the degree of systemic inflammatory response to the tumour. Atrial fibrillation may be regarded as an inflammatory complication. We aimed to determine if atrial fibrillation is a prognostic factor in colorectal cancer. Patients and methods A prospective colorectal cancer patient database was cross-referenced with the hospital clinical-coding database to identify patients who had underwent colorectal cancer surgery and were in atrial fibrillation pre- or postoperatively. Results A total of 175 patients underwent surgery for colorectal cancer over a two-year period. Of these, 13 patients had atrial fibrillation pre- or postoperatively. Atrial fibrillation correlated with worse two-year survival (p = 0.04; log-rank test. However, in a Cox regression analysis, atrial fibrillation was not significantly associated with survival. Conclusion The presence or development of atrial fibrillation in patients undergoing surgery for colorectal cancer is associated with worse overall survival, however it was not found to be an independent factor in multivariate analysis.

  20. Depression and Liver Transplant Survival.

    Science.gov (United States)

    Meller, William; Welle, Nicole; Sutley, Kristen; Thurber, Steven

    Patients who underwent liver transplantation and experienced clinical depression have heretofore evinced lower survival rates when compared to nondepressed counterparts. To investigate the hypothesis that transplant patients who seek and obtain medical treatment for depression would circumvent the prior reduced survival findings. A total of 765 patients with liver transplants were scrutinized for complications following transplantation. Further, 104 patients experienced posttransplant depression as manifested by diagnosis and treatment by medical personnel. Survival analyses were conducted comparing hazard and survival curves for these selected individuals and the remainder of transplant patients. Contrary to prior data and consistent with the aforementioned hypothesis, median survival durations, survival curves, and hazard functions (controlling for age and prolonged posttransplant survival for the depressed patients were better. The improved survival for the depressed patients may simply be related to an amelioration of depressed symptoms via antidepressant medications. However, this interpretation would only be congruent with reduced hazard, not elevated survival, beyond the norm (median) for other transplant participants. Assuming the reliability and generalization of our findings, perhaps a reasonable and compelling interpretation is that combined with the effectiveness of antidepressant medications, the seeking and receiving treatment for depression is a type of proxy measure of a more global pattern of adherence to recommended posttransplant medical regimens. Copyright © 2017 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

  1. Challenges in the estimation of Net SURvival: The CENSUR working survival group.

    Science.gov (United States)

    Giorgi, R

    2016-10-01

    Net survival, the survival probability that would be observed, in a hypothetical world, where the cancer of interest would be the only possible cause of death, is a key indicator in population-based cancer studies. Accounting for mortality due to other causes, it allows cross-country comparisons or trends analysis and provides a useful indicator for public health decision-making. The objective of this study was to show how the creation and formalization of a network comprising established research teams, which already had substantial and complementary experience in both cancer survival analysis and methodological development, make it possible to meet challenges and thus provide more adequate tools, to improve the quality and the comparability of cancer survival data, and to promote methodological transfers in areas of emerging interest. The Challenges in the Estimation of Net SURvival (CENSUR) working survival group is composed of international researchers highly skilled in biostatistics, methodology, and epidemiology, from different research organizations in France, the United Kingdom, Italy, Slovenia, and Canada, and involved in French (FRANCIM) and European (EUROCARE) cancer registry networks. The expected advantages are an interdisciplinary, international, synergistic network capable of addressing problems in public health, for decision-makers at different levels; tools for those in charge of net survival analyses; a common methodology that makes unbiased cross-national comparisons of cancer survival feasible; transfer of methods for net survival estimations to other specific applications (clinical research, occupational epidemiology); and dissemination of results during an international training course. The formalization of the international CENSUR working survival group was motivated by a need felt by scientists conducting population-based cancer research to discuss, develop, and monitor implementation of a common methodology to analyze net survival in order

  2. Cox regression with missing covariate data using a modified partial likelihood method

    DEFF Research Database (Denmark)

    Martinussen, Torben; Holst, Klaus K.; Scheike, Thomas H.

    2016-01-01

    Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard...

  3. Cerebrospinal fluid cytotoxicity does not affect survival in amyotrophic lateral sclerosis.

    Science.gov (United States)

    Galán, L; Matías-Guiu, J; Matias-Guiu, J A; Yáñez, M; Pytel, V; Guerrero-Sola, A; Vela-Souto, A; Arranz-Tagarro, J A; Gómez-Pinedo, U; García, A G

    2017-09-01

    Cerebrospinal fluid (CSF) from some patients with amyotrophic lateral sclerosis (ALS) has been demonstrated to significantly reduce the neuronal viability of primary cell cultures of motor neurons. We aimed to study the potential clinical consequences associated with the cytotoxicity of CSF in a cohort of patients with ALS. We collected CSF from thirty-one patients with ALS. We analysed cytotoxicity by incubating it into the primary cultures of motor cortex neurons. Neural viability was quantified after 24 hours using the colorimetric MTT reduction assay. All patients were followed up from the moment of diagnosis to death, and a complete evaluation during disease progression and survival was performed, including gastrostomy and respiratory assistance. Twenty-one patients (67.7%) presented a cytotoxic CSF. There were no significant differences between patients with and without cytotoxicity regarding mean time from symptom onset to the diagnosis, from the diagnosis to death, from the diagnosis to respiratory assistance with BIPAP, from diagnosis to gastrostomy and from the onset of symptoms to death. In Cox regression analysis, bulbar onset, but not cytotoxicity, gender or age at onset, was associated with a lower risk of survival. Cerebrospinal fluid cytotoxicity was not associated with differential survival rates. This suggests that the presence of cytotoxicity in CSF, measured through neuronal viability in primary cultures of motor cortex neurons, could reflect different mechanisms of the disease, but it does not predict disease outcome. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  5. Transcatheter arterial chemoembolization combined with radiofrequency ablation can improve survival of patients with hepatocellular carcinoma with portal vein tumour thrombosis: Extending the indication for ablation?

    International Nuclear Information System (INIS)

    Zheng, J.-S.; Long, J.; Sun, B.; Lu, N.-N.; Fang, D.; Zhao, L.-Y.; Du, N.

    2014-01-01

    Aim: To retrospectively assess long-term survival benefit and safety of transcatheter arterial chemoembolization (TACE) combined with radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC) patients with portal vein tumour thrombosis (PVTT), and to evaluate factors that significantly affect outcomes of these patients. Materials and methods: One hundred and thirty-four HCC patients (118 men and 16 women; mean age 54.8 years, range 26–79 years) with PVTT were retrospectively assessed. Patients were treated with TACE combined with RFA. Data analysed included patient demographics, liver volume, Child–Pugh score, and Cancer of the Liver Italian Programme (CLIP) score and imaging findings. Survival time (from occurrence of PVTT to last follow-up) was calculated using the Kaplan–Meier method, predictive factors and its correlation with survival was assessed using the multivariate Cox proportional hazards regression method. Results: The median overall survival (OS) time was 29.5 months (range 16.6–42.4 months), the 1, 3, and 5 year OS were 63%, 40%, and 23%. Cox hazards regression analysis revealed that functional remnant liver volume (FRLV), remnant liver volume (RLV)/total liver volume (TLV), radiation, tumour number, vascular endothelial growth factor (VEGF) distribution, and gross type were the only independent predictive factors of outcome (p = 0.039, 0.010, 0.009, 0.034, 0.031, and 0.000, respectively). Conclusion: TACE combined with RFA was found to be an effective therapy, FRLV and RLV/TLV have close correlation with survival for HCC patients with PVTT type I, II, or partial III and Child–Pugh A or B

  6. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  7. The effect of health insurance on childhood cancer survival in the United States.

    Science.gov (United States)

    Lee, Jong Min; Wang, Xiaoyan; Ojha, Rohit P; Johnson, Kimberly J

    2017-12-15

    The effect of health insurance on childhood cancer survival has not been well studied. Using Surveillance, Epidemiology, and End Results (SEER) data, this study was designed to assess the association between health insurance status and childhood cancer survival. Data on cancers diagnosed among children less than 15 years old from 2007 to 2009 were obtained from the SEER 18 registries. The effect of health insurance at diagnosis on 5-year childhood cancer mortality was estimated with marginal survival probabilities, restricted mean survival times, and Cox proportional hazards (PH) regression analyses, which were adjusted for age, sex, race/ethnicity, and county-level poverty. Among 8219 childhood cancer cases, the mean survival time was 1.32 months shorter (95% confidence interval [CI], -4.31 to 1.66) after 5 years for uninsured children (n = 131) versus those with private insurance (n = 4297), whereas the mean survival time was 0.62 months shorter (95% CI, -1.46 to 0.22) for children with Medicaid at diagnosis (n = 2838). In Cox PH models, children who were uninsured had a 1.26-fold higher risk of cancer death (95% CI, 0.84-1.90) than those who were privately insured at diagnosis. The risk for those with Medicaid was similar to the risk for those with private insurance at diagnosis (hazard ratio, 1.06; 95% CI, 0.93-1.21). Overall, the results suggest that cancer survival is largely similar for children with Medicaid and those with private insurance at diagnosis. Slightly inferior survival was observed for those who were uninsured in comparison with those with private insurance at diagnosis. The latter result is based on a small number of uninsured children and should be interpreted cautiously. Further study is needed to confirm and clarify the reasons for these patterns. Cancer 2017;123:4878-85. © 2017 American Cancer Society. © 2017 American Cancer Society.

  8. The survival rate of self-immolators in Kermanshah Province 2010- 2011

    Directory of Open Access Journals (Sweden)

    Farid Najafi

    2013-12-01

    Full Text Available Background: Self-immolation is one of the most violent methods of suicide, which is spreading in Iran. The highest rate of deaths due to committing suicide and self-immolation in Iran is observed in Kermanshah province. This research was conducted to study the survival rate and the factors that influence survival among the ones who commit self-immolation in Kermanshah province. Methods: In this study, all the cases who did not survive, as well as all the ones who were hospitalized due to self-immolation in Kermanshah province during 2010 and 2011 were examined. The Kaplan-Meier method was used to estimate the survival function, and in order to do the comparisons, Logrank test and Cox Regression were employed using Stata 12 software. Results: The results indicated that during 2010 and 2011, 343 individuals committed self-immolation in Kermanshah Province, while, 288 (84% were women. Also, it was found that 184 (53% did not survive, the mean and median of survival time in those who committed suicide deliberately, were 33±2.6 and 11±2 days respectively. Estimation of survival rate using Logrank test indicated that survival rate had a significant relationship with age, mental disorders, drug addiction, and TBSA (Total Body Surface Area, while it did not suggest a statistically significant relationship with gender, marital status and cause of injury. After multivariate analysis using Cox regression, only two variables of age and TBSA could remain in the model and the other variables were excluded from the model. Conclusion: The death toll due to self-immolation is very high and the mean and median of survival time among the people who committed self-immolation is very low. Therefore, it is recommended that remedial action be performed quickly without wasting time.

  9. Prognostic factorsin inoperable adenocarcinoma of the lung: A multivariate regression analysis of 259 patiens

    DEFF Research Database (Denmark)

    Sørensen, Jens Benn; Badsberg, Jens Henrik; Olsen, Jens

    1989-01-01

    The prognostic factors for survival in advanced adenocarcinoma of the lung were investigated in a consecutive series of 259 patients treated with chemotherapy. Twenty-eight pretreatment variables were investigated by use of Cox's multivariate regression model, including histological subtypes and ...

  10. SPECIFICS OF THE APPLICATIONS OF MULTIPLE REGRESSION MODEL IN THE ANALYSES OF THE EFFECTS OF GLOBAL FINANCIAL CRISES

    Directory of Open Access Journals (Sweden)

    Željko V. Račić

    2010-12-01

    Full Text Available This paper aims to present the specifics of the application of multiple linear regression model. The economic (financial crisis is analyzed in terms of gross domestic product which is in a function of the foreign trade balance (on one hand and the credit cards, i.e. indebtedness of the population on this basis (on the other hand, in the USA (from 1999. to 2008. We used the extended application model which shows how the analyst should run the whole development process of regression model. This process began with simple statistical features and the application of regression procedures, and ended with residual analysis, intended for the study of compatibility of data and model settings. This paper also analyzes the values of some standard statistics used in the selection of appropriate regression model. Testing of the model is carried out with the use of the Statistics PASW 17 program.

  11. Extended mitogenomic phylogenetic analyses yield new insight into crocodylian evolution and their survival of the Cretaceous-Tertiary boundary.

    Science.gov (United States)

    Roos, Jonas; Aggarwal, Ramesh K; Janke, Axel

    2007-11-01

    The mitochondrial genomes of the dwarf crocodile, Osteolaemus tetraspis, and two species of dwarf caimans, the smooth-fronted caiman, Paleosuchus trigonatus, and Cuvier's dwarf caiman, Paleosuchus palpebrosus, were sequenced and included in a mitogenomic phylogenetic study. The phylogenetic analyses, which included a total of ten crocodylian species, yielded strong support to a basal split between Crocodylidae and Alligatoridae. Osteolaemus fell within the Crocodylidae as the sister group to Crocodylus. Gavialis and Tomistoma, which joined on a common branch, constituted a sister group to Crocodylus/Osteolaemus. This suggests that extant crocodylians are organized in two families: Alligatoridae and Crocodylidae. Within the Alligatoridae there was a basal split between Alligator and a branch that contained Paleosuchus and Caiman. The analyses also provided molecular estimates of various divergences applying recently established crocodylian and outgroup fossil calibration points. Molecular estimates based on amino acid data placed the divergence between Crocodylidae and Alligatoridae at 97-103 million years ago and that between Alligator and Caiman/Paleosuchus at 65-72 million years ago. Other crocodilian divergences were placed after the Cretaceous-Tertiary boundary. Thus, according to the molecular estimates, three extant crocodylian lineages have their roots in the Cretaceous. Considering the crocodylian diversification in the Cretaceous the molecular datings suggest that the extinction of the dinosaurs was also to some extent paralleled in the crocodylian evolution. However, for whatever reason, some crocodylian lineages survived into the Tertiary.

  12. Individual social capital and survival

    DEFF Research Database (Denmark)

    Ejlskov, Linda; Mortensen, Rikke N; Overgaard, Charlotte

    2014-01-01

    BACKGROUND: The concept of social capital has received increasing attention as a determinant of population survival, but its significance is uncertain. We examined the importance of social capital on survival in a population study while focusing on gender differences. METHODS: We used data from...... a Danish regional health survey with a five-year follow-up period, 2007-2012 (n = 9288, 53.5% men, 46.5% women). We investigated the association between social capital and all-cause mortality, performing separate analyses on a composite measure as well as four specific dimensions of social capital while...... controlling for covariates. Analyses were performed with Cox proportional hazard models by which hazard ratios and 95% confidence intervals were calculated. RESULTS: For women, higher levels of social capital were associated with lower all-cause mortality regardless of age, socioeconomic status, health...

  13. Prehospital helicopter transport and survival of patients with traumatic brain injury.

    Science.gov (United States)

    Bekelis, Kimon; Missios, Symeon; Mackenzie, Todd A

    2015-03-01

    To investigate the association of helicopter transport with survival of patients with traumatic brain injury (TBI), in comparison with ground emergency medical services (EMS). Helicopter utilization and its effect on the outcomes of TBI remain controversial. We performed a retrospective cohort study involving patients with TBI who were registered in the National Trauma Data Bank between 2009 and 2011. Regression techniques with propensity score matching were used to investigate the association of helicopter transport with survival of patients with TBI, in comparison with ground EMS. During the study period, there were 209,529 patients with TBI who were registered in the National Trauma Data Bank and met the inclusion criteria. Of these patients, 35,334 were transported via helicopters and 174,195 via ground EMS. For patients transported to level I trauma centers, 2797 deaths (12%) were recorded after helicopter transport and 8161 (7.8%) after ground EMS. Multivariable logistic regression analysis demonstrated an association of helicopter transport with increased survival [OR (odds ratio), 1.95; 95% confidence interval (CI), 1.81-2.10; absolute risk reduction (ARR), 6.37%]. This persisted after propensity score matching (OR, 1.88; 95% CI, 1.74-2.03; ARR, 5.93%). For patients transported to level II trauma centers, 1282 deaths (10.6%) were recorded after helicopter transport and 5097 (7.3%) after ground EMS. Multivariable logistic regression analysis demonstrated an association of helicopter transport with increased survival (OR, 1.81; 95% CI, 1.64-2.00; ARR 5.17%). This again persisted after propensity score matching (OR, 1.73; 95% CI, 1.55-1.94; ARR, 4.69). Helicopter transport of patients with TBI to level I and II trauma centers was associated with improved survival, in comparison with ground EMS.

  14. Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

    Science.gov (United States)

    Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

    2018-03-01

    Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

  15. Is cancer survival associated with cancer symptom awareness and barriers to seeking medical help in England? An ecological study.

    Science.gov (United States)

    Niksic, Maja; Rachet, Bernard; Duffy, Stephen W; Quaresma, Manuela; Møller, Henrik; Forbes, Lindsay Jl

    2016-09-27

    Campaigns aimed at raising cancer awareness and encouraging early presentation have been implemented in England. However, little is known about whether people with low cancer awareness and increased barriers to seeking medical help have worse cancer survival, and whether there is a geographical variation in cancer awareness and barriers in England. From population-based surveys (n=35 308), using the Cancer Research UK Cancer Awareness Measure, we calculated the age- and sex-standardised symptom awareness and barriers scores for 52 primary care trusts (PCTs). These measures were evaluated in relation to the sex-, age-, and type of cancer-standardised cancer survival index of the corresponding PCT, from the National Cancer Registry, using linear regression. Breast, lung, and bowel cancer survival were analysed separately. Cancer symptom awareness and barriers scores varied greatly between geographical regions in England, with the worst scores observed in socioeconomically deprived parts of East London. Low cancer awareness score was associated with poor cancer survival at PCT level (estimated slope=1.56, 95% CI: 0.56; 2.57). The barriers score was not associated with overall cancer survival, but it was associated with breast cancer survival (estimated slope=-0.66, 95% CI: -1.20; -0.11). Specific barriers, such as embarrassment and difficulties in arranging transport to the doctor's surgery, were associated with worse breast cancer survival. Cancer symptom awareness and cancer survival are associated. Campaigns should focus on improving awareness about cancer symptoms, especially in socioeconomically deprived areas. Efforts should be made to alleviate barriers to seeking medical help in women with symptoms of breast cancer.

  16. Survival after elective surgery for colonic cancer in Denmark

    DEFF Research Database (Denmark)

    Perdawid, S K; Hemmingsen, L; Boesby, S

    2012-01-01

    AIM: Total mesorectal excision (TME) has been shown to improve the outcome for patients with rectal cancer. In contrast, there are fewer data on complete mesocolic excision (CME) for colonic cancer. METHOD: Data from the National Colorectal Cancer Database were analysed. This includes about 95......% of all patients with colorectal cancer in Denmark. Only patients having elective surgery for colonic cancer in the period 2001-2008 were included. Overall and relative survival analyses were carried out. The study period was divided into the periods 2001-2004 and 2005-2008. RESULTS: 9149 patients were...... included for the final analysis. The overall 5-year survival rates were 0.65 in 2001-2004 and 0.66 in 2005-2008. The relative 5-year survival rates were also within 1% of each other. None of these comparisons was statistically significant. CONCLUSION: Survival following elective colon cancer surgery has...

  17. [A SAS marco program for batch processing of univariate Cox regression analysis for great database].

    Science.gov (United States)

    Yang, Rendong; Xiong, Jie; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

    2015-02-01

    To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

  18. Survival and breast relapse in 3834 patients with T1-T2 breast cancer after conserving surgery and adjuvant treatment

    International Nuclear Information System (INIS)

    Livi, Lorenzo; Paiar, Fabiola; Saieva, Calogero; Scoccianti, Silvia; Dicosmo, Dora; Borghesi, Simona; Agresti, Benedetta; Nosi, Fabiano; Orzalesi, Lorenzo; Santini, Roberto; Barca, Raffaella; Biti, Giampaolo P.

    2007-01-01

    Purpose: The aim of the present analysis is to determine the long-term results in terms of breast relapse and specific survival in patients treated with conserving surgery and adjuvant treatment for early breast cancer. Methods: From January 1980 to December 2001, 3834 patients with pT1-T2 breast cancer were treated consecutively at the University of Florence. The median age of the patient population was 55 years (range 30-80). All patients were followed for a median of 7.4 years (range 0.6 year to 22.5 years). The crude probability of survival (or local recurrence) was estimated by using Kaplan-Meier method, and survival (or local recurrence) comparisons were carried out using Cox proportional hazard regression models. Results: The Cox regression model by stepwise selection showed some parameters, such as chemotherapy (HR 1.53; CI 1.19-1.95), pT status (HR 1.62, CI 1.31-2.01), positive axillary lymph nodes (HR 1.92, CI 1.66-2.22), and local recurrence (HR 4.58; CI 3.66-5.73), as independent prognostic factors for breast cancer death. Moreover, we found lower rate survival among patients treated before 1991 in comparison to women treated after 1991 (p = 0.0001) probably due to inadequate treatment. For local disease free survival, age at presentation (HR 0.47; CI 0.35-0.63), use of tamoxifen (HR 0.42; CI 0.25-0.71), surgical margins (HR 2.00; CI 1.21-3.30), and chemotherapy (HR 0.53; CI 0.31-0.91) emerged by multivariate analyses as significant breast relapse predictors. Conclusion: In our experience breast conserving surgery followed by adjuvant radiotherapy treatment gives high rates of local control in women with early breast cancer. The use of routinely adjuvant chemotherapy and hormone therapy lowered the local recurrence and probably the modification of therapeutic approach in the last decades also improved the specific survival

  19. Spontaneous regression of a large hepatocellular carcinoma: case report

    Directory of Open Access Journals (Sweden)

    Alqutub, Adel

    2011-01-01

    Full Text Available The prognosis of untreated advanced hepatocellular carcinoma (HCC is grim with a median survival of less than 6 months. Spontaneous regression of HCC has been defined as the disappearance of the hepatic lesions in the absence of any specific therapy. The spontaneous regression of a very large HCC is very rare and limited data is available in the English literature. We describe spontaneous regression of hepatocellular carcinoma in a 65-year-old male who presented to our clinic with vague abdominal pain and weight loss of two months duration. He was found to have multiple hepatic lesions with elevation of serum alpha-fetoprotein (AFP level to 6,500 µg/L (normal <20 µg/L. Computed tomography revealed advanced HCC replacing almost 80% of the right hepatic lobe. Without any intervention the patient showed gradual improvement over a period of few months. Follow-up CT scan revealed disappearance of hepatic lesions with progressive decline of AFP levels to normal. Various mechanisms have been postulated to explain this rare phenomenon, but the exact mechanism remains a mystery.

  20. Independent contrasts and PGLS regression estimators are equivalent.

    Science.gov (United States)

    Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

    2012-05-01

    We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

  1. Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study.

    Science.gov (United States)

    Shi, Xiao; Zhang, Ting-Ting; Hu, Wei-Ping; Ji, Qing-Hai

    2017-04-25

    The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187-1.339, P married patients were more likely to be diagnosed at earlier stage (P Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role.

  2. Cancer survival for Aboriginal and Torres Strait Islander Australians: a national study of survival rates and excess mortality.

    Science.gov (United States)

    Condon, John R; Zhang, Xiaohua; Baade, Peter; Griffiths, Kalinda; Cunningham, Joan; Roder, David M; Coory, Michael; Jelfs, Paul L; Threlfall, Tim

    2014-01-31

    National cancer survival statistics are available for the total Australian population but not Indigenous Australians, although their cancer mortality rates are known to be higher than those of other Australians. We aimed to validate analysis methods and report cancer survival rates for Indigenous Australians as the basis for regular national reporting. We used national cancer registrations data to calculate all-cancer and site-specific relative survival for Indigenous Australians (compared with non-Indigenous Australians) diagnosed in 2001-2005. Because of limited availability of Indigenous life tables, we validated and used cause-specific survival (rather than relative survival) for proportional hazards regression to analyze time trends and regional variation in all-cancer survival between 1991 and 2005. Survival was lower for Indigenous than non-Indigenous Australians for all cancers combined and for many cancer sites. The excess mortality of Indigenous people with cancer was restricted to the first three years after diagnosis, and greatest in the first year. Survival was lower for rural and remote than urban residents; this disparity was much greater for Indigenous people. Survival improved between 1991 and 2005 for non-Indigenous people (mortality decreased by 28%), but to a much lesser extent for Indigenous people (11%) and only for those in remote areas; cancer survival did not improve for urban Indigenous residents. Cancer survival is lower for Indigenous than other Australians, for all cancers combined and many individual cancer sites, although more accurate recording of Indigenous status by cancer registers is required before the extent of this disadvantage can be known with certainty. Cancer care for Indigenous Australians needs to be considerably improved; cancer diagnosis, treatment, and support services need to be redesigned specifically to be accessible and acceptable to Indigenous people.

  3. The effect of marital status on stage and survival of prostate cancer patients treated with radical prostatectomy: a population-based study.

    Science.gov (United States)

    Abdollah, Firas; Sun, Maxine; Thuret, Rodolphe; Abdo, Al'a; Morgan, Monica; Jeldres, Claudio; Shariat, Shahrokh F; Perrotte, Paul; Montorsi, Francesco; Karakiewicz, Pierre I

    2011-08-01

    The detrimental effect of unmarried marital status on stage and survival has been confirmed in several malignancies. We set to test whether this applied to patients diagnosed with prostate cancer (PCa) treated with radical prostatectomy (RP). We identified 163,697 non-metastatic PCa patients treated with RP, within 17 Surveillance, Epidemiology, and End Results registries. Logistic regression analyses focused on the rate of locally advanced stage (pT3-4/pN1) at RP. Cox regression analyses tested the relationship between marital status and cancer-specific (CSM), as well as all-cause mortality (ACM). Respectively, 9.1 and 7.8% of individuals were separated/divorced/widowed (SDW) and never married. SDW men had more advanced stage at surgery (odds ratio: 1.1; p married men. Similarly, never married marital status portended to a higher ACM rate (HR:1.2, p = 0.001). These findings were consistent when analyses were stratified according to organ confined vs. locally advanced stages. Being SDW significantly increased the risk of more advanced stage at RP. Following surgery, SDW men portended to a higher CSM and ACM rate than married men. Consequently, these individuals may benefit from a more focused health care throughout the natural history of their disease.

  4. Adjuvant Sunitinib for High-risk Renal Cell Carcinoma After Nephrectomy: Subgroup Analyses and Updated Overall Survival Results

    DEFF Research Database (Denmark)

    Motzer, Robert J; Ravaud, Alain; Patard, Jean-Jacques

    2018-01-01

    BACKGROUND: Adjuvant sunitinib significantly improved disease-free survival (DFS) versus placebo in patients with locoregional renal cell carcinoma (RCC) at high risk of recurrence after nephrectomy (hazard ratio [HR] 0.76, 95% confidence interval [CI] 0.59-0.98; p=0.03). OBJECTIVE: To report...... sunitinib over placebo was observed across subgroups, including: higher risk (T3, no or undetermined nodal involvement, Fuhrman grade ≥2, ECOG PS ≥1, T4 and/or nodal involvement; hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.55-0.99; p=0.04), NLR ≤3 (HR 0.72, 95% CI 0.54-0.95; p=0.02), and Fuhrman...... grade 3/4 (HR 0.73, 95% CI 0.55-0.98; p=0.04). All subgroup analyses were exploratory, and no adjustments for multiplicity were made. Median OS was not reached in either arm (HR 0.92, 95% CI 0.66-1.28; p=0.6); 67 and 74 patients died in the sunitinib and placebo arms, respectively. CONCLUSIONS...

  5. Sparing Sphincters and Laparoscopic Resection Improve Survival by Optimizing the Circumferential Resection Margin in Rectal Cancer Patients.

    Science.gov (United States)

    Keskin, Metin; Bayraktar, Adem; Sivirikoz, Emre; Yegen, Gülcin; Karip, Bora; Saglam, Esra; Bulut, Mehmet Türker; Balik, Emre

    2016-02-01

    The goal of rectal cancer treatment is to minimize the local recurrence rate and extend the disease-free survival period and survival. For this aim, obtainment of negative circumferential radial margin (CRM) plays an important role. This study evaluated predictive factors for positive CRM status and its effect on patient survival in mid- and distal rectal tumors.Patients who underwent curative resection for rectal cancer were included. The main factors were demographic data, tumor location, surgical technique, neoadjuvant therapy, tumor diameter, tumor depth, lymph node metastasis, mesorectal integrity, CRM, the rate of local recurrence, distant metastasis, and overall and disease-free survival. Statistical analyses were performed by using the Chi-squared test, Fisher exact test, Student t test, Mann-Whitney U test and the Mantel-Cox log-rank sum test.A total of 420 patients were included, 232 (55%) of whom were male. We observed no significant differences in patient characteristics or surgical treatment between the patients who had positive CRM and who had negative CRM, but a higher positive CRM rate was observed in patients undergone abdominoperineal resection (APR) (P CRM status. Logistic regression analysis revealed that APR (P CRM status. Moreover, positive CRM was associated with decreased 5-year overall and disease-free survival (P = 0.002 and P = 0.004, respectively).This large single-institution series demonstrated that APR and open resection were independent predictive factors for positive CRM status in rectal cancer. Positive CRM independently decreased the 5-year overall and disease-free survival rates.

  6. A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.

    Science.gov (United States)

    Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin

    2018-04-01

    Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  7. Comparative Survival in Patients With Postresection Recurrent Versus Newly Diagnosed Non-Small-Cell Lung Cancer Treated With Radiotherapy

    International Nuclear Information System (INIS)

    Cai Xuwei; Xu Luying; Wang Li; Hayman, James A.; Chang, Andrew C.; Pickens, Allan; Cease, Kemp B.; Orringer, Mark B.; Kong, F.-M.

    2010-01-01

    Purpose: To compare the survival of postresection recurrent vs. newly diagnosed non-small-cell lung cancer (NSCLC) patients treated with radiotherapy or chemoradiotherapy. Methods and Materials: The study population consisted of 661 consecutive patients with NSCLC registered in the radiation oncology databases at two medical centers in the United States between 1992 and 2004. Of the 661 patients, 54 had postresection recurrent NSCLC and 607 had newly diagnosed NSCLC. Kaplan-Meier and Cox regression models were used for the survival analyses. Results: The distribution of relevant clinical factors between these two groups was similar. The median survival time and 5-year overall survival rates were 19.8 months (95% confidence interval [CI], 13.9-25.7) and 14.8% (95% confidence interval, 5.4-24.2%) vs. 12.2 months (95% CI, 10.8-13.6) and 11.0% (95% CI, 8.5-13.5%) for recurrent vs. newly diagnosed patients, respectively (p = .037). For Stage I-III patients, no significant difference was observed in the 5-year overall survival (p = .297) or progression-free survival (p = .935) between recurrent and newly diagnosed patients. For the 46 patients with Stage I-III recurrent disease, multivariate analysis showed that chemotherapy was a significant prognostic factor for 5-year progression-free survival (hazard ratio, 0.45; 95% CI, 0.224-0.914; p = .027). Conclusion: Our institutional data have shown that patients with postresection recurrent NSCLC achieved survival comparable to that of newly diagnosed NSCLC patients when they were both treated with radiotherapy or chemoradiotherapy. These findings suggest that patients with postresection recurrent NSCLC should be treated as aggressively as those with newly diagnosed disease.

  8. Survival Outcomes in Resected Extrahepatic Cholangiocarcinoma: Effect of Adjuvant Radiotherapy in a Surveillance, Epidemiology, and End Results Analysis

    International Nuclear Information System (INIS)

    Vern-Gross, Tamara Z.; Shivnani, Anand T.; Chen, Ke; Lee, Christopher M.; Tward, Jonathan D.; MacDonald, O. Kenneth; Crane, Christopher H.; Talamonti, Mark S.; Munoz, Louis L.; Small, William

    2011-01-01

    Purpose: The benefit of adjuvant radiotherapy (RT) after surgical resection for extrahepatic cholangiocarcinoma has not been clearly established. We analyzed survival outcomes of patients with resected extrahepatic cholangiocarcinoma and examined the effect of adjuvant RT. Methods and Materials: Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) program between 1973 and 2003. The primary endpoint was the overall survival time. Cox regression analysis was used to perform univariate and multivariate analyses of the following clinical variables: age, year of diagnosis, histologic grade, localized (Stage T1-T2) vs. regional (Stage T3 or greater and/or node positive) stage, gender, race, and the use of adjuvant RT after surgical resection. Results: The records for 2,332 patients were obtained. Patients with previous malignancy, distant disease, incomplete or conflicting records, atypical histologic features, and those treated with preoperative/intraoperative RT were excluded. Of the remaining 1,491 patients eligible for analysis, 473 (32%) had undergone adjuvant RT. After a median follow-up of 27 months (among surviving patients), the median overall survival time for the entire cohort was 20 months. Patients with localized and regional disease had a median survival time of 33 and 18 months, respectively (p < .001). The addition of adjuvant RT was not associated with an improvement in overall or cause-specific survival for patients with local or regional disease. Conclusion: Patients with localized disease had significantly better overall survival than those with regional disease. Adjuvant RT was not associated with an improvement in long-term overall survival in patients with resected extrahepatic bile duct cancer. Key data, including margin status and the use of combined chemotherapy, was not available through the SEER database.

  9. Comparative Analyses of Nonpathogenic, Opportunistic, and Totally Pathogenic Mycobacteria Reveal Genomic and Biochemical Variabilities and Highlight the Survival Attributes of Mycobacterium tuberculosis

    Science.gov (United States)

    Singh, Yadvir; Kohli, Sakshi; Ahmad, Javeed; Ehtesham, Nasreen Z.; Tyagi, Anil K.

    2014-01-01

    ABSTRACT Mycobacterial evolution involves various processes, such as genome reduction, gene cooption, and critical gene acquisition. Our comparative genome size analysis of 44 mycobacterial genomes revealed that the nonpathogenic (NP) genomes were bigger than those of opportunistic (OP) or totally pathogenic (TP) mycobacteria, with the TP genomes being smaller yet variable in size—their genomic plasticity reflected their ability to evolve and survive under various environmental conditions. From the 44 mycobacterial species, 13 species, representing TP, OP, and NP, were selected for genomic-relatedness analyses. Analysis of homologous protein-coding genes shared between Mycobacterium indicus pranii (NP), Mycobacterium intracellulare ATCC 13950 (OP), and Mycobacterium tuberculosis H37Rv (TP) revealed that 4,995 (i.e., ~95%) M. indicaus pranii proteins have homology with M. intracellulare, whereas the homologies among M. indicus pranii, M. intracellulare ATCC 13950, and M. tuberculosis H37Rv were significantly lower. A total of 4,153 (~79%) M. indicus pranii proteins and 4,093 (~79%) M. intracellulare ATCC 13950 proteins exhibited homology with the M. tuberculosis H37Rv proteome, while 3,301 (~82%) and 3,295 (~82%) M. tuberculosis H37Rv proteins showed homology with M. indicus pranii and M. intracellulare ATCC 13950 proteomes, respectively. Comparative metabolic pathway analyses of TP/OP/NP mycobacteria showed enzymatic plasticity between M. indicus pranii (NP) and M. intracellulare ATCC 13950 (OP), Mycobacterium avium 104 (OP), and M. tuberculosis H37Rv (TP). Mycobacterium tuberculosis seems to have acquired novel alternate pathways with possible roles in metabolism, host-pathogen interactions, virulence, and intracellular survival, and by implication some of these could be potential drug targets. PMID:25370496

  10. Classification and Regression Tree Analysis of Clinical Patterns that Predict Survival in 127 Chinese Patients with Advanced Non-small Cell Lung Cancer Treated by Gefitinib Who Failed to Previous Chemotherapy

    Directory of Open Access Journals (Sweden)

    Ziping WANG

    2011-09-01

    Full Text Available Background and objective It has been proven that gefitinib produces only 10%-20% tumor regression in heavily pretreated, unselected non-small cell lung cancer (NSCLC patients as the second- and third-line setting. Asian, female, nonsmokers and adenocarcinoma are favorable factors; however, it is difficult to find a patient satisfying all the above clinical characteristics. The aim of this study is to identify novel predicting factors, and to explore the interactions between clinical variables and their impact on the survival of Chinese patients with advanced NSCLC who were heavily treated with gefitinib in the second- or third-line setting. Methods The clinical and follow-up data of 127 advanced NSCLC patients referred to the Cancer Hospital & Institute, Chinese Academy of Medical Sciences from March 2005 to March 2010 were analyzed. Multivariate analysis of progression-free survival (PFS was performed using recursive partitioning, which is referred to as the classification and regression tree (CART analysis. Results The median PFS of 127 eligible consecutive advanced NSCLC patients was 8.0 months (95%CI: 5.8-10.2. CART was performed with an initial split on first-line chemotherapy outcomes and a second split on patients’ age. Three terminal subgroups were formed. The median PFS of the three subsets ranged from 1.0 month (95%CI: 0.8-1.2 for those with progressive disease outcome after the first-line chemotherapy subgroup, 10 months (95%CI: 7.0-13.0 in patients with a partial response or stable disease in first-line chemotherapy and age <70, and 22.0 months for patients obtaining a partial response or stable disease in first-line chemotherapy at age 70-81 (95%CI: 3.8-40.1. Conclusion Partial response, stable disease in first-line chemotherapy and age ≥ 70 are closely correlated with long-term survival treated by gefitinib as a second- or third-line setting in advanced NSCLC. CART can be used to identify previously unappreciated patient

  11. Meta-analysis of single-arm survival studies: a distribution-free approach for estimating summary survival curves with random effects.

    Science.gov (United States)

    Combescure, Christophe; Foucher, Yohann; Jackson, Daniel

    2014-07-10

    In epidemiologic studies and clinical trials with time-dependent outcome (for instance death or disease progression), survival curves are used to describe the risk of the event over time. In meta-analyses of studies reporting a survival curve, the most informative finding is a summary survival curve. In this paper, we propose a method to obtain a distribution-free summary survival curve by expanding the product-limit estimator of survival for aggregated survival data. The extension of DerSimonian and Laird's methodology for multiple outcomes is applied to account for the between-study heterogeneity. Statistics I(2)  and H(2) are used to quantify the impact of the heterogeneity in the published survival curves. A statistical test for between-strata comparison is proposed, with the aim to explore study-level factors potentially associated with survival. The performance of the proposed approach is evaluated in a simulation study. Our approach is also applied to synthesize the survival of untreated patients with hepatocellular carcinoma from aggregate data of 27 studies and synthesize the graft survival of kidney transplant recipients from individual data from six hospitals. Copyright © 2014 John Wiley & Sons, Ltd.

  12. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data.

    Science.gov (United States)

    Nasejje, Justine B; Mwambi, Henry; Dheda, Keertan; Lesosky, Maia

    2017-07-28

    Random survival forest (RSF) models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF) are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. In this study, we compare the random survival forest model to the conditional inference model (CIF) using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points). The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB) which consists of mainly categorical covariates with two levels (few split-points). The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

  13. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data

    Directory of Open Access Journals (Sweden)

    Justine B. Nasejje

    2017-07-01

    Full Text Available Abstract Background Random survival forest (RSF models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. Methods In this study, we compare the random survival forest model to the conditional inference model (CIF using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points. The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB which consists of mainly categorical covariates with two levels (few split-points. Results The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Conclusion Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

  14. Logistic regression and multiple classification analyses to explore risk factors of under-5 mortality in bangladesh

    International Nuclear Information System (INIS)

    Bhowmik, K.R.; Islam, S.

    2016-01-01

    Logistic regression (LR) analysis is the most common statistical methodology to find out the determinants of childhood mortality. However, the significant predictors cannot be ranked according to their influence on the response variable. Multiple classification (MC) analysis can be applied to identify the significant predictors with a priority index which helps to rank the predictors. The main objective of the study is to find the socio-demographic determinants of childhood mortality at neonatal, post-neonatal, and post-infant period by fitting LR model as well as to rank those through MC analysis. The study is conducted using the data of Bangladesh Demographic and Health Survey 2007 where birth and death information of children were collected from their mothers. Three dichotomous response variables are constructed from children age at death to fit the LR and MC models. Socio-economic and demographic variables significantly associated with the response variables separately are considered in LR and MC analyses. Both the LR and MC models identified the same significant predictors for specific childhood mortality. For both the neonatal and child mortality, biological factors of children, regional settings, and parents socio-economic status are found as 1st, 2nd, and 3rd significant groups of predictors respectively. Mother education and household environment are detected as major significant predictors of post-neonatal mortality. This study shows that MC analysis with or without LR analysis can be applied to detect determinants with rank which help the policy makers taking initiatives on a priority basis. (author)

  15. Choline kinase alpha and hexokinase-2 protein expression in hepatocellular carcinoma: association with survival.

    Directory of Open Access Journals (Sweden)

    Sandi A Kwee

    Full Text Available PURPOSE: Hexokinase-2 (HK2 and more recently choline kinase alpha (CKA expression has been correlated with clinical outcomes in several major cancers. This study examines the protein expression of HK2 and CKA in hepatocellular carcinoma (HCC in association with patient survival and other clinicopathologic parameters. METHODS: Immunohistochemical analysis for HK2 and CKA expression was performed on a tissue microarray of 157 HCC tumor samples. Results were analyzed in relation to clinicopathologic data from Surveillance, Epidemiology, and End-Results Program registries. Mortality rates were assessed by Kaplan-Meier estimates and compared using log-rank tests. Predictors of overall survival were assessed using proportional hazards regression. RESULTS: Immunohistochemical expression of HK2 and CKA was detected in 71 (45% and 55 (35% tumor samples, respectively. Differences in tumor HK2 expression were associated with tumor grade (p = 0.008 and cancer stage (p = 0.001, while CKA expression differed significantly only across cancer stage (p = 0.048. Increased mortality was associated with tumor HK2 expression (p = 0.003 as well as CKA expression (p = 0.03 with hazard ratios of 1.86 (95% confidence interval (CI 1.23-2.83 and 1.59 (95% CI 1.04-2.41, respectively. Similar effects on overall survival were noted in a subset analysis of early stage (I and II HCC. Tumor HK2 expression, but not CKA expression, remained a significant predictor of survival in multivariable analyses. CONCLUSION: HK2 and CKA expression may have biologic and prognostic significance in HCC, with tumor HK2 expression being a potential independent predictor of survival.

  16. Dedifferentiated chondrosarcoma: A survival analysis of 159 cases from the SEER database (2001-2011).

    Science.gov (United States)

    Strotman, Patrick K; Reif, Taylor J; Kliethermes, Stephanie A; Sandhu, Jasmin K; Nystrom, Lukas M

    2017-08-01

    Dedifferentiated chondrosarcoma is a rare malignancy with reported 5-year overall survival rates ranging from 7% to 24%. The purpose of this investigation is to determine the overall survival of dedifferentiated chondrosarcoma in a modern patient series and how it is impacted by patient demographics, tumor characteristics, and surgical treatment factors. This is a retrospective review of the Surveillance, Epidemiology, and End Results (SEER) database from 2001 to 2011. Kaplan Meier analyses were used for overall and disease-specific survival. Univariable and multivariable cox regression models were used to identify prognostic factors. Five year overall- and disease-specific survival was 18% (95% CI: 12-26%) and 28% (95% CI: 18-37%), respectively. Individuals with extremity tumors had a worse prognosis than individuals with a primary tumor in the chest wall or axial skeleton (HR 0.20, 95% CI: 0.07-0.56; P = 0.002 and HR 0.60, 95% CI: 0.36-0.99; P = 0.04, respectively). Patients with AJCC stage III or IV disease (HR 2.51, 95% CI: 1.50-4.20; P = 0.001), tumors larger than 8 cm (HR 2.17, 95% CI: 1.11-4.27; P = 0.046), metastatic disease at diagnosis (HR 3.25, 95% CI: 1.98-5.33; P chondrosarcoma is poor with a 5-year overall survival of 18%. Patients with a primary tumor located in the chest wall had a better prognosis. Tumors larger than 8 cm, presence of metastases at diagnosis, and treatment without surgical resection were significant predictors of mortality. © 2017 Wiley Periodicals, Inc.

  17. Simultaneous confidence bands for Cox regression from semiparametric random censorship.

    Science.gov (United States)

    Mondal, Shoubhik; Subramanian, Sundarraman

    2016-01-01

    Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.

  18. Probabilistic Survivability Versus Time Modeling

    Science.gov (United States)

    Joyner, James J., Sr.

    2016-01-01

    This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

  19. Association between obesity with disease-free survival and overall survival in triple-negative breast cancer: A meta-analysis.

    Science.gov (United States)

    Mei, Lin; He, Lin; Song, Yuhua; Lv, Yang; Zhang, Lijiu; Hao, Fengxi; Xu, Mengmeng

    2018-05-01

    To investigate the relationship between obesity and disease-free survival (DFS) and overall survival (OS) of triple-negative breast cancer. Citations were searched in PubMed, Cochrane Library, and Web of Science. Random effect model meta-analysis was conducted by using Revman software version 5.0, and publication bias was evaluated by creating Egger regression with STATA software version 12. Nine studies (4412 patients) were included for DFS meta-analysis, 8 studies (4392 patients) include for OS meta-analysis. There were no statistical significances between obesity with DFS (P = .60) and OS (P = .71) in triple-negative breast cancer (TNBC) patients. Obesity has no impact on DFS and OS in patients with TNBC.

  20. The difference in association between aspirin use and other thrombocyte aggregation inhibitors and survival in patients with colorectal cancer.

    Science.gov (United States)

    Frouws, M A; Rademaker, E; Bastiaannet, E; van Herk-Sukel, M P P; Lemmens, V E; Van de Velde, C J H; Portielje, J E A; Liefers, G J

    2017-05-01

    Several studies have suggested that the association between aspirin and improved cancer survival is mediated through the mechanism of aspirin as thrombocyte aggregation inhibitors (TAI). The aim of this study was to provide epidemiological evidence for this mechanism assessing the association between overall survival and the use of aspirin and non-aspirin TAI in patients with colorectal cancer. In this observational study, data from the Netherlands Comprehensive Cancer Organisation were linked to PHARMO Database Network. Patients using aspirin or aspirin in combination with non-aspirin TAI (dual users) were selected and compared with non-users. The association between overall survival and the use of (non-)aspirin TAI was analysed using Cox regression models with the use of (non-)aspirin TAI as a time-varying covariate. In total, 9196 patients were identified with colorectal cancer and 1766 patients used TAI after diagnosis. Non-aspirin TAI were mostly clopidogrel and dipyridamole. Aspirin use was associated with a significant increased overall survival and hazard ratio (HR) 0.41 (95% confidence interval [CI] 0.37-0.47), and the use of non-aspirin TAI was not associated with survival of HR 0.92 (95% CI 0.70-1.22). Dual users did not have an improved overall survival when compared with patients using solely aspirin. Aspirin use after diagnosis of colorectal cancer was associated with significantly lower mortality rates and this effect remained significant after adjusting for potential confounders. No additional survival benefit was observed in patients using both aspirin and another TAI. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. A genetic polymorphism in TOX3 is associated with survival of gastric cancer in a Chinese population.

    Directory of Open Access Journals (Sweden)

    Xiaojing Zhang

    Full Text Available PURPOSE: Recently, genetic polymorphism (rs3803662C>T in TOX3 was reported to induce the risk of breast cancer. In this study, we hypothesized that rs3803662 could influence gastric cancer survival outcomes. METHODS: With multiplex SNaPshot method, we genotyped TOX3 rs3803662 in 880 gastric patients with surgical resection. The association between genotype and survival outcomes was performed by the Kaplan-Meier method, Cox regression analysis models and the log-rank test. RESULTS: There was no association in the analyses of rs3803662 and survival of gastric cancer. However, the stratified analysis by histology showed that rs3803662 CT/TT genotype was associated with a significantly better survival for diffuse-type gastric cancer (log-rank p = 0.030, hazard ratio [HR]  = 0.67, 95% confidence interval [CI]  = 0.46-0.96, than the CC genotype. In addition, this favorable effect was especially obvious among gastric cancer patients with tumor size >5 cm, T3 and T4 depth of invasion, lymph node metastasis, no drinking, no distant metastasis, no chemotherapy and gastric cardia cancer. CONCLUSIONS: TOX3 rs3803662 might play an important role in the prognostic outcome and treatment of gastric cancer, especially perhaps further help in explaining the reduced risk of death associated with diffuse-type gastric cancer.

  2. Prediction, Regression and Critical Realism

    DEFF Research Database (Denmark)

    Næss, Petter

    2004-01-01

    This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

  3. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  4. Determinants of LSIL Regression in Women from a Colombian Cohort

    International Nuclear Information System (INIS)

    Molano, Monica; Gonzalez, Mauricio; Gamboa, Oscar; Ortiz, Natasha; Luna, Joaquin; Hernandez, Gustavo; Posso, Hector; Murillo, Raul; Munoz, Nubia

    2010-01-01

    Objective: To analyze the role of Human Papillomavirus (HPV) and other risk factors in the regression of cervical lesions in women from the Bogota Cohort. Methods: 200 HPV positive women with abnormal cytology were included for regression analysis. The time of lesion regression was modeled using methods for interval censored survival time data. Median duration of total follow-up was 9 years. Results: 80 (40%) women were diagnosed with Atypical Squamous Cells of Undetermined Significance (ASCUS) or Atypical Glandular Cells of Undetermined Significance (AGUS) while 120 (60%) were diagnosed with Low Grade Squamous Intra-epithelial Lesions (LSIL). Globally, 40% of the lesions were still present at first year of follow up, while 1.5% was still present at 5 year check-up. The multivariate model showed similar regression rates for lesions in women with ASCUS/AGUS and women with LSIL (HR= 0.82, 95% CI 0.59-1.12). Women infected with HR HPV types and those with mixed infections had lower regression rates for lesions than did women infected with LR types (HR=0.526, 95% CI 0.33-0.84, for HR types and HR=0.378, 95% CI 0.20-0.69, for mixed infections). Furthermore, women over 30 years had a higher lesion regression rate than did women under 30 years (HR1.53, 95% CI 1.03-2.27). The study showed that the median time for lesion regression was 9 months while the median time for HPV clearance was 12 months. Conclusions: In the studied population, the type of infection and the age of the women are critical factors for the regression of cervical lesions.

  5. Intermediate and advanced topics in multilevel logistic regression analysis.

    Science.gov (United States)

    Austin, Peter C; Merlo, Juan

    2017-09-10

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  6. Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso.

    Science.gov (United States)

    Kong, Shengchun; Nan, Bin

    2014-01-01

    We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses.

  7. Long-term Survival of Straumann Dental Implants with TPS Surfaces: A Retrospective Study with a Follow-up of 12 to 23 Years.

    Science.gov (United States)

    Becker, Stephan T; Beck-Broichsitter, Benedicta E; Rossmann, Christian M; Behrens, Eleonore; Jochens, Arne; Wiltfang, Jörg

    2016-06-01

    The aim of this study was to evaluate the long-term dental implant survival rates of Straumann dental implants in a university hospital environment over 12 to 23 years. A total of 388 Straumann dental implants with titanium-sprayed surfaces (TPS) were inserted in 92 patients between 1988 and 1999 in the Department of Oral and Maxillofacial Surgery of the University Hospital Schleswig-Holstein in Kiel, and they were reevaluated with standardized clinical and radiological exams. Kaplan-Meier analyses were performed for individual factors. Cox proportional hazard regression analysis was used to detect the factors influencing long-term implant failure. The long-term implant survival rate was 88.03% after an observation time of 12.2 to 23.5 years. Cox regression revealed statistically significant influences of the International Team for Implantology (ITI) implantation type (p = .00354) and tobacco smoking (p = .01264) on implant failure. A proportion 82.8% of the patients with implant losses had a medical history of periodontitis. Peri-implantitis was diagnosed in 9.7% of the remaining implants in the long-term survey. This study emphasized the long-term rehabilitation capabilities of Straumann dental implants in complex cases. The survival rates after several years constitute important information for patients, as well as for clinicians, in deciding about different concepts of tooth replacement. Patient-related and technical factors - determined before implant placement - could help to predict the risk of implant loss. © 2015 Wiley Periodicals, Inc.

  8. Marital Status and Survival in Patients with Carcinoid Tumors.

    Science.gov (United States)

    Greenleaf, Erin K; Cooper, Amanda B; Hollenbeak, Christopher S

    2016-01-01

    Marital status is a known prognostic factor in overall and disease-specific survival in several types of cancer. The impact of marital status on survival in patients with carcinoid tumors remains unknown. We hypothesized that married patients have higher rates of survival than similar unmarried patients with carcinoid tumors. Using the Surveillance, Epidemiology, and End Results database, we identified 23,126 people diagnosed with a carcinoid tumor between 2000 and 2011 and stratified them according to marital status. Univariate and multivariable analyses were performed to compare the characteristics and outcomes between patient cohorts. Overall and cancer-related survival were analyzed using the Kaplan-Meier method. Multivariable survival analyses were performed using Cox proportional hazards models (hazards ratio [HR]), controlling for demographics and tumor-related and treatment-related variables. Propensity score analysis was performed to determine surgical intervention distributions among married and unmarried (ie, single, separated, divorced, widowed) patients. Marital status was significantly related to both overall and cancer-related survival in patients with carcinoid tumors. Divorced and widowed patients had worse overall survival (HR, 1.33 [95% confidence interval {CI}, 1.08-1.33] and 1.34 [95% CI, 1.22-1.46], respectively) and cancer-related survival (HR, 1.15 [95% CI, 1.00-1.31] and 1.15 [95% CI, 1.03-1.29], respectively) than married patients over five years. Single and separated patients had worse overall survival (HR, 1.20 [95% CI, 1.08-1.33] and 1.62 [95% CI, 1.25-2.11], respectively) than married patients over five years, but not worse cancer-related survival. Unmarried patients were more likely than matched married patients to undergo definitive surgical intervention (62.67% vs 53.11%, respectively, P married patients have a survival advantage after diagnosis of any carcinoid tumor, potentially reflecting better social support and financial means

  9. Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

    Science.gov (United States)

    Wu, Dane W.

    2002-01-01

    The year 2000 US presidential election between Al Gore and George Bush has been the most intriguing and controversial one in American history. The state of Florida was the trigger for the controversy, mainly, due to the use of the misleading "butterfly ballot". Using prediction (or confidence) intervals for least squares regression lines…

  10. Extended cox regression model: The choice of timefunction

    Science.gov (United States)

    Isik, Hatice; Tutkun, Nihal Ata; Karasoy, Durdu

    2017-07-01

    Cox regression model (CRM), which takes into account the effect of censored observations, is one the most applicative and usedmodels in survival analysis to evaluate the effects of covariates. Proportional hazard (PH), requires a constant hazard ratio over time, is the assumptionofCRM. Using extended CRM provides the test of including a time dependent covariate to assess the PH assumption or an alternative model in case of nonproportional hazards. In this study, the different types of real data sets are used to choose the time function and the differences between time functions are analyzed and discussed.

  11. Survival of Patients with Stomach Cancer and its Determinants in Kurdistan.

    Science.gov (United States)

    Moradi, Ghobad; Karimi, Kohsar; Esmailnasab, Nader; Roshani, Daem

    2016-01-01

    Stomach cancer is the fourth most common cancer and the second leading cause of death from cancer in the world. In Iran, this type of cancer has high rates of incidence and mortality. This study aimed to assess the survival rate of patients with stomach cancer and its determinants in Kurdistan, a province with one of the highest incidence rates of stomach cancer in the country. We studied a total of 202 patients with stomach cancer who were admitted to Tohid Hospital in Sanandaj from 2009 to 2013. Using KaplanMeier nonparametric methods the survival rate of patients was calculated in terms of different levels of age at diagnosis, gender, education, residential area, occupation, underweight, and clinical variables including tumor histology, site of tumor, disease stage, and type of treatment. In addition, we compared the survival rates using the logrank test. Finally, Cox proportional hazards regression was applied using Stata 12 and R 3.1.0 software. The significance level was set at 0.05. The mean age at diagnosis was 64.7 ± 12.0 years. The survival rate of patients with stomach cancer was 43.9% and 7% at the first and the fifth year after diagnosis, respectively. The results of logrank test showed significant relationships between survival and age at diagnosis, education, disease stage, type of treatment, and degree of being underweight (P<0.05). Moreover, according to the results of Cox proportional hazards regression model, the variables of education, disease stage, and type of treatment were associated with patient survival (P<0.05). The survival rate of patients with stomach cancer is low and the prognosis is very poor. Given the poor prognosis of the patients, it is critical to find ways for early diagnosis and facilitating timely access to effective treatment methods.

  12. Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study

    OpenAIRE

    Shi, Xiao; Zhang, Ting-ting; Hu, Wei-ping; Ji, Qing-hai

    2017-01-01

    Background The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Results Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk ...

  13. Hope, optimism and survival in a randomised trial of chemotherapy for metastatic colorectal cancer.

    Science.gov (United States)

    Schofield, Penelope E; Stockler, M R; Zannino, D; Tebbutt, N C; Price, T J; Simes, R J; Wong, N; Pavlakis, N; Ransom, D; Moylan, E; Underhill, C; Wyld, D; Burns, I; Ward, R; Wilcken, N; Jefford, M

    2016-01-01

    Psychological responses to cancer are widely believed to affect survival. We investigated associations between hope, optimism, anxiety, depression, health utility and survival in patients starting first-line chemotherapy for metastatic colorectal cancer. Four hundred twenty-nine subjects with metastatic colorectal cancer in a randomised controlled trial of chemotherapy completed baseline questionnaires assessing the following: hopefulness, optimism, anxiety and depression and health utility. Hazard ratios (HRs) and P values were calculated with Cox models for overall survival (OS) and progression-free survival (PFS) in univariable and multivariable analyses. Median follow-up was 31 months. Univariable analyses showed that OS was associated negatively with depression (HR 2.04, P optimism, anxiety or hopefulness. PFS was not associated with hope, optimism, anxiety or depression in any analyses. Depression and health utility, but not optimism, hope or anxiety, were associated with survival after controlling for known prognostic factors in patients with advanced colorectal cancer. Further research is required to understand the nature of the relationship between depression and survival. If a causal mechanism is identified, this may lead to interventional possibilities.

  14. Multidimensional Poverty and Child Survival in India

    Science.gov (United States)

    Mohanty, Sanjay K.

    2011-01-01

    Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

  15. Multidimensional poverty and child survival in India.

    Directory of Open Access Journals (Sweden)

    Sanjay K Mohanty

    Full Text Available Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses.The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed.Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

  16. Multidimensional poverty and child survival in India.

    Science.gov (United States)

    Mohanty, Sanjay K

    2011-01-01

    Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

  17. Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with non-cephalic presentation using logistic regression and classification tree analyses.

    Science.gov (United States)

    Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana

    2017-08-01

    Among women with a fetus with a non-cephalic presentation, external cephalic version (ECV) has been shown to reduce the rate of breech presentation at birth and cesarean birth. Compared with ECV at term, beginning ECV prior to 37 weeks' gestation decreases the number of infants in a non-cephalic presentation at birth. The purpose of this secondary analysis was to investigate factors associated with a successful ECV procedure and to present this in a clinically useful format. Data were collected as part of the Early ECV Pilot and Early ECV2 Trials, which randomized 1776 women with a fetus in breech presentation to either early ECV (34-36 weeks' gestation) or delayed ECV (at or after 37 weeks). The outcome of interest was successful ECV, defined as the fetus being in a cephalic presentation immediately following the procedure, as well as at the time of birth. The importance of several factors in predicting successful ECV was investigated using two statistical methods: logistic regression and classification and regression tree (CART) analyses. Among nulliparas, non-engagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, non-engagement of the presenting part, gestation less than 37 weeks and an easily palpable fetal head were found to be independent predictors of success. These findings were consistent with results of the CART analyses. Regardless of parity, descent of the presenting part was the most discriminating factor in predicting successful ECV and cephalic presentation at birth. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  18. Low skeletal muscle radiation attenuation and visceral adiposity are associated with overall survival and surgical site infections in patients with pancreatic cancer.

    Science.gov (United States)

    van Dijk, David P J; Bakens, Maikel J A M; Coolsen, Mariëlle M E; Rensen, Sander S; van Dam, Ronald M; Bours, Martijn J L; Weijenberg, Matty P; Dejong, Cornelis H C; Olde Damink, Steven W M

    2017-04-01

    Cancer cachexia and skeletal muscle wasting are related to poor survival. In this study, quantitative body composition measurements using computed tomography (CT) were investigated in relation to survival, post-operative complications, and surgical site infections in surgical patients with cancer of the head of the pancreas. A prospective cohort of 199 patients with cancer of the head of the pancreas was analysed by CT imaging at the L3 level to determine (i) muscle radiation attenuation (average Hounsfield units of total L3 skeletal muscle); (ii) visceral adipose tissue area; (iii) subcutaneous adipose tissue area; (iv) intermuscular adipose tissue area; and (v) skeletal muscle area. Sex-specific cut-offs were determined at the lower tertile for muscle radiation attenuation and skeletal muscle area and the higher tertile for adipose tissues. These variables of body composition were related to overall survival, severe post-operative complications (Dindo-Clavien ≥ 3), and surgical site infections (wounds inspected daily by an independent trial nurse) using Cox-regression analysis and multivariable logistic regression analysis, respectively. Low muscle radiation attenuation was associated with shorter survival in comparison with moderate and high muscle radiation attenuation [median survival 10.8 (95% CI: 8.8-12.8) vs. 17.4 (95% CI: 14.7-20.1), and 18.5 (95% CI: 9.2-27.8) months, respectively; P site infection rate, OR: 2.4 (95% CI: 1.1-5.3; P = 0.027). Low muscle radiation attenuation was associated with reduced survival, and high visceral adiposity was associated with an increase in surgical site infections. The strong correlation between muscle radiation attenuation and intermuscular adipose tissue suggests the presence of ectopic fat in muscle, warranting further investigation. CT image analysis could be implemented in pre-operative risk assessment to assist in treatment decision-making. © 2016 The Authors. Journal of Cachexia, Sarcopenia and Muscle

  19. Pretreatment tumor SUV{sub max} predicts disease-specific and overall survival in patients with head and neck soft tissue sarcoma

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Seung Cheol; Roh, Jong-Lyel; Choi, Seung-Ho; Nam, Soon Yuhl; Kim, Sang Yoon [University of Ulsan College of Medicine, Departments of Otolaryngology, Asan Medical Center, Songpa-gu, Seoul (Korea, Republic of); Oh, Jungsu S.; Moon, Hyojeong; Kim, Jae Seung [University of Ulsan College of Medicine, Departments of Nuclear Medicine, Asan Medical Center, Seoul (Korea, Republic of); Cho, Kyung-Ja [University of Ulsan College of Medicine, Departments of Pathology, Asan Medical Center, Seoul (Korea, Republic of)

    2017-01-15

    Head and neck soft tissue sarcoma (HNSTS) is a rare type of tumor with various histological presentations and clinical behaviors. {sup 18}F-FDG PET/CT is being increasingly used for staging, grading, and predicting treatment outcomes in various types of human cancers, although this modality has been rarely studied in the survival prediction of HNSTS. Here we examined the prognostic value of tumor metabolic parameters measured using {sup 18}F-FDG PET/CT in patients with HNSTS. This study included 36 consecutive patients with HNSTS who underwent {sup 18}F-FDG PET/CT scanning prior to treatment at our institution. Tumor gross total volume (GTV) was measured from pretreatment contrast-enhanced CT scans, and maximum standardized uptake value (SUV{sub max}), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured using pretreatment {sup 18}F-FDG PET/CT scans. Univariate and multivariate Cox proportional hazard regression analyses were used to identify associations between imaging parameters and disease-specific survival (DSS) or overall survival (OS). Univariate analyses showed that SUV{sub max}, MTV, and TLG, but not GTV, were significantly associated with DSS and OS (all P < 0.05). After controlling for clinicopathological factors, SUV{sub max}, MTV, and TLG were significantly associated with DSS and OS (all P < 0.05). Patients with a tumor SUV{sub max} value of >7.0 experienced an approximately fivefold increase in mortality in terms of DSS and OS relative to those with a tumor SUV{sub max} <7.0. Quantitative metabolic measurements on pretreatment {sup 18}F-FDG PET/CT can yield values that are significantly predictive of survival after treatment for HNSTS. (orig.)

  20. Mental vulnerability and survival after cancer

    DEFF Research Database (Denmark)

    Nakaya, Naoki; Bidstrup, Pernille E; Eplov, Lene F

    2009-01-01

    BACKGROUND: It has been hypothesized that personality traits affect survival after cancer, but studies have produced inconsistent results. This study examined the association between mental vulnerability and survival after cancer in Denmark in a prospective cohort study. METHODS: Between 1976...... and 2001, 12733 residents of Copenhagen completed a questionnaire eliciting information on a 12-item mental vulnerability scale, as well as various personal data. Follow-up in the Danish Cancer Registry until 2003 identified 884 incident cases of primary cancer, and follow-up for death from the date...... of cancer diagnosis until 2003 identified 382 deaths. Mental vulnerability scores were divided into 4 approximately equal-sized groups. Cox proportional hazards regression models were used to estimate the hazard ratio (HR) of all-cause mortality. RESULTS: Multivariate HR for all-cause mortality for persons...

  1. Impact of Symptomatic Metastatic Spinal Cord Compression on Survival of Patients with Non-Small-Cell Lung Cancer.

    Science.gov (United States)

    da Silva, Gustavo Telles; Bergmann, Anke; Thuler, Luiz Claudio Santos

    2017-12-01

    Non-small-cell lung cancer (NSCLC) is one of the most common primary tumor sites among patients with metastatic spinal cord compression (MSCC). This disorder is related to neurologic dysfunction and can reduce the quality of life, but the association between MSCC and death is unclear. The aim of this study was to analyze the impact of the occurrence of symptomatic MSCC on overall survival of patients with NSCLC. A cohort study was carried out involving 1112 patients with NSCLC who were enrolled between 2006 and 2014 in a single cancer center. Clinical and sociodemographic data were extracted from the physical and electronic records. Survival analysis of patients with NSCLC was conducted using the Kaplan-Meier method. A log-rank test was used to assess differences between survival curves. Cox proportional hazards regression analyses were carried out to quantify the relationship between the independent variable (MSCC) and the outcome (overall survival). During the study period, the incidence of MSCC was 4.1%. Patients who presented with MSCC were 1.43 times more likely to die than were those with no history of MSCC (hazard ratio, 1.43; 95% confidence interval [CI], 1.03-2.00; P = 0.031). The median survival time was 8.04 months (95% CI, 6.13-9.96) for those who presented MSCC and 11.95 months (95% CI, 10.80-13.11) for those who did not presented MSCC during the course of disease (P = 0.002). MSCC is an important and independent predictor of NSCLC worse survival. This effect was not influenced by sociodemographic and clinical factors. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. The Impact of Comorbid Depression on Educational Inequality in Survival after Acute Coronary Syndrome in a Cohort of 83 062 Patients and a Matched Reference Population.

    Directory of Open Access Journals (Sweden)

    Merete Osler

    Full Text Available Patients with low socioeconomic position have higher rates of mortality after diagnosis of acute coronary syndrome (ACS, but little is known about the mechanisms behind this social inequality. The aim of the present study was to examine whether any educational inequality in survival after ACS was influenced by comorbid conditions including depression.From 2001 to 2009 all first-time ACS patients were identified in the Danish National Patient Registry. This cohort of 83 062 ACS patients and a matched reference population were followed for incident depression and mortality until December 2012 by linkage to person, patients and prescription registries. Educational status was defined at study entry and the impact of potential confounders and mediators (age, gender, cohabitation status, somatic comorbidity and depression on the relation between education and mortality were identified by drawing a directed acyclic graph and analysed using multiple Cox regression analyses.During follow-up, 29 583(35.6% of ACS patients and 19 105(22.9% of the reference population died. Cox regression analyses showed an increased mortality in the lowest educated compared to those with high education in both ACS patients and the reference population. Adjustment for previous and incident depression or other covariables only attenuated the relations slightly. This pattern of associations was seen for mortality after 30 days, 1 year and during total follow-up.In this study the relative excess mortality rate in lower educated ACS patients was comparable with the excess risk associated with low education in the background population. This educational inequality in survival remained after adjustment for somatic comorbidity and depression.

  3. Survival analysis of postoperative nausea and vomiting in patients receiving patient-controlled epidural analgesia

    Directory of Open Access Journals (Sweden)

    Shang-Yi Lee

    2014-11-01

    Conclusion: Survival analysis using Cox regression showed that the average consumption of opioids played an important role in postoperative nausea and vomiting, a result not found by logistic regression. Therefore, the incidence of postoperative nausea and vomiting in patients cannot be reliably determined on the basis of a single visit at one point in time.

  4. The association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000

    Directory of Open Access Journals (Sweden)

    Young Harriet

    2007-01-01

    Full Text Available Abstract Background Many studies have found socioeconomic differentials in cancer survival. Previous studies have generally demonstrated poorer cancer survival with decreasing socioeconomic status but mostly used only ecological measures of status and analytical methods estimating simple survival. This study investigate socio-economic differentials in cancer survival using four indicators of socioeconomic status; three individual and one ecological. It uses a relative survival method which gives a measure of excess mortality due to cancer. Methods This study uses prospective record linkage data from The Office for National Statistics Longitudinal Study for England and Wales. The participants are Longitudinal Study members, recorded at census in 1971 and 1981 and with a primary malignant cancer diagnosed at age 45 or above, between 1981 and 1997, with follow-up until end 2000. The outcome measure is relative survival/excess mortality, compared with age and sex adjusted survival of the general population. Relative survival and Poisson regression analyses are presented, giving models of relative excess mortality, adjusted for covariates. Results Different socioeconomic indicators detect survival differentials of varying magnitude and definition. For all cancers combined, the four indicators show similar effects. For individual cancers there are differences between indicators. Where there is an association, all indicators show poorer survival with lower socioeconomic status. Conclusion Cancer survival differs markedly by socio-economic status. The commonly used ecological measure, the Carstairs Index, is adequate at demonstrating socioeconomic differentials in survival for combined cancers and some individual cancers. A combination of car access and housing tenure is more sensitive than the ecological Carstairs measure at detecting socioeconomic effects on survival – confirming Carstairs effects where they occur but additionally identifying

  5. Comparative Analysis and Predictors of 10-year Tumor Necrosis Factor Inhibitors Drug Survival in Patients with Spondyloarthritis: First-year Response Predicts Longterm Drug Persistence.

    Science.gov (United States)

    Flouri, Irini D; Markatseli, Theodora E; Boki, Kyriaki A; Papadopoulos, Ioannis; Skopouli, Fotini N; Voulgari, Paraskevi V; Settas, Loukas; Zisopoulos, Dimitrios; Iliopoulos, Alexios; Geborek, Pierre; Drosos, Alexandros A; Boumpas, Dimitrios T; Sidiropoulos, Prodromos

    2018-04-01

    To evaluate the 10-year drug survival of the first tumor necrosis factor inhibitor (TNFi) administered to patients with spondyloarthritis (SpA) overall and comparatively between SpA subsets, and to identify predictors of drug retention. Patients with SpA in the Hellenic Registry of Biologic Therapies, a prospective multicenter observational cohort, starting their first TNFi between 2004-2014 were analyzed. Kaplan-Meier curves and Cox regression models were used. Overall, 404 out of 1077 patients (37.5%) discontinued treatment (followup: 4288 patient-yrs). Ten-year drug survival was 49%. In the unadjusted analyses, higher TNFi survival was observed in patients with ankylosing spondylitis (AS) compared to undifferentiated SpA and psoriatic arthritis [PsA; significant beyond the first 2.5 (p = 0.003) years and 7 years (p < 0.001), respectively], and in patients treated for isolated axial versus peripheral arthritis (p = 0.001). In all multivariable analyses, male sex was a predictor for longer TNFi survival. Use of methotrexate (MTX) was a predictor in PsA and in patients with peripheral arthritis. Absence of peripheral arthritis and use of a monoclonal antibody (as opposed to non-antibody TNFi) independently predicted longer TNFi survival in axial disease because of lower rates of inefficacy. Achievement of major responses during the first year in either axial or peripheral arthritis was the strongest predictor of longer therapy retention (HR 0.33, 95% CI 0.26-0.41 for Ankylosing Spondylitis Disease Activity Score inactive disease, and HR 0.35, 95% CI 0.24-0.50 for 28-joint Disease Activity Score remission). The longterm retention of the first TNFi administered to patients with SpA is high, especially for males with axial disease. The strongest predictor of longterm TNFi survival is a major response within the first year of treatment.

  6. Geodesic least squares regression for scaling studies in magnetic confinement fusion

    International Nuclear Information System (INIS)

    Verdoolaege, Geert

    2015-01-01

    In regression analyses for deriving scaling laws that occur in various scientific disciplines, usually standard regression methods have been applied, of which ordinary least squares (OLS) is the most popular. However, concerns have been raised with respect to several assumptions underlying OLS in its application to scaling laws. We here discuss a new regression method that is robust in the presence of significant uncertainty on both the data and the regression model. The method, which we call geodesic least squares regression (GLS), is based on minimization of the Rao geodesic distance on a probabilistic manifold. We demonstrate the superiority of the method using synthetic data and we present an application to the scaling law for the power threshold for the transition to the high confinement regime in magnetic confinement fusion devices

  7. Impact of socioeconomic status on survival for patients with anal cancer.

    Science.gov (United States)

    Lin, Daniel; Gold, Heather T; Schreiber, David; Leichman, Lawrence P; Sherman, Scott E; Becker, Daniel J

    2018-04-15

    Although outcomes for patients with squamous cell carcinoma of the anus (SCCA) have improved, the gains in benefit may not be shared uniformly among patients of disparate socioeconomic status. In the current study, the authors investigated whether area-based median household income (MHI) is predictive of survival among patients with SCCA. Patients diagnosed with SCCA from 2004 through 2013 in the Surveillance, Epidemiology, and End Results registry were included. Socioeconomic status was defined by census-tract MHI level and divided into quintiles. Multivariable Cox proportional hazards models and logistic regression were used to study predictors of survival and radiotherapy receipt. A total of 9550 cases of SCCA were included. The median age of the patients was 58 years, 63% were female, 85% were white, and 38% were married. In multivariable analyses, patients living in areas with lower MHI were found to have worse overall survival and cancer-specific survival (CSS) compared with those in the highest income areas. Mortality hazard ratios for lowest to highest income were 1.32 (95% confidence interval [95% CI], 1.18-1.49), 1.31 (95% CI, 1.16-1.48), 1.19 (95% CI, 1.06-1.34), and 1.16 (95% CI, 1.03-1.30). The hazard ratios for CSS similarly ranged from 1.34 to 1.22 for lowest to highest income. Older age, black race, male sex, unmarried marital status, an earlier year of diagnosis, higher tumor grade, and later American Joint Committee on Cancer stage of disease also were associated with worse CSS. Income was not found to be associated with the odds of initiating radiotherapy in multivariable analysis (odds ratio of 0.87 for lowest to highest income level; 95% CI, 0.63-1.20). MHI appears to independently predict CSS and overall survival in patients with SCCA. Black race was found to remain a predictor of SCCA survival despite controlling for income. Further study is needed to understand the mechanisms by which socioeconomic inequalities affect cancer care and

  8. Resection of oligometastatic lung cancer to the pancreas may yield a survival benefit in select patients--a systematic review.

    Science.gov (United States)

    DeLuzio, Matthew R; Moores, Craig; Dhamija, Ankit; Wang, Zuoheng; Cha, Charles; Boffa, Daniel J; Detterbeck, Frank C; Kim, Anthony W

    2015-01-01

    To conduct a systematic review of the existing literature regarding surgical therapy for oligometastatic lung cancer to the pancreas. Data was collected on patients with singular pancreatic metastases from lung cancer from papers published between January 1970 and June 2014. This was performed following the Preferred Reporting Items for Systematic reviews and Meta-analysis (PRISMA) guidelines. Kaplan-Meier and Cox Regression analyses were then used to determine and compare survival. There were 27 papers that fulfilled the search criteria, from which data on 32 patients was collected. Non-small cell lung cancer (NSCLC) was the most prevalent type of primary lung malignancy, and metachronous presentations of metastases were most common. Lesions were most frequently located in the pancreatic head and consequently the most common curative intent metastasectomy was pancreaticoduodenectomy. There was a statistically significant survival benefit for patients whose metastasis were discovered incidentally by surveillance CT as opposed to those whose metastasis were discovered during a work up for new somatic complaints (p = 0.024). The overall median survival for patients undergoing curative intent resection was 29 months, with 2-year and 5-year survivals of 65% and 21% respectively. Palliative surgery or medical only management was associated with a median survival of 8 months and 2-year and 5-year survivals of 25% and 8% respectively. Curative intent resection of isolated pancreatic metastasis from lung cancer may be beneficial in a select group of patients. Copyright © 2015 IAP and EPC. Published by Elsevier B.V. All rights reserved.

  9. Validation of Progression‐Free Survival as a Surrogate Endpoint for Overall Survival in Malignant Mesothelioma: Analysis of Cancer and Leukemia Group B and North Central Cancer Treatment Group (Alliance) Trials

    Science.gov (United States)

    Wang, Xiaoyi; Hodgson, Lydia; George, Stephen L.; Sargent, Daniel J.; Foster, Nate R.; Ganti, Apar Kishor; Stinchcombe, Thomas E.; Crawford, Jeffrey; Kratzke, Robert; Adjei, Alex A.; Kindler, Hedy L.; Vokes, Everett E.; Pang, Herbert

    2017-01-01

    Abstract Purpose. The aim of this study was to investigate whether progression‐free survival (PFS) can be considered a surrogate endpoint for overall survival (OS) in malignant mesothelioma. Materials and Methods. Individual data were collected from 15 Cancer and Leukemia Group B (615 patients) and 2 North Central Cancer Treatment Group (101 patients) phase II trials. The effects of 5 risk factors for OS and PFS, including age, histology, performance status (PS), white blood cell count, and European Organisation for Research and Treatment of Cancer (EORTC) risk score, were used in the analysis. Individual‐level surrogacy was assessed by Kendall's tau through a Clayton bivariate Copula survival (CBCS) model. Summary‐level surrogacy was evaluated via the association between logarithms of the hazard ratio (log HR)—log HROS and log HRPFS—measured in R2 from a weighted least‐square (WLS) regression model and the CBCS model. Results. The median PFS for all patients was 3.0 months (95% confidence interval [CI], 2.8–3.5 months) and the median OS was 7.2 months (95% CI, 6.5–8.0 months). Moderate correlations between PFS and OS were observed across all risk factors at the individual level, with Kendall's tau ranging from 0.46 to 0.47. The summary‐level surrogacy varied among risk factors. The Copula R2 ranged from 0.51 for PS to 0.78 for histology. The WLS R2 ranged from 0.26 for EORTC and PS to 0.67 for age. Conclusions. The analyses demonstrated low to moderate individual‐level surrogacy between PFS and OS. At the summary level, the surrogacy between PFS and OS varied significantly across different risk factors. With a short postprogression survival and a moderate correlation between PFS and OS, there is no evidence that PFS is a valid surrogate endpoint for OS in malignant mesothelioma. Implications for Practice. For better disease management and for more efficient clinical trial designs, it is important to know if progression‐free survival (PFS) is

  10. Influence of nutrient levels in Tamarix on Diorhabda sublineata (Coleoptera: Chrysomelidae) survival and fitness with implications for biological control.

    Science.gov (United States)

    Guenther, D A; Gardner, K T; Thompson, D C

    2011-02-01

    Establishment of the saltcedar leaf beetle (Diorhabda spp.) has been unpredictable when caged or released in the field for saltcedar (Tamarix spp.) biocontrol. It has been observed that one caged tree might be voraciously fed upon by beetles while an adjacent tree in the cage is left untouched. We hypothesized that differences in the nutrient content of individual trees may explain this behavior. We evaluated survival, development rate, and egg production of beetles fed in the laboratory on saltcedar foliage from trees that had been grown under a range of fertilizer treatments. Tissue samples from the experimental trees and from the field were analyzed for percent nitrogen, phosphorus, and potassium. There was essentially no survival of beetle larvae fed foliage from saltcedar trees at nitrogen levels below 2.0%. At levels above 2.0% N, beetle larvae had corresponding increased survival rates and shorter development times. Multiple regression analyses indicated that nitrogen and phosphorus are important for larval survival and faster development rates. Higher levels of potassium were important for increased egg cluster production. The plant tissue analysis showed that the percentage of nitrogen in the experimental trees reflected the range of trees in the field and also that there is high variability within trees in the field. Our research indicates that if beetles are released on trees with poor nutrient quality, the larvae will not survive. © 2011 Entomological Society of America

  11. EGFR immunoexpression, RAS immunoexpression and their effects on survival in lung adenocarcinoma cases.

    Science.gov (United States)

    Gundogdu, Ahmet Gokhan; Onder, Sevgen; Firat, Pinar; Dogan, Riza

    2014-06-01

    The impacts of epidermal growth factor receptor (EGFR) immunoexpression and RAS immunoexpression on the survival and prognosis of lung adenocarcinoma patients are debated in the literature. Twenty-six patients, who underwent pulmonary resections between 2002 and 2007 in our clinic, and whose pathologic examinations yielded adenocarcinoma, were included in the study. EGFR and RAS expression levels were examined by immunohistochemical methods. The results were compared with the survival, stage of the disease, nodal involvement, lymphovascular invasion, and pleural invasion. Nonparametric bivariate analyses were used for statistical analyses. A significant link between EGFR immunoexpression and survival has been identified while RAS immunoexpression and survival have been proven to be irrelevant. Neither EGFR, nor RAS has displayed a significant link with the stage of the disease, nodal involvement, lymphovascular invasion, or pleural invasion. Positive EGFR immunoexpression affects survival negatively, while RAS immunoexpression has no effect on survival in lung adenocarcinoma patients.

  12. Easy methods for extracting individual regression slopes: Comparing SPSS, R, and Excel

    Directory of Open Access Journals (Sweden)

    Roland Pfister

    2013-10-01

    Full Text Available Three different methods for extracting coefficientsof linear regression analyses are presented. The focus is on automatic and easy-to-use approaches for common statistical packages: SPSS, R, and MS Excel / LibreOffice Calc. Hands-on examples are included for each analysis, followed by a brief description of how a subsequent regression coefficient analysis is performed.

  13. The analysis of nonstationary time series using regression, correlation and cointegration

    DEFF Research Database (Denmark)

    Johansen, Søren

    2012-01-01

    There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we...... analyse some monthly data from US on interest rates as an illustration of the methods...

  14. Survival Analysis of Patients with End Stage Renal Disease

    Science.gov (United States)

    Urrutia, J. D.; Gayo, W. S.; Bautista, L. A.; Baccay, E. B.

    2015-06-01

    This paper provides a survival analysis of End Stage Renal Disease (ESRD) under Kaplan-Meier Estimates and Weibull Distribution. The data were obtained from the records of V. L. MakabaliMemorial Hospital with respect to time t (patient's age), covariates such as developed secondary disease (Pulmonary Congestion and Cardiovascular Disease), gender, and the event of interest: the death of ESRD patients. Survival and hazard rates were estimated using NCSS for Weibull Distribution and SPSS for Kaplan-Meier Estimates. These lead to the same conclusion that hazard rate increases and survival rate decreases of ESRD patient diagnosed with Pulmonary Congestion, Cardiovascular Disease and both diseases with respect to time. It also shows that female patients have a greater risk of death compared to males. The probability risk was given the equation R = 1 — e-H(t) where e-H(t) is the survival function, H(t) the cumulative hazard function which was created using Cox-Regression.

  15. Brachytherapy Improves Survival in Stage III Endometrial Cancer With Cervical Involvement

    Energy Technology Data Exchange (ETDEWEB)

    Bingham, Brian [Department of Radiation Oncology, Vanderbilt University, Nashville, Tennessee (United States); Orton, Andrew; Boothe, Dustin [Department of Radiation Oncology, University of Utah, Salt Lake City, Utah (United States); Stoddard, Greg [Division of Epidemiology, University of Utah, Salt Lake City, Utah (United States); Huang, Y. Jessica; Gaffney, David K. [Department of Radiation Oncology, University of Utah, Salt Lake City, Utah (United States); Poppe, Matthew M., E-mail: Matthew.poppe@hci.utah.edu [Department of Radiation Oncology, University of Utah, Salt Lake City, Utah (United States)

    2017-04-01

    Purpose: To evaluate the survival benefit of adding vaginal brachytherapy (BT) to pelvic external beam radiation therapy (EBRT) in women with stage III endometrial cancer. Methods and Materials: The National Cancer Data Base was used to identify patients with stage III endometrial cancer from 2004 to 2013. Only women who received adjuvant EBRT were analyzed. Women were grouped according to receipt of BT. Logistic regression modeling was used to identify predictors of receiving BT. Log–rank statistics were used to compare survival outcomes. Cox proportional hazards modeling was used to evaluate the effect of BT on survival. A propensity score–matched analysis was also conducted among women with cervical involvement. Results: We evaluated 12,988 patients with stage III endometrial carcinoma, 39% of whom received EBRT plus BT. Women who received BT were more likely to have endocervical or cervical stromal involvement (odds ratios 2.03 and 1.77; P<.01, respectively). For patients receiving EBRT alone, the 5-year survival was 66% versus 69% with the addition of BT at 5 years (P<.01). Brachytherapy remained significantly predictive of decreased risk of death (hazard ratio 0.86; P<.01) on multivariate Cox regression. The addition of BT to EBRT did not affect survival among women without cervical involvement (P=.84). For women with endocervical or cervical stromal invasion, the addition of BT significantly improved survival (log–rank P<.01). Receipt of EBRT plus BT was associated with improved survival in women with positive and negative surgical margins, and receiving chemotherapy did not alter the benefit of BT. Propensity score–matched analysis results confirmed the benefit of BT among women with cervical involvement (hazard ratio 0.80; P=.01). Conclusions: In this population of women with stage III endometrial cancer the addition of BT to EBRT was associated with an improvement in survival for women with endocervical or cervical stromal invasion.

  16. Brachytherapy Improves Survival in Stage III Endometrial Cancer With Cervical Involvement

    International Nuclear Information System (INIS)

    Bingham, Brian; Orton, Andrew; Boothe, Dustin; Stoddard, Greg; Huang, Y. Jessica; Gaffney, David K.; Poppe, Matthew M.

    2017-01-01

    Purpose: To evaluate the survival benefit of adding vaginal brachytherapy (BT) to pelvic external beam radiation therapy (EBRT) in women with stage III endometrial cancer. Methods and Materials: The National Cancer Data Base was used to identify patients with stage III endometrial cancer from 2004 to 2013. Only women who received adjuvant EBRT were analyzed. Women were grouped according to receipt of BT. Logistic regression modeling was used to identify predictors of receiving BT. Log–rank statistics were used to compare survival outcomes. Cox proportional hazards modeling was used to evaluate the effect of BT on survival. A propensity score–matched analysis was also conducted among women with cervical involvement. Results: We evaluated 12,988 patients with stage III endometrial carcinoma, 39% of whom received EBRT plus BT. Women who received BT were more likely to have endocervical or cervical stromal involvement (odds ratios 2.03 and 1.77; P<.01, respectively). For patients receiving EBRT alone, the 5-year survival was 66% versus 69% with the addition of BT at 5 years (P<.01). Brachytherapy remained significantly predictive of decreased risk of death (hazard ratio 0.86; P<.01) on multivariate Cox regression. The addition of BT to EBRT did not affect survival among women without cervical involvement (P=.84). For women with endocervical or cervical stromal invasion, the addition of BT significantly improved survival (log–rank P<.01). Receipt of EBRT plus BT was associated with improved survival in women with positive and negative surgical margins, and receiving chemotherapy did not alter the benefit of BT. Propensity score–matched analysis results confirmed the benefit of BT among women with cervical involvement (hazard ratio 0.80; P=.01). Conclusions: In this population of women with stage III endometrial cancer the addition of BT to EBRT was associated with an improvement in survival for women with endocervical or cervical stromal invasion.

  17. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  18. Do stage of disease, comorbidity or access to treatment explain socioeconomic differences in survival after ovarian cancer?

    DEFF Research Database (Denmark)

    Ibfelt, Else Helene; Dalton, Susanne Oksbjerg; Høgdall, Claus

    2015-01-01

    educated women. After adjustment for comorbid conditions, cancer stage, tumour histology, operation status and lifestyle factors, socioeconomic differences in survival persisted. CONCLUSIONS: Socioeconomic disparities in survival after ovarian cancer were to some extent, but not fully explained...... we retrieved information on prognostic factors, treatment information and lifestyle factors. Age, vital status, comorbidity, education, income and cohabitation status were ascertained from nationwide administrative registers. Associations were analyzed with logistic regression and Cox regression...... models. RESULTS: Educational level was weakly associated with cancer stage. Short education, lower income and living without a partner were related to poorer survival after ovarian cancer. Among women with early cancer stage, HR (95% CI) for death was 1.75 (1.20-2.54) in shorter compared to longer...

  19. Adoptive cell transfer after chemotherapy enhances survival in patients with resectable HNSCC.

    Science.gov (United States)

    Jiang, Pan; Zhang, Yan; J Archibald, Steve; Wang, Hua

    2015-09-01

    The aims of this study were to evaluate the therapeutic efficacy and to determine the immune factors for treatment success in patients with head and neck squamous cell carcinoma (HNSCC) treated with chemotherapy followed by adoptive cell transfer (ACT). A total of 43 HNSCC patients who received radical resection and chemotherapy were analysed in this study. Twenty-one of the patients were repeatedly treated with ACT after chemotherapy (ACT group), and the other twenty-two patients without ACT treatment were included as part of the control group. To investigate the immunological differences underlying these observations, we expanded and profiled improving cytokine-induced killer cells (iCIK) from peripheral blood mononuclear cells (PBMCs) with the timed addition of RetroNectin, OKT3 mAb, IFN γ and IL-2. The median of progression-free survival (PFS) and overall survival (OS) in the ACT group were significantly higher as compared to the control group (56 vs. 40; 58 vs. 45 months). In iCIK culture, there was a significant reduction in CD3+CD4+ T-cell proliferation and cytokines (IL-2, TNF) production from patients who received chemotherapy compared to patients without chemotherapy. Intra-arterial infusion of iCIK, in coordination with chemotherapy, considerably rescued iCIK culture from the suppression of systemic immunity induced by chemotherapy and induced tumour regression. Altogether, these findings suggest that ACT is an effective neo-adjuvant therapy for rescuing systemic immune suppression and improving survival time in patients with HNSCC. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Percutaneous radiofrequency ablation for early hepatocellular carcinoma: Risk factors for survival

    Science.gov (United States)

    Kikuchi, Luciana; Menezes, Marcos; Chagas, Aline L; Tani, Claudia M; Alencar, Regiane SSM; Diniz, Marcio A; Alves, Venâncio AF; D’Albuquerque, Luiz Augusto Carneiro; Carrilho, Flair José

    2014-01-01

    AIM: To evaluate outcomes of radiofrequency ablation (RFA) therapy for early hepatocellular carcinoma (HCC) and identify survival- and recurrence-related factors. METHODS: Consecutive patients diagnosed with early HCC by computed tomography (CT) or magnetic resonance imaging (MRI) (single nodule of ≤ 5 cm, or multi- (up to 3) nodules of ≤ 3 cm each) and who underwent RFA treatment with curative intent between January 2010 and August 2011 at the Instituto do Câncer do Estado de São Paulo, Brazil were enrolled in the study. RFA of the liver tumors (with 1.0 cm ablative margin) was carried out under CT-fluoro scan and ultrasonic image guidance of the percutaneous ablation probes. Procedure-related complications were recorded. At 1-mo post-RFA and 3-mo intervals thereafter, CT and MRI were performed to assess outcomes of complete response (absence of enhancing tissue at the tumor site) or incomplete response (enhancing tissue remaining at the tumor site). Overall survival and disease-free survival rates were estimated by the Kaplan-Meier method and compared by the log rank test or simple Cox regression. The effect of risk factors on survival was assessed by the Cox proportional hazard model. RESULTS: A total of 38 RFA sessions were performed during the study period on 34 patients (age in years: mean, 63 and range, 49-84). The mean follow-up time was 22 mo (range, 1-33). The study population showed predominance of male sex (76%), less severe liver disease (Child-Pugh A, n = 26; Child-Pugh B, n = 8), and single tumor (65%). The maximum tumor diameters ranged from 10 to 50 mm (median, 26 mm). The initial (immediately post-procedure) rate of RFA-induced complete tumor necrosis was 90%. The probability of achieving complete response was significantly greater in patients with a single nodule (vs patients with multi-nodules, P = 0.04). Two patients experienced major complications, including acute pulmonary edema (resolved with intervention) and intestinal perforation

  1. Marginal regression analysis of recurrent events with coarsened censoring times.

    Science.gov (United States)

    Hu, X Joan; Rosychuk, Rhonda J

    2016-12-01

    Motivated by an ongoing pediatric mental health care (PMHC) study, this article presents weakly structured methods for analyzing doubly censored recurrent event data where only coarsened information on censoring is available. The study extracted administrative records of emergency department visits from provincial health administrative databases. The available information of each individual subject is limited to a subject-specific time window determined up to concealed data. To evaluate time-dependent effect of exposures, we adapt the local linear estimation with right censored survival times under the Cox regression model with time-varying coefficients (cf. Cai and Sun, Scandinavian Journal of Statistics 2003, 30, 93-111). We establish the pointwise consistency and asymptotic normality of the regression parameter estimator, and examine its performance by simulation. The PMHC study illustrates the proposed approach throughout the article. © 2016, The International Biometric Society.

  2. Tutorial on Using Regression Models with Count Outcomes Using R

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2016-02-01

    Full Text Available Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares either with or without transforming the count variables. In either case, using typical regression for count data can produce parameter estimates that are biased, thus diminishing any inferences made from such data. As count-variable regression models are seldom taught in training programs, we present a tutorial to help educational researchers use such methods in their own research. We demonstrate analyzing and interpreting count data using Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. The count regression methods are introduced through an example using the number of times students skipped class. The data for this example are freely available and the R syntax used run the example analyses are included in the Appendix.

  3. Use of probabilistic weights to enhance linear regression myoelectric control.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2015-12-01

    Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  4. Advanced statistics: linear regression, part I: simple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  5. Marital Status and Survival in Patients with Carcinoid Tumors

    Directory of Open Access Journals (Sweden)

    Erin K. Greenleaf

    2016-01-01

    Full Text Available Background Marital status is a known prognostic factor in overall and disease-specific survival in several types of cancer. The impact of marital status on survival in patients with carcinoid tumors remains unknown. We hypothesized that married patients have higher rates of survival than similar unmarried patients with carcinoid tumors. Methods Using the Surveillance, Epidemiology, and End Results database, we identified 23,126 people diagnosed with a carcinoid tumor between 2000 and 2011 and stratified them according to marital status. Univariate and multivariable analyses were performed to compare the characteristics and outcomes between patient cohorts. Overall and cancer-related survival were analyzed using the Kaplan–Meier method. Multivariable survival analyses were performed using Cox proportional hazards models (hazards ratio [HR], controlling for demographics and tumor-related and treatment-related variables. Propensity score analysis was performed to determine surgical intervention distributions among married and unmarried (ie, single, separated, divorced, widowed patients. Results Marital status was significantly related to both overall and cancer-related survival in patients with carcinoid tumors. Divorced and widowed patients had worse overall survival (HR, 1.33 [95% confidence interval {CI}, 1.08–1.33] and 1.34 [95% CI, 1.22–1.46], respectively and cancer-related survival (HR, 1.15 [95% CI, 1.00–1.31] and 1.15 [95% CI, 1.03–1.29], respectively than married patients over five years. Single and separated patients had worse overall survival (HR, 1.20 [95% CI, 1.08–1.33] and 1.62 [95% CI, 1.25–2.11], respectively than married patients over five years, but not worse cancer-related survival. Unmarried patients were more likely than matched married patients to undergo definitive surgical intervention (62.67% vs 53.11%, respectively, P < 0.0001. Conclusions Even after controlling for other prognostic factors, married patients

  6. Post-transplant survival in idiopathic pulmonary fibrosis patients concurrently listed for single and double lung transplantation.

    Science.gov (United States)

    Chauhan, Dhaval; Karanam, Ashwin B; Merlo, Aurelie; Tom Bozzay, P A; Zucker, Mark J; Seethamraju, Harish; Shariati, Nazly; Russo, Mark J

    2016-05-01

    Lung transplantation is a widely accepted treatment for patients with end-stage lung disease related to idiopathic pulmonary fibrosis (IPF). However, there are conflicting data on whether double lung transplant (DLT) or single lung transplant (SLT) is the superior therapy in these patients. The purpose of this study was to determine whether actuarial post-transplant graft survival among IPF patients concurrently listed for DLT and SLT is greater for recipients undergoing the former or the latter. The United Network for Organ Sharing provided de-identified patient-level data. Analysis included lung transplant candidates with IPF listed between January 1, 2001 and December 31, 2009 (n = 3,411). The study population included 1,001 (29.3%) lung transplant recipients concurrently listed for DLT and SLT, all ≥18 years of age. The primary outcome measure was actuarial post-transplant graft survival, expressed in years. Among the study population, 433 (43.26%) recipients underwent SLT and 568 (56.74%) recipients underwent DLT. The analysis included 2,722.5 years at risk, with median graft survival of 5.31 years. On univariate (p = 0.317) and multivariate (p = 0.415) regression analyses, there was no difference in graft survival between DLT and SLT. Among IPF recipients concurrently listed for DLT and SLT, there is no statistical difference in actuarial graft survival between recipients undergoing DLT vs SLT. This analysis suggests that increased use of SLT for IPF patients may increase the availability of organs to other candidates, and thus increase the net benefit of these organs, without measurably compromising outcomes. Copyright © 2016 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

  7. Clinicopathological characteristics and survival outcomes of invasive lobular carcinoma in different races

    Science.gov (United States)

    Yang, Li-Yuan; Yang, Li-Peng; Zhu, Biao

    2017-01-01

    To investigate the clinicopathological characteristics and to determine whether there is a differential effect of race and examine survival outcomes according to race, 18,295 breast invasive lobular carcinoma (ILC) patients were identified in the Surveillance, Epidemiology, and End Result (SEER) database, which includes White patients (n=15,936), Black patients (n=1,451) and patients of other races (including American Indians/Alaskan Natives and Asian/Pacific Islanders) (n=908). The Black ILC patients presented a higher rate of advanced histological grades and American Joint Committee on Cancer (AJCC) stages, a higher rate of lymph node (LN) involvement and a lower rate of progesterone receptors (PR)-positivity than the White patients and other races. The five-year overall survival (OS) and five-year breast cancer specific survival (BCSS) were worst in the Black patients among these patients (85.5%, 76.0% and 87.7%, P<0.01; 91.1%, 84.4% and 91.6%, P<0.01). Multivariate regression analyses were performed to determine the risk hazards ratios (HR) of death for patients of the White, Black and other races. Among these patients, the Black patients had the worst survival outcomes in five-year OS and BCSS outcomes (HR=1.35, 95% confidence interval (CI) :1.20-1.51, P<0.01; HR=1.39, 95%CI:1.21-1.61, P<0.01, respectively). After a 1:1:1 matching of the three groups, the Black patients still presented worse survival outcomes in BCSS compared to White patients (HR=1.88, 95%CI: 1.14-3.10, P=0.013), however, there was no difference in OS (HR=1.35, 95%CI: 0.93-1.96, P=0.111). Difference in outcomes may partially explained by difference in histological grades, AJCC stage, LN and PR status among the three groups. In conclusion, this study revealed that the Black patients had worse five-year OS and BCSS than White and other race patients. PMID:29088785

  8. Perioperative blood transfusion: does it influence survival and cancer progression in metastatic spine tumor surgery?

    Science.gov (United States)

    Zaw, Aye Sandar; Kantharajanna, Shashidhar B; Maharajan, Karthikeyan; Tan, Barry; Vellayappan, Balamurugan; Kumar, Naresh

    2017-02-01

    Despite advances in surgical techniques for spinal metastases, there is often substantial blood loss, resulting in patients requiring blood transfusion during the perioperative period. Allogeneic blood transfusion (ABT) has been the main replenishment method for lost blood. However, the impact of ABT on cancer-related outcomes has been controversial in various studies. We aimed to evaluate the influence of perioperative ABT on disease progression and survival in patients undergoing metastatic spinal tumor surgery (MSTS). We conducted a retrospective study that included 247 patients who underwent MSTS at a single tertiary institution between 2005 and 2014. The impact of using perioperative ABT (either exposure to or quantities of transfusion) on disease progression and survival was assessed using Cox regression analyses while adjusting for potential confounding variables. Of 247 patients, 133 (54%) received ABT. The overall median number of blood units transfused was 2 (range, 0-10 units). Neither blood transfusion exposure nor quantities of transfusion were associated with overall survival (hazard ratio [HR], 1.15 [p = 0.35] and 1.10 [p = 0.11], respectively) and progression-free survival (HR, 0.87 [p = 0.18] and 0.98 [p = 0.11], respectively). The factors that influenced overall survival were primary tumor type and preoperative Eastern Cooperative Oncology Group performance status, whereas primary tumor type was the only factor that had an impact on progression-free survival. This is the first study providing evidence that disease progression and survival in patients who undergo MSTS are less likely to be influenced by perioperative ABT. The worst oncologic outcomes are more likely to be caused by the clinical circumstances necessitating blood transfusion, but not transfusion itself. However, because ABT can have a propensity toward developing postoperative infections, including surgical site infection, the use of patient blood management

  9. Complete hazard ranking to analyze right-censored data: An ALS survival study.

    Science.gov (United States)

    Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan; Goutman, Stephen A; Mukherjee, Bhramar; Dinov, Ivo D; Guan, Yuanfang

    2017-12-01

    Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

  10. The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration

    Directory of Open Access Journals (Sweden)

    Søren Johansen

    2012-06-01

    Full Text Available There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we analyse some monthly data from US on interest rates as an illustration of the methods.

  11. Cancer survival classification using integrated data sets and intermediate information.

    Science.gov (United States)

    Kim, Shinuk; Park, Taesung; Kon, Mark

    2014-09-01

    Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS

  12. Tools to support interpreting multiple regression in the face of multicollinearity.

    Science.gov (United States)

    Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

    2012-01-01

    While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

  13. Testing and Modeling Fuel Regression Rate in a Miniature Hybrid Burner

    Directory of Open Access Journals (Sweden)

    Luciano Fanton

    2012-01-01

    Full Text Available Ballistic characterization of an extended group of innovative HTPB-based solid fuel formulations for hybrid rocket propulsion was performed in a lab-scale burner. An optical time-resolved technique was used to assess the quasisteady regression history of single perforation, cylindrical samples. The effects of metalized additives and radiant heat transfer on the regression rate of such formulations were assessed. Under the investigated operating conditions and based on phenomenological models from the literature, analyses of the collected experimental data show an appreciable influence of the radiant heat flux from burnt gases and soot for both unloaded and loaded fuel formulations. Pure HTPB regression rate data are satisfactorily reproduced, while the impressive initial regression rates of metalized formulations require further assessment.

  14. One year Survival Rate of Ketac Molar versus Vitro Molar for Occlusoproximal ART Restorations: a RCT

    Directory of Open Access Journals (Sweden)

    PACHECO Anna Luisa de Brito

    2017-11-01

    Full Text Available Abstract Good survival rates for single-surface Atraumatic Restorative Treatment (ART restorations have been reported, while multi-surface ART restorations have not shown similar results. The aim of this study was to evaluate the survival rate of occluso-proximal ART restorations using two different filling materials: Ketac Molar EasyMix (3M ESPE and Vitro Molar (DFL. A total of 117 primary molars with occluso-proximal caries lesions were selected in 4 to 8 years old children in Barueri city, Brazil. Only one tooth was selected per child. The subjetcs were randomly allocated in two groups according to the filling material. All treatments were performed following the ART premises and all restorations were evaluated after 2, 6 and 12 months. Restoration survival was evaluated using Kaplan-Meier survival analysis and Log-rank test, while Cox regression analysis was used for testing association with clinical factors (α = 5%. There was no difference in survival rate between the materials tested, (HR = 1.60, CI = 0.98–2.62, p = 0.058. The overall survival rate of restorations was 42.74% and the survival rate per group was Ketac Molar = 50,8% and Vitro Molar G2 = 34.5%. Cox regression test showed no association between the analyzed clinical variables and the success of the restorations. After 12 months evaluation, no difference in the survival rate of ART occluso-proximal restorations was found between tested materials.

  15. Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

    DEFF Research Database (Denmark)

    Scott, Neil W; Fayers, Peter M; Aaronson, Neil K

    2010-01-01

    Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise ...... when testing for DIF in HRQoL instruments. We focus on logistic regression methods, which are often used because of their efficiency, simplicity and ease of application....

  16. A common variant within the HNF1B gene is associated with overall survival of multiple myeloma patients

    DEFF Research Database (Denmark)

    Ríos-Tamayo, Rafael; Lupiañez, Carmen Belén; Campa, Daniele

    2016-01-01

    Diabetogenic single nucleotide polymorphisms (SNPs) have recently been associated with multiple myeloma (MM) risk but their impact on overall survival (OS) of MM patients has not been analysed yet. In order to investigate the impact of 58 GWAS-identified variants for type 2 diabetes (T2D) on OS...... of patients with MM, we analysed genotyping data of 936 MM patients collected by the International Multiple Myeloma rESEarch (IMMENSE) consortium and an independent set of 700 MM patients recruited by the University Clinic of Heidelberg. A meta-analysis of the cox regression results of the two sets showed...... that rs7501939 located in the HNF1B gene negatively impacted OS (HRRec= 1.44, 95% CI = 1.18-1.76, P = 0.0001). The meta-analysis also showed a noteworthy gender-specific association of the SLC30A8rs13266634 SNP with OS. The presence of each additional copy of the minor allele at rs13266634 was associated...

  17. Survival analysis in hematologic malignancies: recommendations for clinicians

    Science.gov (United States)

    Delgado, Julio; Pereira, Arturo; Villamor, Neus; López-Guillermo, Armando; Rozman, Ciril

    2014-01-01

    The widespread availability of statistical packages has undoubtedly helped hematologists worldwide in the analysis of their data, but has also led to the inappropriate use of statistical methods. In this article, we review some basic concepts of survival analysis and also make recommendations about how and when to perform each particular test using SPSS, Stata and R. In particular, we describe a simple way of defining cut-off points for continuous variables and the appropriate and inappropriate uses of the Kaplan-Meier method and Cox proportional hazard regression models. We also provide practical advice on how to check the proportional hazards assumption and briefly review the role of relative survival and multiple imputation. PMID:25176982

  18. Updating prognosis in primary biliary cirrhosis using a time-dependent Cox regression model. PBC1 and PBC2 trial groups

    DEFF Research Database (Denmark)

    Christensen, E; Altman, D G; Neuberger, J

    1993-01-01

    BACKGROUND: The precision of current prognostic models in primary biliary cirrhosis (PBC) is rather low, partly because they are based on data from just one time during the course of the disease. The aim of this study was to design a new, more precise prognostic model by incorporating follow......-up data in the development of the model. METHODS: We have performed Cox regression analyses with time-dependent variables in 237 PBC patients followed up regularly for up to 11 years. The validity of the obtained models was tested by comparing predicted and observed survival in 147 independent PBC...... patients followed for up to 6 years. RESULTS: In the obtained model the following time-dependent variables independently indicated a poor prognosis: high bilirubin, low albumin, ascites, gastrointestinal bleeding, and old age. When including histological variables, cirrhosis, central cholestasis, and low...

  19. Using a Regression Discontinuity Design to Estimate the Impact of Placement Decisions in Developmental Math

    Science.gov (United States)

    Melguizo, Tatiana; Bos, Johannes M.; Ngo, Federick; Mills, Nicholas; Prather, George

    2016-01-01

    This study evaluates the effectiveness of math placement policies for entering community college students on these students' academic success in math. We estimate the impact of placement decisions by using a discrete-time survival model within a regression discontinuity framework. The primary conclusion that emerges is that initial placement in a…

  20. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

    Science.gov (United States)

    Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

    2009-02-01

    Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

  1. The effect of parathyroidectomy on patient survival in secondary hyperparathyroidism.

    Science.gov (United States)

    Ivarsson, Kerstin M; Akaberi, Shahriar; Isaksson, Elin; Reihnér, Eva; Rylance, Rebecca; Prütz, Karl-Göran; Clyne, Naomi; Almquist, Martin

    2015-12-01

    Secondary hyperparathyroidism is a common condition in patients with end-stage renal disease and is associated with osteoporosis and cardiovascular disease. Despite improved medical treatment, parathyroidectomy (PTX) is still necessary for many patients on renal replacement therapy. The aim of this study was to evaluate the effect of PTX on patient survival. A nested index-referent study was performed within the Swedish Renal Registry (SRR). Patients on maintenance dialysis and transplantation at the time of PTX were analysed separately. The PTX patients in each of these strata were matched for age, sex and underlying renal diseases with up to five referent patients who had not undergone PTX. To calculate survival time and hazard ratios, indexes and referents were assigned the calendar date (d) of the PTX of the index patient. The risk of death after PTX was calculated using crude and adjusted Cox proportional hazards regressions. There were 20 056 patients in the SRR between 1991 and 2009. Of these, 579 (423 on dialysis and 156 with a renal transplant at d) incident patients with PTX were matched with 1234/892 non-PTX patients. The adjusted relative risk of death was a hazard ratio (HR) of 0.80 [95% confidence interval (CI) 0.65-0.99] for dialysis patients at d who had undergone PTX compared with matched patients who had not. Corresponding results for the patients with a renal allograft at d were an HR of 1.10 (95% CI 0.71-1.70). PTX was associated with improved survival in patients on maintenance dialysis but not in patients with renal allograft. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  2. Baseline Tumor Size Is an Independent Prognostic Factor for Overall Survival in Patients With Melanoma Treated With Pembrolizumab.

    Science.gov (United States)

    Joseph, Richard W; Elassaiss-Schaap, Jeroen; Kefford, Richard F; Hwu, Wen-Jen; Wolchok, Jedd D; Joshua, Anthony Michael; Ribas, Antoni; Hodi, F Stephen; Hamid, Omid; Robert, Caroline; Daud, Adil I; Dronca, Roxana S; Hersey, Peter; Weber, Jeffrey S; Patnaik, Amita; de Alwis, Dinesh P; Perrone, Andrea M; Zhang, Jin; Kang, Soonmo Peter; Ebbinghaus, Scot W; Anderson, Keaven M; Gangadhar, Tara

    2018-04-23

    To assess the association of baseline tumor size (BTS) with other baseline clinical factors and outcomes in pembrolizumab-treated patients with advanced melanoma in KEYNOTE-001 (NCT01295827). BTS was quantified by adding the sum of the longest dimensions of all measurable baseline target lesions. BTS as a dichotomous and continuous variable was evaluated with other baseline factors using logistic regression for objective response rate (ORR) and Cox regression for overall survival (OS). Nominal P values with no multiplicity adjustment describe the strength of observed associations. Per central review by RECIST v1.1, 583 of 655 patients had baseline measurable disease and were included in this post hoc analysis. Median BTS was 10.2 cm (range, 1-89.5). Larger median BTS was associated with Eastern Cooperative Oncology Group performance status 1, elevated lactate dehydrogenase (LDH), stage M1c disease, and liver metastases (with or without any other sites) (all P ≤ 0.001). In univariate analyses, BTS below the median was associated with higher ORR (44% vs 23%; P BTS below the median remained an independent prognostic marker of OS (P BTS below the median and PD-L1-positive tumors were independently associated with higher ORR and longer OS. BTS is associated with many other baseline clinical factors but is also independently prognostic of survival in pembrolizumab-treated patients with advanced melanoma. Copyright ©2018, American Association for Cancer Research.

  3. Application of principal component regression and partial least squares regression in ultraviolet spectrum water quality detection

    Science.gov (United States)

    Li, Jiangtong; Luo, Yongdao; Dai, Honglin

    2018-01-01

    Water is the source of life and the essential foundation of all life. With the development of industrialization, the phenomenon of water pollution is becoming more and more frequent, which directly affects the survival and development of human. Water quality detection is one of the necessary measures to protect water resources. Ultraviolet (UV) spectral analysis is an important research method in the field of water quality detection, which partial least squares regression (PLSR) analysis method is becoming predominant technology, however, in some special cases, PLSR's analysis produce considerable errors. In order to solve this problem, the traditional principal component regression (PCR) analysis method was improved by using the principle of PLSR in this paper. The experimental results show that for some special experimental data set, improved PCR analysis method performance is better than PLSR. The PCR and PLSR is the focus of this paper. Firstly, the principal component analysis (PCA) is performed by MATLAB to reduce the dimensionality of the spectral data; on the basis of a large number of experiments, the optimized principal component is extracted by using the principle of PLSR, which carries most of the original data information. Secondly, the linear regression analysis of the principal component is carried out with statistic package for social science (SPSS), which the coefficients and relations of principal components can be obtained. Finally, calculating a same water spectral data set by PLSR and improved PCR, analyzing and comparing two results, improved PCR and PLSR is similar for most data, but improved PCR is better than PLSR for data near the detection limit. Both PLSR and improved PCR can be used in Ultraviolet spectral analysis of water, but for data near the detection limit, improved PCR's result better than PLSR.

  4. Conditional Melanoma Cancer Survival in the United States

    Directory of Open Access Journals (Sweden)

    Ray M. Merrill

    2016-02-01

    Full Text Available Beyond relative survival, which indicates the likelihood that patients will not die from causes associated with their cancer, conditional relative survival probabilities provide further useful prognostic information to cancer patients, tailored to the time already survived from diagnosis. This study presents conditional relative survival for melanoma patients in the United States, diagnosed during 2000–2008 and followed through 2012. Analyses are based on 62,803 male and 50,261 female cases in population-based cancer registries in the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute. Five-year relative survival estimates are presented for melanoma patients who have already survived one, two, three, four, or five years after the initial diagnosis. Five- and ten-year relative survival decreases with age, stage at diagnosis, and is lower among males, Blacks, and Hispanics. Five-year conditional relative survival improves with each year already survived. The potential for improvement in five-year conditional relative survival is greatest for older age, males, Blacks, Hispanics, and in later staged cases. For local disease, five-year conditional relative survival was significantly lower in ages greater than 65 years and in Blacks. It was significantly higher in females, non-Hispanics, and married individuals. Age had a greater inverse relationship with five-year survival in later staged disease. A similar result occurred for females and married individuals. In contrast, non-Hispanics had better five-year survival if diagnosed with local or regional disease, but not distant disease.

  5. An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy

    DEFF Research Database (Denmark)

    Merlo, Juan; Wagner, Philippe; Ghith, Nermin

    2016-01-01

    BACKGROUND AND AIM: Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that disting...

  6. Metagenes Associated with Survival in Non-Small Cell Lung Cancer

    Science.gov (United States)

    Urgard, Egon; Vooder, Tõnu; Võsa, Urmo; Välk, Kristjan; Liu, Mingming; Luo, Cheng; Hoti, Fabian; Roosipuu, Retlav; Annilo, Tarmo; Laine, Jukka; Frenz, Christopher M.; Zhang, Liqing; Metspalu, Andres

    2011-01-01

    NSCLC (non-small cell lung cancer) comprises about 80% of all lung cancer cases worldwide. Surgery is most effective treatment for patients with early-stage disease. However, 30%–55% of these patients develop recurrence within 5 years. Therefore, markers that can be used to accurately classify early-stage NSCLC patients into different prognostic groups may be helpful in selecting patients who should receive specific therapies. A previously published dataset was used to evaluate gene expression profiles of different NSCLC subtypes. A moderated two-sample t-test was used to identify differentially expressed genes between all tumor samples and cancer-free control tissue, between SCC samples and AC/BC samples and between stage I tumor samples and all other tumor samples. Gene expression microarray measurements were validated using qRT-PCR. Bayesian regression analysis and Kaplan-Meier survival analysis were performed to determine metagenes associated with survival. We identified 599 genes which were down-regulated and 402 genes which were up-regulated in NSCLC compared to the normal lung tissue and 112 genes which were up-regulated and 101 genes which were down-regulated in AC/BC compared to the SCC. Further, for stage Ib patients the metagenes potentially associated with survival were identified. Genes that expressed differently between normal lung tissue and cancer showed enrichment in gene ontology terms which were associated with mitosis and proliferation. Bayesian regression and Kaplan-Meier analysis showed that gene-expression patterns and metagene profiles can be applied to predict the probability of different survival outcomes in NSCLC patients. PMID:21695068

  7. Low temperature and dust favour in vitro survival of Mycoplasma hyopneumoniae: time to revisit indirect transmission in pig housing.

    Science.gov (United States)

    Browne, C; Loeffler, A; Holt, H R; Chang, Y M; Lloyd, D H; Nevel, A

    2017-01-01

    Porcine enzootic pneumonia (EP) caused by Mycoplasma hyopneumoniae adversely affects pig welfare and is associated with major economic losses in the pig industry worldwide. Transmission is predominantly by direct contact, but the role of indirect transmission remains poorly understood. This study examined survival of six M. hyopneumoniae isolates dried onto five different surfaces encountered in pig units and exposed to temperatures of 4, 25 and 37°C for up to 12 days. Survival of the organisms was determined by recovering the organism from the surface material and culturing in Friis broth. Data were analysed by logistic regression to identify factors influencing survival of M. hyopneumoniae. Maximum survival was 8 days for all isolates on at least one surface (except stainless steel) at 4°C and was limited to 2 days at 25 and 37°C. Overall, dust and polypropylene copolymer supported M. hyopneumoniae survival the longest when compared with other surface materials. In conclusion, we have demonstrated that M. hyopneumoniae can survive outside the host for at least 8 days. Understanding the transmission of Mycoplasma hyopneumoniae and optimizing biosecurity practices are keys to reducing the use of antimicrobial agents to control this pathogen. Direct transmission of the pathogen between pigs is the main route of spread and its lack of cell wall may compromise its resilience outside the host. The results from our study show that M. hyopneumoniae can survive for up to several days on dry surfaces and therefore may have the potential to infect pigs by indirect transmission. Factors influencing the survival of M. hyopneumoniae outside the host are further elucidated. © 2016 The Society for Applied Microbiology.

  8. Non-small cell lung cancer in young adults: presentation and survival in the English National Lung Cancer Audit.

    Science.gov (United States)

    Rich, A L; Khakwani, A; Free, C M; Tata, L J; Stanley, R A; Peake, M D; Hubbard, R B; Baldwin, D R

    2015-11-01

    Non-small cell lung cancer (NSCLC) in young adults is a rare but devastating illness with significant socioeconomic implications, and studies of this patient subgroup are limited. This study employed the National Lung Cancer Audit to compare the clinical features and survival of young adults with NSCLC with the older age groups. A retrospective cohort review using a validated national audit dataset. Data were analysed for the period between 1 January 2004 and 31 December 2011. Young adults were defined as between 18 and 39 years, and all others were divided into decade age groups, up to the 80 years and above group. We performed logistic and Cox regression analyses to assess clinical outcomes. Of a total of 1 46 422 patients, 651 (0.5%) were young adults, of whom a higher proportion had adenocarcinoma (48%) than in any other age group. Stage distribution of NSCLC was similar across the age groups and 71% of young patients had stage IIIb/IV. Performance status (PS) was 0-1 for 85%. Young adults were more likely to have surgery and chemotherapy compared with the older age groups and had better overall and post-operative survival. The proportion with adenocarcinoma, better PS and that receiving surgery or chemotherapy diminished progressively with advancing decade age groups. In our cohort of young adults with NSCLC, the majority had good PS despite the same late-stage disease as older patients. They were more likely to have treatment and survive longer than older patients. © The Author 2015. Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. Assessing the relative importance of local and regional processes on the survival of a threatened salmon population.

    Science.gov (United States)

    Miller, Jessica A; Teel, David J; Peterson, William T; Baptista, Antonio M

    2014-01-01

    Research on regulatory mechanisms in biological populations often focuses on environmental covariates. An integrated approach that combines environmental indices with organismal-level information can provide additional insight on regulatory mechanisms. Survival of spring/summer Snake River Chinook salmon (Oncorhynchus tshawytscha) is consistently low whereas some adjacent populations with similar life histories experience greater survival. It is not known if populations with differential survival respond similarly during early marine residence, a critical period in the life history. Ocean collections, genetic stock identification, and otolith analyses were combined to evaluate the growth-mortality and match-mismatch hypotheses during early marine residence of spring/summer Snake River Chinook salmon. Interannual variation in juvenile attributes, including size at marine entry and marine growth rate, was compared with estimates of survival and physical and biological metrics. Multiple linear regression and multi-model inference were used to evaluate the relative importance of biological and physical metrics in explaining interannual variation in survival. There was relatively weak support for the match-mismatch hypothesis and stronger evidence for the growth-mortality hypothesis. Marine growth and size at capture were strongly, positively related to survival, a finding similar to spring Chinook salmon from the Mid-Upper Columbia River. In hindcast models, basin-scale indices (Pacific Decadal Oscillation (PDO) and the North Pacific Gyre Oscillation (NPGO)) and biological indices (juvenile salmon catch-per-unit-effort (CPUE) and a copepod community index (CCI)) accounted for substantial and similar portions of variation in survival for juvenile emigration years 1998-2008 (R2>0.70). However, in forecast models for emigration years 2009-2011, there was an increasing discrepancy between predictions based on the PDO (50-448% of observed value) compared with those based on

  10. Assessing the relative importance of local and regional processes on the survival of a threatened salmon population.

    Directory of Open Access Journals (Sweden)

    Jessica A Miller

    Full Text Available Research on regulatory mechanisms in biological populations often focuses on environmental covariates. An integrated approach that combines environmental indices with organismal-level information can provide additional insight on regulatory mechanisms. Survival of spring/summer Snake River Chinook salmon (Oncorhynchus tshawytscha is consistently low whereas some adjacent populations with similar life histories experience greater survival. It is not known if populations with differential survival respond similarly during early marine residence, a critical period in the life history. Ocean collections, genetic stock identification, and otolith analyses were combined to evaluate the growth-mortality and match-mismatch hypotheses during early marine residence of spring/summer Snake River Chinook salmon. Interannual variation in juvenile attributes, including size at marine entry and marine growth rate, was compared with estimates of survival and physical and biological metrics. Multiple linear regression and multi-model inference were used to evaluate the relative importance of biological and physical metrics in explaining interannual variation in survival. There was relatively weak support for the match-mismatch hypothesis and stronger evidence for the growth-mortality hypothesis. Marine growth and size at capture were strongly, positively related to survival, a finding similar to spring Chinook salmon from the Mid-Upper Columbia River. In hindcast models, basin-scale indices (Pacific Decadal Oscillation (PDO and the North Pacific Gyre Oscillation (NPGO and biological indices (juvenile salmon catch-per-unit-effort (CPUE and a copepod community index (CCI accounted for substantial and similar portions of variation in survival for juvenile emigration years 1998-2008 (R2>0.70. However, in forecast models for emigration years 2009-2011, there was an increasing discrepancy between predictions based on the PDO (50-448% of observed value compared with

  11. Progression-free survival, post-progression survival, and tumor response as surrogate markers for overall survival in patients with extensive small cell lung cancer

    Directory of Open Access Journals (Sweden)

    Hisao Imai

    2015-01-01

    Full Text Available Objectives: The effects of first-line chemotherapy on overall survival (OS might be confounded by subsequent therapies in patients with small cell lung cancer (SCLC. We examined whether progression-free survival (PFS, post-progression survival (PPS, and tumor response could be valid surrogate endpoints for OS after first-line chemotherapies for patients with extensive SCLC using individual-level data. Methods: Between September 2002 and November 2012, we analyzed 49 cases of patients with extensive SCLC who were treated with cisplatin and irinotecan as first-line chemotherapy. The relationships of PFS, PPS, and tumor response with OS were analyzed at the individual level. Results: Spearman rank correlation analysis and linear regression analysis showed that PPS was strongly correlated with OS (r = 0.97, p < 0.05, R 2 = 0.94, PFS was moderately correlated with OS (r = 0.58, p < 0.05, R 2 = 0.24, and tumor shrinkage was weakly correlated with OS (r = 0.37, p < 0.05, R 2 = 0.13. The best response to second-line treatment, and the number of regimens employed after progression beyond first-line chemotherapy were both significantly associated with PPS ( p ≤ 0.05. Conclusion: PPS is a potential surrogate for OS in patients with extensive SCLC. Our findings also suggest that subsequent treatment after disease progression following first-line chemotherapy may greatly influence OS.

  12. Hepatorenal Syndrome: Outcome of Response to Therapy and Predictors of Survival

    Directory of Open Access Journals (Sweden)

    Jan Heidemann

    2015-01-01

    Full Text Available Aim. Treatment of hepatorenal syndrome (HRS in patients with liver cirrhosis is still challenging and characterized by a very high mortality. This study aimed to delineate treatment patterns and clinical outcomes of patients with HRS intravenously treated with terlipressin. Methods. In this retrospective single-center cohort study, 119 patients (median [IQR]; 56.50 [50.75–63.00] years of age with HRS were included. All patients were treated with terlipressin and human albumin intravenously. Those with response to treatment (n=65 were compared to the patient cohort without improvement (n=54. Patient characteristics and clinical parameters (Child stage, ascites, hepatic encephalopathy, HRS type I/II, and initial MELD score were retrieved. Univariate analysis of factors influencing the success of terlipressin therapy and Cox regression analysis of factors influencing survival was carried out. Results. One-month survival was significantly longer in the group of responders (p=0.048. Cox regression analysis identified age [Hazard ratio, 95% confidence interval (CI; 1.05, 1.01–1.09, resp.], alcohol abuse [HR 3.05, 95% CI 1.11–8.38], duration of treatment [HR 0.92, 95% CI 0.88–0.96], and MELD score [HR 1.08, 95% CI 1.02–1.14] to be independent predictors of survival. Conclusions. Survival of HRS patients after treatment depends on age, etiology of liver disease, and the duration of treatment.

  13. Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

    International Nuclear Information System (INIS)

    Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

    2007-01-01

    Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

  14. Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

    Science.gov (United States)

    Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim

    2012-01-01

    Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…

  15. Survival analysis and classification methods for forest fire size.

    Science.gov (United States)

    Tremblay, Pier-Olivier; Duchesne, Thierry; Cumming, Steven G

    2018-01-01

    Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at "being held" (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at "being held" exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances.

  16. Estimating the exceedance probability of rain rate by logistic regression

    Science.gov (United States)

    Chiu, Long S.; Kedem, Benjamin

    1990-01-01

    Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

  17. Linear regression and the normality assumption.

    Science.gov (United States)

    Schmidt, Amand F; Finan, Chris

    2017-12-16

    Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Complete hazard ranking to analyze right-censored data: An ALS survival study.

    Directory of Open Access Journals (Sweden)

    Zhengnan Huang

    2017-12-01

    Full Text Available Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

  19. Molecular Signature for Lymphatic Invasion Associated with Survival of Epithelial Ovarian Cancer.

    Science.gov (United States)

    Paik, E Sun; Choi, Hyun Jin; Kim, Tae-Joong; Lee, Jeong-Won; Kim, Byoung-Gie; Bae, Duk-Soo; Choi, Chel Hun

    2018-04-01

    We aimed to develop molecular classifier that can predict lymphatic invasion and their clinical significance in epithelial ovarian cancer (EOC) patients. We analyzed gene expression (mRNA, methylated DNA) in data from The Cancer Genome Atlas. To identify molecular signatures for lymphatic invasion, we found differentially expressed genes. The performance of classifier was validated by receiver operating characteristics analysis, logistic regression, linear discriminant analysis (LDA), and support vector machine (SVM). We assessed prognostic role of classifier using random survival forest (RSF) model and pathway deregulation score (PDS). For external validation,we analyzed microarray data from 26 EOC samples of Samsung Medical Center and curatedOvarianData database. We identified 21 mRNAs, and seven methylated DNAs from primary EOC tissues that predicted lymphatic invasion and created prognostic models. The classifier predicted lymphatic invasion well, which was validated by logistic regression, LDA, and SVM algorithm (C-index of 0.90, 0.71, and 0.74 for mRNA and C-index of 0.64, 0.68, and 0.69 for DNA methylation). Using RSF model, incorporating molecular data with clinical variables improved prediction of progression-free survival compared with using only clinical variables (p < 0.001 and p=0.008). Similarly, PDS enabled us to classify patients into high-risk and low-risk group, which resulted in survival difference in mRNA profiles (log-rank p-value=0.011). In external validation, gene signature was well correlated with prediction of lymphatic invasion and patients' survival. Molecular signature model predicting lymphatic invasion was well performed and also associated with survival of EOC patients.

  20. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  1. Survival prediction model for postoperative hepatocellular carcinoma patients.

    Science.gov (United States)

    Ren, Zhihui; He, Shasha; Fan, Xiaotang; He, Fangping; Sang, Wei; Bao, Yongxing; Ren, Weixin; Zhao, Jinming; Ji, Xuewen; Wen, Hao

    2017-09-01

    This study is to establish a predictive index (PI) model of 5-year survival rate for patients with hepatocellular carcinoma (HCC) after radical resection and to evaluate its prediction sensitivity, specificity, and accuracy.Patients underwent HCC surgical resection were enrolled and randomly divided into prediction model group (101 patients) and model evaluation group (100 patients). Cox regression model was used for univariate and multivariate survival analysis. A PI model was established based on multivariate analysis and receiver operating characteristic (ROC) curve was drawn accordingly. The area under ROC (AUROC) and PI cutoff value was identified.Multiple Cox regression analysis of prediction model group showed that neutrophil to lymphocyte ratio, histological grade, microvascular invasion, positive resection margin, number of tumor, and postoperative transcatheter arterial chemoembolization treatment were the independent predictors for the 5-year survival rate for HCC patients. The model was PI = 0.377 × NLR + 0.554 × HG + 0.927 × PRM + 0.778 × MVI + 0.740 × NT - 0.831 × transcatheter arterial chemoembolization (TACE). In the prediction model group, AUROC was 0.832 and the PI cutoff value was 3.38. The sensitivity, specificity, and accuracy were 78.0%, 80%, and 79.2%, respectively. In model evaluation group, AUROC was 0.822, and the PI cutoff value was well corresponded to the prediction model group with sensitivity, specificity, and accuracy of 85.0%, 83.3%, and 84.0%, respectively.The PI model can quantify the mortality risk of hepatitis B related HCC with high sensitivity, specificity, and accuracy.

  2. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  3. Survival rate of breast cancer patients in Malaysia: a population-based study.

    Science.gov (United States)

    Abdullah, Nor Aini; Wan Mahiyuddin, Wan Rozita; Muhammad, Nor Asiah; Ali, Zainudin Mohamad; Ibrahim, Lailanor; Ibrahim Tamim, Nor Saleha; Mustafa, Amal Nasir; Kamaluddin, Muhammad Amir

    2013-01-01

    Breast cancer is the most common cancer among Malaysian women. Other than hospital-based results, there are no documented population-based survival rates of Malaysian women for breast cancers. This population- based retrospective cohort study was therefore conducted. Data were obtained from Health Informatics Centre, Ministry of Health Malaysia, National Cancer Registry and National Registration Department for the period from 1st Jan 2000 to 31st December 2005. Cases were captured by ICD-10 and linked to death certificates to identify the status. Only complete data were analysed. Survival time was calculated from the estimated date of diagnosis to the date of death or date of loss to follow-up. Observed survival rates were estimated by Kaplan- Meier method using SPSS Statistical Software version 17. A total of 10,230 complete data sets were analysed. The mean age at diagnosis was 50.6 years old. The overall 5-year survival rate was 49% with median survival time of 68.1 months. Indian women had a higher survival rate of 54% compared to Chinese women (49%) and Malays (45%). The overall 5-year survival rate of breast cancer patient among Malaysian women was still low for the cohort of 2000 to 2005 as compared to survival rates in developed nations. Therefore, it is necessary to enhance the strategies for early detection and intervention.

  4. The best of both worlds: Phylogenetic eigenvector regression and mapping

    Directory of Open Access Journals (Sweden)

    José Alexandre Felizola Diniz Filho

    2015-09-01

    Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

  5. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  6. Influence of human development and predators on nest survival of tundra birds, Arctic Coastal Plain, Alaska.

    Science.gov (United States)

    Liebezeit, J R; Kendall, S J; Brown, S; Johnson, C B; Martin, P; McDonald, T L; Payer, D C; Rea, C L; Streever, B; Wildman, A M; Zack, S

    2009-09-01

    Nest predation may influence population dynamics of birds on the Arctic Coastal Plain (ACP) of Alaska, USA. Anthropogenic development on the ACP is increasing, which may attract nest predators by providing artificial sources of food, perches, den sites, and nest sites. Enhanced populations or concentrations of human-subsidized predators may reduce nest survival for tundra-nesting birds. In this study, we tested the hypothesis that nest survival decreases in proximity to human infrastructure. We monitored 1257 nests of 13 shorebird species and 619 nests of four passerine species at seven sites on the ACP from 2002 to 2005. Study sites were chosen to represent a range of distances to infrastructure from 100 m to 80 km. We used Cox proportional hazards regression models to evaluate the effects of background (i.e., natural) factors and infrastructure on nest survival. We documented high spatial and temporal variability in nest survival, and site and year were both included in the best background model. We did not detect an effect of human infrastructure on nest survival for shorebirds as a group. In contrast, we found evidence that risk of predation for passerine nests increased within 5 km of infrastructure. This finding provides quantitative evidence of a relationship between infrastructure and nest survival for breeding passerines on the ACP. A posteriori finer-scale analyses (within oil field sites and individual species) suggested that Red and Red-necked Phalaropes combined (Phalaropus fulicarius, P. lobatus) had lower productivity closer to infrastructure and in areas with higher abundance of subsidized predators. However, we did not detect such a relationship between infrastructure and nest survival for Semipalmated and Pectoral Sandpipers (Calidris pusilla, C. melanotos), the two most abundant shorebirds. High variability in environmental conditions, nest survival, and predator numbers between sites and years may have contributed to these inconsistent results

  7. Does the association between leisure activities and survival in old age differ by living arrangement?

    Science.gov (United States)

    Nilsen, Charlotta; Agahi, Neda; Shaw, Benjamin A

    2018-01-01

    Government policies to promote ageing in place have led to a growing frail population living at home in advanced old age, many of whom live alone. Living alone in old age is associated with adverse health outcomes, but we know little about whether it moderates the health impact of other risk and protective factors. Engagement in leisure activities is considered critical to successful ageing. We investigated whether the association between different types of leisure activities and survival in non-institutionalised older adults (aged 76 and above) differs by living arrangement and gender. We used the Swedish Panel Study of Living Conditions of the Oldest Old study from 2011 and the Swedish Cause of Death Register (until 30 June 2014) to conduct Cox regression analyses (n=669). Incident mortality was 30.2% during the follow-up period. Overall level of leisure activity was not significantly associated with survival in either living arrangement, but some specific leisure activities, and associations, were different across gender and living arrangement. More specifically, certain social activities (participation in organisations and having relatives visit) were associated with longer survival, but only in men living alone. In women, most results were statistically non-significant, with the exception of solving crosswords being associated with longer survival in women living with someone. In order to facilitate engagement with life, interventions focusing on leisure activities in the oldest age groups should take gender and living arrangement into consideration when determining the type of activity most needed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  8. Glutathione S-transferase M1 null genotype: lack of association with tumour characteristics and survival in advanced breast cancer

    International Nuclear Information System (INIS)

    Lizard-Nacol, Sarab; Coudert, Bruno; Colosetti, Pascal; Riedinger, Jean-Marc; Fargeot, Pierre; Brunet-Lecomte, Patrick

    1999-01-01

    Glutathione S-transferase (GST)M1, a member of the μ class GST gene family, has been shown to be polymorphic because of a partial gene deletion. This results in a failure to express the GSTM1 gene in 50-60% of individuals. Several studies have demonstrated a possible link with the GSTM1-null genotype and susceptibility to cancer. Furthermore, a GSTM1 isoenzyme has been positively associated with protective effect against mutagenic drugs, such as alkylating agents and anthracyclines. To determine whether GSTM1 polymorphisms are associated with tumour characteristics and survival in advanced breast cancer patients, and whether it may constitute a prognostic factor. We genotyped 92 patients receiving primary chemotherapy, which included cyclophosphamide, doxorubicine and 5-fluorouracil. The relationships between allelism at GSTM1 and clinicopathological parameters including age, menopausal status, tumour size, grade hormone receptors, involved nodes and p53 gene mutations were analysed. Of the patients with GSTM1-positive genotype, tissue samples obtained before and after treatment were available from 28 cases, allowing RNA extraction and GSTM1 expression by reverse transcription polymerase chain reaction. Relationships with clinical response to chemotherapy, and disease-free and overall survival were also evaluated. The data obtained was analysed using logistic regression to estimate the odds ratio and 95% confidence interval. Of 92 patients, 57.6% (n = 53) were classified as heritably GSTM1-deficient, and 42.4% (n = 39) were of the GSTM1-positive genotype. There were no statistically significant relationships between GSTM1-null genotype and the clinicopathological parameters analysed. No relationship was observed between GSTM1 RNA expression and objective clinical response to chemotherapy. Objective clinical response to chemotherapy was related only to clinical tumour size (P = 0.0177) and to the absence of intraductal carcinoma (P = 0.0013). GSTM1-null genotype

  9. Pretreatment oral hygiene habits and survival of head and neck squamous cell carcinoma (HNSCC) patients.

    Science.gov (United States)

    Friemel, Juliane; Foraita, Ronja; Günther, Kathrin; Heibeck, Mathias; Günther, Frauke; Pflueger, Maren; Pohlabeln, Hermann; Behrens, Thomas; Bullerdiek, Jörn; Nimzyk, Rolf; Ahrens, Wolfgang

    2016-03-11

    The survival time of patients with head and neck squamous cell carcinoma (HNSCC) is related to health behavior, such as tobacco smoking and alcohol consumption. Poor oral health (OH), dental care (DC) and the frequent use of mouthwash have been shown to represent independent risk factors for head and neck cancerogenesis, but their impact on the survival of HNSCC patients has not been systematically investigated. Two hundred seventy-six incident HNSCC cases recruited for the ARCAGE study were followed through a period of 6-10 years. Interview-based information on wearing of dentures, gum bleeding, teeth brushing, use of floss and dentist visits were grouped into weighted composite scores, i.e. oral health (OH) and dental care (DH). Use of mouthwash was assessed as frequency per day. Also obtained were other types of health behavior, such as smoking, alcohol drinking and diet, appreciated as both confounding and study variables. Endpoints were progression-free survival, overall survival and tumor-specific survival. Prognostic values were estimated using Kaplan-Meier analysis and Cox proportional hazards regression models. A good dental care score, summarizing annual dental visits, daily teeth cleaning and use of floss was associated with longer overall survival time (p = .001). The results of the Cox regression models similarly suggested a higher risk of tumor progression and shortened overall survival in patients with poor dental care, but the results lost their statistical significance after other types of health behavior had been controlled for. Frequent use of mouthwash (≥ 2 times/day) significantly increased the risk of tumor-specific death (HR = 2.26; CI = 1.19-4.32). Alcohol consumption and tobacco smoking were dose-dependently associated with tumor progression and shorter overall survival. Frequent mouthwash use of ≥ 2 times/day seems to elevate the risk of tumor-specific death in HNSCC patients. Good dental care scores are associated with longer overall

  10. Prediction of radiation levels in residences: A methodological comparison of CART [Classification and Regression Tree Analysis] and conventional regression

    International Nuclear Information System (INIS)

    Janssen, I.; Stebbings, J.H.

    1990-01-01

    In environmental epidemiology, trace and toxic substance concentrations frequently have very highly skewed distributions ranging over one or more orders of magnitude, and prediction by conventional regression is often poor. Classification and Regression Tree Analysis (CART) is an alternative in such contexts. To compare the techniques, two Pennsylvania data sets and three independent variables are used: house radon progeny (RnD) and gamma levels as predicted by construction characteristics in 1330 houses; and ∼200 house radon (Rn) measurements as predicted by topographic parameters. CART may identify structural variables of interest not identified by conventional regression, and vice versa, but in general the regression models are similar. CART has major advantages in dealing with other common characteristics of environmental data sets, such as missing values, continuous variables requiring transformations, and large sets of potential independent variables. CART is most useful in the identification and screening of independent variables, greatly reducing the need for cross-tabulations and nested breakdown analyses. There is no need to discard cases with missing values for the independent variables because surrogate variables are intrinsic to CART. The tree-structured approach is also independent of the scale on which the independent variables are measured, so that transformations are unnecessary. CART identifies important interactions as well as main effects. The major advantages of CART appear to be in exploring data. Once the important variables are identified, conventional regressions seem to lead to results similar but more interpretable by most audiences. 12 refs., 8 figs., 10 tabs

  11. Hospital-based colorectal cancer survival trend of different tumor locations from 1960s to 2000s.

    Directory of Open Access Journals (Sweden)

    Yu-Jing Fang

    Full Text Available BACKGROUND: Our aim is to explore the trend of association between the survival rates of colorectal cancer (CRC and the different clinical characteristics in patients registered from 1960s to 2000s. We hypothesized that the survival rate of CRC increases over time and varies according to anatomic subsites. METHODS: Information from a total of 4558 stage T(1-4N(1-2M0 CRC patients registered from 1960s to 2008 were analyzed. The association of CRC overall survival with age, gender, tumor locations, time, histopathology types, pathology grades, no. of examined lymph nodes, the T stage, and the N stage was analyzed. The assessment of the influence of prognostic factors on patient survival was performed using Cox's proportional hazard regression models. RESULTS: From 1960 to 2008, the studied CRC patients included 2625 (57.6% and 1933 (42.4% males and females, respectively. These included 1896 (41.6% colon cancers, and 2662 (58.4% rectum cancers. The 5-year survival rate was 49%, 58%, 58%, 70%, and 77% for the time duration of 1960s, 1970s, 1980s, 1990s and 2000s, respectively. An increased 5-year survival rate was observed in the colon cancer and rectum cancer patients. Patients older than 60 years of age were more likely to develop colonic cancer (sigmoid than rectum cancer (49.2% vs. 39.9%. The Cox regression model showed that only rectum cancer survival was related to time duration. CONCLUSION: The overall survival and 5-year survival rates showed an increase from the 1960s to 2000s. There is a trend of rightward shift of tumor location in CRC patients.

  12. Logistic Regression Analysis of Operational Errors and Routine Operations Using Sector Characteristics

    National Research Council Canada - National Science Library

    Pfleiderer, Elaine M; Scroggins, Cheryl L; Manning, Carol A

    2009-01-01

    Two separate logistic regression analyses were conducted for low- and high-altitude sectors to determine whether a set of dynamic sector characteristics variables could reliably discriminate between operational error (OE...

  13. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  14. A computer program for multiple decrement life table analyses.

    Science.gov (United States)

    Poole, W K; Cooley, P C

    1977-06-01

    Life table analysis has traditionally been the tool of choice in analyzing distribution of "survival" times when a parametric form for the survival curve could not be reasonably assumed. Chiang, in two papers [1,2] formalized the theory of life table analyses in a Markov chain framework and derived maximum likelihood estimates of the relevant parameters for the analyses. He also discussed how the techniques could be generalized to consider competing risks and follow-up studies. Although various computer programs exist for doing different types of life table analysis [3] to date, there has not been a generally available, well documented computer program to carry out multiple decrement analyses, either by Chiang's or any other method. This paper describes such a program developed by Research Triangle Institute. A user's manual is available at printing costs which supplements the contents of this paper with a discussion of the formula used in the program listing.

  15. Survival of Patients with Oral Cavity Cancer in Germany

    Science.gov (United States)

    Listl, Stefan; Jansen, Lina; Stenzinger, Albrecht; Freier, Kolja; Emrich, Katharina; Holleczek, Bernd; Katalinic, Alexander; Gondos, Adam; Brenner, Hermann

    2013-01-01

    The purpose of the present study was to describe the survival of patients diagnosed with oral cavity cancer in Germany. The analyses relied on data from eleven population-based cancer registries in Germany covering a population of 33 million inhabitants. Patients with a diagnosis of oral cavity cancer (ICD-10: C00-06) between 1997 and 2006 are included. Period analysis for 2002–2006 was applied to estimate five-year age-standardized relative survival, taking into account patients' sex as well as grade and tumor stage. Overall five-year relative survival for oral cavity cancer patients was 54.6%. According to tumor localization, five-year survival was 86.5% for lip cancer, 48.1% for tongue cancer and 51.7% for other regions of the oral cavity. Differences in survival were identified with respect to age, sex, tumor grade and stage. The present study is the first to provide a comprehensive overview on survival of oral cavity cancer patients in Germany. PMID:23349710

  16. Trends of Incidence and Survival of Gastrointestinal Neuroendocrine Tumors in the United States: A Seer Analysis

    Directory of Open Access Journals (Sweden)

    Vassiliki L. Tsikitis, Betsy C. Wertheim, Marlon A. Guerrero

    2012-01-01

    Full Text Available OBJECTIVES: To examine trends in detection and survival of hollow viscus gastrointestinal neuroendocrine tumors (NETs across time and geographic regions of the U.S.METHODS: We used the Surveillance, Epidemiology and End Results (SEER database to investigate 19,669 individuals with newly diagnosed gastrointestinal NETs. Trends in incidence were tested using Poisson regression. Cox proportional hazards regression was used to examine survival.RESULTS: Incidence increased over time for NETs of all gastrointestinal sites (all P < 0.001, except appendix. Rates have risen faster for NETs of the small intestine and rectum than stomach and colon. Rectal NETs were detected at a faster pace among blacks than whites (P < 0.001 and slower in the East than other regions (P < 0.001. We observed that appendiceal and rectal NETs carry the best prognosis and survival of small intestinal and colon NETs has improved for both men and women. Colon NETs showed different temporal trends in survival according to geographic region (Pinteraction = 0.028. Improved prognosis was more consistent across the country for small intestinal NETs.CONCLUSIONS: Incidence of gastrointestinal NETs has increased, accompanied by inconsistently improved survival for different anatomic sites among certain groups defined by race and geographic region.

  17. The Preoperative Controlling Nutritional Status Score Predicts Survival After Curative Surgery in Patients with Pathological Stage I Non-small Cell Lung Cancer.

    Science.gov (United States)

    Shoji, Fumihiro; Haratake, Naoki; Akamine, Takaki; Takamori, Shinkichi; Katsura, Masakazu; Takada, Kazuki; Toyokawa, Gouji; Okamoto, Tatsuro; Maehara, Yoshihiko

    2017-02-01

    The prognostic Controlling Nutritional Status (CONUT) score is used to evaluate immuno-nutritional conditions and is a predictive factor of postoperative survival in patients with digestive tract cancer. We retrospectively analyzed clinicopathological features of patients with pathological stage I non-small cell lung cancer (NSCLC) to identify predictors or prognostic factors of postoperative survival and to investigate the role of preoperative CONUT score in predicting survival. We selected 138 consecutive patients with pathological stage I NSCLC treated from August 2005 to August 2010. We measured their preoperative CONUT score in uni- and multivariate Cox regression analyses of postoperative survival. A high CONUT score was positively associated with preoperative serum carcinoembryonic antigen level (p=0.0100) and postoperative recurrence (p=0.0767). In multivariate analysis, the preoperative CONUT score [relative risk (RR)=6.058; 95% confidence interval (CI)=1.068-113.941; p=0.0407), increasing age (RR=7.858; 95% CI=2.034-36.185; p=0.0029), and pleural invasion (RR=36.615; 95% CI=5.900-362.620; pcancer-specific survival (CS), and overall survival (OS), the group with high CONUT score had a significantly shorter RFS, CS, and OS than did the low-CONUT score group by log-rank test (p=0.0458, p=0.0104 and p=0.0096, respectively). The preoperative CONUT score is both a predictive and prognostic factor in patients with pathological stage I NSCLC. This immuno-nutritional score can indicate patients at high risk of postoperative recurrence and death. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  18. Improved survival in HIV treatment programs in Asia

    Science.gov (United States)

    De La Mata, Nicole L; Kumarasamy, Nagalingeswaran; Khol, Vohith; Ng, Oon Tek; Van Nguyen, Kinh; Merati, Tuti Parwati; Pham, Thuy Thanh; Lee, Man Po; Durier, Nicolas; Law, Matthew

    2016-01-01

    Background Antiretroviral treatment (ART) for HIV-positive patients has expanded rapidly in Asia over the last ten years. Our study aimed to describe the time trends and risk factors for overall survival in patients receiving first-line ART in Asia. Methods We included HIV-positive adult patients who initiated ART between 2003–2013 (n=16 546), from seven sites across six Asia-Pacific countries. Patient follow-up was to May 2014. We compared survival for each country and overall by time period of ART initiation using Kaplan-Meier curves. Factors associated with mortality were assessed using Cox regression, stratified by site. We also summarized first-line ART regimens, CD4 count at ART initiation, and CD4 and HIV viral load testing frequencies. Results There were 880 deaths observed over 54 532 person-years of follow-up, a crude rate of 1.61 (1.51, 1.72) per 100 person-years. Survival significantly improved in more recent years of ART initiation. The survival probabilities at 4 years follow-up for those initiating ART in 2003–05 was 92.1%, 2006–09 was 94.3% and 2010–2013 was 94.5% (pAsia have improved survival in more recent years of ART initiation. This is likely a consequence of improvements in treatment and, patient management and monitoring over time. PMID:26961354

  19. Fissure sealants in caries prevention:a practice-based study using survival analysis

    OpenAIRE

    Leskinen, K. (Kaja)

    2010-01-01

    Abstract The purpose of this study was to analyse the effectiveness and cost of fissure sealant treatment in preventing dental caries in children in a practice-based research network using survival analysis. The survival times of first permanent molars in children were analysed in three countries: in Finland (age cohorts 1970–1972 and 1980–1982), in Sweden (1980–1982) and in Greece (1980–1982), and additionally at two municipal health centres in Finland (age cohorts 1988–1990 in Kemi...

  20. A Monte Carlo simulation study comparing linear regression, beta regression, variable-dispersion beta regression and fractional logit regression at recovering average difference measures in a two sample design.

    Science.gov (United States)

    Meaney, Christopher; Moineddin, Rahim

    2014-01-24

    In biomedical research, response variables are often encountered which have bounded support on the open unit interval--(0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar results were observed if the

  1. Severity of acidosis affects long-term survival in COPD patients with hypoxemia after intensive care unit discharge.

    Science.gov (United States)

    Gungor, Sinem; Kargin, Feyza; Irmak, Ilim; Ciyiltepe, Fulya; Acartürk Tunçay, Eylem; Atagun Guney, Pinar; Aksoy, Emine; Ocakli, Birsen; Adiguzel, Nalan; Karakurt, Zuhal

    2018-01-01

    those with LTOT. Kaplan-Meier cumulative survival analysis showed that the 28-day and 1-, 2-, and 3-year mortality rates were 12.2%, 36.2%, 52.6%, 63.3%, respectively ( p =0.09). The Cox regression analyses showed that older age, PaO 2 /FiO 2 <300 mmHg, and body mass index ≤20 kg/m 2 was associated with mortality of all patients after 3 years. Severely acidotic COPD patients had a poorer short- and long-term prognosis compared with mild-to-moderate acidotic COPD patients if acute and chronic hypoxemia was predominant.

  2. Marital status and survival in patients with rectal cancer: An analysis of the Surveillance, Epidemiology and End Results (SEER) database.

    Science.gov (United States)

    Wang, Xiangyang; Cao, Weilan; Zheng, Chenguo; Hu, Wanle; Liu, Changbao

    2018-06-01

    Marital status has been validated as an independent prognostic factor for survival in several cancer types, but is controversial in rectal cancer (RC). The objective of this study was to investigate the impact of marital status on the survival outcomes of patients with RC. We extracted data of 27,498 eligible patients diagnosed with RC between 2004 and 2009 from the Surveillance, Epidemiology and End Results (SEER) database. Patients were categorized into married, never married, divorced/separated and widowed groups.We used Chi-square tests to compare characteristics of patients with different marital status.Rectal cancer specific survival was compared using the Kaplan-Meier method,and multivariate Cox regression analyses was used to analyze the survival outcome risk factors in different marital status. The widowed group had the highest percentage of elderly patients and women,higher proportion of adenocarcinomas, and more stage I/II in tumor stage (P married group (76.7% VS 85.4%). Compared with the married patients, the never married (HR 1.40), widowed (HR 1.61,) and divorced/separated patients (HR 1.16) had an increased overall 5-year mortality. A further analysis showed that widowed patients had an increased overall 5-year cause-specific survival(CSS) compared with married patients at stage I(HR 1.92),stage II (HR 1.65),stage III (HR 1.73),and stage IV (HR 1.38). Our study showed marriage was associated with better outcomes of RC patients, but unmarried RC patients, especially widowed patients,are at greater risk of cancer specific mortality. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Marital status, treatment, and survival in patients with glioblastoma multiforme: a population based study.

    Science.gov (United States)

    Chang, Susan M; Barker, Fred G

    2005-11-01

    Social factors influence cancer treatment choices, potentially affecting patient survival. In the current study, the authors studied the interrelations between marital status, treatment received, and survival in patients with glioblastoma multiforme (GM), using population-based data. The data source was the Surveillance, Epidemiology, and End Results (SEER) Public Use Database, 1988-2001, 2004 release, all registries. Multivariate logistic, ordinal, and Cox regression analyses adjusted for demographic and clinical variables were used. Of 10,987 patients with GM, 67% were married, 31% were unmarried, and 2% were of unknown marital status. Tumors were slightly larger at the time of diagnosis in unmarried patients (49% of unmarried patients had tumors larger than 45 mm vs. 45% of married patients; P = 0.004, multivariate analysis). Unmarried patients were less likely to undergo surgical resection (vs. biopsy; 75% of unmarried patients vs. 78% of married patients) and were less likely to receive postoperative radiation therapy (RT) (70% of unmarried patients vs. 79% of married patients). On multivariate analysis, the odds ratio (OR) for resection (vs. biopsy) in unmarried patients was 0.88 (95% confidence interval [95% CI], 0.79-0.98; P = 0.02), and the OR for RT in unmarried patients was 0.69 (95% CI, 0.62-0.77; P Unmarried patients more often refused both surgical resection and RT. Unmarried patients who underwent surgical resection and RT were found to have a shorter survival than similarly treated married patients (hazard ratio for unmarried patients, 1.10; P = 0.003). Unmarried patients with GM presented with larger tumors, were less likely to undergo both surgical resection and postoperative RT, and had a shorter survival after diagnosis when compared with married patients, even after adjustment for treatment and other prognostic factors. (c) 2005 American Cancer Society.

  4. Prediction of survival after surgery due to skeletal metastases in the extremities

    DEFF Research Database (Denmark)

    Sørensen, M S; Gerds, T A; Hindsø, K

    2016-01-01

    metastases and American Society of Anaesthesiologist's score were included into a series of logistic regression models. The outcome was the survival status at three, six and 12 months respectively. Results were internally validated based on 1000 cross-validations and reported as time-dependent area under...

  5. Self-rated health supersedes patient satisfaction with service quality as a predictor of survival in prostate cancer.

    Science.gov (United States)

    Gupta, Digant; Patel, Kamal; Lis, Christopher G

    2015-09-04

    We have previously reported that higher patient satisfaction (PS) with service quality is associated with favorable survival outcomes in a variety of cancers. However, we argued that patients with greater satisfaction might be the ones with better self-rated health (SRH), a recognized predictor of cancer survival. We therefore investigated whether SRH can supersede patient satisfaction as a predictor of survival in prostate cancer. Nine hundred seventeen prostate cancer treated at four Cancer Treatment Centers of America(®) hospitals between July 2011 and March 2013. PS was measured on a 7-point scale ranging from "completely dissatisfied" to "completely satisfied". SRH was measured on a 7-point scale ranging from "very poor" to "excellent". Both were dichotomized into two categories: top box response (7) versus all others (1-6). Patient survival was the primary end point. Cox regression was used to evaluate the association between PS and survival controlling for covariates. The response rate for this study was 72%. Majority of patients (n = 517) had stage II disease. Seven hundred eighty-seven (85.8%) patients were "completely satisfied". Three hundred nineteen (34.8%) patients had "excellent" SRH. There was a weak but significant correlation between satisfaction and SRH (Kendall's tau b = 0.18; p < 0.001). On univariate analysis, "completely satisfied" patients had a significantly lower risk of mortality (HR = 0.46; 95% CI: 0.25-0.85; p = 0.01). Similarly, patients with "excellent" SRH had a significantly lower risk of mortality (HR = 0.25; 95% CI: 0.11-0.58; p = 0.001). On multivariate analysis, SRH was found to be a significant predictor of survival (HR = 0.31; 95% CI: 0.12-0.79; p = 0.01) while patient satisfaction was not (HR = 0.76; 95% CI: 0.40-1.5; p = 0.40). SRH supersedes patient satisfaction with service quality as a predictor of survival in prostate cancer. SRH should be used as a control variable in analyses involving patient satisfaction as a

  6. Social determinants of health and 5-year survival of colorectal cancer.

    Science.gov (United States)

    Heidarnia, Mohammad Ali; Monfared, Esmat Davoudi; Akbari, Mohammad Esmail; Yavari, Parvin; Amanpour, Farzaneh; Mohseni, Maryam

    2013-01-01

    Early in the 21st century, cancers are the second cause of death worldwide. Colon cancer is third most common cancer and one of the few amenable to early diagnosis and treatment. Evaluation of factors affecting this cancer is important to increase survival time. Some of these factors affecting all diseases including cancer are social determinants of health. According to the importance of this disease and relation with these factors, this study was conducted to assess the relationship between social determinants of health and colon cancer survival. This was a cross-sectional, descriptive study for patients with colon cancer registered in the Cancer Research Center of Shahid Beheshti University of Medical Science, from April 2005 to November 2006, performed using questionnaires filled by telephone interview with patients (if patients had died, with family members). Data was analyzed with SPSS software (version 19) for descriptive analysis and STATA software for survival analysis including log rank test and three step Cox Proportional Hazard regression. Five hundred fifty nine patients with ages ranging from 23 to 88 years with mean ± standard deviation of 63 ± 11.8 years were included in the study. The five year survival was 68.3%( 387 patients were alive and 172 patients were dead by the end of the study). The Cox proportional hazard regression showed 5-year survival was related to age (HR=0.53, p=0.042 for>50 years versusmanual versus non manual jobs), region of residency (HR=3.49, p=0.018 for west versus south regions), parents in childhood (HR=2.87, p=0.012 for having both parents versus not having), anatomical cancer location (HR=2.16, psurvival of colon cancer and it may be better to consider these factors in addition to developing cancer treatment and to focus on these determinants of health in long-time planning.

  7. Stability of alert survivable forces during reductions

    Energy Technology Data Exchange (ETDEWEB)

    Canavan, G.H.

    1998-01-01

    The stability of current and projected strategic forces are discussed within a framework that contains elements of current US and Russian analyses. For current force levels and high alert, stability levels are high, as are the levels of potential strikes, due to the large forces deployed. As force levels drop towards those of current value target sets, the analysis becomes linear, concern shifts from stability to reconstitution, and survivable forces drop out. Adverse marginal costs generally provide disincentives for the reduction of vulnerable weapons, but the exchange of vulnerable for survivable weapons could reduce cost while increasing stability even for aggressive participants. Exchanges between effective vulnerable and survivable missile forces are studied with an aggregated, probabilistic model, which optimizes each sides` first and determines each sides` second strikes and costs by minimizing first strike costs.

  8. Physical activity and survival in breast cancer

    DEFF Research Database (Denmark)

    Ammitzbøll, Gunn; Søgaard, Karen; Karlsen, Randi V

    2016-01-01

    PURPOSE: Knowledge about lifestyle factors possibly influencing survival after breast cancer (BC) is paramount. We examined associations between two types of postdiagnosis physical activity (PA) and overall survival after BC. PATIENTS AND METHODS: We used prospective data on 959 BC survivors from...... the Diet, Cancer, and Health cohort, all enrolled before diagnosis. Self-reported PA was measured as time per activity, and estimated metabolic equivalent task (MET)-hours per week were summed for each activity. We constructed measures for household, exercise, and total PA. The association between...... from all causes during the study period. In adjusted analyses, exercise PA above eight MET h/week compared to lower levels of activity was significantly associated with improved overall survival (HR, 0.68; confidence interval [CI]: 0.47-0.99). When comparing participation in exercise to non...

  9. [Survival time of HIV/AIDS cases and related factors in Beijing, 1995-2015].

    Science.gov (United States)

    Li, Y; Wang, J; He, S F; Chen, J; Lu, H Y

    2017-11-10

    Objective: To analyze the survival time of HIV/AIDS cases and related factors in Beijing from 1995 to 2015. Methods: A retrospective cohort study was conducted to analyze the data of 12 874 HIV/AIDS cases. The data were collected from Chinese HIV/AIDS Comprehensive Information Management System. Life table method was applied to calculate the survival proportion, and Cox proportion hazard regression model were used to identify the factors related with survival time. Results: Among 12 874 HIV/AIDS cases, 303 (2.4%) died of AIDS related diseases; 9 346 (72.6%) received antiretroviral therapy. The average survival time was 226.5 months (95 %CI : 223.0-230.1), and the survival rates of 1, 5, 10, and 15 years were 98.2%, 96.4%, 93.2%, and 91.9% respectively. Multivariate Cox proportion hazard regression model showed that AIDS phase ( HR =1.439, 95 %CI : 1.041-1.989), heterosexual transmission ( HR =1.646, 95 %CI : 1.184-2.289), being married ( HR =2.186, 95 %CI : 1.510-3.164); older age (≥60 years) at diagnosis ( HR =6.608, 95 %CI : 3.546-12.316); lower CD(4)(+)T cell counts at diagnosis (<350 cells/μl) ( HR =8.711, 95 %CI : 5.757-13.181); receiving no antiretroviral therapy (ART) ( HR =18.223, 95 %CI : 13.317-24.937) were the high risk factors influencing the survival of AIDS patients compared with HIV phase, homosexual transmission, being unmarried, younger age (≤30 years), higher CD(4)(+)T cell count (≥350 cell/μl) and receiving ART. Conclusion: The average survival time of HIV/AIDS cases was 226.5 months after diagnoses. Receiving ART, higher CD(4)(+)T cell counts at the first test, HIV phase, younger age, being unmarried and the homosexual transmission were related to the longer survival time of HIV/AIDS cases. Receiving no ART, the lower CD(4)(+)T cell counts at the first test, AIDS phase, older age, being married and heterosexual transmission indicated higher risk of death due to AIDS.

  10. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  11. Gallbladder cancer: incidence and survival in a high-risk area of Chile.

    Science.gov (United States)

    Bertran, Enriqueta; Heise, Katy; Andia, Marcelo E; Ferreccio, Catterina

    2010-11-15

    We assessed population incidence rates 1998-2002 and 5-year survival rates of 317 primary gallbladder cancer (GBC) entered in the population-based cancer registry in Valdivia. We analyzed GBC incidence (Poisson regression) and GBC survival (Cox regression). Cases were identified by histology (69.4%), clinical work-up (21.8%), or death certificate only (8.8%). Main symptoms were abdominal pain (82.8%), jaundice (53.6%) nausea (42.6%), and weight loss (38.2%); at diagnosis, 64% had Stage TNM IV. In the period, 4% of histopathological studies from presumptively benign cholecystectomies presented GBC. GBC cases were mainly females (76.0%), urban residents (70.3%), Hispanic (83.7%) of low schooling Mapuche 25.0, Hispanic 16.2 (p = 0.09). The highest SIRs were in Mapuche (269.2) and Hispanic women (199.6) with 8 years of schooling. Low schooling, female and urban residence were independent risk factors. By December 31, 2007, 6 (1.9%) cases were living, 280 (88.3%) died from GBC, 32 (10.1%) were lost of follow-up. Kaplan Meier Global 5-year survival was: 10.3%, 85% at stage I and 1.9% at stage IV; median survival: 3.4 months. Independent poor prognostic factors were TNM IV, jaundice and nonincidental diagnoses. Our results suggest that women of Mapuche ancestry with low schooling (>50 years) are at the highest risk of presenting and dying from GBC and should be the target for early detection programs.

  12. Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

    Science.gov (United States)

    Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

    2017-03-05

    The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized

  13. Identification by random forest method of HLA class I amino acid substitutions associated with lower survival at day 100 in unrelated donor hematopoietic cell transplantation.

    Science.gov (United States)

    Marino, S R; Lin, S; Maiers, M; Haagenson, M; Spellman, S; Klein, J P; Binkowski, T A; Lee, S J; van Besien, K

    2012-02-01

    The identification of important amino acid substitutions associated with low survival in hematopoietic cell transplantation (HCT) is hampered by the large number of observed substitutions compared with the small number of patients available for analysis. Random forest analysis is designed to address these limitations. We studied 2107 HCT recipients with good or intermediate risk hematological malignancies to identify HLA class I amino acid substitutions associated with reduced survival at day 100 post transplant. Random forest analysis and traditional univariate and multivariate analyses were used. Random forest analysis identified amino acid substitutions in 33 positions that were associated with reduced 100 day survival, including HLA-A 9, 43, 62, 63, 76, 77, 95, 97, 114, 116, 152, 156, 166 and 167; HLA-B 97, 109, 116 and 156; and HLA-C 6, 9, 11, 14, 21, 66, 77, 80, 95, 97, 99, 116, 156, 163 and 173. In all 13 had been previously reported by other investigators using classical biostatistical approaches. Using the same data set, traditional multivariate logistic regression identified only five amino acid substitutions associated with lower day 100 survival. Random forest analysis is a novel statistical methodology for analysis of HLA mismatching and outcome studies, capable of identifying important amino acid substitutions missed by other methods.

  14. Treatment factors influencing survival in pancreatic carcinoma; Der Einfluss der Therapie auf das Ueberleben von Patienten mit Pankreaskarzinom. Eine Analyse von Einzelfaktoren

    Energy Technology Data Exchange (ETDEWEB)

    Warszawski, N.; Warszawski, A.; Schneider, B.M.; Roettinger, E.M. [Ulm Univ. (Germany). Abt. Radiologie 2 (Strahlentherapie); Link, K.H.; Gansauge, F. [Ulm Univ. (Germany). Abt. fuer Allgemeinchirurgie; Lutz, M.P. [Ulm Univ. (Germany). Abt. Innere Medizin 1

    1999-07-01

    Purpose: To identify the impact of treatment factors on overall survival in patients with pancreatic carcinoma. Patients and methods: We performed a follow-up study on 38 patients with adenocarcinoma of the pancreas treated from 1984 to 1998. 18/38 patients were resected. Irradiated volume included the primary tumor (or tumor bed) and regional lymph nodes. Thirty-seven patients received in addition chemotherapy consisting of mitoxantrone, 5-fluorouracil and cis-platin, either i.v. (14/38) or i.a. (23/38). The influence of treatment related factors on the overall survival was tested. Biologically effective dose was calculated by the linear-quadratic model ({alpha}/{beta}=25 Gy) and by losing 0.85 Gy per day starting accelerated repopulation at day 28. Results: Treatment factors influencing overall survival were resection (p=0.02), overall treatment time (p=0.03) and biologically effective dose (p<0.002). Total dose and kind of chemotherapy had no significant influence. Treatment volume had a negative correlation (r=-0.5, p=0.06) with overall survival, without any correlation between tumor size, tumor stage, and treatment volume. In multivariate analysis only biologically effective dose remained significant (p=0.02). Conclusions: Among with surgery, biologically effective dose strongly influences overall survival in patients treated for pancreatic carcinoma. Treatment volume should be kept as small as possible and all efforts should be made to avoid treatments splits in radiation therapy. (orig.) [Deutsch] Ziel: Behandlungsfaktoren zu identifizieren, die einen Einfluss auf das Ueberleben von Patienten mit Pankreaskarzinom haben. Patienten und Methode: In einer nichtrandomisierten Studie wurden 38 Patienten ausgewertet, die von 1984 bis 1998 wegen eines Adenokarzinoms des Pankreas behandelt worden waren. Bei 18/38 Patienten war eine Resektion vorgenommen worden. Das Bestrahlungsvolumen beinhaltete den Primaertumor bzw. das Tumorbett und die regionaeren Lymphknoten

  15. Lung cancer survival in Norway, 1997-2011: from nihilism to optimism.

    Science.gov (United States)

    Nilssen, Yngvar; Strand, Trond Eirik; Fjellbirkeland, Lars; Bartnes, Kristian; Møller, Bjørn

    2016-01-01

    We examine changes in survival and patient-, tumour- and treatment-related factors among resected and nonresected lung cancer patients, and identify subgroups with the largest and smallest survival improvements.National population-based data from the Cancer Registry of Norway, Statistics Norway and the Norwegian Patient Register were linked for lung cancer patients diagnosed during 1997-2011. The 1- and 5-year relative survival were estimated, and Cox proportional hazard regression, adjusted for selected patient characteristics, was used to assess prognostic factors for survival in lung cancer patients overall and stratified by resection status.We identified 34 157 patients with lung cancer. The proportion of histological diagnoses accompanied by molecular genetics testing increased from 0% to 26%, while those accompanied by immunohistochemistry increased from 8% to 26%. The 1-year relative survival among nonresected and resected patients increased from 21.7% to 34.2% and 75.4% to 91.5%, respectively. The improved survival remained significant after adjustment for age, sex, stage and histology. The largest improvements in survival occurred among resected and adenocarcinoma patients, while patients ≥80 years experienced the smallest increase.Lung cancer survival has increased considerably in Norway. The explanation is probably multifactorial, including improved attitude towards diagnostic work-up and treatment, and more accurate diagnostic testing that allows for improved selection for resection and improved treatment options. Copyright ©ERS 2016.

  16. A method for fitting regression splines with varying polynomial order in the linear mixed model.

    Science.gov (United States)

    Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

    2006-02-15

    The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

  17. Survival chance in papillary thyroid cancer in Hungary: individual survival probability estimation using the Markov method

    International Nuclear Information System (INIS)

    Esik, Olga; Tusnady, Gabor; Daubner, Kornel; Nemeth, Gyoergy; Fuezy, Marton; Szentirmay, Zoltan

    1997-01-01

    Purpose: The typically benign, but occasionally rapidly fatal clinical course of papillary thyroid cancer has raised the need for individual survival probability estimation, to tailor the treatment strategy exclusively to a given patient. Materials and methods: A retrospective study was performed on 400 papillary thyroid cancer patients with a median follow-up time of 7.1 years to establish a clinical database for uni- and multivariate analysis of the prognostic factors related to survival (Kaplan-Meier product limit method and Cox regression). For a more precise prognosis estimation, the effect of the most important clinical events were then investigated on the basis of a Markov renewal model. The basic concept of this approach is that each patient has an individual disease course which (besides the initial clinical categories) is affected by special events, e.g. internal covariates (local/regional/distant relapses). On the supposition that these events and the cause-specific death are influenced by the same biological processes, the parameters of transient survival probability characterizing the speed of the course of the disease for each clinical event and their sequence were determined. The individual survival curves for each patient were calculated by using these parameters and the independent significant clinical variables selected from multivariate studies, summation of which resulted in a mean cause-specific survival function valid for the entire group. On the basis of this Markov model, prediction of the cause-specific survival probability is possible for extrastudy cases, if it is supposed that the clinical events occur within new patients in the same manner and with the similar probability as within the study population. Results: The patient's age, a distant metastasis at presentation, the extent of the surgical intervention, the primary tumor size and extent (pT), the external irradiation dosage and the degree of TSH suppression proved to be

  18. Replica analysis of overfitting in regression models for time-to-event data

    Science.gov (United States)

    Coolen, A. C. C.; Barrett, J. E.; Paga, P.; Perez-Vicente, C. J.

    2017-09-01

    Overfitting, which happens when the number of parameters in a model is too large compared to the number of data points available for determining these parameters, is a serious and growing problem in survival analysis. While modern medicine presents us with data of unprecedented dimensionality, these data cannot yet be used effectively for clinical outcome prediction. Standard error measures in maximum likelihood regression, such as p-values and z-scores, are blind to overfitting, and even for Cox’s proportional hazards model (the main tool of medical statisticians), one finds in literature only rules of thumb on the number of samples required to avoid overfitting. In this paper we present a mathematical theory of overfitting in regression models for time-to-event data, which aims to increase our quantitative understanding of the problem and provide practical tools with which to correct regression outcomes for the impact of overfitting. It is based on the replica method, a statistical mechanical technique for the analysis of heterogeneous many-variable systems that has been used successfully for several decades in physics, biology, and computer science, but not yet in medical statistics. We develop the theory initially for arbitrary regression models for time-to-event data, and verify its predictions in detail for the popular Cox model.

  19. Survival analysis of heart failure patients: A case study.

    Science.gov (United States)

    Ahmad, Tanvir; Munir, Assia; Bhatti, Sajjad Haider; Aftab, Muhammad; Raza, Muhammad Ali

    2017-01-01

    This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

  20. Number of Lymph Nodes Removed and Survival after Gastric Cancer Resection: An Analysis from the US Gastric Cancer Collaborative.

    Science.gov (United States)

    Gholami, Sepideh; Janson, Lucas; Worhunsky, David J; Tran, Thuy B; Squires, Malcolm Hart; Jin, Linda X; Spolverato, Gaya; Votanopoulos, Konstantinos I; Schmidt, Carl; Weber, Sharon M; Bloomston, Mark; Cho, Clifford S; Levine, Edward A; Fields, Ryan C; Pawlik, Timothy M; Maithel, Shishir K; Efron, Bradley; Norton, Jeffrey A; Poultsides, George A

    2015-08-01

    Examination of at least 16 lymph nodes (LNs) has been traditionally recommended during gastric adenocarcinoma resection to optimize staging, but the impact of this strategy on survival is uncertain. Because recent randomized trials have demonstrated a therapeutic benefit from extended lymphadenectomy, we sought to investigate the impact of the number of LNs removed on prognosis after gastric adenocarcinoma resection. We analyzed patients who underwent gastrectomy for gastric adenocarcinoma from 2000 to 2012, at 7 US academic institutions. Patients with M1 disease or R2 resections were excluded. Disease-specific survival (DSS) was calculated using the Kaplan-Meier method and compared using log-rank and Cox regression analyses. Of 742 patients, 257 (35%) had 7 to 15 LNs removed and 485 (65%) had ≥16 LNs removed. Disease-specific survival was not significantly longer after removal of ≥16 vs 7 to 15 LNs (10-year survival, 55% vs 47%, respectively; p = 0.53) for the entire cohort, but was significantly improved in the subset of patients with stage IA to IIIA (10-year survival, 74% vs 57%, respectively; p = 0.018) or N0-2 disease (72% vs 55%, respectively; p = 0.023). Similarly, for patients who were classified to more likely be "true N0-2," based on frequentist analysis incorporating both the number of positive and of total LNs removed, the hazard ratio for disease-related death (adjusted for T stage, R status, grade, receipt of neoadjuvant and adjuvant therapy, and institution) significantly decreased as the number of LNs removed increased. The number of LNs removed during gastrectomy for adenocarcinoma appears itself to have prognostic implications for long-term survival. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  1. Impact of anastomotic leak on recurrence and survival after colorectal cancer surgery: a BioGrid Australia analysis.

    Science.gov (United States)

    Sammour, Tarik; Hayes, Ian P; Jones, Ian T; Steel, Malcolm C; Faragher, Ian; Gibbs, Peter

    2018-01-01

    There is conflicting evidence regarding the oncological impact of anastomotic leak following colorectal cancer surgery. This study aims to test the hypothesis that anastomotic leak is independently associated with local recurrence and overall and cancer-specific survival. Analysis of prospectively collected data from multiple centres in Victoria between 1988 and 2015 including all patients who underwent colon or rectal resection for cancer with anastomosis was presented. Overall and cancer-specific survival rates and rates of local recurrence were compared using Cox regression analysis. A total of 4892 patients were included, of which 2856 had completed 5-year follow-up. The overall anastomotic leak rate was 4.0%. Cox regression analysis accounting for differences in age, sex, body mass index, American Society of Anesthesiologists score and tumour stage demonstrated that anastomotic leak was associated with significantly worse 5-year overall survival (χ 2 = 6.459, P = 0.011) for colon cancer, but only if early deaths were included. There was no difference in 5-year colon cancer-specific survival (χ 2 = 0.582, P = 0.446) or local recurrence (χ 2 = 0.735, P = 0.391). For rectal cancer, there was no difference in 5-year overall survival (χ 2 = 0.266, P = 0.606), cancer-specific survival (χ 2 = 0.008, P = 0.928) or local recurrence (χ 2 = 2.192, P = 0.139). Anastomotic leak may reduce 5-year overall survival in colon cancer patients but does not appear to influence the 5-year overall survival in rectal cancer patients. There was no effect on local recurrence or cancer-specific survival. © 2016 Royal Australasian College of Surgeons.

  2. The study of logistic regression of risk factor on the death cause of uranium miners

    International Nuclear Information System (INIS)

    Wen Jinai; Yuan Liyun; Jiang Ruyi

    1999-01-01

    Logistic regression model has widely been used in the field of medicine. The computer software on this model is popular, but it is worth to discuss how to use this model correctly. Using SPSS (Statistical Package for the Social Science) software, unconditional logistic regression method was adopted to carry out multi-factor analyses on the cause of total death, cancer death and lung cancer death of uranium miners. The data is from radioepidemiological database of one uranium mine. The result show that attained age is a risk factor in the logistic regression analyses of total death, cancer death and lung cancer death. In the logistic regression analysis of cancer death, there is a negative correlation between the age of exposure and cancer death. This shows that the younger the age at exposure, the bigger the risk of cancer death. In the logistic regression analysis of lung cancer death, there is a positive correlation between the cumulated exposure and lung cancer death, this show that cumulated exposure is a most important risk factor of lung cancer death on uranium miners. It has been documented by many foreign reports that the lung cancer death rate is higher in uranium miners

  3. Factors affecting route selection and survival of steelhead kelts at Snake River dams in 2012 and 2013

    Energy Technology Data Exchange (ETDEWEB)

    Harnish, Ryan A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Colotelo, Alison H. A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Li, Xinya [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fu, Tao [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ham, Kenneth D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Deng, Zhiqun [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Green, Ethan D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-31

    In 2012 and 2013, Pacific Northwest National Laboratory (PNNL) conducted a study that summarized the passage route proportions and route-specific survival rates of steelhead kelts that passed through Federal Columbia River Power System (FCRPS) dams. To accomplish this, a total of 811 steelhead kelts were tagged with Juvenile Salmon Acoustic Telemetry System (JSATS) transmitters. Acoustic receivers, both autonomous and cabled, were deployed throughout the FCRPS to monitor the downstream movements of tagged kelts. Kelts were also tagged with passive integrated transponder tags to monitor passage through juvenile bypass systems (JBS) and detect returning fish. The current study evaluated data collected in 2012 and 2013 to identify environmental, temporal, operational, individual, and behavioral variables that were related to forebay residence time, route of passage, and survival of steelhead kelts at FCRPS dams on the Snake River. Multiple approaches, including 3-D tracking, bivariate and multivariable regression modeling, and decision tree analyses were used to identify the environmental, temporal, operational, individual, and behavioral variables that had the greatest effect on forebay residence time, route of passage, and route-specific and overall dam passage survival probabilities for tagged kelts at Lower Granite (LGR), Little Goose (LGS), and Lower Monumental (LMN) dams. In general, kelt behavior and discharge appeared to work independently to affect forebay residence times. Kelt behavior, primarily approach location, migration depth, and “searching” activities in the forebay, was found to have the greatest influence on their route of passage. The condition of kelts was the single most important factor affecting their survival. The information gathered in this study may be used by dam operators and fisheries managers to identify potential management actions to improve in-river survival of kelts or collection methods for kelt reconditioning programs to aid

  4. Logistic regression models for polymorphic and antagonistic pleiotropic gene action on human aging and longevity

    DEFF Research Database (Denmark)

    Tan, Qihua; Bathum, L; Christiansen, L

    2003-01-01

    In this paper, we apply logistic regression models to measure genetic association with human survival for highly polymorphic and pleiotropic genes. By modelling genotype frequency as a function of age, we introduce a logistic regression model with polytomous responses to handle the polymorphic...... situation. Genotype and allele-based parameterization can be used to investigate the modes of gene action and to reduce the number of parameters, so that the power is increased while the amount of multiple testing minimized. A binomial logistic regression model with fractional polynomials is used to capture...... the age-dependent or antagonistic pleiotropic effects. The models are applied to HFE genotype data to assess the effects on human longevity by different alleles and to detect if an age-dependent effect exists. Application has shown that these methods can serve as useful tools in searching for important...

  5. Carbonic anhydrase IX and response to postmastectomy radiotherapy in high-risk breast cancer: a subgroup analysis of the DBCG82 b and c trials

    DEFF Research Database (Denmark)

    Kyndi, M.; Sorensen, F.B.; Alsner, J.

    2008-01-01

    -points were loco-regional recurrence, distant metastases, disease-specific survival and overall survival. Statistical analyses included kappa statistics, chi(2) or exact tests, Kaplan-Meier probability plots, Log-rank test and Cox regression analyses. Results CA IX was assessable in 945 cores. The percentage...

  6. Additional androgen deprivation makes the difference. Biochemical recurrence-free survival in prostate cancer patients after HDR brachytherapy and external beam radiotherapy

    International Nuclear Information System (INIS)

    Schiffmann, Jonas; Tennstedt, Pierre; Beyer, Burkhard; Boehm, Katharina; Tilki, Derya; Salomon, Georg; Graefen, Markus; Lesmana, Hans; Platz, Volker; Petersen, Cordula; Kruell, Andreas; Schwarz, Rudolf

    2015-01-01

    The role of additional androgen deprivation therapy (ADT) in prostate cancer (PCa) patients treated with combined HDR brachytherapy (HDR-BT) and external beam radiotherapy (EBRT) is still unknown. Consecutive PCa patients classified as D'Amico intermediate and high-risk who underwent HDR-BT and EBRT treatment ± ADT at our institution between January 1999 and February 2009 were assessed. Multivariable Cox regression models predicting biochemical recurrence (BCR) were performed. BCR-free survival was assessed with Kaplan-Meier analyses. Overall, 392 patients were assessable. Of these, 221 (56.4 %) underwent trimodality (HDR-BT and EBRT and ADT) and 171 (43.6 %) bimodality (HDR-BT and EBRT) treatment. Additional ADT administration reduced the risk of BCR (HR: 0.4, 95 % CI: 0.3-0.7, p < 0.001). D'Amico high-risk patients had superior BCR-free survival when additional ADT was administered (log-rank p < 0.001). No significant difference for BCR-free survival was recorded when additional ADT was administered to D'Amico intermediate-risk patients (log-rank p = 0.2). Additional ADT administration improves biochemical control in D'Amico high-risk patients when HDR-BT and EBRT are combined. Physicians should consider the oncological benefit of ADT administration for these patients during the decision-making process. (orig.) [de

  7. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  8. FIRST USE OF STEREOLOGY TO QUANTIFY THE SURVIVAL OF FAT AUTOGRAFTS

    Directory of Open Access Journals (Sweden)

    Eduardo Serna Cuéllar

    2011-05-01

    Full Text Available It is not usual to perform quantitative analyses on surgical materials. Rather, they are evaluated clinically, through qualitative methods, and if quantitation is done, it is on a 2-dimensional basis. In this study, the long-term survival of fat autografts (FAG in 40 subjects with facial soft tissue defects is quantified. An adipose tissue preparation from the abdomen obtained through liposuction and centrifugation is injected subcutaneously. Approximately 14 months later, the treated area is biopsied. Extensive computer-based histological analyses were performed using the stereological method in order to directly obtain three parameters: volume fraction of adipocytes in the fat tissue (VV, density (number per volume of adipocytes in the fat tissue (NV, and the mean cell volume of adipocytes (VA in each tissue sample. A set of equations based on these three quantitative parameters is produced for evaluation of the volumetric survival fraction (VSF of FAG. The presented data evidenced a 66% survival fraction at the 14-month follow-up. In routine practice, it would be sufficient to perform this volumetric analysis on the injected and biopsied fat samples to know what fraction of the FAG has survived. This is an objective method for quantifying FAG survival and will allow a standardized comparison between different research series and authors.

  9. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  10. Survival analysis and classification methods for forest fire size

    Science.gov (United States)

    2018-01-01

    Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at “being held” (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at “being held” exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances. PMID:29320497

  11. Malformations associated with congenital diaphragmatic hernia: Impact on survival.

    Science.gov (United States)

    Bojanić, Katarina; Pritišanac, Ena; Luetić, Tomislav; Vuković, Jurica; Sprung, Juraj; Weingarten, Toby N; Schroeder, Darrell R; Grizelj, Ruža

    2015-11-01

    Congenital diaphragmatic hernia (CDH) is associated with high mortality. Survival is influenced by the extent of pulmonary hypoplasia and additional congenital defects. The purpose of this study was to assess the association of congenital anomalies and admission capillary carbon dioxide levels (PcCO2), as a measure of extent of pulmonary hypoplasia, on survival in neonates with CDH. This is a retrospective review of neonates with CDH admitted to a tertiary neonatal intensive care unit between 1990 and 2014. Logistic regression was used to assess whether hospital survival was associated with admission PcCO2 or associated anomalies (isolated CDH, CDH with cardiovascular anomalies, and CDH with noncardiac anomalies). The probabilities of survival (POS) score, based on birth weight and 5-min Apgar as defined by the Congenital Diaphragmatic Hernia Study Group were included as a covariate. Of 97 patients, 55 had additional malformations (cardiovascular n=12, noncardiac anomalies n=43). POS was lower in CDH with other anomalies compared to isolated CDH. Survival rate was 61.9%, 53.5% and 41.7% in isolated CDH, CDH with noncardiac anomalies and CDH with cardiovascular anomalies, respectively. After adjusting for POS score the likelihood of survival in CDH groups with additional anomalies was similar to isolated CDH (OR 0.95, 95% CI 0.22-4.15, and 1.10, 0.39-3.08, for CDH with and without cardiovascular anomalies, respectively). After adjusting for POS score, lower PcCO2 levels (OR=1.25 per 5mmHg decrease, P=0.003) were associated with better survival. Neonates with CDH have a high prevalence of congenital malformations. However, after adjusting for POS score the presence of additional anomalies was not associated with survival. The POS score and admission PcCO2 were important prognosticating factors for survival. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Regression to Causality : Regression-style presentation influences causal attribution

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

  13. Management of hepatocellular carcinoma: an overview of major findings from meta-analyses

    Science.gov (United States)

    Guo, Xiaozhong; Han, Guohong

    2016-01-01

    This paper aims to systematically review the major findings from meta-analyses comparing different treatment options for hepatocellular carcinoma (HCC). A total of 153 relevant papers were searched via the PubMed, EMBASE, and Cochrane library databases. They were classified according to the mainstay treatment modalities (i.e., liver transplantation, surgical resection, radiofrequency ablation, transarterial embolization or chemoembolization, sorafenib, and others). The primary outcome data, such as overall survival, diseases-free survival or recurrence-free survival, progression-free survival, and safety, were summarized. The recommendations and uncertainties regarding the treatment of HCC were also proposed. PMID:27167195

  14. Survival time and effect of selected predictor variables on survival in owned pet cats seropositive for feline immunodeficiency and leukemia virus attending a referral clinic in northern Italy.

    Science.gov (United States)

    Spada, Eva; Perego, Roberta; Sgamma, Elena Assunta; Proverbio, Daniela

    2018-02-01

    Feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV) are among the most important feline infectious diseases worldwide. This retrospective study investigated survival times and effects of selected predictor factors on survival time in a population of owned pet cats in Northern Italy testing positive for the presence of FIV antibodies and FeLV antigen. One hundred and three retrovirus-seropositive cats, 53 FIV-seropositive cats, 40 FeLV-seropositive cats, and 10 FIV+FeLV-seropositive cats were included in the study. A population of 103 retrovirus-seronegative age and sex-matched cats was selected. Survival time was calculated and compared between retrovirus-seronegative, FIV, FeLV and FIV+FeLV-seropositive cats using Kaplan-Meier survival analysis. Cox proportional-hazards regression analysis was used to study the effect of selected predictor factors (male gender, peripheral blood cytopenia as reduced red blood cells - RBC- count, leukopenia, neutropenia and lymphopenia, hypercreatininemia and reduced albumin to globulin ratio) on survival time in retrovirus-seropositive populations. Median survival times for seronegative cats, FIV, FeLV and FIV+FeLV-seropositive cats were 3960, 2040, 714 and 77days, respectively. Compared to retrovirus-seronegative cats median survival time was significantly lower (P<0.000) in FeLV and FIV+FeLV-seropositive cats. Median survival time in FeLV and FIV+FeLV-seropositive cats was also significant lower (P<0.000) when compared to FIV-seropositive cats. Hazard ratio of death in FeLV and FIV+FeLV-seropositive cats being respectively 3.4 and 7.4 times higher, in comparison to seronegative cats and 2.3 and 4.8 times higher in FeLV and FIV+FeLV-seropositive cats as compared to FIV-seropositive cats. A Cox proportional-hazards regression analysis showed that FIV and FeLV-seropositive cats with reduced RBC counts at time of diagnosis of seropositivity had significantly shorter survival times when compared to FIV and Fe

  15. After accounting for competing causes of death and more advanced stage, do Aboriginal and Torres Strait Islander peoples with cancer still have worse survival? A population-based cohort study in New South Wales.

    Science.gov (United States)

    Tervonen, Hanna E; Walton, Richard; You, Hui; Baker, Deborah; Roder, David; Currow, David; Aranda, Sanchia

    2017-06-02

    Aboriginal and Torres Strait Islander peoples in Australia have been found to have poorer cancer survival than non-Aboriginal people. However, use of conventional relative survival analyses is limited due to a lack of life tables. This cohort study examined whether poorer survival persist after accounting for competing risks of death from other causes and disparities in cancer stage at diagnosis, for all cancers collectively and by cancer site. People diagnosed in 2000-2008 were extracted from the population-based New South Wales Cancer Registry. Aboriginal status was multiply imputed for people with missing information (12.9%). Logistic regression models were used to compute odds ratios (ORs) with 95% confidence intervals (CIs) for 'advanced stage' at diagnosis (separately for distant and distant/regional stage). Survival was examined using competing risk regression to compute subhazard ratios (SHRs) with 95%CIs. Of the 301,356 cases, 2517 (0.84%) identified as Aboriginal (0.94% after imputation). After adjusting for age, sex, year of diagnosis, socio-economic status, remoteness, and cancer site Aboriginal peoples were more likely to be diagnosed with distant (OR 1.30, 95%CI 1.17-1.44) or distant/regional stage (OR 1.29, 95%CI 1.18-1.40) for all cancers collectively. This applied to cancers of the female breast, uterus, prostate, kidney, others (those not included in other categories) and cervix (when analyses were restricted to cases with known stages/known Aboriginal status). Aboriginal peoples had a higher hazard of death than non-Aboriginal people after accounting for competing risks from other causes of death, socio-demographic factors, stage and cancer site (SHR 1.40, 95%CI 1.31-1.50 for all cancers collectively). Consistent results applied to colorectal, lung, breast, prostate and other cancers. Aboriginal peoples with cancer have an elevated hazard of cancer death compared with non-Aboriginal people, after accounting for more advanced stage and competing

  16. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies

    DEFF Research Database (Denmark)

    Tybjærg-Hansen, Anne

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements...... of the risk factors are observed on a subsample. We extend the multivariate RC techniques to a meta-analysis framework where multiple studies provide independent repeat measurements and information on disease outcome. We consider the cases where some or all studies have repeat measurements, and compare study......-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies...

  17. Linear Regression with a Randomly Censored Covariate: Application to an Alzheimer's Study.

    Science.gov (United States)

    Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

    2017-01-01

    The association between maternal age of onset of dementia and amyloid deposition (measured by in vivo positron emission tomography (PET) imaging) in cognitively normal older offspring is of interest. In a regression model for amyloid, special methods are required due to the random right censoring of the covariate of maternal age of onset of dementia. Prior literature has proposed methods to address the problem of censoring due to assay limit of detection, but not random censoring. We propose imputation methods and a survival regression method that do not require parametric assumptions about the distribution of the censored covariate. Existing imputation methods address missing covariates, but not right censored covariates. In simulation studies, we compare these methods to the simple, but inefficient complete case analysis, and to thresholding approaches. We apply the methods to the Alzheimer's study.

  18. A Survival Model for Shortleaf Pine Tress Growing in Uneven-Aged Stands

    Science.gov (United States)

    Thomas B. Lynch; Lawrence R. Gering; Michael M. Huebschmann; Paul A. Murphy

    1999-01-01

    A survival model for shortleaf pine (Pinus echinata Mill.) trees growing in uneven-aged stands was developed using data from permanently established plots maintained by an industrial forestry company in western Arkansas. Parameters were fitted to a logistic regression model with a Bernoulli dependent variable in which "0" represented...

  19. The impact of geographic unit of analysis on socioeconomic inequalities in cancer survival and distant summary stage - a population-based study.

    Science.gov (United States)

    Tervonen, Hanna E; Morrell, Stephen; Aranda, Sanchia; Roder, David; You, Hui; Niyonsenga, Theo; Walton, Richard; Baker, Deborah; Currow, David

    2016-12-13

    When using area-level disadvantage measures, size of geographic unit can have major effects on recorded socioeconomic cancer disparities. This study examined the extent of changes in recorded socioeconomic inequalities in cancer survival and distant stage when the measure of socioeconomic disadvantage was based on smaller Census Collection Districts (CDs) instead of Statistical Local Areas (SLAs). Population-based New South Wales Cancer Registry data were used to identify cases diagnosed with primary invasive cancer in 2000-2008 (n=264,236). Logistic regression and competing risk regression modelling were performed to examine socioeconomic differences in odds of distant stage and hazard of cancer death for all sites combined and separately for breast, prostate, colorectal and lung cancers. For all sites collectively, associations between socioeconomic disadvantage and cancer survival and distant stage were stronger when the CD-based socioeconomic disadvantage measure was used compared with the SLA-based measure. The CD-based measure showed a more consistent socioeconomic gradient with a linear upward trend of risk of cancer death/distant stage with increasing socioeconomic disadvantage. Site-specific analyses provided similar findings for the risk of death but less consistent results for the likelihood of distant stage. The use of socioeconomic disadvantage measure based on the smallest available spatial unit should be encouraged in the future. Implications for Public Health: Disadvantage measures based on small spatial units can more accurately identify socioeconomic cancer disparities to inform priority settings in service planning. © 2016 Public Health Association of Australia.

  20. No association of CpG island methylator phenotype and colorectal cancer survival: population-based study.

    Science.gov (United States)

    Jia, Min; Jansen, Lina; Walter, Viola; Tagscherer, Katrin; Roth, Wilfried; Herpel, Esther; Kloor, Matthias; Bläker, Hendrik; Chang-Claude, Jenny; Brenner, Hermann; Hoffmeister, Michael

    2016-11-22

    Previous studies have shown adverse effects of CpG island methylator phenotype (CIMP) on colorectal cancer (CRC) prognosis. However, sample sizes were often limited and only few studies were able to adjust for relevant molecular features associated with CIMP. The aim of this study was to investigate the impact of CIMP on CRC survival in a large population-based study with comprehensive adjustment. The CIMP status and other molecular tumour features were analysed in 1385 CRC patients diagnosed between 2003 and 2010. Detailed information were obtained from standardised personal interviews and medical records. During follow-up (median: 4.9 years), we assessed vital status, cause of death and therapy details. Cox proportional hazard regression models were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of survival after CRC. The CIMP-H occurred more frequently in patients with older age, female gender, cancer in the proximal colon, BRAF mutation and microsatellite instability-high (MSI-H). However, CIMP status was not associated with CRC prognosis in CRC patients (HR=1.00; 95% CI=0.72-1.40 for overall survival; HR=0.96; 95% CI=0.65-1.41 for disease-specific survival) or in any of the subgroups. Although CIMP status was associated with the presence of MSI-H and BRAF mutation, the prognostic effects of MSI-H (HR=0.49; 95% CI=0.27-0.90) and BRAF mutation (HR=1.78; 95% CI=1.10-2.84) were independent of CIMP status. Similar benefit of chemotherapy was found for CRC outcomes in both the CIMP-low/negative group and the CIMP-high group. CpG island methylator phenotype was not associated with CRC prognosis after adjusting for other important clinical factors and associated mutations.

  1. KRAS polymorphisms are associated with survival of CRC in Chinese population.

    Science.gov (United States)

    Dai, Qiong; Wei, Hui Lian; Huang, Juan; Zhou, Tie Jun; Chai, Li; Yang, Zhi-Hui

    2016-04-01

    rs12245, rs12587, rs9266, rs1137282, rs61764370, and rs712 of KRAS oncogene are characterized in the 3'UTR. The study highlights the important role of these polymorphisms playing in the susceptibility, oxaliplatin-based chemotherapy sensitivity, progression, and prognosis of CRC. Improved multiplex ligation detection reaction (iMLDR) technique is used for genotyping. An unconditional logistic regression model was used to estimate the association of certain polymorphism and CRC risk. The Kaplan-Meier method, log-rank test, and Cox regression model were used to evaluate the effects of polymorphisms on survival analysis. Results demonstrated that TT genotype and T allele of rs712 were associated with the increased risk of CRC; the patients with GG genotype and G allele of rs61764370 had a shorter survival and a higher risk of relapse or metastasis of CRC. Our studies supported the conclusions that rs61764370 and rs712 polymorphisms of the KRAS are functional and it may play an important role in the development of CRC and oxaliplatin-based chemotherapy efficiency and prognosis of CRC.

  2. Influence of body composition on survival in patients with head and neck cancer.

    Science.gov (United States)

    Karnell, Lucy Hynds; Sperry, Steven M; Anderson, Carryn M; Pagedar, Nitin A

    2016-04-01

    Recent evidence has suggested links between obesity and outcomes for various types of cancer. This study investigates the impact that body composition has on survival in patients with head and neck cancer. Data prospectively collected from 578 patients were analyzed using Cox regression models to determine independent associations that pretreatment body mass index (BMI) and 3-month weight change have on observed survival. Higher BMIs were associated with better survival (p < .001). Five-year rates ranged from 33.8% for underweight to 75.3% for overweight/obese patients. Patients with stable weight had the highest 5-year rate (72.6%; p = .019), whereas patients who gained ≥5% had worse survival (45.8%) than those who lost ≥5% (65.8%). BMI independently predicted survival, whereas weight change was not an independent predictor. This demonstrated association between BMI and survival provides useful information when offering prognoses and investigating optimal treatments © 2015 Wiley Periodicals, Inc. Head Neck 38: E261-E267, 2016. © 2015 Wiley Periodicals, Inc.

  3. Disparities in breast cancer tumor characteristics, treatment, time to treatment, and survival probability among African American and white women.

    Science.gov (United States)

    Foy, Kevin Chu; Fisher, James L; Lustberg, Maryam B; Gray, Darrell M; DeGraffinreid, Cecilia R; Paskett, Electra D

    2018-01-01

    African American (AA) women have a 42% higher breast cancer death rate compared to white women despite recent advancements in management of the disease. We examined racial differences in clinical and tumor characteristics, treatment and survival in patients diagnosed with breast cancer between 2005 and 2014 at a single institution, the James Cancer Hospital, and who were included in the Arthur G. James Cancer Hospital and Richard J. Solove Research Institute Cancer Registry in Columbus OH. Statistical analyses included likelihood ratio chi-square tests for differences in proportions, as well as univariate and multivariate Cox proportional hazards regressions to examine associations between race and overall and progression-free survival probabilities. AA women made up 10.2% (469 of 4593) the sample. Average time to onset of treatment after diagnosis was almost two times longer in AA women compared to white women (62.0 days vs 35.5 days, p  triple negative and late stage breast cancer, and were less likely to receive surgery, especially mastectomy and reconstruction following mastectomy. After adjustment for confounding factors (age, grade, and surgery), overall survival probability was significantly associated with race (HR = 1.33; 95% CI 1.03-1.72). These findings highlight the need for efforts focused on screening and receipt of prompt treatment among AA women diagnosed with breast cancer.

  4. Survival from tumours of the central nervous system in Danish children

    DEFF Research Database (Denmark)

    Erdmann, Friederike; Winther, Jeanette Falck; Dalton, Susanne Oksbjerg

    2018-01-01

    associations between survival and any family characteristic. Analyses by CNS tumour subtypes showed reduced survival for children with glioma when living outside of Copenhagen (HR 1.55; CI 1.03; 2.35). For embryonal CNS tumours, the number of full siblings was associated with worse survival (HR for having 3......Little is known about social inequalities in childhood cancer survival. We investigated the impact of family circumstances on survival from paediatric central nervous system (CNS) tumours in a nationwide, register-based cohort of Danish children. All children born between 1973 and 2006...... and diagnosed with a CNS tumour before the age of 20 years (N = 1,261) were followed until 10 years from diagnosis. Using Cox proportional hazards models, the impact of various family characteristics on overall survival was estimated. Hazard ratios (HRs) for all CNS tumours combined did not show strong...

  5. Survival of Alzheimer's disease patients in Korea.

    Science.gov (United States)

    Go, Seok Min; Lee, Kang Soo; Seo, Sang Won; Chin, Juhee; Kang, Sue J; Moon, So Young; Na, Duk L; Cheong, Hae-Kwan

    2013-01-01

    The natural history of Alzheimer's disease (AD) has rarely been studied in the Korean population. Our study on survival analyses in Korean AD patients potentially provides a basis for cross-cultural comparisons. We studied 724 consecutive patients from a memory disorder clinic in a tertiary hospital in Seoul, who were diagnosed as having AD between April 1995 and December 2005. Deaths were identified by the Statistics Korea database. The Kaplan-Meier method was used for survival analysis, and a Cox proportional hazard model was used to assess factors related to patient survival. The overall median survival from the onset of first symptoms and from the time of diagnosis was 12.6 years (95% confidence interval 11.7-13.4) and 9.3 years (95% confidence interval 8.7-9.9), respectively. The age of onset, male gender, history of diabetes mellitus, lower Mini-Mental State Examination score, and higher Clinical Dementia Rating score were negatively associated with survival. There was a reversal of risk of AD between early-onset and later-onset AD, 9.1 years after onset. The results of our study show a different pattern of survival compared to those studies carried out with western AD populations. Mortality risk of early-onset AD varied depending on the duration of follow-up. Copyright © 2013 S. Karger AG, Basel.

  6. Organochlorine insecticides DDT and chlordane in relation to survival following breast cancer.

    Science.gov (United States)

    Parada, Humberto; Wolff, Mary S; Engel, Lawrence S; White, Alexandra J; Eng, Sybil M; Cleveland, Rebecca J; Khankari, Nikhil K; Teitelbaum, Susan L; Neugut, Alfred I; Gammon, Marilie D

    2016-02-01

    Organochlorine insecticides have been studied extensively in relation to breast cancer incidence, and results from two meta-analyses have been null for late-life residues, possibly due to measurement error. Whether these compounds influence survival remains to be fully explored. We examined associations between organochlorine insecticides [p,p'-DDT (dichlorodiphenyltrichloroethane), its primary metabolite, p,p'-DDE, and chlordane] assessed shortly after diagnosis and survival among women with breast cancer. A population-based sample of women diagnosed with a first primary invasive or in situ breast cancer in 1996-1997 and with available organochlorine blood measures (n = 633) were followed for vital status through 2011. After follow-up of 5 and 15 years, we identified 55 and 189 deaths, of which 36 and 74, respectively, were breast cancer-related. Using Cox regression models, we estimated the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for lipid-adjusted organochlorine concentrations with all-cause and breast cancer-specific mortality. At 5 years after diagnosis, the highest tertile of DDT concentration was associated with all-cause (HR = 2.19; 95% CI: 1.02, 4.67) and breast cancer-specific (HR = 2.72; 95% CI: 1.04, 7.13) mortality. At 15 years, middle tertile concentrations of DDT (HR = 1.42; 95% CI 0.99, 2.06) and chlordane (HR = 1.42; 95% CI: 0.94, 2.12) were modestly associated with all-cause and breast cancer-specific mortality. Third tertile DDE concentrations were inversely associated with 15-year all-cause mortality (HR = 0.66; 95% CI: 0.44, 0.99). This is the first population-based study in the United States to show that DDT may adversely impact survival following breast cancer diagnosis. Further studies are warranted given the high breast cancer burden and the ubiquity of these chemicals. © 2015 UICC.

  7. Trends in colorectal cancer survival in northern Denmark: 1985-2004.

    Science.gov (United States)

    Iversen, L H; Nørgaard, M; Jepsen, P; Jacobsen, J; Christensen, M M; Gandrup, P; Madsen, M R; Laurberg, S; Wogelius, P; Sørensen, H T

    2007-03-01

    The prognosis for colorectal cancer (CRC) is less favourable in Denmark than in neighbouring countries. To improve cancer treatment in Denmark, a National Cancer Plan was proposed in 2000. We conducted this population-based study to monitor recent trends in CRC survival and mortality in four Danish counties. We used hospital discharge registry data for the period January 1985-March 2004 in the counties of north Jutland, Ringkjøbing, Viborg and Aarhus. We computed crude survival and used Cox proportional hazards regression analysis to compare mortality over time, adjusted for age and gender. A total of 19,515 CRC patients were identified and linked with the Central Office of Civil Registration to ascertain survival through January 2005. From 1985 to 2004, 1-year and 5-year survival improved both for patients with colon and rectal cancer. From 1995-1999 to 2000-2004, overall 1-year survival of 65% for colon cancer did not improve, and some age groups experienced a decreasing 1-year survival probability. For rectal cancer, overall 1-year survival increased from 71% in 1995-1999 to 74% in 2000-2004. Using 1985-1989 as reference period, 30-day mortality did not decrease after implementation of the National Cancer Plan in 2000, neither for patients with colon nor rectal cancer. However, 1-year mortality for patients with rectal cancer did decline after its implementation. Survival and mortality from colon and rectal cancer improved before the National Cancer Plan was proposed; after its implementation, however, improvement has been observed for rectal cancer only.

  8. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

    Science.gov (United States)

    Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

    2016-01-01

    Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  9. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

    Science.gov (United States)

    Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

    2016-01-01

    Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

  10. Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models

    Directory of Open Access Journals (Sweden)

    Lois A Gelfand

    2016-03-01

    Full Text Available Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH and fully parametric accelerated failure time (AFT approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  11. Information fusion via constrained principal component regression for robust quantification with incomplete calibrations

    International Nuclear Information System (INIS)

    Vogt, Frank

    2013-01-01

    Graphical abstract: Analysis Task: Determine the albumin (= protein) concentration in microalgae cells as a function of the cells’ nutrient availability. Left Panel: The predicted albumin concentrations as obtained by conventional principal component regression features low reproducibility and are partially higher than the concentrations of algae in which albumin is contained. Right Panel: Augmenting an incomplete PCR calibration with additional expert information derives reasonable albumin concentrations which now reveal a significant dependency on the algae's nutrient situation. -- Highlights: •Make quantitative analyses of compounds embedded in largely unknown chemical matrices robust. •Improved concentration prediction with originally insufficient calibration models. •Chemometric approach for incorporating expertise from other fields and/or researchers. •Ensure chemical, biological, or medicinal meaningfulness of quantitative analyses. -- Abstract: Incomplete calibrations are encountered in many applications and hamper chemometric data analyses. Such situations arise when target analytes are embedded in a chemically complex matrix from which calibration concentrations cannot be determined with reasonable efforts. In other cases, the samples’ chemical composition may fluctuate in an unpredictable way and thus cannot be comprehensively covered by calibration samples. The reason for calibration model to fail is the regression principle itself which seeks to explain measured data optimally in terms of the (potentially incomplete) calibration model but does not consider chemical meaningfulness. This study presents a novel chemometric approach which is based on experimentally feasible calibrations, i.e. concentration series of the target analytes outside the chemical matrix (‘ex situ calibration’). The inherent lack-of-information is then compensated by incorporating additional knowledge in form of regression constraints. Any outside knowledge can be

  12. Paradox of spontaneous cancer regression: implications for fluctuational radiothermy and radiotherapy

    International Nuclear Information System (INIS)

    Roy, Prasun K.; Dutta Majumder, D.; Biswas, Jaydip

    1999-01-01

    Spontaneous regression of malignant tumours without treatment is a most enigmatic phenomenon with immense therapeutic potentialities. We analyse such cases to find that the commonest cause is a preceding episode of high fever-induced thermal fluctuation which produce fluctuation of biochemical and immunological parameters. Using Prigogine-Glansdorff thermodynamic stability formalism and biocybernetic principles, we develop the theoretical foundation of tumour regression induced by thermal, radiational or oxygenational fluctuations. For regression, a preliminary threshold condition of fluctuations is derived, namely σ > 2.83. We present some striking confirmation of such fluctuation-induced regression of various therapy-resistant masses as Ewing tumour, neurogranuloma and Lewis lung carcinoma by utilising σ > 2.83. Our biothermodynamic stability model of malignancy appears to illuminate the marked increase of aggressiveness of mammalian malignancy which occurred around 250 million years ago when homeothermic warm-blooded pre-mammals evolved. Using experimental data, we propose a novel approach of multi-modal hyper-fluctuation therapy involving modulation of radiotherapeutic hyper-fractionation, temperature, radiothermy and immune-status. (author)

  13. The time dependent association of adrenaline administration and survival from out-of-hospital cardiac arrest.

    Science.gov (United States)

    Ewy, Gordon A; Bobrow, Bentley J; Chikani, Vatsal; Sanders, Arthur B; Otto, Charles W; Spaite, Daniel W; Kern, Karl B

    2015-11-01

    Recommended for decades, the therapeutic value of adrenaline (epinephrine) in the resuscitation of patients with out-of-hospital cardiac arrest (OHCA) is controversial. To investigate the possible time-dependent outcomes associated with adrenaline administration by Emergency Medical Services personnel (EMS). A retrospective analysis of prospectively collected data from a near statewide cardiac resuscitation database between 1 January 2005 and 30 November 2013. Multivariable logistic regression was used to analyze the effect of the time interval between EMS dispatch and the initial dose of adrenaline on survival. The primary endpoints were survival to hospital discharge and favourable neurologic outcome. Data from 3469 patients with witnessed OHCA were analyzed. Their mean age was 66.3 years and 69% were male. An initially shockable rhythm was present in 41.8% of patients. Based on a multivariable logistic regression model with initial adrenaline administration time interval (AATI) from EMS dispatch as the covariate, survival was greatest when adrenaline was administered very early but decreased rapidly with increasing (AATI); odds ratio 0.94 (95% Confidence Interval (CI) 0.92-0.97). The AATI had no significant effect on good neurological outcome (OR=0.96, 95% CI=0.90-1.02). In patients with OHCA, survival to hospital discharge was greater in those treated early with adrenaline by EMS especially in the subset of patients with a shockable rhythm. However survival rapidly decreased with increasing adrenaline administration time intervals (AATI). Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  14. Young patients with colorectal cancer have poor survival in the first twenty months after operation and predictable survival in the medium and long-term: Analysis of survival and prognostic markers

    Directory of Open Access Journals (Sweden)

    Wickramarachchi RE

    2010-09-01

    Full Text Available Abstract Objectives This study compares clinico-pathological features in young (50 years with colorectal cancer, survival in the young and the influence of pre-operative clinical and histological factors on survival. Materials and methods A twelve year prospective database of colorectal cancer was analysed. Fifty-three young patients were compared with forty seven consecutive older patients over fifty years old. An analysis of survival was undertaken in young patients using Kaplan Meier graphs, non parametric methods, Cox's Proportional Hazard Ratios and Weibull Hazard models. Results Young patients comprised 13.4 percent of 397 with colorectal cancer. Duration of symptoms and presentation in the young was similar to older patients (median, range; young patients; 6 months, 2 weeks to 2 years, older patients; 4 months, 4 weeks to 3 years, p > 0.05. In both groups, the majority presented without bowel obstruction (young - 81%, older - 94%. Cancer proximal to the splenic flexure was present more in young than in older patients. Synchronous cancers were found exclusively in the young. Mucinous tumours were seen in 16% of young and 4% of older patients (p Conclusion If patients, who are less than 40 years old with colorectal cancer, survive twenty months after operation, the prognosis improves and their survival becomes predictable.

  15. Structured Additive Regression Models: An R Interface to BayesX

    Directory of Open Access Journals (Sweden)

    Nikolaus Umlauf

    2015-02-01

    Full Text Available Structured additive regression (STAR models provide a flexible framework for model- ing possible nonlinear effects of covariates: They contain the well established frameworks of generalized linear models and generalized additive models as special cases but also allow a wider class of effects, e.g., for geographical or spatio-temporal data, allowing for specification of complex and realistic models. BayesX is standalone software package providing software for fitting general class of STAR models. Based on a comprehensive open-source regression toolbox written in C++, BayesX uses Bayesian inference for estimating STAR models based on Markov chain Monte Carlo simulation techniques, a mixed model representation of STAR models, or stepwise regression techniques combining penalized least squares estimation with model selection. BayesX not only covers models for responses from univariate exponential families, but also models from less-standard regression situations such as models for multi-categorical responses with either ordered or unordered categories, continuous time survival data, or continuous time multi-state models. This paper presents a new fully interactive R interface to BayesX: the R package R2BayesX. With the new package, STAR models can be conveniently specified using Rs formula language (with some extended terms, fitted using the BayesX binary, represented in R with objects of suitable classes, and finally printed/summarized/plotted. This makes BayesX much more accessible to users familiar with R and adds extensive graphics capabilities for visualizing fitted STAR models. Furthermore, R2BayesX complements the already impressive capabilities for semiparametric regression in R by a comprehensive toolbox comprising in particular more complex response types and alternative inferential procedures such as simulation-based Bayesian inference.

  16. Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.

    Science.gov (United States)

    Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H

    2014-12-30

    For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. Copyright © 2014 John Wiley & Sons

  17. Lean body mass predicts long-term survival in Chinese patients on peritoneal dialysis.

    Directory of Open Access Journals (Sweden)

    Jenq-Wen Huang

    Full Text Available BACKGROUND: Reduced lean body mass (LBM is one of the main indicators in malnutrition inflammation syndrome among patients on dialysis. However, the influence of LBM on peritoneal dialysis (PD patients' outcomes and the factors related to increasing LBM are seldom reported. METHODS: We enrolled 103 incident PD patients between 2002 and 2003, and followed them until December 2011. Clinical characteristics, PD-associated parameters, residual renal function, and serum chemistry profiles of each patient were collected at 1 month and 1 year after initiating PD. LBM was estimated using creatinine index corrected with body weight. Multiple linear regression analysis, Kaplan-Meier survival analysis, and Cox regression proportional hazard analysis were used to define independent variables and compare survival between groups. RESULTS: Using the median LBM value (70% for men and 64% for women, patients were divided into group 1 (n = 52; low LBM and group 2 (n = 51; high LBM. Group 1 patients had higher rates of peritonitis (1.6 vs. 1.1/100 patient months; p<0.05 and hospitalization (14.6 vs. 9.7/100 patient months; p<0.05. Group 1 patients also had shorter overall survival and technique survival (p<0.01. Each percentage point increase in LBM reduced the hazard ratio for mortality by 8% after adjustment for diabetes, age, sex, and body mass index (BMI. Changes in residual renal function and protein catabolic rate were independently associated with changes in LBM in the first year of PD. CONCLUSIONS: LBM serves as a good parameter in addition to BMI to predict the survival of patients on PD. Preserving residual renal function and increasing protein intake can increase LBM.

  18. Genetic variants in fanconi anemia pathway genes BRCA2 and FANCA predict melanoma survival.

    Science.gov (United States)

    Yin, Jieyun; Liu, Hongliang; Liu, Zhensheng; Wang, Li-E; Chen, Wei V; Zhu, Dakai; Amos, Christopher I; Fang, Shenying; Lee, Jeffrey E; Wei, Qingyi

    2015-02-01

    Cutaneous melanoma (CM) is the most lethal skin cancer. The Fanconi anemia (FA) pathway involved in DNA crosslink repair may affect CM susceptibility and prognosis. Using data derived from published genome-wide association study, we comprehensively analyzed the associations of 2,339 common single-nucleotide polymorphisms (SNPs) in 14 autosomal FA genes with overall survival (OS) in 858 CM patients. By performing false-positive report probability corrections and stepwise Cox proportional hazards regression analyses, we identified significant associations between CM OS and four putatively functional SNPs: BRCA2 rs10492396 (AG vs. GG: adjusted hazard ratio (adjHR)=1.85, 95% confidence interval (CI)=1.16-2.95, P=0.010), rs206118 (CC vs. TT+TC: adjHR=2.44, 95% CI=1.27-4.67, P=0.007), rs3752447 (CC vs. TT+TC: adjHR=2.10, 95% CI=1.38-3.18, P=0.0005), and FANCA rs62068372 (TT vs. CC+CT: adjHR=1.85, 95% CI=1.27-2.69, P=0.001). Moreover, patients with an increasing number of unfavorable genotypes (NUG) of these loci had markedly reduced OS and melanoma-specific survival (MSS). The final model incorporating with NUG, tumor stage, and Breslow thickness showed an improved discriminatory ability to classify both 5-year OS and 5-year MSS. Additional investigations, preferably prospective studies, are needed to validate our findings.

  19. High-volume ovarian cancer care: survival impact and disparities in access for advanced-stage disease.

    Science.gov (United States)

    Bristow, Robert E; Chang, Jenny; Ziogas, Argyrios; Randall, Leslie M; Anton-Culver, Hoda

    2014-02-01

    To characterize the impact of hospital and physician ovarian cancer case volume on survival for advanced-stage disease and investigate socio-demographic variables associated with access to high-volume providers. Consecutive patients with stage IIIC/IV epithelial ovarian cancer (1/1/96-12/31/06) were identified from the California Cancer Registry. Disease-specific survival analysis was performed using Cox-proportional hazards model. Multivariate logistic regression analyses were used to evaluate for differences in access to high-volume hospitals (HVH) (≥20 cases/year), high-volume physicians (HVP) (≥10 cases/year), and cross-tabulations of high- or low-volume hospital (LVH) and physician (LVP) according to socio-demographic variables. A total of 11,865 patients were identified. The median ovarian cancer-specific survival for all patients was 28.2 months, and on multivariate analysis the HVH/HVP provider combination (HR = 1.00) was associated with superior ovarian cancer-specific survival compared to LVH/LVP (HR = 1.31, 95%CI = 1.16-1.49). Overall, 2119 patients (17.9%) were cared for at HVHs, and 1791 patients (15.1%) were treated by HVPs. Only 4.3% of patients received care from HVH/HVP, while 53.1% of patients were treated by LVH/LVP. Both race and socio-demographic characteristics were independently associated with an increased likelihood of being cared for by the LVH/LVP combination and included: Hispanic race (OR = 1.72, 95%CI = 1.22-2.42), Asian/Pacific Islander race (OR = 1.57, 95%CI = 1.07-2.32), Medicaid insurance (OR = 2.51, 95%CI = 1.46-4.30), and low socioeconomic status (OR = 2.84, 95%CI = 1.90-4.23). Among patients with advanced-stage ovarian cancer, the provider combination of HVH/HVP is an independent predictor of improved disease-specific survival. Access to high-volume ovarian cancer providers is limited, and barriers are more pronounced for patients with low socioeconomic status, Medicaid insurance, and racial minorities. Copyright © 2013

  20. On the concept of survivability, with application to spacecraft and space-based networks

    International Nuclear Information System (INIS)

    Castet, Jean-Francois; Saleh, Joseph H.

    2012-01-01

    Survivability is an important attribute and requirement for military systems. Recently, survivability has become increasingly important for public infrastructure systems as well. In this work, we bring considerations of survivability to bear on space systems. We develop a conceptual framework and quantitative analyses based on stochastic Petri nets (SPN) to characterize and compare the survivability of different space architectures. The architectures here considered are a monolith spacecraft and a space-based network. To build the stochastic Petri net models for the degradations and failures of these two architectures, we conducted statistical analyses of historical multi-state failure data of spacecraft subsystems, and we assembled these subsystems, and their SPN models, in ways to create our monolith and networked systems. Preliminary results indicate, and quantify the extent to which, a space-based network is more survivable than the monolith spacecraft with respect to on-orbit anomalies and failures. For space systems, during the design and acquisition process, different architectures are benchmarked against several metrics; we argue that if survivability is not accounted for, then the evaluation process is likely to be biased in favor of the traditional dominant design, namely the monolith spacecraft. If however in a given context, survivability is a critical requirement for a customer, the survivability framework here proposed, and the stochastic modeling capability developed, can demonstrate the extent to which a networked space architecture may better satisfy this requirement than a monolith spacecraft. These results should be of interest to operators whose space assets require high levels of survivability, especially in the light of emerging threats.

  1. Association of sugary beverages with survival among patients with cancers of the upper aerodigestive tract

    Science.gov (United States)

    Miles, Fayth L.; Chang, Shen-Chih; Morgenstern, Hal; Tashkin, Donald; Rao, Jian-Yu; Cozen, Wendy; Mack, Thomas; Lu, Qing-Yi

    2017-01-01

    Purpose The role of consumption of added sugars in cancers of the upper aerodigestive tract (UADT) is unclear. We examined associations between sugary beverages and susceptibility to UADT cancer as well as overall survival among UADT cancer patients. Methods The association between dietary added sugar and susceptibility to UADT cancers or overall survival among 601 UADT cancer cases was evaluated using data from a population-based case–control study conducted in Los Angeles County. Unconditional logistic regression was used to estimate odds ratios and 95 % confidence intervals (CI) for cancer susceptibility, and Cox regression was used to estimate hazards ratios (HRs) with 95 % CIs for survival, adjusting for relevant confounders. Results A total of 248 deaths were observed during follow-up (median 12.1 years). A positive association was observed with consumption of grams of sugar from beverages, including soft drinks and fruit juices, and poorer survival among UADT cancer cases (aHR, Q4 vs. Q1:1.88; 95 % CI 1.29, 2.72; p for trend = 0.002), as well as servings of sugary beverages (aHR, Q4 vs. Q1: 95 % CI 1.97, 95 % CI 1.32–2.93). This was due largely to consumption of sugars from soft drinks. Particularly, high consumption of sugary beverages was associated with poorer survival among esophageal cancer cases, driven by squamous cancers. No association was observed between sugary beverages and cancer susceptibility. Conclusion These findings suggest that consumption of sugary beverages may decrease survival associated with UADT cancers. Additional studies should be conducted to examine survival among cancer patients consuming high amounts of added or refined sugars. Such studies may highlight prognostic factors for UADT cancers. PMID:27539643

  2. Genetic variants in the exon region of versican predict survival of patients with resected early-stage hepatitis B virus-associated hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Liu X

    2018-05-01

    Full Text Available Xiaoguang Liu,* Chuangye Han,* Xiwen Liao, Long Yu, Guangzhi Zhu, Hao Su, Wei Qin, Sicong Lu, Xinping Ye, Tao Peng Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China *These authors contributed equally to this work Background: The upregulated expression of versican (VCAN promotes the proliferation, invasion, and metastasis of various types of human cancer cells, including hepatocellular carcinoma (HCC cells. Patients and methods: In this study, genetic variants in the exon region of VCAN were genotyped by DNA sequencing. Prognostic values of VCAN exon single nucleotide polymorphisms (SNPs were assessed by Kaplan–Meier with the log-rank test, and uni- and multivariate Cox proportional hazard regression model. Results: A total of 111 patients with resected hepatitis B virus-associated early-stage HCC were collected for genotyping VCAN exon SNPs using Sanger DNA sequencing. Haplotype analysis was performed using Haploview 4.2. Survival data were analyzed using Kaplan–Meier curves and Cox proportional hazards regression analyses. The rs2652098, rs309559, rs188703, rs160278, and rs160277 SNPs were significantly associated with overall patient survival (p<0.001, p=0.012, p=0.010, p=0.007, and p=0.007, respectively. Patients carrying the TAGTG haplotype had a poorer prognosis than those with the most common CGAAT haplotype, after adjusting for tumor size, tumor capsule, and regional invasion (adjusted hazard ratio [HR] =2.06, 95% CI: 1.27–3.34, p=0.003. Meanwhile, patients with the TAGTG haplotype and a larger tumor size or an incomplete tumor capsule had an increased risk of death, compared with the others (adjusted HR =3.00, 95% CI: 1.67–5.36, p<0.001; and adjusted HR = 1.99, 95% CI = 1.12–3.55, p = 0.02, respectively. The online database mining analysis showed that upregulated VCAN expression in HCC tissues was associated with a poor overall

  3. Association between socioeconomic factors and ICD implantation in a publicly financed health care system

    DEFF Research Database (Denmark)

    Winther-Jensen, Matilde; Hassager, Christian; Lassen, Jens Flensted

    2017-01-01

    Aims: For patients surviving out-of-hospital cardiac arrest (OHCA) with a shockable rhythm, implantable cardioverter defibrillator (ICD) is recommended for non-reversible causes of arrest. We aimed to determine factors associated with implantation of ICD and survival in patients surviving non...... admission. Association to ICD implantation during index admission was analysed in logistic regression, survival was assessed using Cox regression. Implantable cardioverter defibrillator implantation increased during the study period [odds ratio (OR) 1-year increase: 1.04, 95% confidence intervals (95% CI...

  4. Water Properties in Cream Cheeses with Variations in pH, Fat, and Salt Content and Correlation to Microbial Survival

    DEFF Research Database (Denmark)

    Møller, Sandie M.; Hansen, Tina B.; Andersen, Simon Ulf

    2012-01-01

    and Staphylococcus aureus, and partial least-squares regression revealed that H-1 T-2 relaxation decay data were able to explain a large part of the variation in the survival of E. coli O157 (64-83%). However, the predictions of L. innocua and S. aureus survival were strongly dependent on the fat/water content...

  5. Dimethyl phenyl piperazine iodide (DMPP) induces glioma regression by inhibiting angiogenesis

    International Nuclear Information System (INIS)

    He, Yan-qing; Li, Yan; Wang, Xiao-yu; He, Xiao-dong; Jun, Li; Chuai, Manli; Lee, Kenneth Ka Ho; Wang, Ju; Wang, Li-jing; Yang, Xuesong

    2014-01-01

    1,1-Dimethyl-4-phenyl piperazine iodide (DMPP) is a synthetic nicotinic acetylcholine receptor (nAChR) agonist that could reduce airway inflammation. In this study, we demonstrated that DMPP could dramatically inhibit glioma size maintained on the chick embryonic chorioallantoic membrane (CAM). We first performed MTT and BrdU incorporation experiments on U87 glioma cells in vitro to understand the mechanism involved. We established that DMPP did not significantly affect U87 cell proliferation and survival. We speculated that DMPP directly caused the tumor to regress by affecting the vasculature in and around the implanted tumor on our chick CAM model. Hence, we conducted detailed analysis of DMPP's inhibitory effects on angiogenesis. Three vasculogenesis and angiogenesis in vivo models were used in the study which included (1) early chick blood islands formation, (2) chick yolk-sac membrane (YSW) and (3) CAM models. The results revealed that DMPP directly suppressed all developmental stages involved in vasculogenesis and angiogenesis – possibly by acting through Ang-1 and HIF-2α signaling. In sum, our results show that DMPP could induce glioma regression grown on CAM by inhibiting vasculogenesis and angiogenesis. - Highlights: ●We demonstrated that DMPP inhibited the growth of glioma cells on chick CAM. ●DMPP did not significantly affect the proliferation and survival of U87 cells. ●We revealed that DMPP suppressed vasculogenesis and angiogenesis in chick embryo. ●Angiogenesis in chick CAM was inhibited by DMPP via most probably Ang-1 and HIF-2α. ●DMPP could be potentially developed as an anti-tumor drug in the future

  6. 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.

  7. Italian regional health system structure and expected cancer survival.

    Science.gov (United States)

    Vercelli, Marina; Lillini, Roberto; Quaglia, Alberto; Capocaccia, Riccardo

    2014-01-01

    Few studies deal with the association of socioeconomic and health system resource variables with cancer survival at the Italian regional level, where the greatest number of decisions about social and health policies and resource allocations are taken. The present study aimed to describe the causal relationships between socioeconomic and health system resource factors and regional cancer survival and to compute the expected cancer survival at provincial, regional and area levels. Age-standardized relative survival at 5 years from diagnosis of cases incident in 1995-1998 and followed up to 2004 were derived by gender for 11 sites from the Italian Association of Cancer Registries data bank. The socioeconomic and health system resource variables, describing at a regional level the macro-economy, demography, labor market, and health resources for 1995-2005, came from the Health for All database. A principal components factor analysis was applied to the socioeconomic and health system resource variables. For every site, linear regression models were computed considering the relative survival at 5 years as a dependent variable and the principal components factor analysis factors as independent variables. The factors described the socioeconomic and health-related features of the regional systems and were causally related to the characteristics of the patient taken in charge. The models built by the factors allowed computation of the expected relative survival at 5 years with very good concordance with those observed at regional, macro-regional and national levels. In the regions without any cancer registry, survival was coherent with that of neighboring regions with similar socioeconomic and health system resources characteristics. The models highlighted the causal correlations between socioeconomic and health system resources and cancer survival, suggesting that they could be good evaluation tools for the efficiency of the resources allocation and use.

  8. Physics constrained nonlinear regression models for time series

    International Nuclear Information System (INIS)

    Majda, Andrew J; Harlim, John

    2013-01-01

    A central issue in contemporary science is the development of data driven statistical nonlinear dynamical models for time series of partial observations of nature or a complex physical model. It has been established recently that ad hoc quadratic multi-level regression (MLR) models can have finite-time blow up of statistical solutions and/or pathological behaviour of their invariant measure. Here a new class of physics constrained multi-level quadratic regression models are introduced, analysed and applied to build reduced stochastic models from data of nonlinear systems. These models have the advantages of incorporating memory effects in time as well as the nonlinear noise from energy conserving nonlinear interactions. The mathematical guidelines for the performance and behaviour of these physics constrained MLR models as well as filtering algorithms for their implementation are developed here. Data driven applications of these new multi-level nonlinear regression models are developed for test models involving a nonlinear oscillator with memory effects and the difficult test case of the truncated Burgers–Hopf model. These new physics constrained quadratic MLR models are proposed here as process models for Bayesian estimation through Markov chain Monte Carlo algorithms of low frequency behaviour in complex physical data. (paper)

  9. Temporal Synchronization Analysis for Improving Regression Modeling of Fecal Indicator Bacteria Levels

    Science.gov (United States)

    Multiple linear regression models are often used to predict levels of fecal indicator bacteria (FIB) in recreational swimming waters based on independent variables (IVs) such as meteorologic, hydrodynamic, and water-quality measures. The IVs used for these analyses are traditiona...

  10. IL-7 and CCL19 expression in CAR-T cells improves immune cell infiltration and CAR-T cell survival in the tumor.

    Science.gov (United States)

    Adachi, Keishi; Kano, Yosuke; Nagai, Tomohiko; Okuyama, Namiko; Sakoda, Yukimi; Tamada, Koji

    2018-04-01

    Infiltration, accumulation, and survival of chimeric antigen receptor T (CAR-T) cells in solid tumors is crucial for tumor clearance. We engineered CAR-T cells to express interleukin (IL)-7 and CCL19 (7 × 19 CAR-T cells), as these factors are essential for the maintenance of T-cell zones in lymphoid organs. In mice, 7 × 19 CAR-T cells achieved complete regression of pre-established solid tumors and prolonged mouse survival, with superior anti-tumor activity compared to conventional CAR-T cells. Histopathological analyses showed increased infiltration of dendritic cells (DC) and T cells into tumor tissues following 7 × 19 CAR-T cell therapy. Depletion of recipient T cells before 7 × 19 CAR-T cell administration dampened the therapeutic effects of 7 × 19 CAR-T cell treatment, suggesting that CAR-T cells and recipient immune cells collaborated to exert anti-tumor activity. Following treatment of mice with 7 × 19 CAR-T cells, both recipient conventional T cells and administered CAR-T cells generated memory responses against tumors.

  11. Regressão múltipla stepwise e hierárquica em Psicologia Organizacional: aplicações, problemas e soluções Stepwise and hierarchical multiple regression in organizational psychology: Applications, problemas and solutions

    Directory of Open Access Journals (Sweden)

    Gardênia Abbad

    2002-01-01

    Full Text Available Este artigo discute algumas aplicações das técnicas de análise de regressão múltipla stepwise e hierárquica, as quais são muito utilizadas em pesquisas da área de Psicologia Organizacional. São discutidas algumas estratégias de identificação e de solução de problemas relativos à ocorrência de erros do Tipo I e II e aos fenômenos de supressão, complementaridade e redundância nas equações de regressão múltipla. São apresentados alguns exemplos de pesquisas nas quais esses padrões de associação entre variáveis estiveram presentes e descritas as estratégias utilizadas pelos pesquisadores para interpretá-los. São discutidas as aplicações dessas análises no estudo de interação entre variáveis e na realização de testes para avaliação da linearidade do relacionamento entre variáveis. Finalmente, são apresentadas sugestões para lidar com as limitações das análises de regressão múltipla (stepwise e hierárquica.This article discusses applications of stepwise and hierarchical multiple regression analyses to research in organizational psychology. Strategies for identifying type I and II errors, and solutions to potential problems that may arise from such errors are proposed. In addition, phenomena such as suppression, complementarity, and redundancy are reviewed. The article presents examples of research where these phenomena occurred, and the manner in which they were explained by researchers. Some applications of multiple regression analyses to studies involving between-variable interactions are presented, along with tests used to analyze the presence of linearity among variables. Finally, some suggestions are provided for dealing with limitations implicit in multiple regression analyses (stepwise and hierarchical.

  12. Improved survival after an out-of-hospital cardiac arrest using new guidelines

    DEFF Research Database (Denmark)

    Steinmetz, Jacob; Barnung, S.; Nielsen, S.L.

    2008-01-01

    BACKGROUND: An out-of-hospital cardiac arrest (OHCA) is associated with a poor prognosis. We hypothesized that the implementations of 2005 European Resuscitation Council resuscitation guidelines were associated with improved 30-day survival after OHCA. METHODS: We prospectively recorded data on all....... Treatment after implementation was confirmed as a significant predictor of better 30-day survival in a logistic regression analysis. CONCLUSION: The implementation of new resuscitation guidelines was associated with improved 30-day survival after OHCA Udgivelsesdato: 2008/8...... patients with OHCA treated by the Mobile Emergency Care Unit of Copenhagen in two periods: 1 June 2004 until 31 August 2005 (before implementation) and 1 January 2006 until 31 March 2007 (after implementation), separated by a 4-month period in which the above-mentioned change took place. RESULTS: We found...

  13. Diabetes mellitus may affect the long-term survival of hepatitis B virus-related hepatocellular carcinoma patients after liver transplantation.

    Science.gov (United States)

    Zhang, Qing; Deng, Yong-Lin; Liu, Chang; Huang, Li-Hong; Shang, Lei; Chen, Xin-Guo; Wang, Le-Tian; Du, Jin-Zan; Wang, Ying; Wang, Pei-Xiao; Zhang, Hui; Shen, Zhong-Yang

    2016-11-21

    To determine whether diabetes mellitus (DM) affects prognosis/recurrence after liver transplantation (LT) for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). A retrospective study was conducted between January 2000 and August 2013 on 1631 patients with HBV-related HCC who underwent LT with antiviral prophylaxis. Patient data were obtained from the China Liver Transplant Registry (https://www.cltr.org/). To compare the outcomes and tumor recurrence in the HBV-related HCC patients with or without DM, statistical analyses were conducted using χ 2 tests, Mann-Whitney tests, the Kaplan-Meier method, log-rank tests and multivariate step-wise Cox regression analysis. Univariate analysis of 1631 patients who underwent LT found overall 1-, 3- and 5-year survival rates of 79%, 73% and 71% respectively in the DM patients, and 84%, 78% and 76% in the non-DM patients respectively. Overall survival rate differences after LT between the two groups were significant ( P = 0.041), but recurrence-free survival rates were not ( P = 0.096). By stratified analysis, the overall survival rates in DM patients for age > 50 years ( P = 0.002), the presence of vascular invasion ( P = 0.096), tumors ≤ 3 cm ( P = 0.047), two to three tumor nodules ( P = 0.007), Child-Pugh grade B ( P = 0.018), and pre-LT alanine aminotransferase levels between 40 and 80 IU/L ( P = 0.017) were significantly lower than in non-DM patients. Additionally, serum α-fetoprotein level > 2000 ng/mL ( P = 0.052) was associated with a significant survival difference trend between DM and non-DM patients. Multivariate analysis showed that the presence of DM ( P < 0.001, HR = 1.591; 95%CI: 1.239-2.041) was an independent predictor associated with poor survival after LT. HBV-related HCC patients with DM have decreased long-term overall survival and poor LT outcomes. Prevention strategies for HCC patients with DM are recommended.

  14. 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.

  15. Reduced in-hospital survival rates of out-of-hospital cardiac arrest victims with obstructive pulmonary disease

    DEFF Research Database (Denmark)

    Blom, M T; Warnier, M J; Bardai, A

    2013-01-01

    ) had comparable survival to ER (75% vs. 78%, OR 0.9 [95% CI: 0.6-1.3]) and to hospital admission (56% vs. 57%, OR 1.0 [0.7-1.4]). However, survival to hospital discharge was significantly lower among OPD patients (21% vs. 33%, OR 0.6 [0.4-0.9]). Multivariate regression analysis among patients who were...... with obstructive pulmonary disease (OPD) have a lower survival rate after OHCA than non-OPD patients. METHODS: We performed a community-based cohort study of 1172 patients with non-traumatic OHCA with ECG-documented VT/VF between 2005 and 2008. We compared survival to emergency room (ER), to hospital admission...... admitted to hospital (OPD: n=100, no OPD: n=561) revealed that OPD was an independent determinant of reduced 30-day survival rate (39% vs. 59%, adjusted OR 0.6 [0.4-1.0, p=0.035]). CONCLUSION: OPD-patients had lower survival rates after OHCA than non-OPD patients. Survival to ER and to hospital admission...

  16. Factors associated with survival of epiploic foramen entrapment colic: a multicentre, international study.

    Science.gov (United States)

    Archer, D C; Pinchbeck, G L; Proudman, C J

    2011-08-01

    Epiploic foramen entrapment (EFE) has been associated with reduced post operative survival compared to other types of colic but specific factors associated with reduced long-term survival of these cases have not been evaluated in a large number of horses using survival analysis. To describe post operative survival of EFE cases and to identify factors associated with long-term survival. A prospective, multicentre, international study was conducted using clinical data and long-term follow-up information for 126 horses diagnosed with EFE during exploratory laparotomy at 15 clinics in the UK, Ireland and USA. Descriptive data were generated and survival analysis performed to identify factors associated with reduced post operative survival. For the EFE cohort that recovered following anaesthesia, survival to hospital discharge was 78.5%. Survival to 1 and 2 years post operatively was 50.6 and 34.3%, respectively. The median survival time of EFE cases undergoing surgery was 397 days. Increased packed cell volume (PCV) and increased length of small intestine (SI) resected were significantly associated with increased likelihood of mortality when multivariable analysis of pre- and intraoperative variables were analysed. When all pre-, intra- and post operative variables were analysed separately, only horses that developed post operative ileus (POI) were shown to be at increased likelihood of mortality. Increased PCV, increased length of SI resected and POI are all associated with increased likelihood of mortality of EFE cases. This emphasises the importance of early diagnosis and treatment and the need for improved strategies in the management of POI in order to reduce post operative mortality in these cases. The present study provides evidence-based information to clinicians and owners of horses undergoing surgery for EFE about long-term survival. These results are applicable to university and large private clinics over a wide geographical area. © 2011 EVJ Ltd.

  17. Survival, durable tumor remission, and long-term safety in patients with advanced melanoma receiving nivolumab.

    Science.gov (United States)

    Topalian, Suzanne L; Sznol, Mario; McDermott, David F; Kluger, Harriet M; Carvajal, Richard D; Sharfman, William H; Brahmer, Julie R; Lawrence, Donald P; Atkins, Michael B; Powderly, John D; Leming, Philip D; Lipson, Evan J; Puzanov, Igor; Smith, David C; Taube, Janis M; Wigginton, Jon M; Kollia, Georgia D; Gupta, Ashok; Pardoll, Drew M; Sosman, Jeffrey A; Hodi, F Stephen

    2014-04-01

    Programmed cell death 1 (PD-1) is an inhibitory receptor expressed by activated T cells that downmodulates effector functions and limits the generation of immune memory. PD-1 blockade can mediate tumor regression in a substantial proportion of patients with melanoma, but it is not known whether this is associated with extended survival or maintenance of response after treatment is discontinued. Patients with advanced melanoma (N = 107) enrolled between 2008 and 2012 received intravenous nivolumab in an outpatient setting every 2 weeks for up to 96 weeks and were observed for overall survival, long-term safety, and response duration after treatment discontinuation. Median overall survival in nivolumab-treated patients (62% with two to five prior systemic therapies) was 16.8 months, and 1- and 2-year survival rates were 62% and 43%, respectively. Among 33 patients with objective tumor regressions (31%), the Kaplan-Meier estimated median response duration was 2 years. Seventeen patients discontinued therapy for reasons other than disease progression, and 12 (71%) of 17 maintained responses off-therapy for at least 16 weeks (range, 16 to 56+ weeks). Objective response and toxicity rates were similar to those reported previously; in an extended analysis of all 306 patients treated on this trial (including those with other cancer types), exposure-adjusted toxicity rates were not cumulative. Overall survival following nivolumab treatment in patients with advanced treatment-refractory melanoma compares favorably with that in literature studies of similar patient populations. Responses were durable and persisted after drug discontinuation. Long-term safety was acceptable. Ongoing randomized clinical trials will further assess the impact of nivolumab therapy on overall survival in patients with metastatic melanoma.

  18. SAMSN1 is highly expressed and associated with a poor survival in glioblastoma multiforme.

    Directory of Open Access Journals (Sweden)

    Yong Yan

    Full Text Available OBJECTIVES: To study the expression pattern and prognostic significance of SAMSN1 in glioma. METHODS: Affymetrix and Arrystar gene microarray data in the setting of glioma was analyzed to preliminarily study the expression pattern of SAMSN1 in glioma tissues, and Hieratical clustering of gene microarray data was performed to filter out genes that have prognostic value in malignant glioma. Survival analysis by Kaplan-Meier estimates stratified by SAMSN1 expression was then made based on the data of more than 500 GBM cases provided by The Cancer Genome Atlas (TCGA project. At last, we detected the expression of SAMSN1 in large numbers of glioma and normal brain tissue samples using Tissue Microarray (TMA. Survival analysis by Kaplan-Meier estimates in each grade of glioma was stratified by SAMSN1 expression. Multivariate survival analysis was made by Cox proportional hazards regression models in corresponding groups of glioma. RESULTS: With the expression data of SAMSN1 and 68 other genes, high-grade glioma could be classified into two groups with clearly different prognoses. Gene and large sample tissue microarrays showed high expression of SAMSN1 in glioma particularly in GBM. Survival analysis based on the TCGA GBM data matrix and TMA multi-grade glioma dataset found that SAMSN1 expression was closely related to the prognosis of GBM, either PFS or OS (P<0.05. Multivariate survival analysis with Cox proportional hazards regression models confirmed that high expression of SAMSN1 was a strong risk factor for PFS and OS of GBM patients. CONCLUSION: SAMSN1 is over-expressed in glioma as compared with that found in normal brains, especially in GBM. High expression of SAMSN1 is a significant risk factor for the progression free and overall survival of GBM.

  19. Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

    Science.gov (United States)

    Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

    2016-10-01

    In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

  20. Use of probabilistic weights to enhance linear regression myoelectric control

    Science.gov (United States)

    Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

    2015-12-01

    Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  1. Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2016-04-01

    The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

  2. Improved survival with early adjuvant chemotherapy after colonic resection for stage III colonic cancer

    DEFF Research Database (Denmark)

    Klein, Mads; Azaquoun, Najah; Jensen, Benny Vittrup

    2015-01-01

    . Data on patients with stage III colonic cancer operated between January 1, 2005 and August 31, 2012 were retrieved. Perioperative variables, surgical modality, and time to adjuvant therapy (8 weeks) were evaluated and Cox regression was performed to identify factors influencing survival...

  3. Postmastectomy Radiation Therapy Is Associated With Improved Survival in Node-Positive Male Breast Cancer: A Population Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Abrams, Matthew J., E-mail: mabrams@tuftsmedicalcenter.org [Department of Radiation Oncology, Tufts University School of Medicine, Tufts Medical Center, Boston, Massachusetts (United States); Koffer, Paul P. [Department of Radiation Oncology, Tufts University School of Medicine, Tufts Medical Center, Boston, Massachusetts (United States); Wazer, David E. [Department of Radiation Oncology, Tufts University School of Medicine, Tufts Medical Center, Boston, Massachusetts (United States); Department of Radiation Oncology, The Alpert Medical School of Brown University, Rhode Island Hospital, Providence, Rhode Island (United States); Hepel, Jaroslaw T. [Department of Radiation Oncology, The Alpert Medical School of Brown University, Rhode Island Hospital, Providence, Rhode Island (United States)

    2017-06-01

    Purpose: Because of its rarity, there are no randomized trials investigating postmastectomy radiation therapy (PMRT) in male breast cancer. This study retrospectively examines the impact of PMRT in male breast cancer patients in the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database. Methods and Materials: The SEER database 8.3.2 was queried for men ages 20+ with a diagnosis of localized or regional nonmetastatic invasive ductal/lobular carcinoma from 1998 to 2013. Included patients were treated by modified radical mastectomy (MRM), with or without adjuvant external beam radiation. Univariate and multivariate analyses evaluated predictors for PMRT use after MRM. Kaplan-Meier overall survival (OS) curves of the entire cohort and a case-matched cohort were calculated and compared by the log-rank test. Cox regression was used for multivariate survival analyses. Results: A total of 1933 patients were included in the unmatched cohort. There was no difference in 5-year OS between those who received PMRT and those who did not (78% vs 77%, respectively, P=.371); however, in the case-matched analysis, PMRT was associated with improved OS at 5 years (83% vs 54%, P<.001). On subset analysis of the unmatched cohort, PMRT was associated with improved OS in men with 1 to 3 positive nodes (5-year OS 79% vs 72% P=.05) and those with 4+ positive nodes (5-year OS 73% vs 53% P<.001). On multivariate analysis of the unmatched cohort, independent predictors for improved OS were use of PMRT: HR=0.551 (0.412-0.737) and estrogen receptor–positive disease: HR=0.577 (0.339-0.983). Predictors for a survival detriment were higher grade 3/4: HR=1.825 (1.105-3.015), larger tumor T2: HR=1.783 (1.357-2.342), T3/T4: HR=2.683 (1.809-3.978), higher N-stage: N1 HR=1.574 (1.184-2.091), N2/N3: HR=2.328 (1.684-3.218), black race: HR=1.689 (1.222-2.336), and older age 81+: HR=4.164 (1.497-11.582). Conclusions: There may be a survival benefit with the

  4. Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

    1994-01-01

    Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

  5. The Application of Classical and Neural Regression Models for the Valuation of Residential Real Estate

    Directory of Open Access Journals (Sweden)

    Mach Łukasz

    2017-06-01

    Full Text Available The research process aimed at building regression models, which helps to valuate residential real estate, is presented in the following article. Two widely used computational tools i.e. the classical multiple regression and regression models of artificial neural networks were used in order to build models. An attempt to define the utilitarian usefulness of the above-mentioned tools and comparative analysis of them is the aim of the conducted research. Data used for conducting analyses refers to the secondary transactional residential real estate market.

  6. Survival and causes of death in systemic sclerosis patients: a single center registry report from Iran.

    Science.gov (United States)

    Poormoghim, Hadi; Andalib, Elham; Jalali, Arash; Ghaderi, Afshin; Ghorbannia, Ali; Mojtabavi, Nazanin

    2016-07-01

    The aims of the study were to determine prognostic factors for survival and causes of death in a cohort of patients with systemic sclerosis (SSc). This was a cohort study of SSc patients in single rheumatologic center from January 1998 to August 2012. They fulfilled the American College of Rheumatology classification criteria for SSc or had calcinosis Raynaud's phenomenon, esophageal dysmotility, sclerodactyly, telangiectasia or sine sclerosis. Causes of death were classified as SSc related and non-SSc related. Kaplan-Meier and Cox proportional hazard regression models were used in univariate and multivariate analysis to analyse survival in subgroups and determine prognostic factors of survival. The study includes 220 patients (192 female, 28 male). Out of thirty-two (14.5 %) who died, seventeen (53.1 %) deaths were SSc related and in nine (28.1 %) non-SSc-related causes, and in six (18.8 %) of patients causes of death were not defined. Overall survival rate was 92.6 % (95 % CI 87.5-95.7 %) after 5 years and 82.3 % (95 % CI 73.4-88.4 %) after 10 years. Pulmonary involvement was a major SSc-related cause of death, occurred in seven (41.1 %) patients. Cardiovascular events were leading cause of in overall death (11) 34.3 % and 6 in non-SSc-related death. Independent risk factors for mortality were age >50 at diagnosis (HR 5.10) advance pulmonary fibrosis (HR 11.5), tendon friction rub at entry (HR 6.39), arthritis (HR 3.56). In this first Middle Eastern series of SSc registry, pulmonary and cardiac involvements were the leading cause of SSc-related death.

  7. Drawing Nomograms with R: applications to categorical outcome and survival data.

    Science.gov (United States)

    Zhang, Zhongheng; Kattan, Michael W

    2017-05-01

    Outcome prediction is a major task in clinical medicine. The standard approach to this work is to collect a variety of predictors and build a model of appropriate type. The model is a mathematical equation that connects the outcome of interest with the predictors. A new patient with given clinical characteristics can be predicted for outcome with this model. However, the equation describing the relationship between predictors and outcome is often complex and the computation requires software for practical use. There is another method called nomogram which is a graphical calculating device allowing an approximate graphical computation of a mathematical function. In this article, we describe how to draw nomograms for various outcomes with nomogram() function. Binary outcome is fit by logistic regression model and the outcome of interest is the probability of the event of interest. Ordinal outcome variable is also discussed. Survival analysis can be fit with parametric model to fully describe the distributions of survival time. Statistics such as the median survival time, survival probability up to a specific time point are taken as the outcome of interest.

  8. Increasing maternal healthcare use in Rwanda: implications for child nutrition and survival.

    Science.gov (United States)

    Pierce, Hayley; Heaton, Tim B; Hoffmann, John

    2014-04-01

    Rwanda has made great progress in improving maternal utilization of health care through coordination of external aid and more efficient health policy. Using data from the 2005 and 2010 Rwandan Demographic and Health Surveys, we examine three related questions regarding the impact of expansion of health care in Rwanda. First, did the increased use of health center deliveries apply to women across varying levels of education, economic status, and area of residency? Second, did the benefits associated with being delivered at a health center diminish as utilization became more widespread? Finally, did inequality in child outcomes decline as a result of increased health care utilization? Propensity score matching was used to address the selectivity that arises when choosing to deliver at a hospital. In addition, the regression models include a linear model to predict child nutritional status and Cox regression to predict child survival. The analysis shows that the largest increases in delivery at a health center occur among less educated, less wealthy, and rural Rwandan women. In addition, delivery at a health center is associated with better nutritional status and survival and the benefit is not diminished following the dramatic increase in use of health centers. Finally, educational, economic and residential inequality in child survival and nutrition did not decline. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Tax System in Poland – Progressive or Regressive?

    Directory of Open Access Journals (Sweden)

    Jacek Tomkiewicz

    2016-03-01

    Full Text Available Purpose: To analyse the impact of the Polish fiscal regime on the general revenue of the country, and specifically to establish whether the cumulative tax burden borne by Polish households is progressive or regressive.Methodology: On the basis of Eurostat and OECD data, the author has analysed fiscal regimes in EU Member States and in OECD countries. The tax burden of households within different income groups has also been examined pursuant to applicable fiscal laws and data pertaining to the revenue and expenditure of households published by the Central Statistical Office (CSO.Conclusions: The fiscal regime in Poland is regressive; that is, the relative fiscal burden decreases as the taxpayer’s income increases.Research Implications: The article contributes to the on-going discussion on social cohesion, in particular with respect to economic policy instruments aimed at the redistribution of income within the economy.Originality: The author presents an analysis of data pertaining to fiscal policies in EU Member States and OECD countries and assesses the impact of the legal environment (fiscal regime and social security system in Poland on income distribution within the economy. The impact of the total tax burden (direct and indirect taxes, social security contributions on the economic situation of households from different income groups has been calculated using an original formula.

  10. Factors affecting the survival of the “at risk” newborn at Korle Bu ...

    African Journals Online (AJOL)

    The type of delivery other than the spontaneous vaginal route also affects the outcome, though the relationship was not statistically significant. Logistic regression analysis showed that maturity, birthweight and time from birth to admission to NICU were the most significant factors associated with the survival of the neonate.

  11. Equity and child-survival strategies.

    Science.gov (United States)

    Mulholland, Ek; Smith, L; Carneiro, I; Becher, H; Lehmann, D

    2008-05-01

    Recent advances in child survival have often been at the expense of increasing inequity. Successive interventions are applied to the same population sectors, while the same children in other sectors consistently miss out, leading to a trend towards increasing inequity in child survival. This is particularly important in the case of pneumonia, the leading cause of child death, which is closely linked to poverty and malnutrition, and for which effective community-based case management is more difficult to achieve than for other causes of child death. The key strategies for the prevention of childhood pneumonia are case management, mainly through Integrated Management of Childhood Illness (IMCI), and immunization, particularly the newer vaccines against Haemophilus influenzae type b (Hib) and pneumococcus. There is a tendency to introduce both interventions into communities that already have access to basic health care and preventive services, thereby increasing the relative disadvantage experienced by those children without such access. Both strategies can be implemented in such a way as to decrease rather than increase inequity. It is important to monitor equity when introducing child-survival interventions. Economic poverty, as measured by analyses based on wealth quintiles, is an important determinant of inequity in health outcomes but in some settings other factors may be of greater importance. Geography and ethnicity can both lead to failed access to health care, and therefore inequity in child survival. Poorly functioning health facilities are also of major importance. Countries need to be aware of the main determinants of inequity in their communities so that measures can be taken to ensure that IMCI, new vaccine implementation and other child-survival strategies are introduced in an equitable manner.

  12. Prognostic and survival analysis of 837 Chinese colorectal cancer patients.

    Science.gov (United States)

    Yuan, Ying; Li, Mo-Dan; Hu, Han-Guang; Dong, Cai-Xia; Chen, Jia-Qi; Li, Xiao-Fen; Li, Jing-Jing; Shen, Hong

    2013-05-07

    To develop a prognostic model to predict survival of patients with colorectal cancer (CRC). Survival data of 837 CRC patients undergoing surgery between 1996 and 2006 were collected and analyzed by univariate analysis and Cox proportional hazard regression model to reveal the prognostic factors for CRC. All data were recorded using a standard data form and analyzed using SPSS version 18.0 (SPSS, Chicago, IL, United States). Survival curves were calculated by the Kaplan-Meier method. The log rank test was used to assess differences in survival. Univariate hazard ratios and significant and independent predictors of disease-specific survival and were identified by Cox proportional hazard analysis. The stepwise procedure was set to a threshold of 0.05. Statistical significance was defined as P analysis suggested age, preoperative obstruction, serum carcinoembryonic antigen level at diagnosis, status of resection, tumor size, histological grade, pathological type, lymphovascular invasion, invasion of adjacent organs, and tumor node metastasis (TNM) staging were positive prognostic factors (P analysis showed a significant statistical difference in 3-year survival among these groups: LNR1, 73%; LNR2, 55%; and LNR3, 42% (P analysis results showed that histological grade, depth of bowel wall invasion, and number of metastatic lymph nodes were the most important prognostic factors for CRC if we did not consider the interaction of the TNM staging system (P < 0.05). When the TNM staging was taken into account, histological grade lost its statistical significance, while the specific TNM staging system showed a statistically significant difference (P < 0.0001). The overall survival of CRC patients has improved between 1996 and 2006. LNR is a powerful factor for estimating the survival of stage III CRC patients.

  13. The non-condition logistic regression analysis of the reason of hypothyroidism after hyperthyroidism with 131I treatment

    International Nuclear Information System (INIS)

    Dang Yaping; Hu Guoying; Meng Xianwen

    1994-01-01

    There are many opinions on the reason of hypothyroidism after hyperthyroidism with 131 I treatment. In this respect, there are a few scientific analyses and reports. The non-condition logistic regression solved this problem successfully. It has a higher scientific value and confidence in the risk factor analysis. 748 follow-up patients' data were analysed by the non-condition logistic regression. The results shown that the half-life and 131 I dose were the main causes of the incidence of hypothyroidism. The degree of confidence is 92.4%

  14. Survival analysis of heart failure patients: A case study.

    Directory of Open Access Journals (Sweden)

    Tanvir Ahmad

    Full Text Available This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015. All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

  15. Spatial regression analysis on 32 years of total column ozone data

    NARCIS (Netherlands)

    Knibbe, J.S.; van der A, J.R.; de Laat, A.T.J.

    2014-01-01

    Multiple-regression analyses have been performed on 32 years of total ozone column data that was spatially gridded with a 1 × 1.5° resolution. The total ozone data consist of the MSR (Multi Sensor Reanalysis; 1979-2008) and 2 years of assimilated SCIAMACHY (SCanning Imaging Absorption spectroMeter

  16. Influence of conformal radiotherapy technique on survival after chemoradiotherapy for patients with stage III non-small cell lung cancer in the National Cancer Data Base.

    Science.gov (United States)

    Sher, David J; Koshy, Matthew; Liptay, Michael J; Fidler, Mary Jo

    2014-07-01

    Definitive chemoradiotherapy is a core treatment modality for patients with stage III non-small cell lung cancer (NSCLC). Although radiotherapy (RT) technologies have advanced dramatically, to the authors' knowledge relatively little is known regarding the importance of irradiation technique on outcome, particularly given the competing risk of distant metastasis. The National Cancer Data Base was used to determine predictors of overall survival (OS) in patients with AJCC stage III NSCLC who were treated with chemoradiotherapy, focusing on the importance of conformal RT (CRT). Patients with stage III NSCLC who were treated with chemoradiotherapy between 2003 and 2005 in the National Cancer Data Base were included. RT technique was defined as conventional, 3-dimensional-conformal, or intensity-modulated RT (IMRT), the latter 2 combined as CRT. Cox proportional hazards regression was performed for univariable and multivariable analyses of OS. The median, 3-year, and 5-year survival outcomes for the 13,292 patients were 12.9 months, 19%, and 11%, respectively. The 3-year and 5-year survival probabilities of patients receiving CRT versus no CRT were 22% versus 19% and 14% versus 11%, respectively (P < .0001). On multivariable analysis, CRT was found to be significantly associated with improved OS (hazards ratio, 0.89). This effect was confirmed on sensitivity analyses, including restricting the cohort to minimum 6-month survivors, young patients with stage IIIA disease, and propensity score-matching. Institutional academic status and patient volume were not found to be associated with OS. CRT was found to be independently associated with a survival advantage. These results reflect the importance of optimal locoregional therapy in patients with stage III NSCLC and provide motivation for further study of advanced RT technologies in patients with NSCLC. © 2014 American Cancer Society.

  17. Economic Analyses of Ware Yam Production in Orlu Agricultural ...

    African Journals Online (AJOL)

    Economic Analyses of Ware Yam Production in Orlu Agricultural Zone of Imo State. ... International Journal of Agriculture and Rural Development ... statistics, gross margin analysis, marginal analysis and multiple regression analysis. Results ...

  18. Body Composition and Survival in Dialysis Patients: Results from an International Cohort Study

    Science.gov (United States)

    Usvyat, Len A.; Kotanko, Peter; Bayh, Inga; Canaud, Bernard; Etter, Michael; Gatti, Emanuele; Grassmann, Aileen; Wang, Yuedong; Marelli, Cristina; Scatizzi, Laura; Stopper, Andrea; van der Sande, Frank M.; Kooman, Jeroen

    2015-01-01

    Background and objectives High body mass index appears protective in hemodialysis patients, but uncertainty prevails regarding which components of body composition, fat or lean body mass, are primarily associated with survival. Design, setting, participants, & measurements Data between April 2006 and December 2012 were extracted from the Fresenius Medical Care Europe subset of the international MONitoring Dialysis Outcomes initiative. Fresenius Medical Care Europe archives a unique repository of predialysis body composition measurements determined by multifrequency bioimpedance (BCM Body Composition Monitor). The BCM Body Composition Monitor reports lean tissue indices (LTIs) and fat tissue indices (FTIs), which are the respective tissue masses normalized to height squared, relative to an age- and sex-matched healthy population. The relationship between LTI and FTI and all-cause mortality was studied by Kaplan–Meier analysis, multivariate Cox regression, and smoothing spline ANOVA logistic regression. Results In 37,345 hemodialysis patients, median (25th–75th percentile) LTI and FTI were 12.2 (10.3–14.5) and 9.8 (6.6–12.4) kg/m2, respectively. Median (25th–75th percentile) follow-up time was 266 (132–379) days; 3458 (9.2%) patients died during follow-up. Mortality was lowest with both LTI and FTI in the 10th–90th percentile (reference group) and significantly higher at the lower LTI and FTI extreme (hazard ratio [HR], 3.37; 95% confidence interval [95% CI], 2.94 to 3.87; P<0.001). Survival was best with LTI between 15 and 20 kg/m2 and FTI between 4 and 15 kg/m2 (probability of death during follow-up: <5%). When taking the relation between both compartments into account, the interaction was significant (P=0.01). Higher FTI appeared protective in patients with low LTI (HR, 3.37; 95% CI, 2.94 to 3.87; P<0.001 at low LTI–low FTI, decreasing to HR, 1.79; 95% CI, 1.47 to 2.17; P<0.001 at low LTI–high FTI). Conclusions This large international study

  19. Expression of Aurora-B and FOXM1 predict poor survival in patients with nasopharyngeal carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Pei-Yu; Luo, Dong-Hua; Mai, Hai-Qiang [State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou (China); Sun Yat-sen University Cancer Center, Department of Nasopharyngeal Carcinoma, Guangzhou (China); Li, Yan; Zeng, Ting-Ting; Li, Meng-Qing [State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou (China); Hou, Xue; Zhang, Li [State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou (China); Sun Yat-sen University Cancer Center, Department of Medical Oncology, Guangzhou (China)

    2015-08-15

    The purpose of this work was to investigate the relationship between Aurora-B, FOXM1, and clinical outcomes in patients with nasopharyngeal carcinoma (NPC) who were treated with a combination of induction chemotherapy and radiotherapy. The expression of Aurora-B and FOXM1 were investigated by immunohistochemistry using a tissue microarray (TMA) containing samples from 166 NPC patients who were treated with cisplatin (DDP) + fluorouracil (5-FU) induction chemotherapy and radiotherapy between 1999 and 2005. The relationship of Aurora-B, FOXM1, and survival of these NPC patients was analyzed. Informative TMA results were obtained in 91 tumor cases for Aurora-B and 93 tumor cases for FOXM1. The 8-year failure-free survival rate (FFS) for the Aurora-B-negative and Aurora-B-positive group was 65.6 and 37.3 %, respectively (p = 0.024), and the 8-year distant FFS (D-FFS) rate was 65.6 and 41.5 %, respectively (p = 0.047). The 8-year overall survival (OS) in the FOXM1-negative group was moderately higher than in the FOXM1-positive group (58.4 vs 39.1 %, p = 0.081). Cox regression analysis revealed that for FFS, Aurora-B expression was a significant prognostic factor (p = 0.025), while for D-FFS, Aurora-B expression was a marginally significant prognostic factor (p = 0.056). When FOXM1 expression was analyzed, the Cox regression analyses showed that FOXM1 expression was a marginally significant prognostic factor (p = 0.056) for OS. Correlation analysis showed that Aurora-B and FOXM1 expression had no significant correlation. Aurora-B and FOXM1 were both adverse prognostic markers for NPC patients treated with chemoradiotherapy. However, the two markers had no significant correlation. (orig.) [German] Ziel war die Untersuchung der Beziehung zwischen Aurora-B, FOXM1 und den klinischen Ergebnissen bei Patienten mit nasopharyngealem Karzinom (NPC), die mit einer Kombinationstherapie aus Induktionschemotherapie und Radiotherapie behandelt wurden. Die Expression von Aurora-B und

  20. Quantile regression for the statistical analysis of immunological data with many non-detects.

    Science.gov (United States)

    Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

    2012-07-07

    Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

  1. Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

    Science.gov (United States)

    Shafiq, M. Najeeb

    2013-01-01

    Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

  2. Determinants of Survival in Low Birth Weight Infants at a Tertiary Healthcare Facility in the South Eastern Nigeria

    Directory of Open Access Journals (Sweden)

    Ekwochi U

    2017-06-01

    Full Text Available Low birth weight (LBW babies account for a large number of neonatal deaths globally, with over 90% of these occurring in developing countries with low resources. Identifying factors that determine survival in these sub-groups of babies in such a low-resource setting will help clinicians prioritize care and improve outcomes. This study aims to bridge some knowledge gaps in this regard. This was a 45-month prospective study carried out at the Enugu State University Teaching Hospital (ESUTH, Enugu, Nigeria. All eligible newborns weighing between 500g and and lt;2500g that were seen in this period were enrolled and monitored. Data collected were analysed with SPSS Version 24, and significant associations identified using logistic regression models. A total of 166 LBW neonates were enrolled, and 68.2% of them survived. Asphyxia and episodes recurrent apnoea were recorded at least once in 78.8% and 68.4% of the babies respectively, with about two-thirds requiring respiratory support at one time or the other. Survival in these LBW newborns was negatively associated with gestational age at birth of less than 32 weeks (OR 0.17; CI 0.03-0.50; P and lt;0.01 as well as with episodes of recurrent apnoea (OR 0.07; CI 0.02-0.34; P and lt;0.01. However, intra-uterine exposure to malaria was associated with a 15 times higher likelihood of survival (OR 15.41; CI 2.22-106.91; P=0.01. No significant associations was found between survival and attendances to antenatal care, mode of delivery, birth weight and a number of neonatal morbidities like necrotizing enterocolitis, hypothermia, hypoglycaemia, septicaemia, anaemia and neonatal jaundice. Survival rate among low birth weight neonates in a low resource setting is decreased with delivery at less than 32 weeks completed gestation as well as recurrent episodes of apnoea, but is increased with in-utero exposure to malaria.

  3. Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

    Science.gov (United States)

    Cui, Jing; Zhou, Lingjun; Wee, B; Shen, Fengping; Ma, Xiuqiang; Zhao, Jijun

    2014-05-01

    Accurate prediction of prognosis for cancer patients is important for good clinical decision making in therapeutic and care strategies. The application of prognostic tools and indicators could improve prediction accuracy. This study aimed to develop a new prognostic scale to predict survival time of advanced cancer patients in China. We prospectively collected items that we anticipated might influence survival time of advanced cancer patients. Participants were recruited from 12 hospitals in Shanghai, China. We collected data including demographic information, clinical symptoms and signs, and biochemical test results. Log-rank tests, Cox regression, and linear regression were performed to develop a prognostic scale. Three hundred twenty patients with advanced cancer were recruited. Fourteen prognostic factors were included in the prognostic scale: Karnofsky Performance Scale (KPS) score, pain, ascites, hydrothorax, edema, delirium, cachexia, white blood cell (WBC) count, hemoglobin, sodium, total bilirubin, direct bilirubin, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) values. The score was calculated by summing the partial scores, ranging from 0 to 30. When using the cutoff points of 7-day, 30-day, 90-day, and 180-day survival time, the scores were calculated as 12, 10, 8, and 6, respectively. We propose a new prognostic scale including KPS, pain, ascites, hydrothorax, edema, delirium, cachexia, WBC count, hemoglobin, sodium, total bilirubin, direct bilirubin, AST, and ALP values, which may help guide physicians in predicting the likely survival time of cancer patients more accurately. More studies are needed to validate this scale in the future.

  4. Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

    International Nuclear Information System (INIS)

    Garzon, Benjamin; Emblem, Kyrre E.; Mouridsen, Kim; Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K.; Bjoernerud, Atle; Haaberg, Asta K.; Kvinnsland, Yngve

    2011-01-01

    Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

  5. Adjuvant chemotherapy is associated with improved survival in patients with stage II colon cancer.

    Science.gov (United States)

    Casadaban, Leigh; Rauscher, Garth; Aklilu, Mebea; Villenes, Dana; Freels, Sally; Maker, Ajay V

    2016-11-15

    The role of adjuvant chemotherapy in patients with stage II colon cancer remains to be elucidated and its use varies between patients and institutions. Currently, clinical guidelines suggest discussing adjuvant chemotherapy for patients with high-risk stage II disease in the absence of conclusive randomized controlled trial data. To further investigate this relationship, the objective of the current study was to determine whether an association exists between overall survival (OS) and adjuvant chemotherapy in patients stratified by age and pathological risk features. Data from the National Cancer Data Base were analyzed for demographics, tumor characteristics, management, and survival of patients with stage II colon cancer who were diagnosed from 1998 to 2006 with survival information through 2011. Pearson Chi-square tests and binary logistic regression were used to analyze disease and demographic data. Survival analysis was performed with the log-rank test and Cox proportional hazards regression modeling. Propensity score weighting was used to match cohorts. Among 153,110 patients with stage II colon cancer, predictors of receiving chemotherapy included age clinically relevant OS was associated with the receipt of adjuvant chemotherapy in all patient subgroups regardless of high-risk tumor pathologic features (poor or undifferentiated histology, colon cancer evaluated to date, improved OS was found to be associated with adjuvant chemotherapy regardless of treatment regimen, patient age, or high-risk pathologic risk features. Cancer 2016;122:3277-3287. © 2016 American Cancer Society. © 2016 American Cancer Society.

  6. Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

    Energy Technology Data Exchange (ETDEWEB)

    Garzon, Benjamin (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway)), email: benjamin.garzon@ntnu.no; Emblem, Kyrre E. (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway); Dept. of Radiology, MGH-HST AA Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States)); Mouridsen, Kim (Center of Functionally Integrative Neuroscience, Aarhus Univ., Aarhus (Denmark)); Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K. (Dept. of Radiology and Nuclear Medicine, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Bjoernerud, Atle (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Haaberg, Asta K. (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway); Dept. of Medical Imaging, St Olav' s Hospital, Trondheim (Norway)); Kvinnsland, Yngve (NordicImagingLab, Bergen (Norway))

    2011-11-15

    Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

  7. Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

    Science.gov (United States)

    Wilson, Martin; Cummins, Carole L; Macpherson, Lesley; Sun, Yu; Natarajan, Kal; Grundy, Richard G; Arvanitis, Theodoros N; Kauppinen, Risto A; Peet, Andrew C

    2013-01-01

    Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. (1)H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Short echo time (30ms) single voxel (1)H MRS was performed on children attending Birmingham Children's Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (pmodel of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p5e-5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

    Science.gov (United States)

    Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

    2018-02-01

    1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

  9. Association Among Blood Transfusion, Sepsis, and Decreased Long-term Survival After Colon Cancer Resection.

    Science.gov (United States)

    Aquina, Christopher T; Blumberg, Neil; Becerra, Adan Z; Boscoe, Francis P; Schymura, Maria J; Noyes, Katia; Monson, John R T; Fleming, Fergal J

    2017-08-01

    To investigate the potential additive effects of blood transfusion and sepsis on colon cancer disease-specific survival, cardiovascular disease-specific survival, and overall survival after colon cancer surgery. Perioperative blood transfusions are associated with infectious complications and increased risk of cancer recurrence through systemic inflammatory effects. Furthermore, recent studies have suggested an association among sepsis, subsequent systemic inflammation, and adverse cardiovascular outcomes. However, no study has investigated the association among transfusion, sepsis, and disease-specific survival in postoperative patients. The New York State Cancer Registry and Statewide Planning and Research Cooperative System were queried for stage I to III colon cancer resections from 2004 to 2011. Propensity-adjusted survival analyses assessed the association of perioperative allogeneic blood transfusion, sepsis, and 5-year colon cancer disease-specific survival, cardiovascular disease-specific survival, and overall survival. Among 24,230 patients, 29% received a transfusion and 4% developed sepsis. After risk adjustment, transfusion and sepsis were associated with worse colon cancer disease-specific survival [(+)transfusion: hazard ratio (HR) 1.19, 95% confidence interval (CI) 1.09-1.30; (+)sepsis: HR 1.84, 95% CI 1.44-2.35; (+)transfusion/(+)sepsis: HR 2.27, 95% CI 1.87-2.76], cardiovascular disease-specific survival [(+)transfusion: HR 1.18, 95% CI 1.04-1.33; (+)sepsis: HR 1.63, 95% CI 1.14-2.31; (+)transfusion/(+)sepsis: HR 2.04, 95% CI 1.58-2.63], and overall survival [(+)transfusion: HR 1.21, 95% CI 1.14-1.29; (+)sepsis: HR 1.76, 95% CI 1.48-2.09; (+)transfusion/(+)sepsis: HR 2.36, 95% CI 2.07-2.68] relative to (-)transfusion/(-)sepsis. Additional analyses suggested an additive effect with those who both received a blood transfusion and developed sepsis having even worse survival. Perioperative blood transfusions are associated with shorter survival

  10. Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci

    DEFF Research Database (Denmark)

    Glubb, Dylan M; Johnatty, Sharon E; Quinn, Michael C J

    2017-01-01

    We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that MEF2D...... and ZNF100 are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the ZNF100 promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced MEF2D promoter activity...... and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, MEF2D and ZNF100 expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates...

  11. Logistic Regression in the Identification of Hazards in Construction

    Science.gov (United States)

    Drozd, Wojciech

    2017-10-01

    The construction site and its elements create circumstances that are conducive to the formation of risks to safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This article attempts to analyse the characteristics related to the construction site, in order to indicate their importance in defining the circumstances of accidents at work. The study includes sites inspected in 2014 - 2016 by the employees of the District Labour Inspectorate in Krakow (Poland). The analysed set of detailed (disaggregated) data includes both quantitative and qualitative characteristics. The substantive task focused on classification modelling in the identification of hazards in construction and identifying those of the analysed characteristics that are important in an accident. In terms of methodology, resource data analysis using statistical classifiers, in the form of logistic regression, was the method used.

  12. Hydronephrosis in patients with cervical cancer: an assessment of morbidity and survival.

    Science.gov (United States)

    Patel, Krishna; Foster, Nathan R; Kumar, Amanika; Grudem, Megan; Longenbach, Sherri; Bakkum-Gamez, Jamie; Haddock, Michael; Dowdy, Sean; Jatoi, Aminah

    2015-05-01

    Hydronephrosis is a frequently observed but understudied complication in patients with cervical cancer. To better characterize hydronephrosis in cervical cancer patients, the current study sought (1) to describe hydronephrosis-associated morbidity and (2) to analyze the prognostic effect of hydronephrosis in patients with a broad range of cancer stages over time. The Mayo Clinic Tumor Registry was interrogated for all invasive cervical cancer patients seen at the Mayo Clinic from 2008 through 2013 in Rochester, Minnesota; these patients' medical records were then reviewed in detail. Two hundred seventy-nine cervical cancer patients with a median age of 49 years and a range of cancer stages were included. Sixty-five patients (23 %) were diagnosed with hydronephrosis at some point during their disease course. In univariate analyses, hydronephrosis was associated with advanced cancer stage (p hydronephrosis. All but one patient underwent stent placement or urinary diversion; hydronephrosis-related morbidity included pain, urinary tract infections, nausea and vomiting, renal failure, and urinary tract bleeding. In landmark univariate survival analyses, hydronephrosis was associated with worse survival at all time points. In landmark multivariate analyses (adjusted for patient age, stage, cancer treatment, and tumor histology), hydronephrosis was associated with a trend toward worse survival over time (hazard ratios ranged from 1.47 to 4.69). Hydronephrosis in cervical cancer patients is associated with notable morbidity. It is also associated with trends toward worse survival-even if it occurs after the original cancer diagnosis.

  13. Progression-free survival/time to progression as a potential surrogate for overall survival in HR+, HER2– metastatic breast cancer

    Directory of Open Access Journals (Sweden)

    Forsythe A

    2018-05-01

    Full Text Available Anna Forsythe,1 David Chandiwana,2 Janina Barth,3 Marroon Thabane,4 Johan Baeck,2 Gabriel Tremblay1 1Purple Squirrel Economics, New York, NY, 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 3Novartis Pharma GmbH, Nuremberg, Germany; 4Novartis Pharmaceuticals Incorporated, Dorval, QC, Canada Background: Several recent randomized controlled trials (RCTs in hormone receptor-positive (HR+, human epidermal growth factor receptor 2-negative (HER2– metastatic breast cancer (MBC have demonstrated significant improvements in progression-free survival (PFS; however, few have reported improvement in overall survival (OS. The surrogacy of PFS or time to progression (TTP for OS has not been formally investigated in HR+, HER2– MBC.Methods: A systematic literature review of RCTs in HR+, HER2– MBC was conducted to identify studies that reported both median PFS/TTP and OS. The correlation between PFS/TTP and OS was evaluated using Pearson’s product–moment correlation and Spearman’s rank correlation. Subgroup analyses were performed to explore possible reasons for heterogeneity. Errors-in-variables weighted least squares regression (LSR was used to model incremental OS months as a function of incremental PFS/TTP months. An exploratory analysis investigated the impact of three covariates (chemotherapy vs hormonal/targeted therapy, PFS vs TTP, and first-line therapy vs second-line therapy or greater on OS prediction. The lower 95% prediction band was used to determine the minimum incremental PFS/TTP months required to predict OS benefit (surrogate threshold effect [STE].Results: Forty studies were identified. There was a statistically significant correlation between median PFS/TTP and OS (Pearson =0.741, P=0.000; Spearman =0.650, P=0.000. These results proved consistent for chemotherapy and hormonal/targeted therapy. Univariate LSR analysis yielded an R2 of 0.354 with 1 incremental PFS/TTP month corresponding to 1.13 incremental OS months

  14. A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

    Science.gov (United States)

    Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

    2017-06-01

    Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

  15. Use of multiple linear regression and logistic regression models to investigate changes in birthweight for term singleton infants in Scotland.

    Science.gov (United States)

    Bonellie, Sandra R

    2012-10-01

    To illustrate the use of regression and logistic regression models to investigate changes over time in size of babies particularly in relation to social deprivation, age of the mother and smoking. Mean birthweight has been found to be increasing in many countries in recent years, but there are still a group of babies who are born with low birthweights. Population-based retrospective cohort study. Multiple linear regression and logistic regression models are used to analyse data on term 'singleton births' from Scottish hospitals between 1994-2003. Mothers who smoke are shown to give birth to lighter babies on average, a difference of approximately 0.57 Standard deviations lower (95% confidence interval. 0.55-0.58) when adjusted for sex and parity. These mothers are also more likely to have babies that are low birthweight (odds ratio 3.46, 95% confidence interval 3.30-3.63) compared with non-smokers. Low birthweight is 30% more likely where the mother lives in the most deprived areas compared with the least deprived, (odds ratio 1.30, 95% confidence interval 1.21-1.40). Smoking during pregnancy is shown to have a detrimental effect on the size of infants at birth. This effect explains some, though not all, of the observed socioeconomic birthweight. It also explains much of the observed birthweight differences by the age of the mother.   Identifying mothers at greater risk of having a low birthweight baby as important implications for the care and advice this group receives. © 2012 Blackwell Publishing Ltd.

  16. [Survival of Overweight Patients After Coronary Artery Bypass Surgery. Does the Obesity Paradox Play a Role?

    Science.gov (United States)

    Efros, L A; Samorodskaya, I V

    2015-07-01

    Although excessive body mass and obesity are considered risk factors of a number of diseases and conditions numerous results of studies evidence for the existence of the "obesity paradox" - higher long-term survival of overweight and obese patients. Aim of this study was to elucidate impact of body mass index (BMI) on postoperative mortality and long-term survival of patients after coronary artery bypass grafting (CABG). The study was conducted on the basis of register of patients with ischemic heart disease who had undergone CABG with or without correction of valvular defects and/or resection of left ventricular (LV) aneurism during the period from 2000 to 2009 in the Chelyabinsk Interregional Cardiosurgical Center. Duration of follow-up was 1 to 10 years (mean - 2.3+/-2.4 years). The patients were divided into groups in dependence on BMI. Multifactorial logistic regression analysis of association of BMI and hospital mortality was carried out with adjustment for age, sex, arterial pressure, presence of diabetes mellitus (DM), chronic obstructive pulmonary disease, LV aneurism, LV ejection fraction, and character of involvement of vessels. Long term survival was studied using Coxs regression model. Compared with group of patients with normal BMI DM and arterial hypertension were more often registered among patients with excessive body mass and obesity. Elevated body mass was not an independent factor of risk of postoperative and lower long-term survival. There was a tendency to lower survival among patients with BMI >35 rg/m2. Results of this study evidence for the absence of proof of negative impact of excessive BMI on hospital mortality and long term survival.

  17. [Survival of Overweight Patients After Coronary Artery Bypass Surgery. Does the "Obesity Paradox" Play a Role?].

    Science.gov (United States)

    Efros, L A; Samorodskaya, I V

    2015-01-01

    Although excessive body mass and obesity are considered risk factors of a number of diseases and conditions numerous results of studies evidence for the existence of the "obesity paradox"--higher long-term survival of overweight and obese patients. Aim of this study was to elucidate impact of body mass index (BMI) on postoperative mortality and long-term survival of patients after coronary artery bypass grafting (CABG). The study was conducted on the basis of register of patients with ischemic heart disease who had undergone CABG with or without correction of valvular defects and/or resection of left ventricular (LV) aneurism during the period from 2000 to 2009 in the Chelyabinsk Interregional Cardiosurgical Center. Duration of follow-up was 1 to 10 years (mean--2.3 ± 2.4 years). The patients were divided into groups in dependence on BMI. Multifactorial logistic regression analysis of association of BMI and hospital mortality was carried out with adjustment for age, sex, arterial pressure, presence of diabetes mellitus (DM), chronic obstructive pulmonary disease, LV aneurism, LV ejection fraction, and character of involvement of vessels. Long term survival was studied using Cox's regression model. Compared with group of patients with normal BMI DM and arterial hypertension were more often registered among patients with excessive body mass and obesity. Elevated body mass was not an independent factor of risk of postoperative and lower long-term survival. There was a tendency to lower survival among patients with BMI > 35 rg/m2. Results of this study evidence for the absence of proof of negative impact of excessive BMI on hospital mortality and long term survival.

  18. Time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

    2008-01-01

    and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

  19. Intratumoral heterogeneity of 18F-FLT uptake predicts proliferation and survival in patients with newly diagnosed gliomas

    International Nuclear Information System (INIS)

    Mitamura, Katsuya; Yamamoto, Yuka; Kudomi, Nobuyuki; Norikane, Takashi; Miyake, Keisuke; Nishiyama, Yoshihiro; Maeda, Yukito

    2017-01-01

    The nucleoside analog 3'-deoxy-3'- 18 F-fluorothymidine (FLT) has been investigated for evaluating tumor proliferating activity in brain tumors. We evaluated FLT uptake heterogeneity using textural features from the histogram analysis in patients with newly diagnosed gliomas and examined correlation of the results with proliferative activity and patient prognosis, in comparison with the conventional PET parameters. FLT PET was investigated in 37 patients with newly diagnosed gliomas. The conventional parameters [tumor-to-contralateral normal brain tissue (T/N) ratio and metabolic tumor volume (MTV)] and textural parameters (standard deviation, skewness, kurtosis, entropy, and uniformity) were derived from FLT PET images. Linear regression analysis was used to compare PET parameters and the proliferative activity as indicated by the Ki-67 index. The associations between parameters and overall survival (OS) were tested by Cox regression analysis. Median OS was 662 days. For the conventional parameters, linear regression analysis indicated a significant correlation between T/N ratio and Ki-67 index (p = 0.02) and MTV and Ki-67 index (p = 0.02). Among textural parameters, linear regression analysis indicated a significant correlation for kurtosis (p = 0.003), entropy (p < 0.001), and uniformity (p < 0.001) as compared to Ki-67 index, exceeding those of the conventional parameters. The results of univariate analysis suggested that skewness and kurtosis were associated with OS (p = 0.03 and 0.02, respectively). Mean survival for patients with skewness values less than 0.65 was 1462 days, compared with 917 days for those with values greater than 0.65 (p = 0.02). Mean survival for patients with kurtosis values less than 6.16 was 1616 days, compared with 882 days for those with values greater than 6.16 (p = 0.006). Based on the results of this preliminary study in a small patient population, textural features reflecting heterogeneity on FLT PET images seem to be

  20. Time to treatment as a quality metric in lung cancer: Staging studies, time to treatment, and patient survival

    International Nuclear Information System (INIS)

    Gomez, Daniel R.; Liao, Kai-Ping; Swisher, Stephen G.; Blumenschein, George R.; Erasmus, Jeremy J.; Buchholz, Thomas A.; Giordano, Sharon H.; Smith, Benjamin D.

    2015-01-01

    Purpose: Prompt staging and treatment are crucial for non-small cell lung cancer (NSCLC). We determined if predictors of treatment delay after diagnosis were associated with prognosis. Materials and methods: Medicare claims from 28,732 patients diagnosed with NSCLC in 2004–2007 were used to establish the diagnosis-to-treatment interval (ideally ⩽35 days) and identify staging studies during that interval. Factors associated with delay were identified with multivariate logistic regression, and associations between delay and survival by stage were tested with Cox proportional hazard regression. Results: Median diagnosis-to-treatment interval was 27 days. Receipt of PET was associated with delays (57.4% of patients with PET delayed [n = 6646/11,583] versus 22.8% of those without [n = 3908/17,149]; adjusted OR = 4.48, 95% CI 4.23–4.74, p < 0.001). Median diagnosis-to-PET interval was 15 days; PET-to-clinic, 5 days; and clinic-to-treatment, 12 days. Diagnosis-to-treatment intervals <35 days were associated with improved survival for patients with localized disease and those with distant disease surviving ⩾1 year but not for patients with distant disease surviving <1 year. Conclusion: Delays between diagnosing and treating NSCLC are common and associated with use of PET for staging. Reducing time to treatment may improve survival for patients with manageable disease at diagnosis

  1. Mutation in filamin A causes periventricular heterotopia, developmental regression, and West syndrome in males.

    Science.gov (United States)

    Masruha, Marcelo R; Caboclo, Luis O S F; Carrete, Henrique; Cendes, Iscia L; Rodrigues, Murilo G; Garzon, Eliana; Yacubian, Elza M T; Sakamoto, Américo C; Sheen, Volney; Harney, Megan; Neal, Jason; Hill, R Sean; Bodell, Adria; Walsh, Christopher; Vilanova, Luiz C P

    2006-01-01

    Familial periventricular heterotopia (PH) represents a disorder of neuronal migration resulting in multiple gray-matter nodules along the lateral ventricular walls. Prior studies have shown that mutations in the filamin A (FLNA) gene can cause PH through an X-linked dominant pattern. Heterozygotic female patients usually remain asymptomatic until the second or third decade of life, when they may have predominantly focal seizures, whereas hemizygotic male fetuses typically die in utero. Recent studies have also reported mutations in FLNA in male patients with PH who are cognitively normal. We describe PH in three male siblings with PH due to FLNA, severe developmental regression, and West syndrome. The study includes the three affected brothers and their parents. Video-EEG recordings and magnetic resonance image (MRI) scanning were performed on all individuals. Mutations for FLNA were detected by using polymerase chain reaction (PCR) on genomic DNA followed by single-stranded conformational polymorphism (SSCP) analysis or sequencing. Two of the siblings are monozygotic twins, and all had West syndrome with hypsarrhythmia on EEG. MRI of the brain revealed periventricular nodules of cerebral gray-matter intensity, typical for PH. Mutational analyses demonstrated a cytosine-to-thymidine missense mutation (c. C1286T), resulting in a threonine-to-methionine amino acid substitution in exon 9 of the FLNA gene. The association between PH and West syndrome, to our knowledge, has not been previously reported. Males with PH have been known to harbor FLNA mutations, although uniformly, they either show early lethality or survive and have a normal intellect. The current studies show that FLNA mutations can cause periventricular heterotopia, developmental regression, and West syndrome in male patients, suggesting that this type of FLNA mutation may contribute to severe neurologic deficits.

  2. Prognostic nutritional index is associated with survival after total gastrectomy for patients with gastric cancer.

    Science.gov (United States)

    Ishizuka, Mitsuru; Oyama, Yusuke; Abe, Akihito; Tago, Kazuma; Tanaka, Genki; Kubota, Keiichi

    2014-08-01

    To investigate the influence of clinical characteristics including nutritional markers on postoperative survival in patients undergoing total gastrectomy (TG) for gastric cancer (GC). One hundred fifty-four patients were enrolled. Uni- and multivariate analyses using the Cox proportional hazard model were performed to explore the most valuable clinical characteristic that was associated with postoperative survival. Multivariate analysis using twelve clinical characteristics selected from univariate analyses revealed that age (≤ 72/>72), carcinoembryonic antigen (≤ 20/>20) (ng/ml), white blood cell count (≤ 9.5/>9.5) (× 10(3)/mm(3)), prognostic nutritional index (PNI) (≤ 45/>45) and lymph node metastasis (negative/positive) were associated with postoperative survival. Kaplan-Meier analysis and log-rank test showed that patients with higher PNI (>45) had a higher postoperative survival rate than those with lower PNI (≤ 45) (p<0.001). PNI is associated with postoperative survival of patients undergoing TG for GC and is able to divide such patients into two independent groups before surgery. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  3. Dimethyl phenyl piperazine iodide (DMPP) induces glioma regression by inhibiting angiogenesis

    Energy Technology Data Exchange (ETDEWEB)

    He, Yan-qing; Li, Yan; Wang, Xiao-yu [Key Laboratory for Regenerative Medicine of the Ministry of Education, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou 510632 (China); He, Xiao-dong [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510006 (China); Jun, Li [Guangdong Provincial Key Laboratory of Bioengineering Medicine, National Engineering Research Centre of Genetic Medicine, College of Life Science and Technology, Jinan University, Guangzhou 510632 (China); Chuai, Manli [Division of Cell and Developmental Biology, University of Dundee, Dundee, DD1 5EH (United Kingdom); Lee, Kenneth Ka Ho [Key Laboratory for Regenerative Medicine of the Ministry of Education, School of Biomedical Sciences, Chinese University of Hong Kong, Shatin (Hong Kong); Wang, Ju [Guangdong Provincial Key Laboratory of Bioengineering Medicine, National Engineering Research Centre of Genetic Medicine, College of Life Science and Technology, Jinan University, Guangzhou 510632 (China); Wang, Li-jing, E-mail: wanglijing62@163.com [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510006 (China); Yang, Xuesong, E-mail: yang_xuesong@126.com [Key Laboratory for Regenerative Medicine of the Ministry of Education, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou 510632 (China)

    2014-01-15

    1,1-Dimethyl-4-phenyl piperazine iodide (DMPP) is a synthetic nicotinic acetylcholine receptor (nAChR) agonist that could reduce airway inflammation. In this study, we demonstrated that DMPP could dramatically inhibit glioma size maintained on the chick embryonic chorioallantoic membrane (CAM). We first performed MTT and BrdU incorporation experiments on U87 glioma cells in vitro to understand the mechanism involved. We established that DMPP did not significantly affect U87 cell proliferation and survival. We speculated that DMPP directly caused the tumor to regress by affecting the vasculature in and around the implanted tumor on our chick CAM model. Hence, we conducted detailed analysis of DMPP's inhibitory effects on angiogenesis. Three vasculogenesis and angiogenesis in vivo models were used in the study which included (1) early chick blood islands formation, (2) chick yolk-sac membrane (YSW) and (3) CAM models. The results revealed that DMPP directly suppressed all developmental stages involved in vasculogenesis and angiogenesis – possibly by acting through Ang-1 and HIF-2α signaling. In sum, our results show that DMPP could induce glioma regression grown on CAM by inhibiting vasculogenesis and angiogenesis. - Highlights: ●We demonstrated that DMPP inhibited the growth of glioma cells on chick CAM. ●DMPP did not significantly affect the proliferation and survival of U87 cells. ●We revealed that DMPP suppressed vasculogenesis and angiogenesis in chick embryo. ●Angiogenesis in chick CAM was inhibited by DMPP via most probably Ang-1 and HIF-2α. ●DMPP could be potentially developed as an anti-tumor drug in the future.

  4. Evaluation of clinical and histopathologic prognostic factors for survival in canine osteosarcoma of the extracranial flat and irregular bones.

    Science.gov (United States)

    Kruse, M A; Holmes, E S; Balko, J A; Fernandez, S; Brown, D C; Goldschmidt, M H

    2013-07-01

    Osteosarcoma is the most common bone tumor in dogs. However, current literature focuses primarily on appendicular osteosarcoma. This study examined the prognostic value of histological and clinical factors in flat and irregular bone osteosarcomas and hypothesized that clinical factors would have a significant association with survival time while histological factors would not. All osteosarcoma biopsy samples of the vertebra, rib, sternum, scapula, or pelvis were reviewed while survival information and clinical data were obtained from medical records, veterinarians, and owners. Forty-six dogs were included in the analysis of histopathological variables and 27 dogs with complete clinical data were included in the analysis of clinical variables. In the histopathologic cox regression model, there was no significant association between any histologic feature of osteosarcoma, including grade, and survival time. In the clinical cox regression model, there was a significant association between the location of the tumor and survival time as well as between the percent elevation of alkaline phosphatase (ALP) above normal and survival time. Controlling for ALP elevation, dogs with osteosarcoma located in the scapula had a significantly greater hazard for death (2.8) compared to dogs with tumors in other locations. Controlling for tumor location, every 100% increase in ALP from normal increased the hazard for death by 1.7. For canine osteosarcomas of the flat and irregular bones, histopathological features, including grade do not appear to be rigorous predictors of survival. Clinical variables such as increased ALP levels and tumor location in the scapula were associated with decreased survival times.

  5. Treatment of malignant biliary occlusion by means of transhepatic percutaneous biliary drainage with insertion of metal stents - results of an 8-year follow-up and analysis of the prognostic parameters; Behandlung der malignen Gallenwegsstenose mittels perkutaner transhepatischer Metallendoprothesenimplantation: 8 Jahres-Ergebnisse und Analyse prognostischer Faktoren

    Energy Technology Data Exchange (ETDEWEB)

    Alfke, H.; Alfke, B.; Froelich, J.J.; Klose, K.J.; Wagner, H.J. [Klinik fuer Strahlendiagnostik Philipps Univ. Marburg (Germany)

    2003-08-01

    Purpose: To analyze outcome and predictive factors for patient survival and patency rates of unresectable malignant biliary obstruction treated with percutaneous transhepatic insertion of metal stents. Materials and Methods: This is a retroselective analysis of 130 patients treated in one interventional radiological center with data collected from patient records and by telephone interviews. The procedure-related data had been prospectively documented in a computer data base. The Kaplan-Meier analysis was performed for univariate and multivariate comparison of survival and patency rates with the log-rank test used for different tumor types. Predictive factors for survival and 30-day mortality were analyzed by a stepwise logistic regression. Results: Underlying causes of malignant biliary obstructions were cholangiocarcinoma in 50, pancreatic carcinoma in 29, liver metastases in 27, gallbladder carcinoma in 20, and other tumors in 4 patients. The technical success rate was 99%, the complication rate 27% and the 30-day mortality 11%. Primary patency rates (406 days with a median of 207 days) did not differ significantly for different tumor types. The survival rates were significantly (p = 0.03 by log-rank test) better for patients with cholangiocarcinoma than for patients with pancreatic carcinoma and liver metastases. Multiple regression analysis revealed no predictive factor for patient survival and 30-day mortality. Conclusion: Percutaneous transhepatic insertion of metal biliary endoprostheses offers a good initial and long-term relief of jaundice caused by malignant biliary obstruction. Although survival rates for patients with cholangiocarcinoma are better than for other causes of malignant biliary obstruction, a clear predictive factor is lacking for patients undergoing palliative biliary stent insertion. (orig.) [German] Ziel: Ergebnisse der perkutanen transhepatischen Metallendoprothesenimplantation bei malignen Gallenwegsverschluessen zu evaluieren und

  6. DNA-dependent protein kinase catalytic subunit functions in metastasis and influences survival in advanced-stage laryngeal squamous cell carcinoma.

    Science.gov (United States)

    He, Sha-Sha; Chen, Yong; Shen, Xiao-Ming; Wang, Hong-Zhi; Sun, Peng; Dong, Jun; Guo, Gui-Fang; Chen, Ju-Gao; Xia, Liang-Ping; Hu, Pei-Li; Qiu, Hui-Juan; Liu, Shou-Sheng; Zhou, Yi-Xin; Wang, Wei; Hu, Wei-Han; Cai, Xiu-Yu

    2017-01-01

    Background: DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is known to function in several types of cancer. In this study, we investigated the expression and clinicopathologic significance of DNA-PKcs in laryngeal squamous cell carcinoma (LSCC). Methods: We conducted a retrospective study of 208 patients with advanced-stage LSCC treated at Sun Yat-sen University Cancer Center, Guangzhou, China. We assessed DNA-PKcs and p16INK4a (p16) status using immunohistochemistry. We examined the association between DNA-PKcs expression and clinicopathologic features and survival outcomes. To evaluate the independent prognostic relevance of DNA-PKcs, we used univariate and multivariate Cox regression models. We estimated overall survival (OS) and distant metastasis-free survival (DMFS) using the Kaplan-Meier method. Results: Immunohistochemical analyses revealed that 163/208 (78.4%) of the LSCC tissue samples exhibited high DNA-PKcs expression. High DNA-PKcs expression was significantly associated with survival outcomes ( P = 0.016) and distant metastasis ( P = 0.02; chi-squared test). High DNA-PKcs expression was associated with a significantly shorter OS and DMFS than low DNA-PKcs expression ( P = 0.029 and 0.033, respectively; log-rank test), and was associated with poor OS in the p16-positive subgroup ( P = 0.047). Multivariate analysis identified DNA-PKcs as an independent prognostic indicator of OS and DMFS in all patients ( P = 0.039 and 0.037, respectively). Conclusions : Our results suggest that patients with LSCC in whom DNA-PKcs expression is elevated have a higher incidence of distant metastasis and a poorer prognosis. DNA-PKcs may represent a marker of tumor progression in patients with p16-positive LSCC.

  7. Epidermal Growth Factor Receptor Is Related to Poor Survival in Glioblastomas: Single-Institution Experience

    Science.gov (United States)

    Choi, Youngmin; Lee, Hyung-Sik; Hur, Won-Joo; Sung, Ki-Han; Kim, Ki-Uk; Choi, Sun-Seob; Kim, Su-Jin; Kim, Dae-Cheol

    2013-01-01

    Purpose There are conflicting results surrounding the prognostic significance of epidermal growth factor receptor (EGFR) status in glioblastoma (GBM) patients. Accordingly, we attempted to assess the influence of EGFR expression on the survival of GBM patients receiving postoperative radiotherapy. Materials and Methods Thirty three GBM patients who had received surgery and postoperative radiotherapy at our institute, between March 1997 and February 2006, were included. The evaluation of EGFR expression with immunohistochemistry was available for 30 patients. Kaplan-Meier survival analysis and Cox regression were used for statistical analysis. Results EGFR was expressed in 23 patients (76.7%), and not expressed in seven (23.3%). Survival in EGFR expressing GBM patients was significantly less than that in non-expressing patients (median survival: 12.5 versus 17.5 months, p=0.013). Patients who received more than 60 Gy showed improved survival over those who received up to 60 Gy (median survival: 17.0 versus 9.0 months, p=0.000). Negative EGFR expression and a higher radiation dose were significantly correlated with improved survival on multivariate analysis. Survival rates showed no differences according to age, sex, and surgical extent. Conclusion The expression of EGFR demonstrated a significantly deleterious effect on the survival of GBM patients. Therefore, approaches targeting EGFR should be considered in potential treatment methods for GBM patients, in addition to current management strategies. PMID:23225805

  8. Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

    OpenAIRE

    Ole E. Barndorff-Nielsen; Neil Shephard

    2002-01-01

    This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

  9. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  10. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  11. Variations in survival after cardiac arrest among academic medical center-affiliated hospitals.

    Directory of Open Access Journals (Sweden)

    Michael Christopher Kurz

    Full Text Available Variation exists in cardiac arrest (CA survival among institutions. We sought to determine institutional-level characteristics of academic medical centers (AMCs associated with CA survival.We examined discharge data from AMCs participating with Vizient clinical database-resource manager. We identified cases using ICD-9 diagnosis code 427.5 (CA or procedure code 99.60 (CPR. We estimated hospital-specific risk-standardized survival rates (RSSRs using mixed effects logistic regression, adjusting for individual mortality risk. Institutional and community characteristics of AMCs with higher than average survival were compared with those with lower survival.We analyzed data on 3,686,296 discharges in 2012, of which 33,700 (0.91% included a CA diagnosis. Overall survival was 42.3% (95% CI 41.8-42.9 with median institutional RSSR of 42.6% (IQR 35.7-51.0; Min-Max 19.4-101.6. We identified 28 AMCs with above average survival (median RSSR 61.8% and 20 AMCs with below average survival (median RSSR 26.8%. Compared to AMCs with below average survival, those with high CA survival had higher CA volume (median 262 vs.119 discharges, p = 0.002, total beds (722 vs. 452, p = 0.02, and annual surgical volume (24,939 vs. 13,109, p<0.001, more likely to offer cardiac catheterization (100% vs. 72%, p = 0.007 or cardiac surgery (93% vs. 61%, p = 0.02 and cared for catchment areas with higher household income ($61,922 vs. $49,104, p = 0.004 and lower poverty rates (14.6% vs. 17.3%, p = 0.03.Using discharge data from Vizient, we showed AMCs with higher CA and surgical case volume, cardiac catheterization and cardiac surgery facilities, and catchment areas with higher socioeconomic status had higher risk-standardized CA survival.

  12. Survival times of patients with a first hip fracture with and without subsequent major long-bone fractures.

    Science.gov (United States)

    Angthong, Chayanin; Angthong, Wirana; Harnroongroj, Thos; Naito, Masatoshi; Harnroongroj, Thossart

    2013-01-01

    Survival rates are poorer after a second hip fracture than after a first hip fracture. Previous survival studies have included in-hospital mortality. Excluding in-hospital deaths from the analysis allows survival times to be evaluated in community-based patients. There is still a lack of data regarding the effects of subsequent fractures on survival times after hospital discharge following an initial hip fracture. This study compared the survival times of community-dwelling patients with hip fracture who had or did not have a subsequent major long-bone fracture. Hazard ratios and risk factors for subsequent fractures and mortality rates with and without subsequent fractures were calculated. Of 844 patients with hip fracture from 2000 through 2008, 71 had a subsequent major long-bone fracture and 773 did not. Patients who died of other causes, such as perioperative complications, during hospitalization were excluded. Such exclusion allowed us to determine the effect of subsequent fracture on the survival of community-dwelling individuals after hospital discharge or after the time of the fracture if they did not need hospitalization. Demographic data, causes of death, and mortality rates were recorded. Differences in mortality rates between the patient groups and hazard ratios were calculated. Mortality rates during the first year and from 1 to 5 years after the most recent fracture were 5.6% and 1.4%, respectively, in patients with subsequent fractures, and 4.7% and 1.4%, respectively, in patients without subsequent fractures. These rates did not differ significantly between the groups. Cox regression analysis and calculation of hazard ratios did not show significant differences between patients with subsequent fractures and those without. On univariate and multivariate analyses, age fracture. This study found that survival times did not differ significantly between patients with and without subsequent major long-bone fractures after hip fracture. Therefore, all

  13. Privacy-Preserving Distributed Linear Regression on High-Dimensional Data

    Directory of Open Access Journals (Sweden)

    Gascón Adrià

    2017-10-01

    Full Text Available We propose privacy-preserving protocols for computing linear regression models, in the setting where the training dataset is vertically distributed among several parties. Our main contribution is a hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products. Like many machine learning tasks, building a linear regression model involves solving a system of linear equations. We conduct a comprehensive evaluation and comparison of different techniques for securely performing this task, including a new Conjugate Gradient Descent (CGD algorithm. This algorithm is suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers. Our technique improves on Nikolaenko et al.’s method for privacy-preserving ridge regression (S&P 2013, and can be used as a building block in other analyses. We implement a complete system and demonstrate that our approach is highly scalable, solving data analysis problems with one million records and one hundred features in less than one hour of total running time.

  14. Computed tomography in the evaluation of malignant pleural mesothelioma-Association of tumor size to a sarcomatoid histology, a more advanced TNM stage and poor survival.

    Science.gov (United States)

    Paajanen, Juuso; Laaksonen, Sanna; Ilonen, Ilkka; Wolff, Henrik; Husgafvel-Pursiainen, Kirsti; Kuosma, Eeva; Ollila, Hely; Myllärniemi, Marjukka; Vehmas, Tapio

    2018-02-01

    Appropriate clinical staging of malignant pleural mesothelioma (MPM) is critical for correct treatment decisions. Newly revised TNM staging protocol has been released for MPM. We investigated baseline computed tomography (CT) characteristics of MPM patients, the new staging system and a simple tumor size (TS) assessment in terms of survival. As part of our study that included all MPM patients diagnosed in Finland 2000-2012, we retrospectively reviewed 161 CT scans of MPM patients diagnosed between 2007 and 2012 in the Hospital District of Helsinki and Uusimaa. TS was estimated by using the maximal tumor thickness and grading tumor extension along the chest wall. Cox Regression models were used to identify relationships between survival, clinicopathological factors and CT-findings. The median length of follow-up was 9.7 months and the median survival 9.1 months. The right sided tumors tended to be more advanced at baseline and had worse prognosis in the univariate analyses. In the multivariate survival model, TS, pleural effusion along with non-epithelioid histology were predictors of poor survival. Tumor size correlated significantly with a sarcomatoid histopathological finding and several parameters linked to a more advanced TNM stage. Most patients were diagnosed with locally advanced stage, while 12 (7%) had no sign of the tumor in CT. In this study, we demonstrate a novel approach for MPM tumor size evaluation that has a strong relationship with mortality, sarcomatoid histology and TNM stage groups. TS could be used for prognostic purposes and it may be a useful method for assessing therapy responses. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

    Science.gov (United States)

    Bulcock, J. W.

    The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

  16. Quantile regression for the statistical analysis of immunological data with many non-detects

    NARCIS (Netherlands)

    Eilers, P.H.C.; Roder, E.; Savelkoul, H.F.J.; Wijk, van R.G.

    2012-01-01

    Background Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical

  17. Quantile regression for the statistical analysis of immunological data with many non-detects

    NARCIS (Netherlands)

    P.H.C. Eilers (Paul); E. Röder (Esther); H.F.J. Savelkoul (Huub); R. Gerth van Wijk (Roy)

    2012-01-01

    textabstractBackground: Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced

  18. Racial residential segregation, socioeconomic disparities, and the White-Black survival gap

    Science.gov (United States)

    Duffy, Erin; Mendelsohn, Joshua; Escarce, José J.

    2018-01-01

    Objective To evaluate the association between racial residential segregation, a prominent manifestation of systemic racism, and the White-Black survival gap in a contemporary cohort of adults, and to assess the extent to which socioeconomic inequality explains this association. Design This was a cross sectional study of White and Black men and women aged 35–75 living in 102 large US Core Based Statistical Areas. The main outcome was the White-Black survival gap. We used 2009–2013 CDC mortality data for Black and White men and women to calculate age-, sex- and race adjusted White and Black mortality rates. We measured segregation using the Dissimilarity index, obtained from the Manhattan Institute. We used the 2009–2013 American Community Survey to define indicators of socioeconomic inequality. We estimated the CBSA-level White–Black gap in probability of survival using sequential linear regression models accounting for the CBSA dissimilarity index and race-specific socioeconomic indicators. Results Black men and women had a 14% and 9% lower probability of survival from age 35 to 75 than their white counterparts. Residential segregation was strongly associated with the survival gap, and this relationship was partly, but not fully, explained by socioeconomic inequality. At the lowest observed level of segregation, and with the Black socioeconomic status (SES) assumed to be at the White SES level scenario, the survival gap is essentially eliminated. Conclusion White-Black differences in survival remain wide notwithstanding public health efforts to improve life expectancy and initiatives to reduce health disparities. Eliminating racial residential segregation and bringing Black socioeconomic status (SES) to White SES levels would eliminate the White-Black survival gap. PMID:29474451

  19. Racial residential segregation, socioeconomic disparities, and the White-Black survival gap.

    Directory of Open Access Journals (Sweden)

    Ioana Popescu

    Full Text Available To evaluate the association between racial residential segregation, a prominent manifestation of systemic racism, and the White-Black survival gap in a contemporary cohort of adults, and to assess the extent to which socioeconomic inequality explains this association.This was a cross sectional study of White and Black men and women aged 35-75 living in 102 large US Core Based Statistical Areas. The main outcome was the White-Black survival gap. We used 2009-2013 CDC mortality data for Black and White men and women to calculate age-, sex- and race adjusted White and Black mortality rates. We measured segregation using the Dissimilarity index, obtained from the Manhattan Institute. We used the 2009-2013 American Community Survey to define indicators of socioeconomic inequality. We estimated the CBSA-level White-Black gap in probability of survival using sequential linear regression models accounting for the CBSA dissimilarity index and race-specific socioeconomic indicators.Black men and women had a 14% and 9% lower probability of survival from age 35 to 75 than their white counterparts. Residential segregation was strongly associated with the survival gap, and this relationship was partly, but not fully, explained by socioeconomic inequality. At the lowest observed level of segregation, and with the Black socioeconomic status (SES assumed to be at the White SES level scenario, the survival gap is essentially eliminated.White-Black differences in survival remain wide notwithstanding public health efforts to improve life expectancy and initiatives to reduce health disparities. Eliminating racial residential segregation and bringing Black socioeconomic status (SES to White SES levels would eliminate the White-Black survival gap.

  20. Epidermal growth factor receptor: an independent predictor of survival in astrocytic tumors given definitive irradiation

    International Nuclear Information System (INIS)

    An Zhu; Shaeffer, James; Leslie, Susan; Kolm, Paul; El-Mahdi, Anas M.

    1996-01-01

    Purpose: To determine whether the expression of epidermal growth factor receptor (EGFR) protein was predictive of patient survival independently of other prognostic factors in astrocytic tumors. Methods and Materials: Epidermal growth factor receptor protein expression was investigated immunohistochemically in formalin-fixed, paraffin-embedded surgical specimens of 55 glioblastoma multiforme, 14 anaplastic astrocytoma, and 2 astrocytomas given definitive irradiation. We evaluated the relationship of EGFR protein expression and tumor grade, histologic features, age at diagnosis, sex, patient survival, and recurrence-free survival. Results: The percentage of tumor cells which were EGFR positive related to reduced survival by Cox regression analysis in both univariate (p = 0.0424) and multivariate analysis (p = 0.0016). Epidermal growth factor receptor positivity was the only 1 of 11 clinical and histological variables associated with decreased recurrence-free survival by either univariate (p = 0.0353) or multivariate (p = 0.0182) analysis. Epidermal growth factor receptor protein expression was not related to patient age, sex, or histologic features. Conclusion: Epidermal growth factor receptor positivity was a significant and independent prognostic indicator for overall survival and recurrence-free survival for irradiated patients with astrocytic gliomas

  1. Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

    Science.gov (United States)

    Bennett, Bradley C; Husby, Chad E

    2008-03-28

    Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

  2. Regional regression equations for the estimation of selected monthly low-flow duration and frequency statistics at ungaged sites on streams in New Jersey

    Science.gov (United States)

    Watson, Kara M.; McHugh, Amy R.

    2014-01-01

    representative of the increased development of the last 20 years (1989–2008). The two different land- and water-use conditions were used as surrogates for development to determine whether there have been changes in low-flow statistics as a result of changes in development over time. The State was divided into two low-flow regression regions, the Coastal Plain and the non-coastal region, in order to improve the accuracy of the regression equations. The left-censored parametric survival regression method was used for the analyses to account for streamgages and partial-record stations that had zero flow values for some of the statistics. The average standard error of estimate for the 348 regression equations ranged from 16 to 340 percent. These regression equations and basin characteristics are presented in the U.S. Geological Survey (USGS) StreamStats Web-based geographic information system application. This tool allows users to click on an ungaged site on a stream in New Jersey and get the estimated flow-duration and low-flow frequency statistics. Additionally, the user can click on a streamgage or partial-record station and get the “at-site” streamflow statistics. The low-flow characteristics of a stream ultimately affect the use of the stream by humans. Specific information on the low-flow characteristics of streams is essential to water managers who deal with problems related to municipal and industrial water supply, fish and wildlife conservation, and dilution of wastewater.

  3. The R Package threg to Implement Threshold Regression Models

    Directory of Open Access Journals (Sweden)

    Tao Xiao

    2015-08-01

    This new package includes four functions: threg, and the methods hr, predict and plot for threg objects returned by threg. The threg function is the model-fitting function which is used to calculate regression coefficient estimates, asymptotic standard errors and p values. The hr method for threg objects is the hazard-ratio calculation function which provides the estimates of hazard ratios at selected time points for specified scenarios (based on given categories or value settings of covariates. The predict method for threg objects is used for prediction. And the plot method for threg objects provides plots for curves of estimated hazard functions, survival functions and probability density functions of the first-hitting-time; function curves corresponding to different scenarios can be overlaid in the same plot for comparison to give additional research insights.

  4. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  5. Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan.

    Directory of Open Access Journals (Sweden)

    Chun-Ming Chang

    Full Text Available BACKGROUND: Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers. METHODOLOGY: A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations. RESULTS: Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005. CONCLUSIONS: After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.

  6. Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis.

    Science.gov (United States)

    Querin, G; El Mendili, M M; Lenglet, T; Delphine, S; Marchand-Pauvert, V; Benali, H; Pradat, P-F

    2017-08-01

    Assessing survival is a critical issue in patients with amyotrophic lateral sclerosis (ALS). Neuroimaging seems to be promising in the assessment of disease severity and several studies also suggest a strong relationship between spinal cord (SC) atrophy described by magnetic resonance imaging (MRI) and disease progression. The aim of the study was to determine the predictive added value of multimodal SC MRI on survival. Forty-nine ALS patients were recruited and clinical data were collected. Patients were scored on the Revised ALS Functional Rating Scale and manual muscle testing. They were followed longitudinally to assess survival. The cervical SC was imaged using the 3 T MRI system. Cord volume and cross-sectional area (CSA) at each vertebral level were computed. Diffusion tensor imaging metrics were measured. Imaging metrics and clinical variables were used as inputs for a multivariate Cox regression survival model. On building a multivariate Cox regression model with clinical and MRI parameters, fractional anisotropy, magnetization transfer ratio and CSA at C2-C3, C4-C5, C5-C6 and C6-C7 vertebral levels were significant. Moreover, the hazard ratio calculated for CSA at the C3-C4 and C5-C6 levels indicated an increased risk for patients with SC atrophy (respectively 0.66 and 0.68). In our cohort, MRI parameters seem to be more predictive than clinical variables, which had a hazard ratio very close to 1. It is suggested that multimodal SC MRI could be a useful tool in survival prediction especially if used at the beginning of the disease and when combined with clinical variables. To validate it as a biomarker, confirmation of the results in bigger independent cohorts of patients is warranted. © 2017 EAN.

  7. A note on the use of multiple linear regression in molecular ecology.

    Science.gov (United States)

    Frasier, Timothy R

    2016-03-01

    Multiple linear regression analyses (also often referred to as generalized linear models--GLMs, or generalized linear mixed models--GLMMs) are widely used in the analysis of data in molecular ecology, often to assess the relative effects of genetic characteristics on individual fitness or traits, or how environmental characteristics influence patterns of genetic differentiation. However, the coefficients resulting from multiple regression analyses are sometimes misinterpreted, which can lead to incorrect interpretations and conclusions within individual studies, and can propagate to wider-spread errors in the general understanding of a topic. The primary issue revolves around the interpretation of coefficients for independent variables when interaction terms are also included in the analyses. In this scenario, the coefficients associated with each independent variable are often interpreted as the independent effect of each predictor variable on the predicted variable. However, this interpretation is incorrect. The correct interpretation is that these coefficients represent the effect of each predictor variable on the predicted variable when all other predictor variables are zero. This difference may sound subtle, but the ramifications cannot be overstated. Here, my goals are to raise awareness of this issue, to demonstrate and emphasize the problems that can result and to provide alternative approaches for obtaining the desired information. © 2015 John Wiley & Sons Ltd.

  8. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  9. Survival outcomes following salvage surgery for oropharyngeal squamous cell carcinoma: systematic review.

    Science.gov (United States)

    Kao, S S; Ooi, E H

    2018-04-01

    Recurrent oropharyngeal squamous cell carcinoma causes great morbidity and mortality. This systematic review analyses survival outcomes following salvage surgery for recurrent oropharyngeal squamous cell carcinoma. A comprehensive search of various electronic databases was conducted. Studies included patients with recurrent or residual oropharyngeal squamous cell carcinoma treated with salvage surgery. Primary outcomes were survival rates following salvage surgery. Secondary outcomes included time to recurrence, staging at time of recurrence, post-operative complications, and factors associated with mortality and recurrence. Methodological appraisal and data extraction were conducted as per Joanna Briggs Institute methodology. Eighteen articles were included. The two- and five-year survival rates of the patients were 52 per cent and 30 per cent respectively. Improvements in treatment modalities for recurrent oropharyngeal squamous cell carcinoma were associated with improvements in two-year overall survival rates, with minimal change to five-year overall survival rates. Various factors were identified as being associated with long-term overall survival, thus assisting clinicians in patient counselling and selection for salvage surgery.

  10. Chemotherapy response as a prognosticator for survival in patients with limited squamous cell lung cancer treated with combined chemotherapy and radiotherapy

    International Nuclear Information System (INIS)

    Eagan, R.T.; Fleming, T.R.; Lee, R.E.; Ingle, J.N.; Frytak, S.; Creagan, E.T.

    1980-01-01

    Twenty-two patients with limited unresectable squamous cell lung cancer were treated with 6 courses of combination chemotherapy consisting of cyclophosphamide, adriamycin, cisplatin, and bleomycin (CAP-Bleo) and short-course thoracic irradiation started after the first 4 weeks of chemotherapy. Of 20 patients with visible tumor who were treated with 4 weeks of chemotherapy alone, 10 (50%) had a tumor regression in that 4 week period and 10 did not. Those patients with tumor regression had significantly better progression free and overall survivals than did patients with no chemotherapy regressions (medians of 258 days vs. 136 days and 356 days vs. 150 days respectively). The original bleomycin dose had to be reduced by 50% primarily because of excessive radiation esophagitis that has not been reported with use of either the CAP regimen or bleomycin along in conjunction with thoracic irradiation. An initial chemotherapy regression seems to be a good prognosticator for progression-free and overall survival in patients with limited squamous cell lung cancer treated with combined chemotherapy and radiotherapy

  11. Chronic consequences of acute injuries: worse survival after discharge.

    Science.gov (United States)

    Shafi, Shahid; Renfro, Lindsay A; Barnes, Sunni; Rayan, Nadine; Gentilello, Larry M; Fleming, Neil; Ballard, David

    2012-09-01

    The Trauma Quality Improvement Program uses inhospital mortality to measure quality of care, which assumes patients who survive injury are not likely to suffer higher mortality after discharge. We hypothesized that survival rates in trauma patients who survive to discharge remain stable afterward. Patients treated at an urban Level I trauma center (2006-2008) were linked with the Social Security Administration Death Master File. Survival rates were measured at 30, 90, and 180 days and 1 and 2 years from injury among two groups of trauma patients who survived to discharge: major trauma (Abbreviated Injury Scale score ≥ 3 injuries, n = 2,238) and minor trauma (Abbreviated Injury Scale score ≤ 2 injuries, n = 1,171). Control groups matched to each trauma group by age and sex were simulated from the US general population using annual survival probabilities from census data. Kaplan-Meier and log-rank analyses conditional upon survival to each time point were used to determine changes in risk of mortality after discharge. Cox proportional hazards models with left truncation at the time of discharge were used to determine independent predictors of mortality after discharge. The survival rate in trauma patients with major injuries was 92% at 30 days posttrauma and declined to 84% by 3 years (p > 0.05 compared with general population). Minor trauma patients experienced a survival rate similar to the general population. Age and injury severity were the only independent predictors of long-term mortality given survival to discharge. Log-rank tests conditional on survival to each time point showed that mortality risk in patients with major injuries remained significantly higher than the general population for up to 6 months after injury. The survival rate of trauma patients with major injuries remains significantly lower than survival for minor trauma patients and the general population for several months postdischarge. Surveillance for early identification and treatment of

  12. A nomogram for predicting survival in patients with breast cancer brain metastasis.

    Science.gov (United States)

    Huang, Zhou; Sun, Bing; Wu, Shikai; Meng, Xiangying; Cong, Yang; Shen, Ge; Song, Santai

    2018-05-01

    Brain metastasis (BM) is common in patients with breast cancer. Predicting patient survival is critical for the clinical management of breast cancer brain metastasis (BCBM). The present study was designed to develop and evaluate a prognostic model for patients with newly diagnosed BCBM. Based on the clinical data of patients with BCBM treated in the Affiliated Hospital of Academy of Military Medical Sciences (Beijing, China) between 2002 and 2014, a nomogram was developed to predict survival using proportional hazards regression analysis. The model was validated internally by bootstrapping, and the concordance index (c-index) was calculated. A calibration curve and c-index were used to evaluate discriminatory and predictive ability, in order to compare the nomogram with widely used models, including recursive partitioning analysis (RPA), graded prognostic assessment (GPA) and breast-graded prognostic assessment (Breast-GPA). A total of 411 patients with BCBM were included in the development of this predictive model. The median overall survival time was 14.1 months. Statistically significant predictors for patient survival included biological subtype, Karnofsky performance score, leptomeningeal metastasis, extracranial metastasis, the number of brain metastases and disease-free survival. A nomogram for predicting 1- and 2-year overall survival rates was constructed, which exhibited good accuracy in predicting overall survival with a concordance index of 0.735. This model outperformed RPA, GPA and Breast-GPA, based on the comparisons of the c-indexes. The nomogram constructed based on a multiple factor analysis was able to more accurately predict the individual survival probability of patients with BCBM, compared with existing models.

  13. Emotional pain: surviving mental health problems related to childhood experiences.

    Science.gov (United States)

    Holm, A L; Bégat, I; Severinsson, E

    2009-09-01

    Emotional pain is described as intense by women who suffer from borderline personality disorder (BPD), and a high prevalence of reported childhood abuse was found in the literature and in research. The aim of this study was to explore the experiences of women suffering from BPD with focus on emotional pain related to childhood. An explorative design was used. Data were collected from in-depth interviews consisting of women suffering from BPD (n = 13) and an interpretive content analysis was used to analyse the text. The findings revealed two main themes: 'Power' and 'Assessment of vulnerability'. The main theme 'Power' resulted in two categories: 'Surviving the feeling of being forced' and 'Surviving the feeling of having to assume responsibility'. The other main theme 'Assessment of vulnerability' had two categories: 'Surviving the feeling of being victimized' and 'Surviving the feeling of not being loved'. The findings suggest that nursing care need to develop an understanding of how these women endure their emotional pain, and try to survive as fighting spirits and how struggling became their way of life.

  14. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Directory of Open Access Journals (Sweden)

    Minh Vu Trieu

    2017-03-01

    Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  15. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Science.gov (United States)

    Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

    2017-03-01

    This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  16. Incidence and survival from lung cancer in Greenland is comparable to survival in the Nordic countries

    DEFF Research Database (Denmark)

    Gelvan, Allan; Risum, Signe; Langer, Seppo W

    2015-01-01

    INTRODUCTION: Oncological treatment of lung cancer has been available in Greenland since 2004. We evaluated patient characteristics and survival rates for the first six years of local lung cancer treatment. METHODS: From September 2004 to August 2010, a total of 173 patients with lung cancer were...... referred to treatment at Queen Ingrid's Hospital. On 1 February 2014, treatment results, survival, and prognostic variables were analysed. RESULTS: The mean age at diagnosis was 63 years. Non-small cell lung cancer (NSCLC) was diagnosed in 145 patients (84%); 56% had squamous cell carcinoma, 34% had...... adenocarcinoma, 2% had large cell carcinoma and 8% had NSCLC not otherwise specified (NOS). In all, 28 (16%) had small cell lung cancer. A total of 142 patients (82%) received treatment; 20 underwent surgery (ten stage Ib, one stage IIa, five stage IIb, four stage IIIa); palliative chemotherapy was given to 122...

  17. Is patient-prosthesis mismatch a predictor of survival or a surrogate marker of co-morbidities in cardiac surgery?

    Science.gov (United States)

    Dayan, Victor; Soca, Gerardo; Stanham, Roberto; Lorenzo, Alvaro; Ferreiro, Alejandro

    2015-01-01

    Patient-prosthesis mismatch (PPM) has ignited much debate and no definite conclusions have been drawn on the outcome of these patients. Therefore, additional large studies with long-term follow-up are required to help the cardiologist and surgeon outline the best therapeutic strategy for patients with high risk for PPM. Patients who underwent aortic valve replacement (AVR) from 2000 to 2013 were identified. Baseline and operative data was extracted and indexed effective orifice area calculated for each patient. The presence of PPM was defined in those patients with an iEOA ≤ 0.85 cm(2)/m(2). Regression analyses were performed to determine the association of PPM with operative mortality, post-operative complications and survival. Predictors for PPM were evaluated based on clinical and operative data. From 2023 patients who underwent AVR, PPM was present in 64.6%. These patients had increased age, more coronary artery bypass procedures, increased risk of diabetes, hypertension, higher creatinine values and higher Euroscore. Age, body surface area, prosthesis type and size were found to be predictors of mismatch. Operative mortality (8.1% vs 5.7%, p = 0.05), stroke (3.9% vs 2.4, p = 0.02) and acute kidney injury (47.6% vs 35.1%, p =< 0 .001) were more frequent in patients with PPM and mean 10-year survival was reduced (6.6 years, 95% CI: 6.3-6.8 vs 7.3, 95% CI: 6.9-7.2, p < 0.001). After adjusting for confounders, PPM was not found to be associated to either adverse outcome or survival. Patients with PPM have worse operative mortality, post-operative complications and survival mainly due to the fact that they represent a higher risk population based on age and co-morbidities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Impact of delay to treatment upon survival in 1067 patients with breast-cancer.

    Science.gov (United States)

    Rabinovich, M; Vallejo, C; Perez, J; Rodriguez, R; Cuevas, M; Machiavelli, M; Lacava, J; Leone, B; Romero, A; Mickiewicz, E; Chacon, R; Estevez, R

    1993-02-01

    The medical records of 1067 patients with breast cancer were reviewed to evaluate the influence of delay between first symptom and first treatment upon survival. Three delay intervals were considered: 6 months. At a follow-up of 120 months, survival analyses identified a statistically significant difference (p=0.029) favoring patients with 3 months delay between first symptom and first treatment. Better survival rate for patients with a short delay would obey to a greater number of patients in favorable stages and a higher proportion of women aged 50 or older in this group.

  19. SOCR Analyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit

    Directory of Open Access Journals (Sweden)

    Annie Chu

    2009-04-01

    Full Text Available The web-based, Java-written SOCR (Statistical Online Computational Resource toolshave been utilized in many undergraduate and graduate level statistics courses for sevenyears now (Dinov 2006; Dinov et al. 2008b. It has been proven that these resourcescan successfully improve students' learning (Dinov et al. 2008b. Being rst publishedonline in 2005, SOCR Analyses is a somewhat new component and it concentrate on datamodeling for both parametric and non-parametric data analyses with graphical modeldiagnostics. One of the main purposes of SOCR Analyses is to facilitate statistical learn-ing for high school and undergraduate students. As we have already implemented SOCRDistributions and Experiments, SOCR Analyses and Charts fulll the rest of a standardstatistics curricula. Currently, there are four core components of SOCR Analyses. Linearmodels included in SOCR Analyses are simple linear regression, multiple linear regression,one-way and two-way ANOVA. Tests for sample comparisons include t-test in the para-metric category. Some examples of SOCR Analyses' in the non-parametric category areWilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, Kolmogorov-Smirno testand Fligner-Killeen test. Hypothesis testing models include contingency table, Friedman'stest and Fisher's exact test. The last component of Analyses is a utility for computingsample sizes for normal distribution. In this article, we present the design framework,computational implementation and the utilization of SOCR Analyses.

  20. Genome-based comparative analyses of Antarctic and temperate species of Paenibacillus.

    Directory of Open Access Journals (Sweden)

    Melissa Dsouza

    Full Text Available Antarctic soils represent a unique environment characterised by extremes of temperature, salinity, elevated UV radiation, low nutrient and low water content. Despite the harshness of this environment, members of 15 bacterial phyla have been identified in soils of the Ross Sea Region (RSR. However, the survival mechanisms and ecological roles of these phyla are largely unknown. The aim of this study was to investigate whether strains of Paenibacillus darwinianus owe their resilience to substantial genomic changes. For this, genome-based comparative analyses were performed on three P. darwinianus strains, isolated from gamma-irradiated RSR soils, together with nine temperate, soil-dwelling Paenibacillus spp. The genome of each strain was sequenced to over 1,000-fold coverage, then assembled into contigs totalling approximately 3 Mbp per genome. Based on the occurrence of essential, single-copy genes, genome completeness was estimated at approximately 88%. Genome analysis revealed between 3,043-3,091 protein-coding sequences (CDSs, primarily associated with two-component systems, sigma factors, transporters, sporulation and genes induced by cold-shock, oxidative and osmotic stresses. These comparative analyses provide an insight into the metabolic potential of P. darwinianus, revealing potential adaptive mechanisms for survival in Antarctic soils. However, a large proportion of these mechanisms were also identified in temperate Paenibacillus spp., suggesting that these mechanisms are beneficial for growth and survival in a range of soil environments. These analyses have also revealed that the P. darwinianus genomes contain significantly fewer CDSs and have a lower paralogous content. Notwithstanding the incompleteness of the assemblies, the large differences in genome sizes, determined by the number of genes in paralogous clusters and the CDS content, are indicative of genome content scaling. Finally, these sequences are a resource for further