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...

Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study

Science.gov (United States)

Robinson, Emily J; Power, Geraldine S; Nolan, Jerry; Soar, Jasmeet; Spearpoint, Ken; Gwinnutt, Carl; Rowan, Kathryn M

2016-01-01

Background Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events. Objective To describe IHCA demographics during three day/time periods—weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)—and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care. Methods We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals. Results Risk-adjusted outcomes (OR (95% CI)) were worse (p20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses. Conclusions IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during

Stage-specific predictive models for breast cancer survivability.

Science.gov (United States)

Kate, Rohit J; Nadig, Ramya

2017-01-01

Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Life-Cycle Models for Survivable Systems

National Research Council Canada - National Science Library

Linger, Richard

2002-01-01

.... Current software development life-cycle models are not focused on creating survivable systems, and exhibit shortcomings when the goal is to develop systems with a high degree of assurance of survivability...

R.M. Solow Adjusted Model of Economic Growth

Directory of Open Access Journals (Sweden)

Ion Gh. Rosca

2007-05-01

Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans etc., the R.M. Solow model is part of the category which characterizes the economic growth. The paper proposes the study of the R.M. Solow adjusted model of economic growth, while the adjustment consisting in the model adaptation to the Romanian economic characteristics. The article is the first one from a three paper series dedicated to the macroeconomic modelling theme, using the R.M. Solow model, such as: “Measurement of the economic growth and extensions of the R.M. Solow adjusted model” and “Evolution scenarios at the Romanian economy level using the R.M. Solow adjusted model”. The analysis part of the model is based on the study of the equilibrium to the continuous case with some interpretations of the discreet one, by using the state diagram. The optimization problem at the economic level is also used; it is built up of a specified number of representative consumers and firms in order to reveal the interaction between these elements.

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...

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

Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study.

Science.gov (United States)

Robinson, Emily J; Smith, Gary B; Power, Geraldine S; Harrison, David A; Nolan, Jerry; Soar, Jasmeet; Spearpoint, Ken; Gwinnutt, Carl; Rowan, Kathryn M

2016-11-01

Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events. To describe IHCA demographics during three day/time periods-weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)-and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care. We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals. Risk-adjusted outcomes (OR (95% CI)) were worse (p20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses. IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during weekday daytimes. Organisational or care differences at

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.

Survivability Assessment: Modeling A Recovery Process

OpenAIRE

Paputungan, Irving Vitra; Abdullah, Azween

2009-01-01

Survivability is the ability of a system to continue operating, in a timely manner, in the presence ofattacks, failures, or accidents. Recovery in survivability is a process of a system to heal or recover from damageas early as possible to fulfill its mission as condition permit. In this paper, we show a preliminary recoverymodel to enhance the system survivability. The model focuses on how we preserve the system and resumes itscritical service under attacks as soon as possible.Keywords: surv...

Correlated growth and survival of juvenile spectacled eiders: Evidence of habitat limitation?

Science.gov (United States)

Flint, Paul L.; Morse, Julie A.; Grand, James B.; Moran, Christine L.

2006-01-01

We studied the growth and survival of Spectacled Eider (Somateria fischeri) ducklings to 30 days of age along the lower Kashunuk River on the Yukon-Kuskokwim Delta from 1995 to 2000. We replicated this study at a second site, Kigigak Island, in 1999 and 2000. Age-adjusted estimates of duckling mass and survival at 30 days posthatching were highly variable. Duckling survival was consistently higher on Kigigak Island in 1999 and 2000, averaging 67%, while survival on the Kashunuk River averaged 45% during the same time period. Duckling survival was negatively related to hatching date. At the Kashunuk River site our data supported models that indicated age-adjusted mass varied with habitat type and declined with hatching date. Ducklings from Kashunuk River were heavier in 1999, while ducklings from Kigigak Island were heavier in 2000. However, we found a positive correlation between 30-day duckling survival and age-adjusted mass, suggesting a localized environmental effect on both parameters. We conclude that predation may be the proximate mechanism of mortality, but habitat conditions are likely the ultimate factors influencing duckling survival. Geographic variation in rates of duckling survival and apparent growth suggest that spatial heterogeneity in population vital rates is occurring at multiple levels.

[Survival analysis with competing risks: estimating failure probability].

Science.gov (United States)

Llorca, Javier; Delgado-Rodríguez, Miguel

2004-01-01

To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.

Extensions and Applications of the Cox-Aalen Survival Model

DEFF Research Database (Denmark)

Scheike, Thomas H.; Zhang, Mei-Jie

2003-01-01

Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects......Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects...

Age-adjusted Charlson comorbidity index score as predictor of survival of patients with digestive system cancer who have undergone surgical resection.

Science.gov (United States)

Tian, Yaohua; Jian, Zhong; Xu, Beibei; Liu, Hui

2017-10-03

Comorbidities have considerable effects on survival outcomes. The primary objective of this retrospective study was to examine the association between age-adjusted Charlson comorbidity index (ACCI) score and postoperative in-hospital mortality in patients with digestive system cancer who have undergone surgical resection of their cancers. Using electronic hospitalization summary reports, we identified 315,464 patients who had undergone surgery for digestive system cancer in top-rank (Grade 3A) hospitals in China between 2013 and 2015. The Cox proportional hazard regression model was applied to evaluate the effect of ACCI score on postoperative mortality, with adjustments for sex, type of resection, anesthesia methods, and caseload of each healthcare institution. The postoperative in-hospital mortality rate in the study cohort was 1.2% (3,631/315,464). ACCI score had a positive graded association with the risk of postoperative in-hospital mortality for all cancer subtypes. The adjusted HRs for postoperative in-hospital mortality scores ≥ 6 for esophagus, stomach, colorectum, pancreas, and liver and gallbladder cancer were 2.05 (95% CI: 1.45-2.92), 2.00 (95% CI: 1.60-2.49), 2.54 (95% CI: 2.02-3.21), 2.58 (95% CI: 1.68-3.97), and 4.57 (95% CI: 3.37-6.20), respectively, compared to scores of 0-1. These findings suggested that a high ACCI score is an independent predictor of postoperative in-hospital mortality in Chinese patients with digestive system cancer who have undergone surgical resection.

Re-evaluating neonatal-age models for ungulates: does model choice affect survival estimates?

Directory of Open Access Journals (Sweden)

Troy W Grovenburg

Full Text Available New-hoof growth is regarded as the most reliable metric for predicting age of newborn ungulates, but variation in estimated age among hoof-growth equations that have been developed may affect estimates of survival in staggered-entry models. We used known-age newborns to evaluate variation in age estimates among existing hoof-growth equations and to determine the consequences of that variation on survival estimates. During 2001-2009, we captured and radiocollared 174 newborn (≤24-hrs old ungulates: 76 white-tailed deer (Odocoileus virginianus in Minnesota and South Dakota, 61 mule deer (O. hemionus in California, and 37 pronghorn (Antilocapra americana in South Dakota. Estimated age of known-age newborns differed among hoof-growth models and varied by >15 days for white-tailed deer, >20 days for mule deer, and >10 days for pronghorn. Accuracy (i.e., the proportion of neonates assigned to the correct age in aging newborns using published equations ranged from 0.0% to 39.4% in white-tailed deer, 0.0% to 3.3% in mule deer, and was 0.0% for pronghorns. Results of survival modeling indicated that variability in estimates of age-at-capture affected short-term estimates of survival (i.e., 30 days for white-tailed deer and mule deer, and survival estimates over a longer time frame (i.e., 120 days for mule deer. Conversely, survival estimates for pronghorn were not affected by estimates of age. Our analyses indicate that modeling survival in daily intervals is too fine a temporal scale when age-at-capture is unknown given the potential inaccuracies among equations used to estimate age of neonates. Instead, weekly survival intervals are more appropriate because most models accurately predicted ages within 1 week of the known age. Variation among results of neonatal-age models on short- and long-term estimates of survival for known-age young emphasizes the importance of selecting an appropriate hoof-growth equation and appropriately defining intervals (i

Adjusting Expected Mortality Rates Using Information From a Control Population: An Example Using Socioeconomic Status.

Science.gov (United States)

Bower, Hannah; Andersson, Therese M-L; Crowther, Michael J; Dickman, Paul W; Lambe, Mats; Lambert, Paul C

2018-04-01

Expected or reference mortality rates are commonly used in the calculation of measures such as relative survival in population-based cancer survival studies and standardized mortality ratios. These expected rates are usually presented according to age, sex, and calendar year. In certain situations, stratification of expected rates by other factors is required to avoid potential bias if interest lies in quantifying measures according to such factors as, for example, socioeconomic status. If data are not available on a population level, information from a control population could be used to adjust expected rates. We have presented two approaches for adjusting expected mortality rates using information from a control population: a Poisson generalized linear model and a flexible parametric survival model. We used a control group from BCBaSe-a register-based, matched breast cancer cohort in Sweden with diagnoses between 1992 and 2012-to illustrate the two methods using socioeconomic status as a risk factor of interest. Results showed that Poisson and flexible parametric survival approaches estimate similar adjusted mortality rates according to socioeconomic status. Additional uncertainty involved in the methods to estimate stratified, expected mortality rates described in this study can be accounted for using a parametric bootstrap, but this might make little difference if using a large control population.

Extendable linearised adjustment model for deformation analysis

NARCIS (Netherlands)

Hiddo Velsink

2015-01-01

Author supplied: "This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices

Extendable linearised adjustment model for deformation analysis

NARCIS (Netherlands)

Velsink, H.

2015-01-01

This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices and correlation

Developing a scalable modeling architecture for studying survivability technologies

Science.gov (United States)

Mohammad, Syed; Bounker, Paul; Mason, James; Brister, Jason; Shady, Dan; Tucker, David

2006-05-01

To facilitate interoperability of models in a scalable environment, and provide a relevant virtual environment in which Survivability technologies can be evaluated, the US Army Research Development and Engineering Command (RDECOM) Modeling Architecture for Technology Research and Experimentation (MATREX) Science and Technology Objective (STO) program has initiated the Survivability Thread which will seek to address some of the many technical and programmatic challenges associated with the effort. In coordination with different Thread customers, such as the Survivability branches of various Army labs, a collaborative group has been formed to define the requirements for the simulation environment that would in turn provide them a value-added tool for assessing models and gauge system-level performance relevant to Future Combat Systems (FCS) and the Survivability requirements of other burgeoning programs. An initial set of customer requirements has been generated in coordination with the RDECOM Survivability IPT lead, through the Survivability Technology Area at RDECOM Tank-automotive Research Development and Engineering Center (TARDEC, Warren, MI). The results of this project are aimed at a culminating experiment and demonstration scheduled for September, 2006, which will include a multitude of components from within RDECOM and provide the framework for future experiments to support Survivability research. This paper details the components with which the MATREX Survivability Thread was created and executed, and provides insight into the capabilities currently demanded by the Survivability faculty within RDECOM.

Survival rate in nasopharyngeal carcinoma improved by high caseload volume: a nationwide population-based study in Taiwan

International Nuclear Information System (INIS)

Lee, Ching-Chih; Hung, Shih-Kai; Huang, Tze-Ta; Lee, Moon-Sing; Su, Yu-Chieh; Chou, Pesus; Hsiao, Shih-Hsuan; Chiou, Wen-Yen; Lin, Hon-Yi; Chien, Sou-Hsin

2011-01-01

Positive correlation between caseload and outcome has previously been validated for several procedures and cancer treatments. However, there is no information linking caseload and outcome of nasopharyngeal carcinoma (NPC) treatment. We used nationwide population-based data to examine the association between physician case volume and survival rates of patients with NPC. Between 1998 and 2000, a total of 1225 patients were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity score were used to assess the relationship between 10-year survival rates and physician caseloads. As the caseload of individual physicians increased, unadjusted 10-year survival rates increased (p < 0.001). Using a Cox proportional hazard model, patients with NPC treated by high-volume physicians (caseload ≥ 35) had better survival rates (p = 0.001) after adjusting for comorbidities, hospital, and treatment modality. When analyzed by propensity score, the adjusted 10-year survival rate differed significantly between patients treated by high-volume physicians and patients treated by low/medium-volume physicians (75% vs. 61%; p < 0.001). Our data confirm a positive volume-outcome relationship for NPC. After adjusting for differences in the case mix, our analysis found treatment of NPC by high-volume physicians improved 10-year survival rate

Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

Science.gov (United States)

Patricia L. Andrews

2012-01-01

Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

Incidence, treatment and survival of patients with craniopharyngioma in the surveillance, epidemiology and end results program

Science.gov (United States)

Zacharia, Brad E.; Bruce, Samuel S.; Goldstein, Hannah; Malone, Hani R.; Neugut, Alfred I.; Bruce, Jeffrey N.

2012-01-01

Craniopharyngioma is a rare primary central nervous system neoplasm. Our objective was to determine factors associated with incidence, treatment, and survival of craniopharyngiomas in the United States. We used the surveillance, epidemiology and end results program (SEER) database to identify patients who received a diagnosis of craniopharyngioma during 2004–2008. We analyzed clinical and demographic information, including age, race, sex, tumor histology, and treatment. Age-adjusted incidence rates and age, sex, and race-adjusted expected survival rates were calculated. We used Cox proportional hazards models to determine the association between covariates and overall survival. We identified 644 patients with a diagnosis of craniopharyngioma. Black race was associated with an age-adjusted relative risk for craniopharyngioma of 1.26 (95% confidence interval [CI], 0.98–1.59), compared with white race. One- and 3-year survival rates of 91.5% (95% CI, 88.9%–93.5%), and 86.2% (95% CI, 82.7%–89.0%) were observed for the cohort; relative survival rates were 92.1% (95% CI, 89.5%–94.0%) and 87.6% (95% CI, 84.1%–90.4%) for 1- and 3-years, respectively. In the multivariable model, factors associated with prolonged survival included younger age, smaller tumor size, subtotal resection, and radiation therapy. Black race, on the other hand, was associated with worse overall survival in the final model. We demonstrated that >85% of patients survived 3 years after diagnosis and that subtotal resection and radiation therapy were associated with prolonged survival. We also noted a higher incidence rate and worse 1- and 3-year survival rates in the black population. Future investigations should examine these racial disparities and focus on evaluating the efficacy of emerging treatment paradigms. PMID:22735773

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.

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.

Modelling survival: exposure pattern, species sensitivity and uncertainty.

Science.gov (United States)

Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

2016-07-06

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Contact angle adjustment in equation-of-state-based pseudopotential model.

Science.gov (United States)

Hu, Anjie; Li, Longjian; Uddin, Rizwan; Liu, Dong

2016-05-01

The single component pseudopotential lattice Boltzmann model has been widely applied in multiphase simulation due to its simplicity and stability. In many studies, it has been claimed that this model can be stable for density ratios larger than 1000. However, the application of the model is still limited to small density ratios when the contact angle is considered. The reason is that the original contact angle adjustment method influences the stability of the model. Moreover, simulation results in the present work show that, by applying the original contact angle adjustment method, the density distribution near the wall is artificially changed, and the contact angle is dependent on the surface tension. Hence, it is very inconvenient to apply this method with a fixed contact angle, and the accuracy of the model cannot be guaranteed. To solve these problems, a contact angle adjustment method based on the geometry analysis is proposed and numerically compared with the original method. Simulation results show that, with our contact angle adjustment method, the stability of the model is highly improved when the density ratio is relatively large, and it is independent of the surface tension.

Efficient estimation of semiparametric copula models for bivariate survival data

KAUST Repository

Cheng, Guang

2014-01-01

A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.

Living donor risk model for predicting kidney allograft and patient survival in an emerging economy.

Science.gov (United States)

Zafar, Mirza Naqi; Wong, Germaine; Aziz, Tahir; Abbas, Khawar; Adibul Hasan Rizvi, S

2018-03-01

Living donor kidney is the main source of donor organs in low to middle income countries. We aimed to develop a living donor risk model that predicts graft and patient survival in an emerging economy. We used data from the Sindh Institute of Urology and Transplantation (SIUT) database (n = 2283 recipients and n = 2283 living kidney donors, transplanted between 1993 and 2009) and conducted Cox proportional hazard analyses to develop a composite score that predicts graft and patient survivals. Donor factors age, creatinine clearance, nephron dose (estimated by donor/recipient body weight ratio) and human leukocyte antigen (HLA) match were included in the living donor risk model. The adjusted hazard ratios (HRs) for graft failures among those who received a kidney with living donor scores (reference to donor score of zero) of 1, 2, 3 and 4 were 1.14 (95%CI: 0.94-1.39), 1.24 (95%CI:1.03-1.49), 1.25 (95%CI:1.03-1.51) and 1.36 (95%CI:1.08-1.72) (P-value for trend =0.05). Similar findings were observed for patient survival. Similar to findings in high income countries, our study suggests that donor characteristics such as age, nephron dose, creatinine clearance and HLA match are important factors that determine the long-term patient and graft survival in low income countries. However, other crucial but undefined factors may play a role in determining the overall risk of graft failure and mortality in living kidney donor transplant recipients. © 2016 Asian Pacific Society of Nephrology.

Geographic Variation in Oxaliplatin Chemotherapy and Survival in Patients With Colon Cancer.

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Panchal, Janki M; Lairson, David R; Chan, Wenyaw; Du, Xianglin L

2016-01-01

Geographic disparity in colon cancer survival has received less attention, despite the fact that health care delivery varied across regions. To examine geographic variation in colon cancer survival and explore factors affecting this variation, including the use of oxaliplatin chemotherapy, we studied cases with resected stage-III colon cancer in 2004-2009, identified from the Surveillance, Epidemiology and End Results-Medicare linked database. Cox proportional hazard model was used to estimate the effect of oxaliplatin-containing chemotherapy on survival across regions. Propensity score adjustments were made to control for potential selection bias and confounding. Rural regions showed lowest 3-year survival, whereas big metro regions showed better 3-year survival rate than any other region (67.3% in rural regions vs. 69.5% in big metro regions). Hazard ratio for patients residing in metro region was comparable with those residing in big metro region (1.27, 95% confidence interval: 0.90-1.80). However, patients residing in urban area were exhibiting lower mortality than those in other regions, although not statistically significant. Patients who received oxaliplatin chemotherapy were 23% significantly less likely to die of cancer than those received 5-fluorouracil only chemotherapy (adjusted hazard ratio = 0.77, 95% confidence interval: 0.63-0.95). In conclusion, there were some differences in survival across geographic regions, which were not statistically significant after adjusting for sociodemographic, tumor, chemotherapy, and other treatment characteristics. Oxaliplatin chemotherapy was associated with improved survival outcomes compared with 5-fluorouracil only chemotherapy across regions. Further studies may evaluate other factors and newer chemotherapy regimens on mortality/survival of older patients.

Disaster Hits Home: A Model of Displaced Family Adjustment after Hurricane Katrina

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Peek, Lori; Morrissey, Bridget; Marlatt, Holly

2011-01-01

The authors explored individual and family adjustment processes among parents (n = 30) and children (n = 55) who were displaced to Colorado after Hurricane Katrina. Drawing on in-depth interviews with 23 families, this article offers an inductive model of displaced family adjustment. Four stages of family adjustment are presented in the model: (a)…

Adjusting multistate capture-recapture models for misclassification bias: manatee breeding proportions

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Kendall, W.L.; Hines, J.E.; Nichols, J.D.

2003-01-01

Matrix population models are important tools for research and management of populations. Estimating the parameters of these models is an important step in applying them to real populations. Multistate capture-recapture methods have provided a useful means for estimating survival and parameters of transition between locations or life history states but have mostly relied on the assumption that the state occupied by each detected animal is known with certainty. Nevertheless, in some cases animals can be misclassified. Using multiple capture sessions within each period of interest, we developed a method that adjusts estimates of transition probabilities for bias due to misclassification. We applied this method to 10 years of sighting data for a population of Florida manatees (Trichechus manatus latirostris) in order to estimate the annual probability of transition from nonbreeding to breeding status. Some sighted females were unequivocally classified as breeders because they were clearly accompanied by a first-year calf. The remainder were classified, sometimes erroneously, as nonbreeders because an attendant first-year calf was not observed or was classified as more than one year old. We estimated a conditional breeding probability of 0.31 + 0.04 (estimate + 1 SE) when we ignored misclassification bias, and 0.61 + 0.09 when we accounted for misclassification.

An evaluation of bias in propensity score-adjusted non-linear regression models.

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Wan, Fei; Mitra, Nandita

2018-03-01

Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.

Partitioning of excess mortality in population-based cancer patient survival studies using flexible parametric survival models

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Eloranta Sandra

2012-06-01

Full Text Available Abstract Background Relative survival is commonly used for studying survival of cancer patients as it captures both the direct and indirect contribution of a cancer diagnosis on mortality by comparing the observed survival of the patients to the expected survival in a comparable cancer-free population. However, existing methods do not allow estimation of the impact of isolated conditions (e.g., excess cardiovascular mortality on the total excess mortality. For this purpose we extend flexible parametric survival models for relative survival, which use restricted cubic splines for the baseline cumulative excess hazard and for any time-dependent effects. Methods In the extended model we partition the excess mortality associated with a diagnosis of cancer through estimating a separate baseline excess hazard function for the outcomes under investigation. This is done by incorporating mutually exclusive background mortality rates, stratified by the underlying causes of death reported in the Swedish population, and by introducing cause of death as a time-dependent effect in the extended model. This approach thereby enables modeling of temporal trends in e.g., excess cardiovascular mortality and remaining cancer excess mortality simultaneously. Furthermore, we illustrate how the results from the proposed model can be used to derive crude probabilities of death due to the component parts, i.e., probabilities estimated in the presence of competing causes of death. Results The method is illustrated with examples where the total excess mortality experienced by patients diagnosed with breast cancer is partitioned into excess cardiovascular mortality and remaining cancer excess mortality. Conclusions The proposed method can be used to simultaneously study disease patterns and temporal trends for various causes of cancer-consequent deaths. Such information should be of interest for patients and clinicians as one way of improving prognosis after cancer is

Methodological aspects of journaling a dynamic adjusting entry model

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Vlasta Kašparovská

2011-01-01

Full Text Available This paper expands the discussion of the importance and function of adjusting entries for loan receivables. Discussion of the cyclical development of adjusting entries, their negative impact on the business cycle and potential solutions has intensified during the financial crisis. These discussions are still ongoing and continue to be relevant to members of the professional public, banking regulators and representatives of international accounting institutions. The objective of this paper is to evaluate a method of journaling dynamic adjusting entries under current accounting law. It also expresses the authors’ opinions on the potential for consistently implementing basic accounting principles in journaling adjusting entries for loan receivables under a dynamic model.

Capital Structure: Target Adjustment Model and a Mediation Moderation Model with Capital Structure as Mediator

OpenAIRE

Abedmajid, Mohammed

2015-01-01

This study consists of two models. Model one is conducted to check if there is a target adjustment toward optimal capital structure, in the context of Turkish firm listed on the stock market, over the period 2003-2014. Model 2 captures the interaction between firm size, profitability, market value and capital structure using the moderation mediation model. The results of model 1 have shown that there is a partial adjustment of the capital structure to reach target levels. The results of...

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.

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

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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.

Survival rate in nasopharyngeal carcinoma improved by high caseload volume: a nationwide population-based study in Taiwan

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Chou Pesus

2011-08-01

Full Text Available Abstract Background Positive correlation between caseload and outcome has previously been validated for several procedures and cancer treatments. However, there is no information linking caseload and outcome of nasopharyngeal carcinoma (NPC treatment. We used nationwide population-based data to examine the association between physician case volume and survival rates of patients with NPC. Methods Between 1998 and 2000, a total of 1225 patients were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity score were used to assess the relationship between 10-year survival rates and physician caseloads. Results As the caseload of individual physicians increased, unadjusted 10-year survival rates increased (p p = 0.001 after adjusting for comorbidities, hospital, and treatment modality. When analyzed by propensity score, the adjusted 10-year survival rate differed significantly between patients treated by high-volume physicians and patients treated by low/medium-volume physicians (75% vs. 61%; p Conclusions Our data confirm a positive volume-outcome relationship for NPC. After adjusting for differences in the case mix, our analysis found treatment of NPC by high-volume physicians improved 10-year survival rate.

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

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Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

2010-01-01

The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

Husbands' perceptions of their wives' breast cancer coping efficacy: testing congruence models of adjustment.

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Merluzzi, Thomas V; Martinez Sanchez, MaryAnn

2018-01-01

Recent reviews have reinforced the notion that having a supportive spouse can help with the process of coping with and adjusting to cancer. Congruence between spouses' perspectives has been proposed as one mechanism in that process, yet alternative models of congruence have not been examined closely. This study assessed alternative models of congruence in perceptions of coping and their mediating effects on adjustment to breast cancer. Seventy-two women in treatment for breast cancer and their husbands completed measures of marital adjustment, self-efficacy for coping, and adjustment to cancer. Karnofsky Performance Status was obtained from medical records. Wives completed a measure of self-efficacy for coping (wives' ratings of self-efficacy for coping [WSEC]) and husbands completed a measure of self-efficacy for coping (husbands' ratings of wives' self-efficacy for coping [HSEC]) based on their perceptions of their wives' coping efficacy. Interestingly, the correlation between WSEC and HSEC was only 0.207; thus, they are relatively independent perspectives. The following three models were tested to determine the nature of the relationship between WSEC and HSEC: discrepancy model (WSEC - HSEC), additive model (WSEC + HSEC), and multiplicative model (WSEC × HSEC). The discrepancy model was not related to wives' adjustment; however, the additive ( B =0.205, P <0.001) and multiplicative ( B =0.001, P <0.001) models were significantly related to wives' adjustment. Also, the additive model mediated the relationship between performance status and adjustment. Husbands' perception of their wives' coping efficacy contributed marginally to their wives' adjustment, and the combination of WSEC and HSEC mediated the relationship between functional status and wives' adjustment, thus positively impacting wives' adjustment to cancer. Future research is needed to determine the quality of the differences between HSEC and WSEC in order to develop interventions to optimize the

Survival and Neurodevelopmental Outcomes among Periviable Infants.

Science.gov (United States)

Younge, Noelle; Goldstein, Ricki F; Bann, Carla M; Hintz, Susan R; Patel, Ravi M; Smith, P Brian; Bell, Edward F; Rysavy, Matthew A; Duncan, Andrea F; Vohr, Betty R; Das, Abhik; Goldberg, Ronald N; Higgins, Rosemary D; Cotten, C Michael

2017-02-16

Data reported during the past 5 years indicate that rates of survival have increased among infants born at the borderline of viability, but less is known about how increased rates of survival among these infants relate to early childhood neurodevelopmental outcomes. We compared survival and neurodevelopmental outcomes among infants born at 22 to 24 weeks of gestation, as assessed at 18 to 22 months of corrected age, across three consecutive birth-year epochs (2000-2003 [epoch 1], 2004-2007 [epoch 2], and 2008-2011 [epoch 3]). The infants were born at 11 centers that participated in the National Institute of Child Health and Human Development Neonatal Research Network. The primary outcome measure was a three-level outcome - survival without neurodevelopmental impairment, survival with neurodevelopmental impairment, or death. After accounting for differences in infant characteristics, including birth center, we used multinomial generalized logit models to compare the relative risk of survival without neurodevelopmental impairment, survival with neurodevelopmental impairment, and death. Data on the primary outcome were available for 4274 of 4458 infants (96%) born at the 11 centers. The percentage of infants who survived increased from 30% (424 of 1391 infants) in epoch 1 to 36% (487 of 1348 infants) in epoch 3 (Pneurodevelopmental impairment increased from 16% (217 of 1391) in epoch 1 to 20% (276 of 1348) in epoch 3 (P=0.001), whereas the percentage of infants who survived with neurodevelopmental impairment did not change significantly (15% [207 of 1391] in epoch 1 and 16% [211 of 1348] in epoch 3, P=0.29). After adjustment for changes in the baseline characteristics of the infants over time, both the rate of survival with neurodevelopmental impairment (as compared with death) and the rate of survival without neurodevelopmental impairment (as compared with death) increased over time (adjusted relative risks, 1.27 [95% confidence interval {CI}, 1.01 to 1.59] and 1

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

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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.

Modelling the joint distribution of competing risks survival times using copula functions

OpenAIRE

Kaishev, V. K.; Haberman, S.; Dimitrova, D. S.

2005-01-01

The problem of modelling the joint distribution of survival times in a competing risks model, using copula functions is considered. In order to evaluate this joint distribution and the related overall survival function, a system of non-linear differential equations is solved, which relates the crude and net survival functions of the modelled competing risks, through the copula. A similar approach to modelling dependent multiple decrements was applied by Carriere (1994) who used a Gaussian cop...

A survivability model for ejection of green compacts in powder metallurgy technology

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Payman Ahi

2012-01-01

Full Text Available Reliability and quality assurance have become major considerations in the design and manufacture of today’s parts and products. Survivability of green compact using powder metallurgy technology is considered as one of the major quality attributes in manufacturing systems today. During powder metallurgy (PM production, the compaction conditions and behavior of the metal powder dictate the stress and density distribution in the green compact prior to sintering. These parameters greatly influence the mechanical properties and overall strength of the final component. In order to improve these properties, higher compaction pressures are usually employed, which make unloading and ejection of green compacts more challenging, especially for the powder-compacted parts with relatively complicated shapes. This study looked at a mathematical survivability model concerning green compact characteristics in PM technology and the stress-strength failure model in reliability engineering. This model depicts the relationship between mechanical loads (stress during ejection, experimentally determined green strength and survivability of green compact. The resulting survivability is the probability that a green compact survives during and after ejection. This survivability model can be used as an efficient tool for selecting the appropriate parameters for the process planning stage in PM technology. A case study is presented here in order to demonstrate the application of the proposed survivability model.

Rational Multi-curve Models with Counterparty-risk Valuation Adjustments

DEFF Research Database (Denmark)

Crépey, Stéphane; Macrina, Andrea; Nguyen, Tuyet Mai

2016-01-01

We develop a multi-curve term structure set-up in which the modelling ingredients are expressed by rational functionals of Markov processes. We calibrate to London Interbank Offer Rate swaptions data and show that a rational two-factor log-normal multi-curve model is sufficient to match market da...... with regulatory obligations. In order to compute counterparty-risk valuation adjustments, such as credit valuation adjustment, we show how default intensity processes with rational form can be derived. We flesh out our study by applying the results to a basis swap contract....... with accuracy. We elucidate the relationship between the models developed and calibrated under a risk-neutral measure Q and their consistent equivalence class under the real-world probability measure P. The consistent P-pricing models are applied to compute the risk exposures which may be required to comply...

Severity-Adjusted Mortality in Trauma Patients Transported by Police

Science.gov (United States)

Band, Roger A.; Salhi, Rama A.; Holena, Daniel N.; Powell, Elizabeth; Branas, Charles C.; Carr, Brendan G.

2018-01-01

Study objective Two decades ago, Philadelphia began allowing police transport of patients with penetrating trauma. We conduct a large, multiyear, citywide analysis of this policy. We examine the association between mode of out-of-hospital transport (police department versus emergency medical services [EMS]) and mortality among patients with penetrating trauma in Philadelphia. Methods This is a retrospective cohort study of trauma registry data. Patients who sustained any proximal penetrating trauma and presented to any Level I or II trauma center in Philadelphia between January 1, 2003, and December 31, 2007, were included. Analyses were conducted with logistic regression models and were adjusted for injury severity with the Trauma and Injury Severity Score and for case mix with a modified Charlson index. Results Four thousand one hundred twenty-two subjects were identified. Overall mortality was 27.4%. In unadjusted analyses, patients transported by police were more likely to die than patients transported by ambulance (29.8% versus 26.5%; OR 1.18; 95% confidence interval [CI] 1.00 to 1.39). In adjusted models, no significant difference was observed in overall mortality between the police department and EMS groups (odds ratio [OR] 0.78; 95% CI 0.61 to 1.01). In subgroup analysis, patients with severe injury (Injury Severity Score >15) (OR 0.73; 95% CI 0.59 to 0.90), patients with gunshot wounds (OR 0.70; 95% CI 0.53 to 0.94), and patients with stab wounds (OR 0.19; 95% CI 0.08 to 0.45) were more likely to survive if transported by police. Conclusion We found no significant overall difference in adjusted mortality between patients transported by the police department compared with EMS but found increased adjusted survival among 3 key subgroups of patients transported by police. This practice may augment traditional care. PMID:24387925

Premium adjustment: actuarial analysis on epidemiological models ...

African Journals Online (AJOL)

In this paper, we analyse insurance premium adjustment in the context of an epidemiological model where the insurer's future financial liability is greater than the premium from patients. In this situation, it becomes extremely difficult for the insurer since a negative reserve would severely increase its risk of insolvency, ...

SEMI-COMPETING RISKS ON A TRIVARIATE WEIBULL SURVIVAL MODEL

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Jenq-Daw Lee

2008-07-01

Full Text Available A setting of a trivairate survival function using semi-competing risks concept is proposed, in which a terminal event can only occur after other events. The Stanford Heart Transplant data is reanalyzed using a trivariate Weibull distribution model with the proposed survival function.

Machine learning models in breast cancer survival prediction.

Science.gov (United States)

Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

2016-01-01

Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

Science.gov (United States)

The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

Discrete dynamic modeling of T cell survival signaling networks

Science.gov (United States)

Zhang, Ranran

2009-03-01

Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

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.

Ensemble of cell survival experiments after ion irradiation for validation of RBE models

Energy Technology Data Exchange (ETDEWEB)

Friedrich, Thomas; Scholz, Uwe; Scholz, Michael [GSI Helmholtzzentrum fuer Schwerionenforschung, Darmstadt (Germany); Durante, Marco [GSI Helmholtzzentrum fuer Schwerionenforschung, Darmstadt (Germany); Institut fuer Festkoerperphysik, TU Darmstadt, Darmstadt (Germany)

2012-07-01

There is persistent interest in understanding the systematics of the relative biological effectiveness (RBE). Models such as the Local Effect Model (LEM) or the Microdosimetric Kinetic Model have the goal to predict the RBE. For the validation of these models a collection of many in-vitro cell survival experiments is most appropriate. The set-up of an ensemble of in-vitro cell survival data comprising about 850 survival experiments after both ion and photon irradiation is reported. The survival curves have been taken out from publications. The experiments encompass survival curves obtained in different labs, using different ion species from protons to uranium, varying irradiation modalities (shaped or monoenergetic beam), various energies and linear energy transfers, and a whole variety of cell types (human or rodent; normal, mutagenic or tumor; radioresistant or -sensitive). Each cell survival curve has been parameterized by the linear-quadratic model. The photon parameters have been added to the data base to allow to calculate the experimental RBE to any survival level. We report on experimental trends found within the data ensemble. The data will serve as a testing ground for RBE models such as the LEM. Finally, a roadmap for further validation and first model results using the data base in combination with the LEM are presented.

Dose-rate dependent stochastic effects in radiation cell-survival models

International Nuclear Information System (INIS)

Sachs, R.K.; Hlatky, L.R.

1990-01-01

When cells are subjected to ionizing radiation the specific energy rate (microscopic analog of dose-rate) varies from cell to cell. Within one cell, this rate fluctuates during the course of time; a crossing of a sensitive cellular site by a high energy charged particle produces many ionizations almost simultaneously, but during the interval between events no ionizations occur. In any cell-survival model one can incorporate the effect of such fluctuations without changing the basic biological assumptions. Using stochastic differential equations and Monte Carlo methods to take into account stochastic effects we calculated the dose-survival rfelationships in a number of current cell survival models. Some of the models assume quadratic misrepair; others assume saturable repair enzyme systems. It was found that a significant effect of random fluctuations is to decrease the theoretically predicted amount of dose-rate sparing. In the limit of low dose-rates neglecting the stochastic nature of specific energy rates often leads to qualitatively misleading results by overestimating the surviving fraction drastically. In the opposite limit of acute irradiation, analyzing the fluctuations in rates merely amounts to analyzing fluctuations in total specific energy via the usual microdosimetric specific energy distribution function, and neglecting fluctuations usually underestimates the surviving fraction. The Monte Carlo methods interpolate systematically between the low dose-rate and high dose-rate limits. As in other approaches, the slope of the survival curve at low dose-rates is virtually independent of dose and equals the initial slope of the survival curve for acute radiation. (orig.)

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

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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.

Statistical models and methods for reliability and survival analysis

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Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

2013-01-01

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

Impact of housing on the survival of persons with AIDS.

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Schwarcz, Sandra K; Hsu, Ling C; Vittinghoff, Eric; Vu, Annie; Bamberger, Joshua D; Katz, Mitchell H

2009-07-07

Homeless persons with HIV/AIDS have greater morbidity and mortality, more hospitalizations, less use of antiretroviral therapy, and worse medication adherence than HIV-infected persons who are stably housed. We examined the effect of homelessness on the mortality of persons with AIDS and measured the effect of supportive housing on AIDS survival. The San Francisco AIDS registry was used to identify homeless and housed persons who were diagnosed with AIDS between 1996 and 2006. The registry was computer-matched with a housing database of homeless persons who received housing after their AIDS diagnosis. The Kaplan-Meier product limit method was used to compare survival between persons who were homeless at AIDS diagnosis and those who were housed. Proportional hazards models were used to estimate the independent effects of homelessness and supportive housing on survival after AIDS diagnosis. Of the 6,558 AIDS cases, 9.8% were homeless at diagnosis. Sixty-seven percent of the persons who were homeless survived five years compared with 81% of those who were housed (p Homelessness increased the risk of death (adjusted relative hazard [RH] 1.20; 95% confidence limits [CL] 1.03, 1.41). Homeless persons with AIDS who obtained supportive housing had a lower risk of death than those who did not (adjusted RH 0.20; 95% CL 0.05, 0.81). Supportive housing ameliorates the negative effect of homelessness on survival with AIDS.

Improving Risk Adjustment for Mortality After Pediatric Cardiac Surgery: The UK PRAiS2 Model.

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Rogers, Libby; Brown, Katherine L; Franklin, Rodney C; Ambler, Gareth; Anderson, David; Barron, David J; Crowe, Sonya; English, Kate; Stickley, John; Tibby, Shane; Tsang, Victor; Utley, Martin; Witter, Thomas; Pagel, Christina

2017-07-01

Partial Risk Adjustment in Surgery (PRAiS), a risk model for 30-day mortality after children's heart surgery, has been used by the UK National Congenital Heart Disease Audit to report expected risk-adjusted survival since 2013. This study aimed to improve the model by incorporating additional comorbidity and diagnostic information. The model development dataset was all procedures performed between 2009 and 2014 in all UK and Ireland congenital cardiac centers. The outcome measure was death within each 30-day surgical episode. Model development followed an iterative process of clinical discussion and development and assessment of models using logistic regression under 25 × 5 cross-validation. Performance was measured using Akaike information criterion, the area under the receiver-operating characteristic curve (AUC), and calibration. The final model was assessed in an external 2014 to 2015 validation dataset. The development dataset comprised 21,838 30-day surgical episodes, with 539 deaths (mortality, 2.5%). The validation dataset comprised 4,207 episodes, with 97 deaths (mortality, 2.3%). The updated risk model included 15 procedural, 11 diagnostic, and 4 comorbidity groupings, and nonlinear functions of age and weight. Performance under cross-validation was: median AUC of 0.83 (range, 0.82 to 0.83), median calibration slope and intercept of 0.92 (range, 0.64 to 1.25) and -0.23 (range, -1.08 to 0.85) respectively. In the validation dataset, the AUC was 0.86 (95% confidence interval [CI], 0.82 to 0.89), and the calibration slope and intercept were 1.01 (95% CI, 0.83 to 1.18) and 0.11 (95% CI, -0.45 to 0.67), respectively, showing excellent performance. A more sophisticated PRAiS2 risk model for UK use was developed with additional comorbidity and diagnostic information, alongside age and weight as nonlinear variables. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Survival after out-of-hospital cardiac arrest in relation to sex

DEFF Research Database (Denmark)

Wissenberg, Mads; Hansen, Carolina Malta; Folke, Fredrik

2014-01-01

); and in females (4.8% in 2001 to 6.7% in 2010), psexes in patients with a non-shockable rhythm (OR 1.00; CI 0.72-1.40), while female sex was positively associated...... 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.......AIM: 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. METHODS: Patients≥12 years old with OHCA of a presumed cardiac cause, and in whom resuscitation...

Cancer survival among Alaska Native people.

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Nash, Sarah H; Meisner, Angela L W; Zimpelman, Garrett L; Barry, Marc; Wiggins, Charles L

2018-03-26

Recent cancer survival trends among American Indian and Alaska Native (AN) people are not well understood; survival has not been reported among AN people since 2001. This study examined cause-specific survival among AN cancer patients for lung, colorectal, female breast, prostate, and kidney cancers. It evaluated whether survival differed between cancers diagnosed in 1992-2002 (the earlier period) and cancers diagnosed in 2003-2013 (the later period) and by the age at diagnosis (<65 vs ≥65 years), stage at diagnosis (local or regional/distant/unknown), and sex. Kaplan-Meier and Cox proportional hazards models were used to estimate univariate and multivariate-adjusted cause-specific survival for each cancer. An improvement was observed in 5-year survival over time from lung cancer (hazard ratio [HR] for the later period vs the earlier period, 0.83; 95% confidence interval [CI], 0.72-0.97), and a marginally nonsignificant improvement was observed for colorectal cancer (HR, 0.81; 95% CI, 0.66-1.01). Site-specific differences in survival were observed by age and stage at diagnosis. This study presents the first data on cancer survival among AN people in almost 2 decades. During this time, AN people have experienced improvements in survival from lung and colorectal cancers. The reasons for these improvements may include increased access to care (including screening) as well as improvements in treatment. Improving cancer survival should be a priority for reducing the burden of cancer among AN people and eliminating cancer disparities. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.

Estimating true instead of apparent survival using spatial Cormack-Jolly-Seber models

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Schaub, Michael; Royle, J. Andrew

2014-01-01

Survival is often estimated from capture–recapture data using Cormack–Jolly–Seber (CJS) models, where mortality and emigration cannot be distinguished, and the estimated apparent survival probability is the product of the probabilities of true survival and of study area fidelity. Consequently, apparent survival is lower than true survival unless study area fidelity equals one. Underestimation of true survival from capture–recapture data is a main limitation of the method.

Socioeconomic Status, Not Race, Is Associated With Reduced Survival in Esophagectomy Patients.

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Erhunmwunsee, Loretta; Gulack, Brian C; Rushing, Christel; Niedzwiecki, Donna; Berry, Mark F; Hartwig, Matthew G

2017-07-01

Black patients with esophageal cancer have worse survival than white patients. This study examines this racial disparity in conjunction with socioeconomic status (SES) and explores whether race-based outcome differences exist using a national database. The associations between race and SES with overall survival of patients treated with esophagectomy for stages I to III esophageal cancer between 2003 and 2011 in the National Cancer Data Base were investigated using the Kaplan-Meier method and proportional hazards analyses. Median income by zip code and proportion of the zip code residents without a high school diploma were grouped into income and education quartiles, respectively and used as surrogates for SES. The association between race and overall survival stratified by SES is explored. Of 11,599 esophagectomy patients who met study criteria, 3,503 (30.2%) were in the highest income quartile, 2,847 (24.5%) were in the highest education quartile, and 610 patients (5%) were black. Before adjustment for SES, black patients had worse overall survival than white patients (median survival 23.0 versus 34.7 months, log rank p race was not. Prior studies have suggested that survival of esophageal cancer patients after esophagectomy is associated with race. Our study suggests that race is not significantly related to overall survival when adjusted for other prognostic variables. Socioeconomic status, however, remains significantly related to overall survival in our model. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Impact of individual and neighborhood factors on disparities in prostate cancer survival.

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DeRouen, Mindy C; Schupp, Clayton W; Koo, Jocelyn; Yang, Juan; Hertz, Andrew; Shariff-Marco, Salma; Cockburn, Myles; Nelson, David O; Ingles, Sue A; John, Esther M; Gomez, Scarlett L

2018-04-01

We addressed the hypothesis that individual-level factors act jointly with social and built environment factors to influence overall survival for men with prostate cancer and contribute to racial/ethnic and socioeconomic (SES) survival disparities. We analyzed multi-level data, combining (1) individual-level data from the California Collaborative Prostate Cancer Study, a population-based study of non-Hispanic White (NHW), Hispanic, and African American prostate cancer cases (N = 1800) diagnosed from 1997 to 2003, with (2) data on neighborhood SES (nSES) and social and built environment factors from the California Neighborhoods Data System, and (3) data on tumor characteristics, treatment and follow-up through 2009 from the California Cancer Registry. Multivariable, stage-stratified Cox proportional hazards regression models with cluster adjustments were used to assess education and nSES main and joint effects on overall survival, before and after adjustment for social and built environment factors. African American men had worse survival than NHW men, which was attenuated by nSES. Increased risk of death was associated with residence in lower SES neighborhoods (quintile 1 (lowest nSES) vs. 5: HR = 1.56, 95% CI: 1.11-2.19) and lower education (Adjustment for behavioral, hospital, and restaurant and food environment characteristics only slightly attenuated these associations between SES and survival. Both individual- and contextual-level SES influence overall survival of men with prostate cancer. Additional research is needed to identify the mechanisms underlying these robust associations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Implication of Mauk Nursing Rehabilitation Model on Adjustment of Stroke Patients

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Zeinab Ebrahimpour mouziraji

2014-12-01

Full Text Available Objectives: Stroke is a neurological syndrome with sudden onset or gradual destruction of brain vessels, which may take 24 hours or more. Complications of stroke effect in the variation aspects of the individual. According to De Spulveda and Chang’s Studies, disability reduced the effective adjustment. This study aimed to overview the adjustment of stroke patients based on the main concepts of rehabilitation nursing Mauk model. Methods: In a quasi-experimental one group pre-posttest design study, data was collected in the neurology clinic of Imam Khomeini hospital and stroke patient rehabilitation centers in Tehran (Tabassom. Data collection included demographic and adjustment questionnaires of stroke patients. The intervention included seven sessions as Mauk model, each session with one hour training, for seven patients. Data analysis performed with SPSS software with paired t-test and was compared with previous results. Results: There were significant differences between the mean scores of patients with stroke adjustment questionnaire in the pre-test-post-test. But in the adjustment sub-scales, except for relationship with wife and Personal adjustment, in other areas, there is no statistically significant difference between the pre and posttest. Discussion: The results indicated that training has been affected on some aspects of adjustment of stroke patients in order to, as improving functions, complications and its limitations. Nurses can help then with implementing of plans such as patients education in this regard.

Using cure models for analyzing the influence of pathogens on salmon survival

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Ray, Adam R; Perry, Russell W.; Som, Nicholas A.; Bartholomew, Jerri L

2014-01-01

Parasites and pathogens influence the size and stability of wildlife populations, yet many population models ignore the population-level effects of pathogens. Standard survival analysis methods (e.g., accelerated failure time models) are used to assess how survival rates are influenced by disease. However, they assume that each individual is equally susceptible and will eventually experience the event of interest; this assumption is not typically satisfied with regard to pathogens of wildlife populations. In contrast, mixture cure models, which comprise logistic regression and survival analysis components, allow for different covariates to be entered into each part of the model and provide better predictions of survival when a fraction of the population is expected to survive a disease outbreak. We fitted mixture cure models to the host–pathogen dynamics of Chinook Salmon Oncorhynchus tshawytscha and Coho Salmon O. kisutch and the myxozoan parasite Ceratomyxa shasta. Total parasite concentration, water temperature, and discharge were used as covariates to predict the observed parasite-induced mortality in juvenile salmonids collected as part of a long-term monitoring program in the Klamath River, California. The mixture cure models predicted the observed total mortality well, but some of the variability in observed mortality rates was not captured by the models. Parasite concentration and water temperature were positively associated with total mortality and the mortality rate of both Chinook Salmon and Coho Salmon. Discharge was positively associated with total mortality for both species but only affected the mortality rate for Coho Salmon. The mixture cure models provide insights into how daily survival rates change over time in Chinook Salmon and Coho Salmon after they become infected with C. shasta.

Genetic value of herd life adjusted for milk production.

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Allaire, F R; Gibson, J P

1992-05-01

Cow herd life adjusted for lactational milk production was investigated as a genetic trait in the breeding objective. Under a simple model, the relative economic weight of milk to adjusted herd life on a per genetic standard deviation basis was equal to CVY/dCVL where CVY and CVL are the genetic coefficients of variation of milk production and adjusted herd life, respectively, and d is the depreciation per year per cow divided by the total fixed costs per year per cow. The relative economic value of milk to adjusted herd life at the prices and parameters for North America was about 3.2. An increase of 100-kg milk was equivalent to 2.2 mo of adjusted herd life. Three to 7% lower economic gain is expected when only improved milk production is sought compared with a breeding objective that included both production and adjusted herd life for relative value changed +/- 20%. A favorable economic gain to cost ratio probably exists for herd life used as a genetic trait to supplement milk in the breeding objective. Cow survival records are inexpensive, and herd life evaluations from such records may not extend the generation interval when such an evaluation is used in bull sire selection.

[Smoking and student survival at Universidad Santiago de Cali, 2004-2007].

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Tafur-Calderón, Luis A; Millán-Estupiñan, Juan C; Zapata-Ossa, Helmer; Ordoñez-Arana, Gustavo A; Varela, Jesús M

2010-04-01

This article presents the results of monitoring students who enrolled at Universidad Santiago de Cali (USC) during the second half of 2004. Its purpose was to determine the influence of smoking, the academic programme and the cost of enrollment on student survival over a three-year period (2004-2007). The study involved a prospective cohort of 970 students who entered the university in 2004. Cox regression was used for survival analysis to determine the relationship between independent variables and university stay. The results of this model established associations between smoking and department with survival in the university, but discarded association with the cost of enrollment. The risk of university desertion was higher amongst students from the Health faculty adjusted for smoking (RR = 1.277 (1.121-1.455)). Similarly, the risk of desertion was higher in smokers adjusted by faculty (RR = 1.194 (1.026-1.390). It was found that habitual smokers had shorter university stay than nonsmokers. University stay was longer in students enrolled in academic programmes other than health.

Capital adjustment cost and bias in income based dynamic panel models with fixed effects

OpenAIRE

Yoseph Yilma Getachew; Keshab Bhattarai; Parantap Basu

2012-01-01

The fixed effects (FE) estimator of "conditional convergence" in income based dynamic panel models could be biased downward when capital adjustment cost is present. Such a capital adjustment cost means a rising marginal cost of investment which could slow down the convergence. The standard FE regression fails to take into account of this capital adjustment cost and thus it could overestimate the rate of convergence. Using a Ramsey model with long-run adjustment cost of capital, we characteriz...

Ethnicity and health care in cervical cancer survival: comparisons between a Filipino resident population, Filipino-Americans, and Caucasians.

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Redaniel, Maria Theresa; Laudico, Adriano; Mirasol-Lumague, Maria Rica; Gondos, Adam; Uy, Gemma Leonora; Toral, Jean Ann; Benavides, Doris; Brenner, Hermann

2009-08-01

Few studies have assessed and compared cervical cancer survival between developed and developing countries, or between ethnic groups within a country. Fewer still have addressed how much of the international or interracial survival differences can be attributed to ethnicity or health care. To determine the role of ethnicity and health care, 5-year survival of patients with cervical cancer was compared between patients in the Philippines and Filipino-Americans, who have the same ethnicity, and between Filipino-Americans and Caucasians, who have the same health care system. Cervical cancer databases from the Manila and Rizal Cancer Registries and Surveillance, Epidemiology, and End Results 13 were used. Age-adjusted 5-year survival estimates were computed and compared between the three patient groups. Using Cox proportional hazards modeling, potential determinants of survival differences were examined. Overall 5-year relative survival was similar in Filipino-Americans (68.8%) and Caucasians (66.6%), but was lower for Philippine residents (42.9%). Although late stage at diagnosis explained a large proportion of the survival differences between Philippine residents and Filipino-Americans, excess mortality prevailed after adjustment for stage, age, and morphology in multivariate analysis [relative risk (RR), 2.07; 95% confidence interval (CI), 1.68-2.55]. Excess mortality decreased, but persisted, when treatments were included in the multivariate models (RR, 1.78; 95% CI, 1.41-2.23). A moderate, marginally significant excess mortality was found among Caucasians compared with Filipino-Americans (adjusted RR, 1.22; 95% CI, 1.01-1.47). The differences in cervical cancer survival between patients in the Philippines and in the United States highlight the importance of enhanced health care and access to diagnostic and treatment facilities in the Philippines.

Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan.

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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.

Preoperative atrial fibrillation and long-term survival after open heart surgery in a rural tertiary heart institute.

Science.gov (United States)

O'Neal, Wesley T; Efird, Jimmy T; Davies, Stephen W; Choi, Yuk Ming; Anderson, Curtis A; Kindell, Linda C; O'Neal, Jason B; Ferguson, T Bruce; Chitwood, W Randolph; Kypson, Alan P

2013-01-01

Preoperative atrial fibrillation (AF) is associated with increased morbidity and mortality after open heart surgery. However, the impact of preoperative AF on long-term survival after open heart surgery has not been widely examined in rural populations. Patients from rural regions are less likely to receive treatment for cardiac conditions and to have adequate medical insurance coverage. To examine the influence of preoperative AF on long-term survival following open heart surgery in rural eastern North Carolina. Long-term survival was compared in patients with and without preoperative AF after coronary artery bypass grafting (CABG) and CABG plus valve (CABG + V) surgery between 2002 and 2011. Hazard ratios (HR) and 95% confidence intervals (CI) were computed using a Cox regression model. The study population consisted of 5438 patients. A total of 263 (5%) patients had preoperative AF. Preoperative AF was an independent predictor of long-term survival (open heart surgery: adjusted HR = 1.6, 95% CI = 1.3-2.0; CABG: adjusted HR = 1.6, 95% CI = 1.3-2.1; CABG + V: adjusted HR = 1.6, 95% CI = 1.1-2.3). Preoperative AF is an important predictor of long-term survival after open heart surgery in this rural population. Copyright © 2013 Elsevier Inc. All rights reserved.

The frontotemporal syndrome of ALS is associated with poor survival.

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Govaarts, Rosanne; Beeldman, Emma; Kampelmacher, Mike J; van Tol, Marie-Jose; van den Berg, Leonard H; van der Kooi, Anneke J; Wijkstra, Peter J; Zijnen-Suyker, Marianne; Cobben, Nicolle A M; Schmand, Ben A; de Haan, Rob J; de Visser, Marianne; Raaphorst, Joost

2016-12-01

Thirty percent of ALS patients have a frontotemporal syndrome (FS), defined as behavioral changes or cognitive impairment. Despite previous studies, there are no firm conclusions on the effect of the FS on survival and the use of non-invasive ventilation (NIV) in ALS. We examined the effect of the FS on survival and the start and duration of NIV in ALS. Behavioral changes were defined as >22 points on the ALS-Frontotemporal-Dementia-Questionnaire or ≥3 points on ≥2 items of the Neuropsychiatric Inventory. Cognitive impairment was defined as below the fifth percentile on ≥2 tests of executive function, memory or language. Classic ALS was defined as ALS without the frontotemporal syndrome. We performed survival analyses from symptom onset and time from NIV initiation, respectively, to death. The impact of the explanatory variables on survival and NIV initiation were examined using Cox proportional hazards models. We included 110 ALS patients (76 men) with a mean age of 62 years. Median survival time was 4.3 years (95 % CI 3.53-5.13). Forty-seven patients (43 %) had an FS. Factors associated with shorter survival were FS, bulbar onset, older age at onset, short time to diagnosis and a C9orf72 repeat expansion. The adjusted hazard ratio (HR) for the FS was 2.29 (95 % CI 1.44-3.65, p NIV initiation (adjusted HR 2.70, 95 % CI 1.04-4.67, p = 0.04). In conclusion, there is an association between the frontotemporal syndrome and poor survival in ALS, which remains present after initiation of NIV.

Early Pancreatic Ductal Adenocarcinoma Survival Is Dependent on Size: Positive Implications for Future Targeted Screening.

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Hur, Chin; Tramontano, Angela C; Dowling, Emily C; Brooks, Gabriel A; Jeon, Alvin; Brugge, William R; Gazelle, G Scott; Kong, Chung Yin; Pandharipande, Pari V

2016-08-01

Pancreatic ductal adenocarcinoma (PDAC) has not experienced a meaningful mortality improvement for the past few decades. Successful screening is difficult to accomplish because most PDACs present late in their natural history, and current interventions have not provided significant benefit. Our goal was to identify determinants of survival for early PDAC to help inform future screening strategies. Early PDACs from the National Cancer Institute's Surveillance, Epidemiology, and End Results Program database (2000-2010) were analyzed. We stratified by size and included carcinomas in situ (Tis). Overall cancer-specific survival was calculated. A Cox proportional hazards model was developed and the significance of key covariates for survival prediction was evaluated. A Kaplan-Meier plot demonstrated significant differences in survival by size at diagnosis; these survival benefits persisted after adjustment for key covariates in the Cox proportional hazards analysis. In addition, relatively weaker predictors of worse survival included older age, male sex, black race, nodal involvement, tumor location within the head of the pancreas, and no surgery or radiotherapy. For early PDAC, we found tumor size to be the strongest predictor of survival, even after adjustment for other patient characteristics. Our findings suggest that early PDAC detection can have clinical benefit, which has positive implications for future screening strategies.

Comparison of Cox and Gray's survival models in severe sepsis

DEFF Research Database (Denmark)

Kasal, Jan; Andersen, Zorana Jovanovic; Clermont, Gilles

2004-01-01

Although survival is traditionally modeled using Cox proportional hazards modeling, this approach may be inappropriate in sepsis, in which the proportional hazards assumption does not hold. Newer, more flexible models, such as Gray's model, may be more appropriate....

Estimation and model selection of semiparametric multivariate survival functions under general censorship.

Science.gov (United States)

Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

2010-07-01

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

Parenting Stress, Mental Health, Dyadic Adjustment: A Structural Equation Model

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Luca Rollè

2017-05-01

Full Text Available Objective: In the 1st year of the post-partum period, parenting stress, mental health, and dyadic adjustment are important for the wellbeing of both parents and the child. However, there are few studies that analyze the relationship among these three dimensions. The aim of this study is to investigate the relationships between parenting stress, mental health (depressive and anxiety symptoms, and dyadic adjustment among first-time parents.Method: We studied 268 parents (134 couples of healthy babies. At 12 months post-partum, both parents filled out, in a counterbalanced order, the Parenting Stress Index-Short Form, the Edinburgh Post-natal Depression Scale, the State-Trait Anxiety Inventory, and the Dyadic Adjustment Scale. Structural equation modeling was used to analyze the potential mediating effects of mental health on the relationship between parenting stress and dyadic adjustment.Results: Results showed the full mediation effect of mental health between parenting stress and dyadic adjustment. A multi-group analysis further found that the paths did not differ across mothers and fathers.Discussion: The results suggest that mental health is an important dimension that mediates the relationship between parenting stress and dyadic adjustment in the transition to parenthood.

Individual and Neighborhood Socioeconomic Status and Healthcare Resources in Relation to Black-White Breast Cancer Survival Disparities

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Tomi F. Akinyemiju

2013-01-01

Full Text Available Background. Breast cancer survival has improved significantly in the US in the past 10–15 years. However, disparities exist in breast cancer survival between black and white women. Purpose. To investigate the effect of county healthcare resources and SES as well as individual SES status on breast cancer survival disparities between black and white women. Methods. Data from 1,796 breast cancer cases were obtained from the Surveillance Epidemiology and End Results and the National Longitudinal Mortality Study dataset. Cox Proportional Hazards models were constructed accounting for clustering within counties. Three sequential Cox models were fit for each outcome including demographic variables; demographic and clinical variables; and finally demographic, clinical, and county-level variables. Results. In unadjusted analysis, black women had a 53% higher likelihood of dying of breast cancer and 32% higher likelihood of dying of any cause (P<0.05 compared with white women. Adjusting for demographic variables explained away the effect of race on breast cancer survival (HR, 1.40; 95% CI, 0.99–1.97, but not on all-cause mortality. The racial difference in all-cause survival disappeared only after adjusting for county-level variables (HR, 1.27; CI, 0.95–1.71. Conclusions. Improving equitable access to healthcare for all women in the US may help eliminate survival disparities between racial and socioeconomic groups.

Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

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Boone, Spencer

2017-01-01

This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

The effect of individual and neighborhood socioeconomic status on gastric cancer survival.

Directory of Open Access Journals (Sweden)

Chin-Chia Wu

Full Text Available PURPOSE: Gastric cancer is a leading cause of death, particularly in the developing world. The literature reports individual socioeconomic status (SES or neighborhood SES as related to survival, but the effect of both has not been studied. This study investigated the effect of individual and neighborhood SES simultaneously on mortality in gastric cancer patients in Taiwan. MATERIALS AND METHODS: A study was conducted of 3,396 patients diagnosed with gastric cancer between 2002 and 2006. Each patient was followed for five years or until death. Individual SES was defined by income-related insurance premium (low, moderate, and high. Neighborhood SES was based on household income dichotomized into advantaged and disadvantaged areas. Multilevel logistic regression model was used to compare survival rates by SES group after adjusting for possible confounding factors. RESULTS: In patients younger than 65 years, 5-year overall survival rates were lowest for those with low individual SES. After adjusting for patient characteristics (age, gender, Charlson Comorbidity Index Score, gastric cancer patients with high individual SES had 68% risk reduction of mortality (adjusted odds ratio [OR] of mortality, 0.32; 95% confidence interval [CI], 0.17-0.61. Patients aged 65 and above had no statistically significant difference in mortality rates by individual SES group. Different neighborhood SES did not statistically differ in the survival rates. CONCLUSION: Gastric cancer patients aged less than 65 years old with low individual SES have higher risk of mortality, even under an universal healthcare system. Public health strategies, education and welfare policies should seek to correct the inequality in gastric cancer survival, especially in those with lower individual SES.

Survival impact of early lymph node staging in a national study on 454 Danish men with penile cancer

DEFF Research Database (Denmark)

Jakobsen, J. K.; Krarup, K. P.; Sommer, P.

2015-01-01

N) stage so extranodal metastatic extension entails stage pN3. We report population based national survival data from 454 Danish penile cancer patients staged according to the TNM 2009 criteria and evaluate the survival impact of lymph node staging at diagnosis. MATERIAL & METHODS: Penile squamous cell...... intervals. Survival impact of lymph node staging was evaluated in a multivariate cox regression model with adjustment for tumour stage, age and Charlson comorbidity score. RESULTS: Of a total of 454 men 39 did not undergo lymph node staging of any kind. Median follow-up of patients who survived was 7......-45) %. Penile cancer-specific 5-year survival for pN0, pN1, pN2, pN3 and pNx patients was 97 (94-98)%, 82 (62- 92)%, 57 (36-74)%, 12 (5-22)% and 53 (35-69)%. Lymph node staging had a significant impact on penile cancer specific survival after adjustment for age, T-stage and comorbidity (Nx vs all N0, N1, N2, N3...

Risk adjustment models for short-term outcomes after surgical resection for oesophagogastric cancer.

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Fischer, C; Lingsma, H; Hardwick, R; Cromwell, D A; Steyerberg, E; Groene, O

2016-01-01

Outcomes for oesophagogastric cancer surgery are compared with the aim of benchmarking quality of care. Adjusting for patient characteristics is crucial to avoid biased comparisons between providers. The study objective was to develop a case-mix adjustment model for comparing 30- and 90-day mortality and anastomotic leakage rates after oesophagogastric cancer resections. The study reviewed existing models, considered expert opinion and examined audit data in order to select predictors that were consequently used to develop a case-mix adjustment model for the National Oesophago-Gastric Cancer Audit, covering England and Wales. Models were developed on patients undergoing surgical resection between April 2011 and March 2013 using logistic regression. Model calibration and discrimination was quantified using a bootstrap procedure. Most existing risk models for oesophagogastric resections were methodologically weak, outdated or based on detailed laboratory data that are not generally available. In 4882 patients with oesophagogastric cancer used for model development, 30- and 90-day mortality rates were 2·3 and 4·4 per cent respectively, and 6·2 per cent of patients developed an anastomotic leak. The internally validated models, based on predictors selected from the literature, showed moderate discrimination (area under the receiver operating characteristic (ROC) curve 0·646 for 30-day mortality, 0·664 for 90-day mortality and 0·587 for anastomotic leakage) and good calibration. Based on available data, three case-mix adjustment models for postoperative outcomes in patients undergoing curative surgery for oesophagogastric cancer were developed. These models should be used for risk adjustment when assessing hospital performance in the National Health Service, and tested in other large health systems. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.

Increasing incidence and survival in oral cancer

DEFF Research Database (Denmark)

Karnov, Kirstine Kim Schmidt; Grønhøj, Christian; Jensen, David Hebbelstrup

2017-01-01

Background: Oral carcinomas (OCs) make up a significant proportion of head and neck carcinomas (HNCs) and are an important cause of morbidity and mortality globally. The purpose of this population-based study was to determine trends in incidence and survival in OC in the Danish population from 1980...... to 2014. Material and methods: This study covered all patients registered in the nationwide Danish cancer registry (DCR) in the period 1980–2014. Age-adjusted incidence rate (AAIR) per 100,000 and annual percentage change (APC) were evaluated. Also, 5-year overall survival (OS) was calculated with Cox......-standardized incidence of OC during the last 30 years in Denmark, and also an improvement in survival. The 5-year OS was significantly better in recent years even when we adjusted the analysis for relevant covariates....

Steps in the construction and verification of an explanatory model of psychosocial adjustment

Directory of Open Access Journals (Sweden)

Arantzazu Rodríguez-Fernández

2016-06-01

Full Text Available The aim of the present study was to empirically test an explanatory model of psychosocial adjustment during adolescence, with psychosocial adjustment during this stage being understood as a combination of school adjustment (or school engagement and subjective well-being. According to the hypothetic model, psychosocial adjustment depends on self-concept and resilience, which in turn act as mediators of the influence of perceived social support (from family, peers and teachers on this adjustment. Participants were 1250 secondary school students (638 girls and 612 boys aged between 12 and 15 years (Mean = 13.72; SD = 1.09. The results provided evidence of: (a the influence of all three types of perceived support on subject resilience and self-concept, with perceived family support being particularly important in this respect; (b the influence of the support received from teachers on school adjustment and support received from the family on psychological wellbeing; and (c the absence of any direct influence of peer support on psychosocial adjustment, although indirect influence was observed through the psychological variables studied. These results are discussed from an educational perspective and in terms of future research.

Steps in the construction and verification of an explanatory model of psychosocial adjustment

Directory of Open Access Journals (Sweden)

Arantzazu Rodríguez-Fernández

2016-06-01

Full Text Available The aim of the present study was to empirically test an explanatory model of psychosocial adjustment during adolescence, with psychosocial adjustment during this stage being understood as a combination of school adjustment (or school engagement and subjective well-being. According to the hypothetic model, psychosocial adjustment depends on self-concept and resilience, which in turn act as mediators of the influence of perceived social support (from family, peers and teachers on this adjustment. Participants were 1250 secondary school students (638 girls and 612 boys aged between 12 and 15 years (Mean = 13.72; SD = 1.09. The results provided evidence of: (a the influence of all three types of perceived support on subject resilience and self-concept, with perceived family support being particularly important in this respect; (b the influence of the support received from teachers on school adjustment and support received from the family on psychological wellbeing; and (c the absence of any direct influence of peer support on psychosocial adjustment, although indirect influence was observed through the psychological variables studied. These results are discussed from an educational perspective and in terms of future research

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

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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.

Economic evaluation of nivolumab for the treatment of second-line advanced squamous NSCLC in Canada: a comparison of modeling approaches to estimate and extrapolate survival outcomes.

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Goeree, Ron; Villeneuve, Julie; Goeree, Jeff; Penrod, John R; Orsini, Lucinda; Tahami Monfared, Amir Abbas

2016-06-01

Background Lung cancer is the most common type of cancer in the world and is associated with significant mortality. Nivolumab demonstrated statistically significant improvements in progression-free survival (PFS) and overall survival (OS) for patients with advanced squamous non-small cell lung cancer (NSCLC) who were previously treated. The cost-effectiveness of nivolumab has not been assessed in Canada. A contentious component of projecting long-term cost and outcomes in cancer relates to the modeling approach adopted, with the two most common approaches being partitioned survival (PS) and Markov models. The objectives of this analysis were to estimate the cost-utility of nivolumab and to compare the results using these alternative modeling approaches. Methods Both PS and Markov models were developed using docetaxel and erlotinib as comparators. A three-health state model was used consisting of progression-free, progressed disease, and death. Disease progression and time to progression were estimated by identifying best-fitting survival curves from the clinical trial data for PFS and OS. Expected costs and health outcomes were calculated by combining health-state occupancy with medical resource use and quality-of-life assigned to each of the three health states. The health outcomes included in the model were survival and quality-adjusted-life-years (QALYs). Results Nivolumab was found to have the highest expected per-patient cost, but also improved per-patient life years (LYs) and QALYs. Nivolumab cost an additional $151,560 and $140,601 per QALY gained compared to docetaxel and erlotinib, respectively, using a PS model approach. The cost-utility estimates using a Markov model were very similar ($152,229 and $141,838, respectively, per QALY gained). Conclusions Nivolumab was found to involve a trade-off between improved patient survival and QALYs, and increased cost. It was found that the use of a PS or Markov model produced very similar estimates of expected cost

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

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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.

Individual and Neighborhood Socioeconomic Status and Health care Resources in Relation to Black-White Breast Cancer Survival Disparities

International Nuclear Information System (INIS)

Akinyemiju, T. F.

2013-01-01

Breast cancer survival has improved significantly in the US in the past 10-15 years. However, disparities exist in breast cancer survival between black and white women. Purpose. To investigate the effect of county health care resources and SES as well as individual SES status on breast cancer survival disparities between black and white women. Methods. Data from 1,796 breast cancer cases were obtained from the Surveillance Epidemiology and End Results and the National Longitudinal Mortality Study dataset. Cox Proportional Hazards models were constructed accounting for clustering within counties. Three sequential Cox models were fit for each outcome including demographic variables; demographic and clinical variables; and finally demographic, clinical, and county-level variables. Results. In unadjusted analysis, black women had a 53% higher likelihood of dying of breast cancer and 32% higher likelihood of dying of any cause ( P < 0.05) compared with white women. Adjusting for demographic variables explained away the effect of race on breast cancer survival (HR, 1.40; 95% CI, 0.99-1.97), but not on all-cause mortality. The racial difference in all-cause survival disappeared only after adjusting for county-level variables (HR, 1.27; CI, 0.95-1.71). Conclusions. Improving equitable access to health care for all women in the US may help eliminate survival disparities between racial and socioeconomic groups.

Adjusting the Stems Regional Forest Growth Model to Improve Local Predictions

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W. Brad Smith

1983-01-01

A simple procedure using double sampling is described for adjusting growth in the STEMS regional forest growth model to compensate for subregional variations. Predictive accuracy of the STEMS model (a distance-independent, individual tree growth model for Lake States forests) was improved by using this procedure

Does stage of cancer, comorbidity or lifestyle factors explain educational differences in survival after endometrial cancer? A cohort study among Danish women diagnosed 2005-2009.

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Seidelin, Ulla Holten; Ibfelt, Else; Andersen, Ingelise; Steding-Jessen, Marianne; Høgdall, Claus; Kjær, Susanne Krüger; Dalton, Susanne Oksbjerg

2016-06-01

Several studies have documented an association between socioeconomic position and survival from gynaecological cancer, but the mechanisms are unclear. The aim of this study was to examine the association between level of education and survival after endometrial cancer among Danish women; and whether differences in stage at diagnosis and comorbidity contribute to the educational differences in survival. Women with endometrial cancer diagnosed between 2005 and 2009 were identified in the Danish Gynaecological Cancer Database, with information on clinical characteristics, surgery, body mass index (BMI) and smoking status. Information on highest attained education, cohabitation and comorbidity was obtained from nationwide administrative registries. Logistic regression models were used to determine the association between level of education and cancer stage and Cox proportional hazards model for analyses of overall survival. Of the 3638 patients identified during the study period, 787 had died by the end of 2011. The group of patients with short education had a higher odds ratio (OR) for advanced stage at diagnosis, but this was not statistically significant (adjusted OR 1.20; 95% CI 0.97-1.49). The age-adjusted hazard ratio (HR) for dying of patients with short education was 1.47 (CI 95% 1.17-1.80). Adjustment for cohabitation status, BMI, smoking and comorbidity did not change HRs, but further adjustment for cancer stage yielded a HR of 1.36 (1.11-1.67). Early detection in all educational groups might reduce social inequalities in survival, however, the unexplained increased risk for death after adjustment for prognostic factors, warrants increased attention to patients with short education in all age groups throughout treatment and rehabilitation.

Malformations associated with congenital diaphragmatic hernia: Impact on survival.

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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.

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2014-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2013-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Blood Lead, Bone Turnover, and Survival in Amyotrophic Lateral Sclerosis.

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Fang, Fang; Peters, Tracy L; Beard, John D; Umbach, David M; Keller, Jean; Mariosa, Daniela; Allen, Kelli D; Ye, Weimin; Sandler, Dale P; Schmidt, Silke; Kamel, Freya

2017-11-01

Blood lead and bone turnover may be associated with the risk of amyotrophic lateral sclerosis (ALS). We aimed to assess whether these factors were also associated with time from ALS diagnosis to death through a survival analysis of 145 ALS patients enrolled during 2007 in the National Registry of Veterans with ALS. Associations of survival time with blood lead and plasma biomarkers of bone resorption (C-terminal telopeptides of type I collagen (CTX)) and bone formation (procollagen type I amino-terminal peptide (PINP)) were estimated using Cox models adjusted for age at diagnosis, diagnostic certainty, diagnostic delay, site of onset, and score on the Revised ALS Functional Rating Scale. Hazard ratios were calculated for each doubling of biomarker concentration. Blood lead, plasma CTX, and plasma PINP were mutually adjusted for one another. Increased lead (hazard ratio (HR) = 1.38; 95% confidence interval (CI): 1.03, 1.84) and CTX (HR = 2.03; 95% CI: 1.42, 2.89) were both associated with shorter survival, whereas higher PINP was associated with longer survival (HR = 0.59; 95% CI: 0.42, 0.83), after ALS diagnosis. No interactions were observed between lead or bone turnover and other prognostic indicators. Lead toxicity and bone metabolism may be involved in ALS pathophysiology. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Intra-industry adjustment to import competition: theory and application to the German clothing industry

OpenAIRE

Raff, Horst; Wagner, Joachim

2009-01-01

This paper uses an oligopoly model with heterogeneous firms to examine how an industry adjusts to rising import competition. The model predicts that in the short run the least efficient firms in the industry become inactive, surviving firms face a fall in output, mark-ups and profits, and the average productivity of survivors increases. These pro-competitive effects of import penetration on the domestic industry disappear in the long run. The predictions for the short run are confirmed in an ...

Adjusting for treatment switching in randomised controlled trials - A simulation study and a simplified two-stage method.

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Latimer, Nicholas R; Abrams, K R; Lambert, P C; Crowther, M J; Wailoo, A J; Morden, J P; Akehurst, R L; Campbell, M J

2017-04-01

Estimates of the overall survival benefit of new cancer treatments are often confounded by treatment switching in randomised controlled trials (RCTs) - whereby patients randomised to the control group are permitted to switch onto the experimental treatment upon disease progression. In health technology assessment, estimates of the unconfounded overall survival benefit associated with the new treatment are needed. Several switching adjustment methods have been advocated in the literature, some of which have been used in health technology assessment. However, it is unclear which methods are likely to produce least bias in realistic RCT-based scenarios. We simulated RCTs in which switching, associated with patient prognosis, was permitted. Treatment effect size and time dependency, switching proportions and disease severity were varied across scenarios. We assessed the performance of alternative adjustment methods based upon bias, coverage and mean squared error, related to the estimation of true restricted mean survival in the absence of switching in the control group. We found that when the treatment effect was not time-dependent, rank preserving structural failure time models (RPSFTM) and iterative parameter estimation methods produced low levels of bias. However, in the presence of a time-dependent treatment effect, these methods produced higher levels of bias, similar to those produced by an inverse probability of censoring weights method. The inverse probability of censoring weights and structural nested models produced high levels of bias when switching proportions exceeded 85%. A simplified two-stage Weibull method produced low bias across all scenarios and provided the treatment switching mechanism is suitable, represents an appropriate adjustment method.

Socioeconomic deprivation and survival after stroke: findings from the prospective South London Stroke Register of 1995 to 2011.

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Chen, Ruoling; McKevitt, Christopher; Rudd, Anthony G; Wolfe, Charles D A

2014-01-01

Previous findings of the association between socioeconomic deprivation (SED) and survival after stroke are inconsistent. There is less investigation on long-term survival. We assessed the associations in a multi-ethnic population in England. We examined data from 4398 patients (3103 whites, 932 blacks, and 253 Asians/others) with first-ever stroke, collected by a population-based stroke register in South London from 1995 to 2011. SED was measured using the Carstairs index score-the higher score, the more deprived. It was analyzed in multivariate Cox regression models in relation to survival after stroke. During 17-year follow-up 2754 patients died. The quartile data of Carstairs score showed no significant association of SED with survival in patients, except for black Caribbeans and Africans. Black patients with the fourth quartile SED had a multivariate adjusted hazard ratio of 1.76 (95% confidence interval, 1.06-2.94) for 3-month mortality and 1.54 (1.00-2.37) for 1-year mortality. After adjustment for acute stroke care provisions, these were no longer significant. However, the sextile data of Carstairs score showed a consistent association of SED with survival after stroke; all patients with the sixth sextile had a fully adjusted hazard ratio of 1.23 (1.05-1.44) for 3-month mortality and 1.13 (1.01-1.25) for 17-year mortality. There is a weak but significant association of SED with reduced survival after stroke in England. SED in blacks may have a stronger impact on short-term survival when compared with white patients. Further efforts are required to achieve equality in survival among patients with stroke of different socioeconomic groups.

Accounting for Uncertainty in Decision Analytic Models Using Rank Preserving Structural Failure Time Modeling: Application to Parametric Survival Models.

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Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua

2018-01-01

Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Hepatic retransplantation in New England--a regional experience and survival model.

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Powelson, J A; Cosimi, A B; Lewis, W D; Rohrer, R J; Freeman, R B; Vacanti, J P; Jonas, M; Lorber, M I; Marks, W H; Bradley, J

1993-04-01

Hepatic retransplantation (reTx) offers the only alternative to death for patients who have failed primary hepatic transplantation (PTx). Assuming a finite number of donor organs, reTx also denies the chance of survival for some patients awaiting PTx. The impact of reTx on overall survival (i.e., the survival of all candidates for transplantation) must therefore be clarified. Between 1983 and 1991, 651 patients from the New England Organ Bank underwent liver transplantation, and 73 reTx were performed in 71 patients (11% reTx rate). The 1-year actuarial survival for reTx (48%) was significantly less than for PTx (70%, P 365 days, 83%). Patients on the regional waiting list had an 18% mortality rate while awaiting transplantation. These results were incorporated into a mathematical model describing survival as a function of reTx rate, assuming a limited supply of donor livers. ReTx improves the 1-year survival rate for patients undergoing PTx but decreases overall survival (survival of all candidates) for liver transplantation. In the current era of persistently insufficient donor numbers, strategies based on minimizing the use of reTx, especially in the case of patients in whom chances of success are minimal, will result in the best overall rate of patient survival.

Modeling survival: application of the Andersen-Gill model to Yellowstone grizzly bears

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Johnson, Christopher J.; Boyce, Mark S.; Schwartz, Charles C.; Haroldson, Mark A.

2004-01-01

 Wildlife ecologists often use the Kaplan-Meier procedure or Cox proportional hazards model to estimate survival rates, distributions, and magnitude of risk factors. The Andersen-Gill formulation (A-G) of the Cox proportional hazards model has seen limited application to mark-resight data but has a number of advantages, including the ability to accommodate left-censored data, time-varying covariates, multiple events, and discontinuous intervals of risks. We introduce the A-G model including structure of data, interpretation of results, and assessment of assumptions. We then apply the model to 22 years of radiotelemetry data for grizzly bears (Ursus arctos) of the Greater Yellowstone Grizzly Bear Recovery Zone in Montana, Idaho, and Wyoming, USA. We used Akaike's Information Criterion (AICc) and multi-model inference to assess a number of potentially useful predictive models relative to explanatory covariates for demography, human disturbance, and habitat. Using the most parsimonious models, we generated risk ratios, hypothetical survival curves, and a map of the spatial distribution of high-risk areas across the recovery zone. Our results were in agreement with past studies of mortality factors for Yellowstone grizzly bears. Holding other covariates constant, mortality was highest for bears that were subjected to repeated management actions and inhabited areas with high road densities outside Yellowstone National Park. Hazard models developed with covariates descriptive of foraging habitats were not the most parsimonious, but they suggested that high-elevation areas offered lower risks of mortality when compared to agricultural areas.

Radar adjusted data versus modelled precipitation: a case study over Cyprus

Directory of Open Access Journals (Sweden)

M. Casaioli

2006-01-01

Full Text Available In the framework of the European VOLTAIRE project (Fifth Framework Programme, simulations of relatively heavy precipitation events, which occurred over the island of Cyprus, by means of numerical atmospheric models were performed. One of the aims of the project was indeed the comparison of modelled rainfall fields with multi-sensor observations. Thus, for the 5 March 2003 event, the 24-h accumulated precipitation BOlogna Limited Area Model (BOLAM forecast was compared with the available observations reconstructed from ground-based radar data and estimated by rain gauge data. Since radar data may be affected by errors depending on the distance from the radar, these data could be range-adjusted by using other sensors. In this case, the Precipitation Radar aboard the Tropical Rainfall Measuring Mission (TRMM satellite was used to adjust the ground-based radar data with a two-parameter scheme. Thus, in this work, two observational fields were employed: the rain gauge gridded analysis and the observational analysis obtained by merging the range-adjusted radar and rain gauge fields. In order to verify the modelled precipitation, both non-parametric skill scores and the contiguous rain area (CRA analysis were applied. Skill score results show some differences when using the two observational fields. CRA results are instead quite in agreement, showing that in general a 0.27° eastward shift optimizes the forecast with respect to the two observational analyses. This result is also supported by a subjective inspection of the shifted forecast field, whose gross features agree with the analysis pattern more than the non-shifted forecast one. However, some open questions, especially regarding the effect of other range adjustment techniques, remain open and need to be addressed in future works.

Survival outcomes of pediatric osteosarcoma and Ewing's sarcoma: a comparison of surgery type within the SEER database, 1988-2007.

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Schrager, Justin; Patzer, Rachel E; Mink, Pamela J; Ward, Kevin C; Goodman, Michael

2011-01-01

Survival following diagnosis of pediatric Ewing's sarcoma or osteosarcoma is increasing in the United States, but whether survival differs between patients who receive limb salvage surgery compared to amputation has not been evaluated in nationally representative, population-based data. Multivariable-adjusted survival was calculated using Cox regression models among surgically treated pediatric (age Ewing's sarcoma patients with bone cancer of the limbs or joints reported to the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program during 1988-2007. Over half (66.3%) of the 890 osteosarcoma patients underwent limb salvage surgery. Five-year overall survival among patients who received limb salvage was 72.7% for osteosarcoma patients and 71.8% for Ewing's sarcoma patients. Among patients who received amputation, 5-year survival was 60.1% for osteosarcoma and 63.1% for Ewing's sarcoma patients. After multivariable adjustment, the mortality was 35% greater for amputation vs limb salvage (HR=1.35, 95% CI: 1.05-1.75). Among 165 Ewing's sarcoma patients, 73.9% underwent limb salvage (vs amputation), and the adjusted mortality was higher for patients receiving amputation, although results were not statistically significant (HR=1.61, 95% CI: 0.80-3.21). Limb salvage surgery (vs amputation) is associated with longer survival among pediatric patients with bone cancer of the limbs or joints. Patient and physician characteristics and the effectiveness of neoadjuvant therapy may play a role in surgery choice, but we were unable to control for these factors.

Predictive modelling of Lactobacillus casei KN291 survival in fermented soy beverage.

Science.gov (United States)

Zielińska, Dorota; Dorota, Zielińska; Kołożyn-Krajewska, Danuta; Danuta, Kołożyn-Krajewska; Goryl, Antoni; Antoni, Goryl; Motyl, Ilona

2014-02-01

The aim of the study was to construct and verify predictive growth and survival models of a potentially probiotic bacteria in fermented soy beverage. The research material included natural soy beverage (Polgrunt, Poland) and the strain of lactic acid bacteria (LAB) - Lactobacillus casei KN291. To construct predictive models for the growth and survival of L. casei KN291 bacteria in the fermented soy beverage we design an experiment which allowed the collection of CFU data. Fermented soy beverage samples were stored at various temperature conditions (5, 10, 15, and 20°C) for 28 days. On the basis of obtained data concerning the survival of L. casei KN291 bacteria in soy beverage at different temperature and time conditions, two non-linear models (r(2)= 0.68-0.93) and two surface models (r(2)=0.76-0.79) were constructed; these models described the behaviour of the bacteria in the product to a satisfactory extent. Verification of the surface models was carried out utilizing the validation data - at 7°C during 28 days. It was found that applied models were well fitted and charged with small systematic errors, which is evidenced by accuracy factor - Af, bias factor - Bf and mean squared error - MSE. The constructed microbiological growth and survival models of L. casei KN291 in fermented soy beverage enable the estimation of products shelf life period, which in this case is defined by the requirement for the level of the bacteria to be above 10(6) CFU/cm(3). The constructed models may be useful as a tool for the manufacture of probiotic foods to estimate of their shelf life period.

Key factors influencing lung cancer survival in northern Italy.

Science.gov (United States)

Mangone, Lucia; Minicozzi, Pamela; Vicentini, Massimo; Giacomin, Adriano; Caldarella, Adele; Cirilli, Claudia; Falcini, Fabio; Giorgi Rossi, Paolo; Sant, Milena

2013-06-01

Lung cancer is a major cause of cancer death worldwide. The aims of this study were to analyze presentation, treatment and survival for lung cancer in northern Italy, and identify factors influencing survival. A total of 1180 lung cancer cases diagnosed in four north Italian cancer registries (Biella, Modena, Reggio Emilia, Romagna) in 2003-2005 were analyzed. Information on morphology, stage, diagnostic examinations, chemotherapy, radiotherapy, and surgical treatment was collected from clinical records. Three-year relative survival and relative excess risks of death were estimated. Overall, 10% of cases were stage I, 50% stage IV, and 12% stage unknown. Romagna - where sophisticated diagnostic examinations were performed more often - had proportionately more microscopically verified cases and resected cases than Biella. Romagna had also high proportions of cases given chemotherapy and radiotherapy. Three-year survival was 14%, range 10% (Biella) to 19% (Romagna); 69% for stage I, 3% for stage IV. Stage I survival was higher in Romagna (82%) than Reggio Emilia and Biella (60-61%) but for operated stage I cases, survival was similar (88%) in Romagna and Biella. The fully adjusted model showed a higher risk of death in Biella (1.23, 95%CI 1.02-1.48) than Modena (reference). Stage and surgery are key factors influencing survival. Centralizing lung cancer treatment to improve diagnostic work-up may improve outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improved survival for non-Hodgkin lymphoma patients in New South Wales, Australia

Directory of Open Access Journals (Sweden)

O'Connell Dianne L

2010-05-01

Full Text Available Abstract Background We evaluated if the survival benefit of adding rituximab to standard chemotherapy for non-Hodgkin lymphoma (NHL observed in clinical trials has been experienced by an Australian NHL patient population. Methods NHL cases diagnosed in 1985-2004 in New South Wales (NSW were followed-up to the end of 2004. Rituximab prescription data were obtained from Medicare Australia. Using a Poisson regression model adjusted for age group, sex, NHL subtype and time period (1990-1994, 1995-1999 and 2000-2004, we estimated excess risk of death after a diagnosis of NHL. To give context to the survival trend, trends in incidence and mortality were also estimated. Results Compared with 1990-1994, after adjusting for age, sex and NHL subtype the relative excess risk of death was significantly lower (p Conclusion It is likely that some benefit of adding rituximab to the standard chemotherapy for NHL has been experienced at the population level.

Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

Science.gov (United States)

Qiao, Hong; Xi, Xuanyang; Li, Yinlin; Wu, Wei; Li, Fengfu

2015-11-01

Recently, many computational models have been proposed to simulate visual cognition process. For example, the hierarchical Max-Pooling (HMAX) model was proposed according to the hierarchical and bottom-up structure of V1 to V4 in the ventral pathway of primate visual cortex, which could achieve position- and scale-tolerant recognition. In our previous work, we have introduced memory and association into the HMAX model to simulate visual cognition process. In this paper, we improve our theoretical framework by mimicking a more elaborate structure and function of the primate visual cortex. We will mainly focus on the new formation of memory and association in visual processing under different circumstances as well as preliminary cognition and active adjustment in the inferior temporal cortex, which are absent in the HMAX model. The main contributions of this paper are: 1) in the memory and association part, we apply deep convolutional neural networks to extract various episodic features of the objects since people use different features for object recognition. Moreover, to achieve a fast and robust recognition in the retrieval and association process, different types of features are stored in separated clusters and the feature binding of the same object is stimulated in a loop discharge manner and 2) in the preliminary cognition and active adjustment part, we introduce preliminary cognition to classify different types of objects since distinct neural circuits in a human brain are used for identification of various types of objects. Furthermore, active cognition adjustment of occlusion and orientation is implemented to the model to mimic the top-down effect in human cognition process. Finally, our model is evaluated on two face databases CAS-PEAL-R1 and AR. The results demonstrate that our model exhibits its efficiency on visual recognition process with much lower memory storage requirement and a better performance compared with the traditional purely computational

Urate levels predict survival in amyotrophic lateral sclerosis: Analysis of the expanded Pooled Resource Open-Access ALS clinical trials database.

Science.gov (United States)

Paganoni, Sabrina; Nicholson, Katharine; Chan, James; Shui, Amy; Schoenfeld, David; Sherman, Alexander; Berry, James; Cudkowicz, Merit; Atassi, Nazem

2018-03-01

Urate has been identified as a predictor of amyotrophic lateral sclerosis (ALS) survival in some but not all studies. Here we leverage the recent expansion of the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to study the association between urate levels and ALS survival. Pooled data of 1,736 ALS participants from the PRO-ACT database were analyzed. Cox proportional hazards regression models were used to evaluate associations between urate levels at trial entry and survival. After adjustment for potential confounders (i.e., creatinine and body mass index), there was an 11% reduction in risk of reaching a survival endpoint during the study with each 1-mg/dL increase in uric acid levels (adjusted hazard ratio 0.89, 95% confidence interval 0.82-0.97, P ALS and confirms the utility of the PRO-ACT database as a powerful resource for ALS epidemiological research. Muscle Nerve 57: 430-434, 2018. © 2017 Wiley Periodicals, Inc.

Survival As a Quality Metric of Cancer Care: Use of the National Cancer Data Base to Assess Hospital Performance.

Science.gov (United States)

Shulman, Lawrence N; Palis, Bryan E; McCabe, Ryan; Mallin, Kathy; Loomis, Ashley; Winchester, David; McKellar, Daniel

2018-01-01

Survival is considered an important indicator of the quality of cancer care, but the validity of different methodologies to measure comparative survival rates is less well understood. We explored whether the National Cancer Data Base (NCDB) could serve as a source of unadjusted and risk-adjusted cancer survival data and whether these data could be used as quality indicators for individual hospitals or in the aggregate by hospital type. The NCDB, an aggregate of > 1,500 hospital cancer registries, was queried to analyze unadjusted and risk-adjusted hazards of death for patients with stage III breast cancer (n = 116,787) and stage IIIB or IV non-small-cell lung cancer (n = 252,392). Data were analyzed at the individual hospital level and by hospital type. At the hospital level, after risk adjustment, few hospitals had comparative risk-adjusted survival rates that were statistically better or worse. By hospital type, National Cancer Institute-designated comprehensive cancer centers had risk-adjusted survival ratios that were statistically significantly better than those of academic cancer centers and community hospitals. Using the NCDB as the data source, survival rates for patients with stage III breast cancer and stage IIIB or IV non-small-cell lung cancer were statistically better at National Cancer Institute-designated comprehensive cancer centers when compared with other hospital types. Compared with academic hospitals, risk-adjusted survival was lower in community hospitals. At the individual hospital level, after risk adjustment, few hospitals were shown to have statistically better or worse survival, suggesting that, using NCDB data, survival may not be a good metric to determine relative quality of cancer care at this level.

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

Science.gov (United States)

Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

2012-01-01

State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

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.

NanOx, a new model to predict cell survival in the context of particle therapy

Science.gov (United States)

Cunha, M.; Monini, C.; Testa, E.; Beuve, M.

2017-02-01

Particle therapy is increasingly attractive for the treatment of tumors and the number of facilities offering it is rising worldwide. Due to the well-known enhanced effectiveness of ions, it is of utmost importance to plan treatments with great care to ensure tumor killing and healthy tissues sparing. Hence, the accurate quantification of the relative biological effectiveness (RBE) of ions, used in the calculation of the biological dose, is critical. Nevertheless, the RBE is a complex function of many parameters and its determination requires modeling. The approaches currently used have allowed particle therapy to thrive, but still show some shortcomings. We present herein a short description of a new theoretical framework, NanOx, to calculate cell survival in the context of particle therapy. It gathers principles from existing approaches, while addressing some of their weaknesses. NanOx is a multiscale model that takes the stochastic nature of radiation at nanometric and micrometric scales fully into account, integrating also the chemical aspects of radiation-matter interaction. The latter are included in the model by means of a chemical specific energy, determined from the production of reactive chemical species induced by irradiation. Such a production represents the accumulation of oxidative stress and sublethal damage in the cell, potentially generating non-local lethal events in NanOx. The complementary local lethal events occur in a very localized region and can, alone, lead to cell death. Both these classes of events contribute to cell death. The comparison between experimental data and model predictions for the V79 cell line show a good agreement. In particular, the dependence of the typical shoulders of cell survival curves on linear energy transfer are well described, but also the effectiveness of different ions, including the overkill effect. These results required the adjustment of a number of parameters compatible with the application of the model in

Adjusting for the Confounding Effects of Treatment Switching—The BREAK-3 Trial: Dabrafenib Versus Dacarbazine

Science.gov (United States)

Abrams, Keith R.; Amonkar, Mayur M.; Stapelkamp, Ceilidh; Swann, R. Suzanne

2015-01-01

Background. Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48–1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Materials and Methods. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, “treatment group” (assumes treatment effect could continue until death) and “on-treatment observed” (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. Results. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE “treatment group” and “on-treatment observed” analyses performed similarly well. Conclusion. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching—a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Implications for Practice: Treatment switching is common in oncology trials, and the implications of this for the interpretation of the

Adjusting for the Confounding Effects of Treatment Switching-The BREAK-3 Trial: Dabrafenib Versus Dacarbazine.

Science.gov (United States)

Latimer, Nicholas R; Abrams, Keith R; Amonkar, Mayur M; Stapelkamp, Ceilidh; Swann, R Suzanne

2015-07-01

Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48-1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, "treatment group" (assumes treatment effect could continue until death) and "on-treatment observed" (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE "treatment group" and "on-treatment observed" analyses performed similarly well. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching-a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making. Treatment switching is common in oncology trials, and the implications of this for the interpretation of the clinical effectiveness and cost-effectiveness of the novel treatment are important to consider. If

Cell survival in carbon beams - comparison of amorphous track model predictions

DEFF Research Database (Denmark)

Grzanka, L.; Greilich, S.; Korcyl, M.

Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under i....... Amorphous track modelling of luminescence detector efficiency in proton and carbon beams. 4.Tsuruoka C, Suzuki M, Kanai T, et al. LET and ion species dependence for cell killing in normal human skin fibroblasts. Radiat Res. 2005;163:494-500.......Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under ion....... [2] . In addition, a new approach based on microdosimetric distributions is presented and investigated [3] . Material and methods: A suitable software library embrasing the mentioned amorphous track models including numerous submodels with respect to delta-electron range models, radial dose...

Emotional closeness to parents and grandparents: A moderated mediation model predicting adolescent adjustment.

Science.gov (United States)

Attar-Schwartz, Shalhevet

2015-09-01

Warm and emotionally close relationships with parents and grandparents have been found in previous studies to be linked with better adolescent adjustment. The present study, informed by Family Systems Theory and Intergenerational Solidarity Theory, uses a moderated mediation model analyzing the contribution of the dynamics of these intergenerational relationships to adolescent adjustment. Specifically, it examines the mediating role of emotional closeness to the closest grandparent in the relationship between emotional closeness to a parent (the offspring of the closest grandparent) and adolescent adjustment difficulties. The model also examines the moderating role of emotional closeness to parents in the relationship between emotional closeness to grandparents and adjustment difficulties. The study was based on a sample of 1,405 Jewish Israeli secondary school students (ages 12-18) who completed a structured questionnaire. It was found that emotional closeness to the closest grandparent was more strongly associated with reduced adjustment difficulties among adolescents with higher levels of emotional closeness to their parents. In addition, adolescent adjustment and emotional closeness to parents was partially mediated by emotional closeness to grandparents. Examining the family conditions under which adolescents' relationships with grandparents is stronger and more beneficial for them can help elucidate variations in grandparent-grandchild ties and expand our understanding of the mechanisms that shape child outcomes. (c) 2015 APA, all rights reserved).

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.

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

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.

A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

Energy Technology Data Exchange (ETDEWEB)

Oberije, Cary, E-mail: cary.oberije@maastro.nl [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); De Ruysscher, Dirk [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Universitaire Ziekenhuizen Leuven, KU Leuven (Belgium); Houben, Ruud [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Heuvel, Michel van de; Uyterlinde, Wilma [Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Deasy, Joseph O. [Memorial Sloan Kettering Cancer Center, New York (United States); Belderbos, Jose [Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Dingemans, Anne-Marie C. [Department of Pulmonology, University Hospital Maastricht, Research Institute GROW of Oncology, Maastricht (Netherlands); Rimner, Andreas; Din, Shaun [Memorial Sloan Kettering Cancer Center, New York (United States); Lambin, Philippe [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands)

2015-07-15

Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

PACE and the Medicare+Choice risk-adjusted payment model.

Science.gov (United States)

Temkin-Greener, H; Meiners, M R; Gruenberg, L

2001-01-01

This paper investigates the impact of the Medicare principal inpatient diagnostic cost group (PIP-DCG) payment model on the Program of All-Inclusive Care for the Elderly (PACE). Currently, more than 6,000 Medicare beneficiaries who are nursing home certifiable receive care from PACE, a program poised for expansion under the Balanced Budget Act of 1997. Overall, our analysis suggests that the application of the PIP-DCG model to the PACE program would reduce Medicare payments to PACE, on average, by 38%. The PIP-DCG payment model bases its risk adjustment on inpatient diagnoses and does not capture adequately the risk of caring for a population with functional impairments.

Disparities in cervical cancer survival among Asian American women

Science.gov (United States)

Nghiem, Van T.; Davies, Kalatu R.; Chan, Wenyaw; Mulla, Zuber D.; Cantor, Scott B.

2015-01-01

Purpose We compared overall survival and influencing factors between Asian American women as a whole and by subgroup with white women with cervical cancer. Methods Cervical cancer data were from the Surveillance, Epidemiology, and End Results registry; socioeconomic information was from the Area Health Resource File. We used standard tests to compare characteristics between groups; the Kaplan-Meier method with log-rank test to assess overall survival and compare it between groups; and Cox proportional hazards models to determine the effect of race and other covariates on overall survival (with/without age-stratification). Results Being 3.3 years older than white women at diagnosis (pAsian American women were more likely to be in a spousal relationship, had more progressive disease, and were better off socioeconomically. Women of Filipino, Japanese, and Korean origin had similar clinical characteristics compared with white women. Asian American women had higher 36- and 60-month survival rates (p=0.004 and p=0.013, respectively), higher overall survival rates (p=0.049), and longer overall survival durations after adjusting for age and other covariates (hazard ratio=0.77, 95% confidence interval: 0.68–0.86). Overall survival differed across age strata between the two racial groups. With the exception of women of Japanese or Korean origin, Asian American women grouped by geographic origin had better overall survival than white women. Conclusions Although Asian American women, except those of Japanese or Korean origin, had better overall survival than white women, their older age at cervical cancer diagnosis suggests that they have less access to screening programs. PMID:26552330

Disparities in cervical cancer survival among Asian-American women.

Science.gov (United States)

Nghiem, Van T; Davies, Kalatu R; Chan, Wenyaw; Mulla, Zuber D; Cantor, Scott B

2016-01-01

We compared overall survival and influencing factors between Asian-American women as a whole and by subgroup with white women with cervical cancer. Cervical cancer data were from the Surveillance, Epidemiology, and End Results registry; socioeconomic information was from the Area Health Resource File. We used standard tests to compare characteristics between groups; the Kaplan-Meier method with log-rank test to assess overall survival and compare it between groups; and Cox proportional hazards models to determine the effect of race and other covariates on overall survival (with and/or without age stratification). Being 3.3 years older than white women at diagnosis (P Asian-American women were more likely to be in a spousal relationship, had more progressive disease, and were better off socioeconomically. Women of Filipino, Japanese, and Korean origin had similar clinical characteristics compared to white women. Asian-American women had higher 36- and 60-month survival rates (P = .004 and P = .013, respectively), higher overall survival rates (P = .049), and longer overall survival durations after adjusting for age and other covariates (hazard ratio = 0.77, 95% confidence interval: 0.68-0.86). Overall survival differed across age strata between the two racial groups. With the exception of women of Japanese or Korean origin, Asian-American women grouped by geographic origin had better overall survival than white women. Although Asian-American women, except those of Japanese or Korean origin, had better overall survival than white women, their older age at cervical cancer diagnosis suggests that they have less access to screening programs. Copyright © 2016 Elsevier Inc. All rights reserved.

CT findings associated with survival in chronic hypersensitivity pneumonitis

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Chung, Jonathan H.; Montner, Steven M.; Adegunsoye, Ayodeji; Vij, Rekha; Noth, Imre; Strek, Mary E.; Oldham, Justin M.; Husain, Aliya N.

2017-01-01

To identify CT findings in chronic hypersensitivity pneumonitis (cHP) associated with survival. Two thoracic radiologists assessed CT scans for specific imaging findings and patterns in 132 subjects with cHP. Survival analyses were performed. The majority of subjects had an inconsistent with usual interstitial pneumonitis pattern on CT (55.3%,73/132). Hypersensitivity pneumonitis (HP) diagnosis on CT was less common in those with fibrosis (66.1%, 74/112) than those without fibrosis (85%,17/20). Smoking was associated with a lower prevalence of HP on CT (p=0.04). CT features of pulmonary fibrosis, especially traction bronchiectasis (HR 8.34, 95% CI 1.98-35.21) and increased pulmonary artery (PA)/aorta ratio (HR 2.49, 95% CI 1.27-4.89) were associated with worse survival, while ground-glass opacity (HR 0.31, 95% CI 0.12-0.79) was associated with improved survival. Survival association with imaging was less pronounced after adjustment for gender, age and physiology score. A substantial proportion of cHP cases have a non-HP-like appearance. Ground-glass opacity, pulmonary fibrosis features and elevated PA/aorta ratio on CT likely reflect varying degrees of disease severity in cHP and may inform future clinical prediction models. (orig.)

CT findings associated with survival in chronic hypersensitivity pneumonitis

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Chung, Jonathan H.; Montner, Steven M. [University of Chicago Medical Center, Department of Radiology, Chicago, IL (United States); Adegunsoye, Ayodeji; Vij, Rekha; Noth, Imre; Strek, Mary E. [University of Chicago Medical Center, Section of Pulmonary/Critical Care, Department of Medicine, Chicago, IL (United States); Oldham, Justin M. [University of California at Davis, Section of Pulmonary/Critical Care, Department of Medicine, Sacramento, CA (United States); Husain, Aliya N. [University of Chicago Medical Center, Department of Pathology, Chicago, IL (United States)

2017-12-15

To identify CT findings in chronic hypersensitivity pneumonitis (cHP) associated with survival. Two thoracic radiologists assessed CT scans for specific imaging findings and patterns in 132 subjects with cHP. Survival analyses were performed. The majority of subjects had an inconsistent with usual interstitial pneumonitis pattern on CT (55.3%,73/132). Hypersensitivity pneumonitis (HP) diagnosis on CT was less common in those with fibrosis (66.1%, 74/112) than those without fibrosis (85%,17/20). Smoking was associated with a lower prevalence of HP on CT (p=0.04). CT features of pulmonary fibrosis, especially traction bronchiectasis (HR 8.34, 95% CI 1.98-35.21) and increased pulmonary artery (PA)/aorta ratio (HR 2.49, 95% CI 1.27-4.89) were associated with worse survival, while ground-glass opacity (HR 0.31, 95% CI 0.12-0.79) was associated with improved survival. Survival association with imaging was less pronounced after adjustment for gender, age and physiology score. A substantial proportion of cHP cases have a non-HP-like appearance. Ground-glass opacity, pulmonary fibrosis features and elevated PA/aorta ratio on CT likely reflect varying degrees of disease severity in cHP and may inform future clinical prediction models. (orig.)

No association of CpG island methylator phenotype and colorectal cancer survival: population-based study.

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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.

Female breast cancer incidence and survival in Utah according to religious preference, 1985-1999.

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Merrill, Ray M; Folsom, Jeffrey A

2005-05-18

Female breast cancer incidence rates in Utah are among the lowest in the U.S. The influence of the Church of Jesus Christ of Latter-day Saint (LDS or Mormon) religion on these rates, as well as on disease-specific survival, will be explored for individuals diagnosed with breast cancer in Utah from 1985 through 1999. Population-based records for incident female breast cancer patients were linked with membership records from the LDS Church to determine religious affiliation and, for LDS Church members, level of religiosity. Incidence rates were age-adjusted to the 2000 U.S. standard population using the direct method. Cox proportional hazards model was used to compare survival among religiously active LDS, less religiously active LDS, and non-LDS with simultaneous adjustment for prognostic factors. Age-adjusted breast cancer incidence rates were consistently lower for LDS than non-LDS in Utah from 1985 through 1999. Rates were lower among LDS compared with non-LDS across the age span. In 1995-99, the age-adjusted incidence rates were 107.6 (95% CI: 103.9 - 111.3) for LDS women and 130.5 (123.2 - 137.9) for non-LDS women. If non-LDS women in Utah had the same breast cancer risk profile as LDS women, an estimated 214 (4.8%) fewer malignant breast cancer cases would have occurred during 1995-99. With religiously active LDS serving as the reference group, the adjusted death hazard ratio for religiously less active LDS was 1.09 (0.94 - 1.27) and for non-LDS was 0.86 (0.75 - 0.98). In Utah, LDS lifestyle is associated with lower incidence rates of female breast cancer. However, LDS experience poorer survivability from breast cancer than their non-LDS counterparts. Parity and breastfeeding, while protective factors against breast cancer, may contribute to poorer prognosis of female breast cancer in LDS women.

Survival analysis II: Cox regression

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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

Multilevel survival analysis of health inequalities in life expectancy

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Merlo Juan

2009-08-01

Full Text Available Abstract Background The health status of individuals is determined by multiple factors operating at both micro and macro levels and the interactive effects of them. Measures of health inequalities should reflect such determinants explicitly through sources of levels and combining mean differences at group levels and the variation of individuals, for the benefits of decision making and intervention planning. Measures derived recently from marginal models such as beta-binomial and frailty survival, address this issue to some extent, but are limited in handling data with complex structures. Beta-binomial models were also limited in relation to measuring inequalities of life expectancy (LE directly. Methods We propose a multilevel survival model analysis that estimates life expectancy based on survival time with censored data. The model explicitly disentangles total health inequalities in terms of variance components of life expectancy compared to the source of variation at the level of individuals in households and parishes and so on, and estimates group differences of inequalities at the same time. Adjusted distributions of life expectancy by gender and by household socioeconomic level are calculated. Relative and absolute health inequality indices are derived based on model estimates. The model based analysis is illustrated on a large Swedish cohort of 22,680 men and 26,474 women aged 65–69 in 1970 and followed up for 30 years. Model based inequality measures are compared to the conventional calculations. Results Much variation of life expectancy is observed at individual and household levels. Contextual effects at Parish and Municipality level are negligible. Women have longer life expectancy than men and lower inequality. There is marked inequality by the level of household socioeconomic status measured by the median life expectancy in each socio-economic group and the variation in life expectancy within each group. Conclusion Multilevel

Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock

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Loman, Zachary G.; Monroe, Adrian; Riffell, Samuel K.; Miller, Darren A.; Vilella, Francisco; Wheat, Bradley R.; Rush, Scott A.; Martin, James A.

2018-01-01

Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.Synthesis and applications. Community models represent a viable

A hands-on approach for fitting long-term survival models under the GAMLSS framework.

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de Castro, Mário; Cancho, Vicente G; Rodrigues, Josemar

2010-02-01

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. In this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

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

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Unkel, Steffen; Belka, Claus; Lauber, Kirsten

2016-01-01

The most frequently used method to quantitatively describe the response to ionizing irradiation in terms of clonogenic survival is the linear-quadratic (LQ) model. In the LQ model, the logarithm of the surviving fraction is regressed linearly on the radiation dose by means of a second-degree polynomial. The ratio of the estimated parameters for the linear and quadratic term, respectively, represents the dose at which both terms have the same weight in the abrogation of clonogenic survival. This ratio is known as the α/β ratio. However, there are plausible scenarios in which the α/β ratio fails to sufficiently reflect differences between dose-response curves, for example when curves with similar α/β ratio but different overall steepness are being compared. In such situations, the interpretation of the LQ model is severely limited. Colony formation assays were performed in order to measure the clonogenic survival of nine human pancreatic cancer cell lines and immortalized human pancreatic ductal epithelial cells upon irradiation at 0-10 Gy. The resulting dataset was subjected to LQ regression and non-linear log-logistic regression. Dimensionality reduction of the data was performed by cluster analysis and principal component analysis. Both the LQ model and the non-linear log-logistic regression model resulted in accurate approximations of the observed dose-response relationships in the dataset of clonogenic survival. However, in contrast to the LQ model the non-linear regression model allowed the discrimination of curves with different overall steepness but similar α/β ratio and revealed an improved goodness-of-fit. Additionally, the estimated parameters in the non-linear model exhibit a more direct interpretation than the α/β ratio. Dimensionality reduction of clonogenic survival data by means of cluster analysis was shown to be a useful tool for classifying radioresistant and sensitive cell lines. More quantitatively, principal component analysis allowed

Modeling and Control of the Redundant Parallel Adjustment Mechanism on a Deployable Antenna Panel

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Lili Tian

2016-10-01

Full Text Available With the aim of developing multiple input and multiple output (MIMO coupling systems with a redundant parallel adjustment mechanism on the deployable antenna panel, a structural control integrated design methodology is proposed in this paper. Firstly, the modal information from the finite element model of the structure of the antenna panel is extracted, and then the mathematical model is established with the Hamilton principle; Secondly, the discrete Linear Quadratic Regulator (LQR controller is added to the model in order to control the actuators and adjust the shape of the panel. Finally, the engineering practicality of the modeling and control method based on finite element analysis simulation is verified.

Validation of a Predictive Model for Survival in Metastatic Cancer Patients Attending an Outpatient Palliative Radiotherapy Clinic

International Nuclear Information System (INIS)

Chow, Edward; Abdolell, Mohamed; Panzarella, Tony; Harris, Kristin; Bezjak, Andrea; Warde, Padraig; Tannock, Ian

2009-01-01

Purpose: To validate a predictive model for survival of patients attending a palliative radiotherapy clinic. Methods and Materials: We described previously a model that had good predictive value for survival of patients referred during 1999 (1). The six prognostic factors (primary cancer site, site of metastases, Karnofsky performance score, and the fatigue, appetite and shortness-of-breath items from the Edmonton Symptom Assessment Scale) identified in this training set were extracted from the prospective database for the year 2000. We generated a partial score whereby each prognostic factor was assigned a value proportional to its prognostic weight. The sum of the partial scores for each patient was used to construct a survival prediction score (SPS). Patients were also grouped according to the number of these risk factors (NRF) that they possessed. The probability of survival at 3, 6, and 12 months was generated. The models were evaluated for their ability to predict survival in this validation set with appropriate statistical tests. Results: The median survival and survival probabilities of the training and validation sets were similar when separated into three groups using both SPS and NRF methods. There was no statistical difference in the performance of the SPS and NRF methods in survival prediction. Conclusion: Both the SPS and NRF models for predicting survival in patients referred for palliative radiotherapy have been validated. The NRF model is preferred because it is simpler and avoids the need to remember the weightings among the prognostic factors

Conference Innovations in Derivatives Market : Fixed Income Modeling, Valuation Adjustments, Risk Management, and Regulation

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Grbac, Zorana; Scherer, Matthias; Zagst, Rudi

2016-01-01

This book presents 20 peer-reviewed chapters on current aspects of derivatives markets and derivative pricing. The contributions, written by leading researchers in the field as well as experienced authors from the financial industry, present the state of the art in: • Modeling counterparty credit risk: credit valuation adjustment, debit valuation adjustment, funding valuation adjustment, and wrong way risk. • Pricing and hedging in fixed-income markets and multi-curve interest-rate modeling. • Recent developments concerning contingent convertible bonds, the measuring of basis spreads, and the modeling of implied correlations. The recent financial crisis has cast tremendous doubts on the classical view on derivative pricing. Now, counterparty credit risk and liquidity issues are integral aspects of a prudent valuation procedure and the reference interest rates are represented by a multitude of curves according to their different periods and maturities. A panel discussion included in the book (featuring D...

Military service, deployments, and exposures in relation to amyotrophic lateral sclerosis survival.

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John D Beard

Full Text Available Military veterans may have higher rates of amyotrophic lateral sclerosis (ALS mortality than non-veterans. Few studies, with sparse exposure information and mixed results, have studied relationships between military-related factors and ALS survival. We evaluated associations between military-related factors and ALS survival among U.S. military veteran cases.We followed 616 medical record-confirmed cases from enrollment (2005-2010 in the Genes and Environmental Exposures in Veterans with Amyotrophic Lateral Sclerosis study until death or July 25, 2013, whichever came first. We ascertained vital status information from several sources within the Department of Veterans Affairs. We obtained information regarding military service, deployments, and 39 related exposures via standardized telephone interviews. We used Cox proportional hazards regression models to estimate hazard ratios (HRs and 95% confidence intervals. We adjusted for potential confounding and missing covariate data biases via inverse probability weights. We also used inverse probability weights to adjust for potential selection bias among a case group that included a disproportionate number of long-term survivors at enrollment.We observed 446 deaths during 24,267 person-months of follow-up (median follow-up: 28 months. Survival was shorter for cases who served before 1950, were deployed to World War II, or mixed and applied burning agents, with HRs between 1.58 and 2.57. Longer survival was associated with exposure to: paint, solvents, or petrochemical substances; local food not provided by the Armed Forces; or burning agents or Agent Orange in the field with HRs between 0.56 and 0.73.Although most military-related factors were not associated with survival, associations we observed with shorter survival are potentially important because of the large number of military veterans.

Breast density and mode of detection in relation to breast cancer specific survival: a cohort study

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Olsson, Åsa; Sartor, Hanna; Borgquist, Signe; Zackrisson, Sophia; Manjer, Jonas

2014-01-01

The aim of this study was to examine breast density in relation to breast cancer specific survival and to assess if this potential association was modified by mode of detection. An additional aim was to study whether the established association between mode of detection and survival is modified by breast density. The study included 619 cases from a prospective cohort, The Malmö Diet and Cancer Study. Breast density estimated qualitatively, was analyzed in relation to breast cancer death, in non-symptomatic and symptomatic women, using Cox regression calculating hazard ratios (HR) with 95% confidence intervals. Adjustments were made in several steps for; diagnostic age, tumour size, axillary lymph node involvement, grade, hormone receptor status, body mass index (baseline), diagnostic period, use of hormone replacement therapy at diagnosis and mode of detection. Detection mode in relation to survival was analyzed stratified for breast density. Differences in HR following different adjustments were analyzed by Freedmans%. After adjustment for age and other prognostic factors, women with dense, as compared to fatty breasts, had an increased risk of breast cancer death, HR 2.56:1.07-6.11, with a statistically significant trend over density categories, p = 0.04. In the stratified analysis, the effect was less pronounced in non-symptomatic women, HR 2.04:0.49-8.49 as compared to symptomatic, HR 3.40:1.06-10.90. In the unadjusted model, symptomatic women had a higher risk of breast cancer death, regardless of breast density. Analyzed by Freedmans%, age, tumour size, lymph nodes, grade, diagnostic period, ER and PgR explained 55.5% of the observed differences in mortality between non-symptomatic and symptomatic cases. Additional adjustment for breast density caused only a minor change. High breast density at diagnosis may be associated with decreased breast cancer survival. This association appears to be stronger in women with symptomatic cancers but breast density could

An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan.

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Chang, Hsien-Yen; Weiner, Jonathan P

2010-01-18

Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI) programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG) case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234), while those in both 2002 and 2003 were included for prospective analyses (n = 164,562). Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group) model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster). When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Given the widespread availability of claims data and the superior explanatory

Survival analysis

International Nuclear Information System (INIS)

Badwe, R.A.

1999-01-01

The primary endpoint in the majority of the studies has been either disease recurrence or death. This kind of analysis requires a special method since all patients in the study experience the endpoint. The standard method for estimating such survival distribution is Kaplan Meier method. The survival function is defined as the proportion of individuals who survive beyond certain time. Multi-variate comparison for survival has been carried out with Cox's proportional hazard model

Socioeconomic disparities in breast cancer survival: relation to stage at diagnosis, treatment and race

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Yu Xue

2009-10-01

Full Text Available Abstract Background Previous studies have documented lower breast cancer survival among women with lower socioeconomic status (SES in the United States. In this study, I examined the extent to which socioeconomic disparity in breast cancer survival was explained by stage at diagnosis, treatment, race and rural/urban residence using the Surveillance, Epidemiology, and End Results (SEER data. Methods Women diagnosed with breast cancer during 1998-2002 in the 13 SEER cancer registry areas were followed-up to the end of 2005. The association between an area-based measure of SES and cause-specific five-year survival was estimated using Cox regression models. Six models were used to assess the extent to which SES differences in survival were explained by clinical and demographical factors. The base model estimated the hazard ratio (HR by SES only and then additional adjustments were made sequentially for: 1 age and year of diagnosis; 2 stage at diagnosis; 3 first course treatment; 4 race; and 5 rural/urban residence. Results An inverse association was found between SES and risk of dying from breast cancer (p Conclusion Stage at diagnosis, first course treatment and race explained most of the socioeconomic disparity in breast cancer survival. Targeted interventions to increase breast cancer screening and treatment coverage in patients with lower SES could reduce much of socioeconomic disparity.

Parameter resolution in two models for cell survival after radiation

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Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.

1989-01-01

The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)

Characterization of Pediatric Acute Lymphoblastic Leukemia Survival Patterns by Age at Diagnosis

International Nuclear Information System (INIS)

Hossain, M. J.; Xie, L.; McCahan, S. M.; Hossain, M. J.

2014-01-01

Age at diagnosis is a key prognostic factor in pediatric acute lymphoblastic leukemia (ALL) survivorship. However, literature providing adequate assessment of the survival variability by age at diagnosis is scarce. The aim of this study is to assess the impact of this prognostic factor in pediatric ALL survival. We estimated incidence rate of mortality, 5-year survival rate, Kaplan-Meier survival function, and hazard ratio using the Surveillance Epidemiology and End Results (SEER) data during 1973-2009. There was significant variability in pediatric ALL survival by age at diagnosis. Survival peaked among children diagnosed at 1-4 years and steadily declined among those diagnosed at older ages. Infants (<1 year) had the lowest survivorship. In a multivariable Cox proportional hazard model stratified by year of diagnosis, those diagnosed in age groups 1-4, 5-9, 10-14, and 15-19 years were 82%, 75%, 57%, and 32% less likely to die compared to children diagnosed in infancy, respectively. Age at diagnosis remained to be a crucial determinant of the survival variability of pediatric ALL patients, after adjusting for sex, race, radiation therapy, primary tumor sites, immuno phenotype, and year of diagnosis. Further research is warranted to disentangle the effects of age-dependent biological and environmental processes on this association.

Adrenaline (epinephrine) dosing period and survival after in-hospital cardiac arrest: a retrospective review of prospectively collected data.

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Warren, Sam A; Huszti, Ella; Bradley, Steven M; Chan, Paul S; Bryson, Chris L; Fitzpatrick, Annette L; Nichol, Graham

2014-03-01

Expert guidelines for treatment of cardiac arrest recommend administration of adrenaline (epinephrine) every three to five minutes. However, the effects of different dosing periods of epinephrine remain unclear. We sought to evaluate the association between epinephrine average dosing period and survival to hospital discharge in adults with an in-hospital cardiac arrest (IHCA). We performed a retrospective review of prospectively collected data on 20,909 IHCA events from 505 hospitals participating in the Get With The Guidelines-Resuscitation (GWTG-R) quality improvement registry. Epinephrine average dosing period was defined as the time between the first epinephrine dose and the resuscitation endpoint, divided by the total number of epinephrine doses received subsequent to the first epinephrine dose. Associations with survival to hospital discharge were assessed by using generalized estimating equations to construct multivariable logistic regression models. Compared to a referent epinephrine average dosing period of 4 to <5 min per dose, survival to hospital discharge was significantly higher in patients with the following epinephrine average dosing periods: for 6 to <7 min/dose, adjusted odds ratio [OR], 1.41 (95%CI: 1.12, 1.78); for 7 to <8 min/dose, adjusted OR, 1.30 (95%CI: 1.02, 1.65); for 8 to <9 min/dose, adjusted OR, 1.79 (95%CI: 1.38, 2.32); for 9 to <10 min/dose, adjusted OR, 2.17 (95%CI: 1.62, 2.92). This pattern was consistent for both shockable and non-shockable cardiac arrest rhythms. Less frequent average epinephrine dosing than recommended by consensus guidelines was associated with improved survival of in-hospital cardiac arrest. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer

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Borges, Ana; Sousa, Inês; Castro, Luis

2017-06-01

This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of

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.

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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.

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.

Breast cancer molecular subtypes and survival in a hospital-based sample in Puerto Rico

International Nuclear Information System (INIS)

Ortiz, Ana Patricia; Frías, Orquidea; Pérez, Javier; Cabanillas, Fernando; Martínez, Lisa; Sánchez, Carola; Capó-Ramos, David E; González-Keelan, Carmen; Mora, Edna; Suárez, Erick

2013-01-01

Information on the impact of hormone receptor status subtypes in breast cancer (BC) prognosis is still limited for Hispanics. We aimed to evaluate the association of BC molecular subtypes and other clinical factors with survival in a hospital-based female population of BC cases in Puerto Rico. We analyzed 663 cases of invasive BC diagnosed between 2002 and 2005. Information on HER-2/neu (HER-2) overexpression, estrogen (ER), and progesterone (PR) receptor status and clinical characteristics were retrieved from hospitals cancer registries and record review. Survival probabilities by covariates of interest were described using the Kaplan–Meier estimators. Cox proportional hazards models were employed to assess factors associated with risk of BC death. Overall, 17.3% of BC cases were triple-negative (TN), 61.8% were Luminal-A, 13.3% were Luminal-B, and 7.5% were HER-2 overexpressed. In the multivariate Cox model, among patients with localized stage, women with TN BC had higher risk of death (adjusted hazard ratio [HR]: 2.57, 95% confidence interval [CI]: 1.29–5.12) as compared to those with Luminal-A status, after adjusting for age at diagnosis. In addition, among women with regional/distant stage at diagnosis, those with TN BC (HR: 5.48, 95% CI: 2.63–11.47) and those HER-2+, including HER-2 overexpressed and Luminal-B, (HR: 2.73, 95% CI:1.30–5.75) had a higher mortality. This is the most comprehensive epidemiological study to date on the impact of hormone receptor expression subtypes in BC survival in Puerto Rico. Consistent to results in other populations, the TN subtype and HER-2+ tumors were associated with decreased survival

Inference for shared-frailty survival models with left-truncated data

NARCIS (Netherlands)

van den Berg, G.J.; Drepper, B.

2016-01-01

Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated

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.

Adjusting the Adjusted X[superscript 2]/df Ratio Statistic for Dichotomous Item Response Theory Analyses: Does the Model Fit?

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Tay, Louis; Drasgow, Fritz

2012-01-01

Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…

Comparison of six different models describing survival of mammalian cells after irradiation

International Nuclear Information System (INIS)

Sontag, W.

1990-01-01

Six different cell-survival models have been compared. All models are based on the similar assumption that irradiated cells are able to exist in one of three states. S A is the state of a totally repaired cell, in state S C the cell contains lethal lesions and in state S b the cell contains potentially lethal lesions i.e. those which either can be repaired or converted into lethal lesions. The differences between the six models lie in the different mathematical relationships between the three states. To test the six models, six different sets of experimental data were used which describe cell survival at different repair times after irradiation with sparsely ionizing irradiation. In order to compare the models, a goodness-of-fit function was used. The differences between the six models were tested by use of the nonparametric Mann-Whitney two sample test. Based on the 95% confidence limit, this required separation into three groups. (orig.)

An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan

Directory of Open Access Journals (Sweden)

Weiner Jonathan P

2010-01-01

Full Text Available Abstract Background Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. Methods A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234, while those in both 2002 and 2003 were included for prospective analyses (n = 164,562. Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. Results The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster. When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Conclusions Given the

A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data

DEFF Research Database (Denmark)

He, Peng; Eriksson, Frank; Scheike, Thomas H.

2016-01-01

function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight......With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution...... and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight...

Parametric and semiparametric models with applications to reliability, survival analysis, and quality of life

CERN Document Server

Nikulin, M; Mesbah, M; Limnios, N

2004-01-01

Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.

Squamous cell carcinoma of the breast in the United States: incidence, demographics, tumor characteristics, and survival.

Science.gov (United States)

Yadav, Siddhartha; Yadav, Dhiraj; Zakalik, Dana

2017-07-01

Squamous cell carcinoma of breast accounts for less than 0.1% of all breast cancers. The purpose of this study is to describe the epidemiology and survival of this rare malignancy. Data were extracted from the National Cancer Institute's Surveillance, Epidemiology and End Results Registry to identify women diagnosed with squamous cell carcinoma of breast between 1998 and 2013. SEER*Stat 8.3.1 was used to calculate age-adjusted incidence, age-wise distribution, and annual percentage change in incidence. Kaplan-Meier curves were plotted for survival analysis. Univariate and multivariate Cox proportional hazard regression model was used to determine predictors of survival. A total of 445 cases of squamous cell carcinoma of breast were diagnosed during the study period. The median age of diagnosis was 67 years. The overall age-adjusted incidence between 1998 and 2013 was 0.62 per 1,000,000 per year, and the incidence has been on a decline. Approximately half of the tumors were poorly differentiated. Stage II was the most common stage at presentation. Majority of the cases were negative for expression of estrogen and progesterone receptor. One-third of the cases underwent breast conservation surgery while more than half of the cases underwent mastectomy (unilateral or bilateral). Approximately one-third of cases received radiation treatment. The 1-year and 5-year cause-specific survival was 81.6 and 63.5%, respectively. Excluding patient with metastasis or unknown stage at presentation, in multivariate Cox proportional hazard model, older age at diagnosis and higher tumor stage (T3 or T4) or nodal stage at presentation were significant predictors of poor survival. Our study describes the unique characteristics of squamous cell carcinoma of breast and demonstrates that it is an aggressive tumor with a poor survival. Older age and higher tumor or nodal stages at presentation were independent predictors of poor survival for loco-regional stages.

Droop Control with an Adjustable Complex Virtual Impedance Loop based on Cloud Model Theory

DEFF Research Database (Denmark)

Li, Yan; Shuai, Zhikang; Xu, Qinming

2016-01-01

Droop control framework with an adjustable virtual impedance loop is proposed in this paper, which is based on the cloud model theory. The proposed virtual impedance loop includes two terms: a negative virtual resistor and an adjustable virtual inductance. The negative virtual resistor term...... sometimes. The cloud model theory is applied to get online the changing line impedance value, which relies on the relevance of the reactive power responding the changing line impedance. The verification of the proposed control strategy is done according to the simulation in a low voltage microgrid in Matlab....

Modeling the airborne survival of influenza virus in a residential setting: the impacts of home humidification

Science.gov (United States)

2010-01-01

Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH) conditions. Further analysis has shown that absolute humidity (AH) may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US) using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity indoors. PMID:20815876

Modeling the airborne survival of influenza virus in a residential setting: the impacts of home humidification

Directory of Open Access Journals (Sweden)

Myatt Theodore A

2010-09-01

Full Text Available Abstract Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH conditions. Further analysis has shown that absolute humidity (AH may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity

Connecting single-stock assessment models through correlated survival

DEFF Research Database (Denmark)

Albertsen, Christoffer Moesgaard; Nielsen, Anders; Thygesen, Uffe Høgsbro

2017-01-01

times. We propose a simple alternative. In three case studies each with two stocks, we improve the single-stock models, as measured by Akaike information criterion, by adding correlation in the cohort survival. To limit the number of parameters, the correlations are parameterized through...... the corresponding partial correlations. We consider six models where the partial correlation matrix between stocks follows a band structure ranging from independent assessments to complex correlation structures. Further, a simulation study illustrates the importance of handling correlated data sufficiently...... by investigating the coverage of confidence intervals for estimated fishing mortality. The results presented will allow managers to evaluate stock statuses based on a more accurate evaluation of model output uncertainty. The methods are directly implementable for stocks with an analytical assessment and do...

Lung cancer survival in Norway, 1997-2011: from nihilism to optimism.

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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.

Player Modeling for Intelligent Difficulty Adjustment

Science.gov (United States)

Missura, Olana; Gärtner, Thomas

In this paper we aim at automatically adjusting the difficulty of computer games by clustering players into different types and supervised prediction of the type from short traces of gameplay. An important ingredient of video games is to challenge players by providing them with tasks of appropriate and increasing difficulty. How this difficulty should be chosen and increase over time strongly depends on the ability, experience, perception and learning curve of each individual player. It is a subjective parameter that is very difficult to set. Wrong choices can easily lead to players stopping to play the game as they get bored (if underburdened) or frustrated (if overburdened). An ideal game should be able to adjust its difficulty dynamically governed by the player’s performance. Modern video games utilise a game-testing process to investigate among other factors the perceived difficulty for a multitude of players. In this paper, we investigate how machine learning techniques can be used for automatic difficulty adjustment. Our experiments confirm the potential of machine learning in this application.

Using Green's Functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model

Science.gov (United States)

Brix, H.; Menemenlis, D.; Hill, C.; Dutkiewicz, S.; Jahn, O.; Wang, D.; Bowman, K.; Zhang, H.

2015-11-01

The NASA Carbon Monitoring System (CMS) Flux Project aims to attribute changes in the atmospheric accumulation of carbon dioxide to spatially resolved fluxes by utilizing the full suite of NASA data, models, and assimilation capabilities. For the oceanic part of this project, we introduce ECCO2-Darwin, a new ocean biogeochemistry general circulation model based on combining the following pre-existing components: (i) a full-depth, eddying, global-ocean configuration of the Massachusetts Institute of Technology general circulation model (MITgcm), (ii) an adjoint-method-based estimate of ocean circulation from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) project, (iii) the MIT ecosystem model "Darwin", and (iv) a marine carbon chemistry model. Air-sea gas exchange coefficients and initial conditions of dissolved inorganic carbon, alkalinity, and oxygen are adjusted using a Green's Functions approach in order to optimize modeled air-sea CO2 fluxes. Data constraints include observations of carbon dioxide partial pressure (pCO2) for 2009-2010, global air-sea CO2 flux estimates, and the seasonal cycle of the Takahashi et al. (2009) Atlas. The model sensitivity experiments (or Green's Functions) include simulations that start from different initial conditions as well as experiments that perturb air-sea gas exchange parameters and the ratio of particulate inorganic to organic carbon. The Green's Functions approach yields a linear combination of these sensitivity experiments that minimizes model-data differences. The resulting initial conditions and gas exchange coefficients are then used to integrate the ECCO2-Darwin model forward. Despite the small number (six) of control parameters, the adjusted simulation is significantly closer to the data constraints (37% cost function reduction, i.e., reduction in the model-data difference, relative to the baseline simulation) and to independent observations (e.g., alkalinity). The adjusted air-sea gas

Chest compression rates and survival following out-of-hospital cardiac arrest.

Science.gov (United States)

Idris, Ahamed H; Guffey, Danielle; Pepe, Paul E; Brown, Siobhan P; Brooks, Steven C; Callaway, Clifton W; Christenson, Jim; Davis, Daniel P; Daya, Mohamud R; Gray, Randal; Kudenchuk, Peter J; Larsen, Jonathan; Lin, Steve; Menegazzi, James J; Sheehan, Kellie; Sopko, George; Stiell, Ian; Nichol, Graham; Aufderheide, Tom P

2015-04-01

Guidelines for cardiopulmonary resuscitation recommend a chest compression rate of at least 100 compressions/min. A recent clinical study reported optimal return of spontaneous circulation with rates between 100 and 120/min during cardiopulmonary resuscitation for out-of-hospital cardiac arrest. However, the relationship between compression rate and survival is still undetermined. Prospective, observational study. Data is from the Resuscitation Outcomes Consortium Prehospital Resuscitation IMpedance threshold device and Early versus Delayed analysis clinical trial. Adults with out-of-hospital cardiac arrest treated by emergency medical service providers. None. Data were abstracted from monitor-defibrillator recordings for the first five minutes of emergency medical service cardiopulmonary resuscitation. Multiple logistic regression assessed odds ratio for survival by compression rate categories (compression fraction and depth, first rhythm, and study site. Compression rate data were available for 10,371 patients; 6,399 also had chest compression fraction and depth data. Age (mean±SD) was 67±16 years. Chest compression rate was 111±19 per minute, compression fraction was 0.70±0.17, and compression depth was 42±12 mm. Circulation was restored in 34%; 9% survived to hospital discharge. After adjustment for covariates without chest compression depth and fraction (n=10,371), a global test found no significant relationship between compression rate and survival (p=0.19). However, after adjustment for covariates including chest compression depth and fraction (n=6,399), the global test found a significant relationship between compression rate and survival (p=0.02), with the reference group (100-119 compressions/min) having the greatest likelihood for survival. After adjustment for chest compression fraction and depth, compression rates between 100 and 120 per minute were associated with greatest survival to hospital discharge.

Rethinking plant functional types in Earth System Models: pan-tropical analysis of tree survival across environmental gradients

Science.gov (United States)

Johnson, D. J.; Needham, J.; Xu, C.; Davies, S. J.; Bunyavejchewin, S.; Giardina, C. P.; Condit, R.; Cordell, S.; Litton, C. M.; Hubbell, S.; Kassim, A. R. B.; Shawn, L. K. Y.; Nasardin, M. B.; Ong, P.; Ostertag, R.; Sack, L.; Tan, S. K. S.; Yap, S.; McDowell, N. G.; McMahon, S.

2016-12-01

Terrestrial carbon cycling is a function of the growth and survival of trees. Current model representations of tree growth and survival at a global scale rely on coarse plant functional traits that are parameterized very generally. In view of the large biodiversity in the tropical forests, it is important that we account for the functional diversity in order to better predict tropical forest responses to future climate changes. Several next generation Earth System Models are moving towards a size-structured, trait-based approach to modelling vegetation globally, but the challenge of which and how many traits are necessary to capture forest complexity remains. Additionally, the challenge of collecting sufficient trait data to describe the vast species richness of tropical forests is enormous. We propose a more fundamental approach to these problems by characterizing forests by their patterns of survival. We expect our approach to distill real-world tree survival into a reasonable number of functional types. Using 10 large-area tropical forest plots that span geographic, edaphic and climatic gradients, we model tree survival as a function of tree size for hundreds of species. We found surprisingly few categories of size-survival functions emerge. This indicates some fundamental strategies at play across diverse forests to constrain the range of possible size-survival functions. Initial cluster analysis indicates that four to eight functional forms are necessary to describe variation in size-survival relations. Temporal variation in size-survival functions can be related to local environmental variation, allowing us to parameterize how demographically similar groups of species respond to perturbations in the ecosystem. We believe this methodology will yield a synthetic approach to classifying forest systems that will greatly reduce uncertainty and complexity in global vegetation models.

Testing an Attachment Model of Latina/o College Students' Psychological Adjustment

Science.gov (United States)

Garriott, Patton O.; Love, Keisha M.; Tyler, Kenneth M.; Thomas, Deneia M.; Roan-Belle, Clarissa R.; Brown, Carrie L.

2010-01-01

The present study examined the influence of attachment relationships on the psychological adjustment of Latina/o university students (N = 80) attending predominantly White institutions of higher education. A path analysis conducted to test a hypothesized model of parent and peer attachment, self-esteem, and psychological distress indicated that…

Towards an Integrated Conceptual Model of International Student Adjustment and Adaptation

Science.gov (United States)

Schartner, Alina; Young, Tony Johnstone

2016-01-01

Despite a burgeoning body of empirical research on "the international student experience", the area remains under-theorized. The literature to date lacks a guiding conceptual model that captures the adjustment and adaptation trajectories of this unique, growing, and important sojourner group. In this paper, we therefore put forward a…

Survival models for harvest management of mourning dove populations

Science.gov (United States)

Otis, D.L.

2002-01-01

Quantitative models of the relationship between annual survival and harvest rate of migratory game-bird populations are essential to science-based harvest management strategies. I used the best available band-recovery and harvest data for mourning doves (Zenaida macroura) to build a set of models based on different assumptions about compensatory harvest mortality. Although these models suffer from lack of contemporary data, they can be used in development of an initial set of population models that synthesize existing demographic data on a management-unit scale, and serve as a tool for prioritization of population demographic information needs. Credible harvest management plans for mourning dove populations will require a long-term commitment to population monitoring and iterative population analysis.

10 km running performance predicted by a multiple linear regression model with allometrically adjusted variables.

Science.gov (United States)

Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O

2016-06-01

The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

[The survival prediction model of advanced gallbladder cancer based on Bayesian network: a multi-institutional study].

Science.gov (United States)

Tang, Z H; Geng, Z M; Chen, C; Si, S B; Cai, Z Q; Song, T Q; Gong, P; Jiang, L; Qiu, Y H; He, Y; Zhai, W L; Li, S P; Zhang, Y C; Yang, Y

2018-05-01

Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8

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.

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....

High-dose chemotherapy for patients with high-risk breast cancer: a clinical and economic assessment using a quality-adjusted survival analysis.

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Marino, Patricia; Roché, Henri; Moatti, Jean-Paul

2008-04-01

The benefit of high-dose chemotherapy (HDC) has not been clearly demonstrated. It may offer disease-free survival improvement at the expense of major toxicity and increasing cost. We evaluated the trade-offs between toxicity, relapse, and costs using a quality-adjusted time without symptoms or toxicity (Q-TWiST) analysis. The analysis was conducted in the context of a randomized trial (PEGASE 01) evaluating the benefit of HDC for 314 patients with high-risk breast cancer. A Q-TWiST analysis was first performed to compare HDC with standard chemotherapy. We then used the results of this Q-TWiST analysis to inform a cost per quality-adjusted life-year (QALY) comparison between treatments. Q-TWiST durations were in favor of HDC, whatever the weighting coefficients used for the analysis. This benefit was significant when the weighting coefficient related to the time spent after relapse was low (0.78), HDC offered no benefit. For intermediate values, the results depended on the weighting coefficient attributed to the toxicity period. The incremental cost per QALY ranged from 12,691euro/QALY to 26,439euro/QALY, according to the coefficients used to weight toxicity and relapse. The benefits of HDC outweigh the burdens of treatment for a wide range of utility coefficients. Economic impact is not a barrier to HDC diffusion in this situation. Nevertheless, no significant benefit was demonstrated for a certain range of utility values.

Conceptual Model for Simulating the Adjustments of Bankfull Characteristics in the Lower Yellow River, China

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Yuanjian Wang

2014-01-01

Full Text Available We present a conceptual model for simulating the temporal adjustments in the banks of the Lower Yellow River (LYR. Basic conservation equations for mass, friction, and sediment transport capacity and the Exner equation were adopted to simulate the hydrodynamics underlying fluvial processes. The relationship between changing rates in bankfull width and depth, derived from quasiuniversal hydraulic geometries, was used as a closure for the hydrodynamic equations. On inputting the daily flow discharge and sediment load, the conceptual model successfully simulated the 30-year adjustments in the bankfull geometries of typical reaches of the LYR. The square of the correlating coefficient reached 0.74 for Huayuankou Station in the multiple-thread reach and exceeded 0.90 for Lijin Station in the meandering reach. This proposed model allows multiple dependent variables and the input of daily hydrological data for long-term simulations. This links the hydrodynamic and geomorphic processes in a fluvial river and has potential applicability to fluvial rivers undergoing significant adjustments.

Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate.

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West, Robert; Mobilia, Mauro; Rucklidge, Alastair M

2018-02-01

We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate

Science.gov (United States)

West, Robert; Mobilia, Mauro; Rucklidge, Alastair M.

2018-02-01

We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

Evaluation of the Stress Adjustment and Adaptation Model among Families Reporting Economic Pressure

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Vandsburger, Etty; Biggerstaff, Marilyn A.

2004-01-01

This research evaluates the Stress Adjustment and Adaptation Model (double ABCX model) examining the effects resiliency resources on family functioning when families experience economic pressure. Families (N = 128) with incomes at or below the poverty line from a rural area of a southern state completed measures of perceived economic pressure,…

Quantifying the changes in survival inequality for Indigenous people diagnosed with cancer in Queensland, Australia.

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Baade, Peter D; Dasgupta, Paramita; Dickman, Paul W; Cramb, Susanna; Williamson, John D; Condon, John R; Garvey, Gail

2016-08-01

The survival inequality faced by Indigenous Australians after a cancer diagnosis is well documented; what is less understood is whether this inequality has changed over time and what this means in terms of the impact a cancer diagnosis has on Indigenous people. Survival information for all patients identified as either Indigenous (n=3168) or non-Indigenous (n=211,615) and diagnosed in Queensland between 1997 and 2012 were obtained from the Queensland Cancer Registry, with mortality followed up to 31st December, 2013. Flexible parametric survival models were used to quantify changes in the cause-specific survival inequalities and the number of lives that might be saved if these inequalities were removed. Among Indigenous cancer patients, the 5-year cause-specific survival (adjusted by age, sex and broad cancer type) increased from 52.9% in 1997-2006 to 58.6% in 2007-2012, while it improved from 61.0% to 64.9% among non-Indigenous patients. This meant that the adjusted 5-year comparative survival ratio (Indigenous: non-Indigenous) increased from 0.87 [0.83-0.88] to 0.89 [0.87-0.93], with similar improvements in the 1-year comparative survival. Using a simulated cohort corresponding to the number and age-distribution of Indigenous people diagnosed with cancer in Queensland each year (n=300), based on the 1997-2006 cohort mortality rates, 35 of the 170 deaths due to cancer (21%) expected within five years of diagnosis were due to the Indigenous: non-Indigenous survival inequality. This percentage was similar when applying 2007-2012 cohort mortality rates (19%; 27 out of 140 deaths). Indigenous people diagnosed with cancer still face a poorer survival outlook than their non-Indigenous counterparts, particularly in the first year after diagnosis. The improving survival outcomes among both Indigenous and non-Indigenous cancer patients, and the decreasing absolute impact of the Indigenous survival disadvantage, should provide increased motivation to continue and enhance

Model for Adjustment of Aggregate Forecasts using Fuzzy Logic

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Taracena–Sanz L. F.

2010-07-01

Full Text Available This research suggests a contribution in the implementation of forecasting models. The proposed model is developed with the aim to fit the projection of demand to surroundings of firms, and this is based on three considerations that cause that in many cases the forecasts of the demand are different from reality, such as: 1 one of the problems most difficult to model in the forecasts is the uncertainty related to the information available; 2 the methods traditionally used by firms for the projection of demand mainly are based on past behavior of the market (historical demand; and 3 these methods do not consider in their analysis the factors that are influencing so that the observed behaviour occurs. Therefore, the proposed model is based on the implementation of Fuzzy Logic, integrating the main variables that affect the behavior of market demand, and which are not considered in the classical statistical methods. The model was applied to a bottling of carbonated beverages, and with the adjustment of the projection of demand a more reliable forecast was obtained.

Do female cancer patients display better survival rates compared with males? Analysis of the Korean National Registry data, 2005-2009.

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Kyu-Won Jung

Full Text Available BACKGROUND: Sex differences have been reported in the prognosis of certain cancers. In this study, we investigated whether Korean females display better survival rates compared with male patients for solid tumor sites. METHODS: We analyzed data from the Korean National Cancer Incidence Database from 599,288 adult patients diagnosed with solid cancers between 2005 and 2009. Patients were followed until December 2010. We applied a relative excess risk (RER model adjusting for year of follow-up, age at diagnosis, and stage at diagnosis. RESULTS: For all solid cancer sites combined, women displayed an 11% lower risk of death compared to men (RER 0.89; 95% CI 0.88-0.90 after adjusting for year of follow-up, age, stage, and case mix. Women showed significantly lower RERs for the following sites: head/neck, esophagus, small intestine, liver, nasal cavities, lung, bone/cartilages, melanoma of skin, soft tissue, brain and CNS, and thyroid. In contrast, women displayed a poorer prognosis than did men for colorectal, laryngeal, kidney and bladder cancer. However, the survival gaps between men and women narrowed by increase in age; female patients over 75 years of age displayed a 3% higher RER of death compared with males in this age group. CONCLUSIONS: Female cancer patients display an improved survival for the majority of solid tumor sites, even after adjustment for age and stage. Age at diagnosis was the major contributor to the women's survival advantage.

Testing a social ecological model for relations between political violence and child adjustment in Northern Ireland.

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Cummings, E Mark; Merrilees, Christine E; Schermerhorn, Alice C; Goeke-Morey, Marcie C; Shirlow, Peter; Cairns, Ed

2010-05-01

Relations between political violence and child adjustment are matters of international concern. Past research demonstrates the significance of community, family, and child psychological processes in child adjustment, supporting study of interrelations between multiple social ecological factors and child adjustment in contexts of political violence. Testing a social ecological model, 300 mothers and their children (M = 12.28 years, SD = 1.77) from Catholic and Protestant working class neighborhoods in Belfast, Northern Ireland, completed measures of community discord, family relations, and children's regulatory processes (i.e., emotional security) and outcomes. Historical political violence in neighborhoods based on objective records (i.e., politically motivated deaths) were related to family members' reports of current sectarian antisocial behavior and nonsectarian antisocial behavior. Interparental conflict and parental monitoring and children's emotional security about both the community and family contributed to explanatory pathways for relations between sectarian antisocial behavior in communities and children's adjustment problems. The discussion evaluates support for social ecological models for relations between political violence and child adjustment and its implications for understanding relations in other parts of the world.

Utilizing Visual Effects Software for Efficient and Flexible Isostatic Adjustment Modelling

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Meldgaard, A.; Nielsen, L.; Iaffaldano, G.

2017-12-01

The isostatic adjustment signal generated by transient ice sheet loading is an important indicator of past ice sheet extent and the rheological constitution of the interior of the Earth. Finite element modelling has proved to be a very useful tool in these studies. We present a simple numerical model for 3D visco elastic Earth deformation and a new approach to the design of such models utilizing visual effects software designed for the film and game industry. The software package Houdini offers an assortment of optimized tools and libraries which greatly facilitate the creation of efficient numerical algorithms. In particular, we make use of Houdini's procedural work flow, the SIMD programming language VEX, Houdini's sparse matrix creation and inversion libraries, an inbuilt tetrahedralizer for grid creation, and the user interface, which facilitates effortless manipulation of 3D geometry. We mitigate many of the time consuming steps associated with the authoring of efficient algorithms from scratch while still keeping the flexibility that may be lost with the use of commercial dedicated finite element programs. We test the efficiency of the algorithm by comparing simulation times with off-the-shelf solutions from the Abaqus software package. The algorithm is tailored for the study of local isostatic adjustment patterns, in close vicinity to present ice sheet margins. In particular, we wish to examine possible causes for the considerable spatial differences in the uplift magnitude which are apparent from field observations in these areas. Such features, with spatial scales of tens of kilometres, are not resolvable with current global isostatic adjustment models, and may require the inclusion of local topographic features. We use the presented algorithm to study a near field area where field observations are abundant, namely, Disko Bay in West Greenland with the intention of constraining Earth parameters and ice thickness. In addition, we assess how local

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...

An Efficient Bundle Adjustment Model Based on Parallax Parametrization for Environmental Monitoring

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Chen, R.; Sun, Y. Y.; Lei, Y.

2017-12-01

With the rapid development of Unmanned Aircraft Systems (UAS), more and more research fields have been successfully equipped with this mature technology, among which is environmental monitoring. One difficult task is how to acquire accurate position of ground object in order to reconstruct the scene more accurate. To handle this problem, we combine bundle adjustment method from Photogrammetry with parallax parametrization from Computer Vision to create a new method call APCP (aerial polar-coordinate photogrammetry). One impressive advantage of this method compared with traditional method is that the 3-dimensional point in space is represented using three angles (elevation angle, azimuth angle and parallax angle) rather than the XYZ value. As the basis for APCP, bundle adjustment could be used to optimize the UAS sensors' pose accurately, reconstruct the 3D models of environment, thus serving as the criterion of accurate position for monitoring. To verity the effectiveness of the proposed method, we test on several UAV dataset obtained by non-metric digital cameras with large attitude angles, and we find that our methods could achieve 1 or 2 times better efficiency with no loss of accuracy than traditional ones. For the classical nonlinear optimization of bundle adjustment model based on the rectangular coordinate, it suffers the problem of being seriously dependent on the initial values, making it unable to converge fast or converge to a stable state. On the contrary, APCP method could deal with quite complex condition of UAS when conducting monitoring as it represent the points in space with angles, including the condition that the sequential images focusing on one object have zero parallax angle. In brief, this paper presents the parameterization of 3D feature points based on APCP, and derives a full bundle adjustment model and the corresponding nonlinear optimization problems based on this method. In addition, we analyze the influence of convergence and

Ovarian cancer survival population differences: a "high resolution study" comparing Philippine residents, and Filipino-Americans and Caucasians living in the US.

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Redaniel, Maria Theresa M; Laudico, Adriano; Mirasol-Lumague, Maria Rica; Gondos, Adam; Uy, Gemma Leonora; Toral, Jean Ann; Benavides, Doris; Brenner, Hermann

2009-09-24

In contrast to most other forms of cancer, data from some developing and developed countries show surprisingly similar survival rates for ovarian cancer. We aimed to compare ovarian cancer survival in Philippine residents, Filipino-Americans and Caucasians living in the US, using a high resolution approach, taking potential differences in prognostic factors into account. Using databases from the SEER 13 and from the Manila and Rizal Cancer Registries, age-adjusted five-year absolute and relative survival estimates were computed using the period analysis method and compared between Filipino-American ovarian cancer patients with cancer patients from the Philippines and Caucasians in the US. Cox proportional hazards modelling was used to determine factors affecting survival differences. Despite more favorable distribution of age and cancer morphology and similar stage distribution, 5-year absolute and relative survival were lower in Philippine residents (Absolute survival, AS, 44%, Standard Error, SE, 2.9 and Relative survival, RS, 49.7%, SE, 3.7) than in Filipino-Americans (AS, 51.3%, SE, 3.1 and RS, 54.1%, SE, 3.4). After adjustment for these and additional covariates, strong excess risk of death for Philippine residents was found (Relative Risk, RR, 2.45, 95% confidence interval, 95% CI, 1.99-3.01). In contrast, no significant differences were found between Filipino-Americans and Caucasians living in the US. Multivariate analyses disclosed strong survival disadvantages of Philippine residents compared to Filipino-American patients, for which differences in access to health care might have played an important role. Survival is no worse among Filipino-Americans than among Caucasians living in the US.

IGF-1 and Survival in ESRD

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Jia, Ting; Gama Axelsson, Thiane; Heimbürger, Olof; Bárány, Peter; Stenvinkel, Peter; Qureshi, Abdul Rashid

2014-01-01

Summary Background and objectives IGF-1 deficiency links to malnutrition in CKD patients; however, it is not clear to what extent it associates with survival among these patients. Design, setting, participants, & measurements Serum IGF-1 and other biochemical, clinical (subjective global assessment), and densitometric (dual energy x-ray absorptiometry) markers of nutritional status and mineral and bone metabolism were measured in a cohort of 365 Swedish clinically stable CKD stage 5 patients (median age of 53 years) initiating dialysis between 1994 and 2009; in 207 patients, measurements were also taken after 1 year of dialysis. Deaths were registered during a median follow-up of 5 years. Associations of mortality with baseline IGF-1 and changes of IGF-1 after 1 year of dialysis were evaluated by Cox models. Results At baseline, IGF-1 concentrations associated negatively with age, diabetes mellitus, cardiovascular disease, poor nutritional status, IL-6, and osteoprotegerin and positively with body fat mass, bone mineral density, serum phosphate, calcium, and fibroblast growth factor-23. At 1 year, IGF-1 had increased by 33%. In multivariate regression, low age, diabetes mellitus, and high serum phosphate and calcium associated with IGF-1 at baseline, and in a mixed model, these factors, together with high fat body mass, associated with changes of IGF-1 during the first 1 year of dialysis. Adjusting for calendar year of inclusion, age, sex, diabetes mellitus, cardiovascular disease, IL-6, and poor nutritional status, a 1 SD higher level of IGF-1 at baseline associated with lower mortality risk (hazard ratio, 0.57; 95% confidence interval, 0.32 to 0.98). Persistently low or decreasing IGF-1 levels during the first 1 year on dialysis predicted worse survival (adjusted hazard ratio, 2.19; 95% confidence interval, 1.06 to 4.50). Conclusion In incident dialysis patients, low serum IGF-1 associates with body composition and markers of mineral and bone metabolism, and it

Peak Serum AST Is a Better Predictor of Acute Liver Graft Injury after Liver Transplantation When Adjusted for Donor/Recipient BSA Size Mismatch (ASTi

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Kyota Fukazawa

2014-01-01

Full Text Available Background. Despite the marked advances in the perioperative management of the liver transplant recipient, an assessment of clinically significant graft injury following preservation and reperfusion remains difficult. In this study, we hypothesized that size-adjusted AST could better approximate real AST values and consequently provide a better reflection of the extent of graft damage, with better sensitivity and specificity than current criteria. Methods. We reviewed data on 930 orthotopic liver transplant recipients. Size-adjusted AST (ASTi was calculated by dividing peak AST by our previously reported index for donor-recipient size mismatch, the BSAi. The predictive value of ASTi of primary nonfunction (PNF and graft survival was assessed by receiver operating characteristic curve, logistic regression, Kaplan-Meier survival, and Cox proportional hazard model. Results. Size-adjusted peak AST (ASTi was significantly associated with subsequent occurrence of PNF and graft failure. In our study cohort, the prediction of PNF by the combination of ASTi and PT-INR had a higher sensitivity and specificity compared to current UNOS criteria. Conclusions. We conclude that size-adjusted AST (ASTi is a simple, reproducible, and sensitive marker of clinically significant graft damage.

A Survival Model for Shortleaf Pine Tress Growing in Uneven-Aged Stands

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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...

Metformin Use and Endometrial Cancer Survival

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Nevadunsky, Nicole S.; Van Arsdale, Anne; Strickler, Howard D.; Moadel, Alyson; Kaur, Gurpreet; Frimer, Marina; Conroy, Erin; Goldberg, Gary L.; Einstein, Mark H.

2013-01-01

Objective Impaired glucose tolerance and diabetes are risk factors for the development of uterine cancer. Although greater progression free survival among diabetic patients with ovarian and breast cancer using metformin have been reported, no studies have assessed the association of metformin use with survival in women with endometrial cancer (EC). Methods We conducted a single-institution retrospective cohort study of all patients treated for uterine cancer from January 1999 through December 2009. Demographic, medical, social, and survival data were abstracted from medical records and the national death registry. Overall survival (OS) was estimated using Kaplan-Meier methods. Cox models were utilized for multivariate analysis. All statistical tests were two-sided. Results Of 985 patients, 114 (12%) had diabetes and were treated with metformin, 136 (14%) were diabetic but did not use metformin, and 735 (74%) had not been diagnosed with diabetes. Greater OS was observed in diabetics with non-endometrioid EC who used metformin than in diabetic cases not using metformin and non-endometrioid EC cases without diabetes (log rank test (p=0.02)). This association remained significant (hazard ratio = 0.54, 95% CI: 0.30–0.97, p<0.04) after adjusting for age, clinical stage, grade, chemotherapy treatment, radiation treatment and presence of hyperlipidemia in multivariate analysis. No association between metformin use and OS in diabetics with endometrioid histology was observed. Conclusion Diabetic EC patients with non-endometrioid tumors who used metformin had lower risk of death than women with EC who did not use metformin. These data suggest that metformin might be useful as adjuvant therapy for non-endometrioid EC. PMID:24189334

Female breast cancer incidence and survival in Utah according to religious preference, 1985–1999

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Merrill, Ray M; Folsom, Jeffrey A

2005-01-01

Background Female breast cancer incidence rates in Utah are among the lowest in the U.S. The influence of the Church of Jesus Christ of Latter-day Saint (LDS or Mormon) religion on these rates, as well as on disease-specific survival, will be explored for individuals diagnosed with breast cancer in Utah from 1985 through 1999. Methods Population-based records for incident female breast cancer patients were linked with membership records from the LDS Church to determine religious affiliation and, for LDS Church members, level of religiosity. Incidence rates were age-adjusted to the 2000 U.S. standard population using the direct method. Cox proportional hazards model was used to compare survival among religiously active LDS, less religiously active LDS, and non-LDS with simultaneous adjustment for prognostic factors. Results Age-adjusted breast cancer incidence rates were consistently lower for LDS than non-LDS in Utah from 1985 through 1999. Rates were lower among LDS compared with non-LDS across the age span. In 1995–99, the age-adjusted incidence rates were 107.6 (95% CI: 103.9 – 111.3) for LDS women and 130.5 (123.2 – 137.9) for non-LDS women. If non-LDS women in Utah had the same breast cancer risk profile as LDS women, an estimated 214 (4.8%) fewer malignant breast cancer cases would have occurred during 1995–99. With religiously active LDS serving as the reference group, the adjusted death hazard ratio for religiously less active LDS was 1.09 (0.94 – 1.27) and for non-LDS was 0.86 (0.75 – 0.98). Conclusion In Utah, LDS lifestyle is associated with lower incidence rates of female breast cancer. However, LDS experience poorer survivability from breast cancer than their non-LDS counterparts. Parity and breastfeeding, while protective factors against breast cancer, may contribute to poorer prognosis of female breast cancer in LDS women. PMID:15904509

Embolotherapy for Neuroendocrine Tumor Liver Metastases: Prognostic Factors for Hepatic Progression-Free Survival and Overall Survival

International Nuclear Information System (INIS)

Chen, James X.; Rose, Steven; White, Sarah B.; El-Haddad, Ghassan; Fidelman, Nicholas; Yarmohammadi, Hooman; Hwang, Winifred; Sze, Daniel Y.; Kothary, Nishita; Stashek, Kristen; Wileyto, E. Paul; Salem, Riad; Metz, David C.; Soulen, Michael C.

2017-01-01

PurposeThe purpose of the study was to evaluate prognostic factors for survival outcomes following embolotherapy for neuroendocrine tumor (NET) liver metastases.Materials and MethodsThis was a multicenter retrospective study of 155 patients (60 years mean age, 57 % male) with NET liver metastases from pancreas (n = 71), gut (n = 68), lung (n = 8), or other/unknown (n = 8) primary sites treated with conventional transarterial chemoembolization (TACE, n = 50), transarterial radioembolization (TARE, n = 64), or transarterial embolization (TAE, n = 41) between 2004 and 2015. Patient-, tumor-, and treatment-related factors were evaluated for prognostic effect on hepatic progression-free survival (HPFS) and overall survival (OS) using unadjusted and propensity score-weighted univariate and multivariate Cox proportional hazards models.ResultsMedian HPFS and OS were 18.5 and 125.1 months for G1 (n = 75), 12.2 and 33.9 months for G2 (n = 60), and 4.9 and 9.3 months for G3 tumors (n = 20), respectively (p  50 % hepatic volume demonstrated 5.5- and 26.8-month shorter median HPFS and OS, respectively, versus burden ≤50 % (p < 0.05). There were no significant differences in HPFS or OS between gut or pancreas primaries. In multivariate HPFS analysis, there were no significant differences among embolotherapy modalities. In multivariate OS analysis, TARE had a higher hazard ratio than TACE (unadjusted Cox model: HR 2.1, p = 0.02; propensity score adjusted model: HR 1.8, p = 0.11), while TAE did not differ significantly from TACE.ConclusionHigher tumor grade and tumor burden prognosticated shorter HPFS and OS. TARE had a higher hazard ratio for OS than TACE. There were no significant differences in HPFS among embolotherapy modalities.

Embolotherapy for Neuroendocrine Tumor Liver Metastases: Prognostic Factors for Hepatic Progression-Free Survival and Overall Survival

Energy Technology Data Exchange (ETDEWEB)

Chen, James X. [Hospital of the University of Pennsylvania, Division of Interventional Radiology, Department of Radiology (United States); Rose, Steven [University of San Diego Medical Center, Division of Interventional Radiology, Department of Radiology (United States); White, Sarah B. [Medical College of Wisconsin, Division of Interventional Radiology, Department of Radiology (United States); El-Haddad, Ghassan [Moffitt Cancer Center, Division of Interventional Radiology, Department of Radiology (United States); Fidelman, Nicholas [University of San Francisco Medical Center, Division of Interventional Radiology, Department of Radiology (United States); Yarmohammadi, Hooman [Memorial Sloan Kettering Cancer Center, Division of Interventional Radiology, Department of Radiology (United States); Hwang, Winifred; Sze, Daniel Y.; Kothary, Nishita [Stanford University Medical Center, Division of Interventional Radiology, Department of Radiology (United States); Stashek, Kristen [Hospital of the University of Pennsylvania, Department of Pathology (United States); Wileyto, E. Paul [University of Pennsylvania, Department of Biostatistics and Epidemiology (United States); Salem, Riad [Northwestern Memorial Hospital, Division of Interventional Radiology, Department of Radiology (United States); Metz, David C. [Hospital of the University of Pennsylvania, Division of Gastroenterology, Department of Medicine (United States); Soulen, Michael C., E-mail: michael.soulen@uphs.upenn.edu [Hospital of the University of Pennsylvania, Division of Interventional Radiology, Department of Radiology (United States)

2017-01-15

PurposeThe purpose of the study was to evaluate prognostic factors for survival outcomes following embolotherapy for neuroendocrine tumor (NET) liver metastases.Materials and MethodsThis was a multicenter retrospective study of 155 patients (60 years mean age, 57 % male) with NET liver metastases from pancreas (n = 71), gut (n = 68), lung (n = 8), or other/unknown (n = 8) primary sites treated with conventional transarterial chemoembolization (TACE, n = 50), transarterial radioembolization (TARE, n = 64), or transarterial embolization (TAE, n = 41) between 2004 and 2015. Patient-, tumor-, and treatment-related factors were evaluated for prognostic effect on hepatic progression-free survival (HPFS) and overall survival (OS) using unadjusted and propensity score-weighted univariate and multivariate Cox proportional hazards models.ResultsMedian HPFS and OS were 18.5 and 125.1 months for G1 (n = 75), 12.2 and 33.9 months for G2 (n = 60), and 4.9 and 9.3 months for G3 tumors (n = 20), respectively (p < 0.05). Tumor burden >50 % hepatic volume demonstrated 5.5- and 26.8-month shorter median HPFS and OS, respectively, versus burden ≤50 % (p < 0.05). There were no significant differences in HPFS or OS between gut or pancreas primaries. In multivariate HPFS analysis, there were no significant differences among embolotherapy modalities. In multivariate OS analysis, TARE had a higher hazard ratio than TACE (unadjusted Cox model: HR 2.1, p = 0.02; propensity score adjusted model: HR 1.8, p = 0.11), while TAE did not differ significantly from TACE.ConclusionHigher tumor grade and tumor burden prognosticated shorter HPFS and OS. TARE had a higher hazard ratio for OS than TACE. There were no significant differences in HPFS among embolotherapy modalities.

Advanced statistical methods to study the effects of gastric tube and non-invasive ventilation on functional decline and survival in amyotrophic lateral sclerosis.

Science.gov (United States)

Atassi, Nazem; Cudkowicz, Merit E; Schoenfeld, David A

2011-07-01

A few studies suggest that non-invasive ventilation (1) and gastric tube (G-tube) may have a positive impact on survival but the effect on functional decline is unclear. Confounding by indication may have produced biased estimates of the benefit seen in some of these retrospective studies. The objective of this study was to evaluate the effects of G-tube and NIV on survival and functional decline using advanced statistical models that adjust for confounding by indications. A database of 331 subjects enrolled in previous clinical trials in ALS was available for analysis. Marginal structural models (MSM) were used to compare the mortality hazards and ALSFRS-R slopes between treatment and non-treatment groups, after adjusting for confounding by indication. Results showed that the placement of a G-tube was associated with an additional 1.42 units/month decline in the ALSFRS-R slope (p NIV had no significant effect on ALSFRS-R decline or mortality. In conclusion, marginal structural models can be used to adjust for confounding by indication in retrospective ALS studies. G-tube placement could be followed by a faster rate of functional decline and increased mortality. Our results may suffer from some of the limitations of retrospective analyses.

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.

Monitoring risk-adjusted outcomes in congenital heart surgery: does the appropriateness of a risk model change with time?

Science.gov (United States)

Tsang, Victor T; Brown, Katherine L; Synnergren, Mats Johanssen; Kang, Nicholas; de Leval, Marc R; Gallivan, Steve; Utley, Martin

2009-02-01

Risk adjustment of outcomes in pediatric congenital heart surgery is challenging due to the great diversity in diagnoses and procedures. We have previously shown that variable life-adjusted display (VLAD) charts provide an effective graphic display of risk-adjusted outcomes in this specialty. A question arises as to whether the risk model used remains appropriate over time. We used a recently developed graphic technique to evaluate the performance of an existing risk model among those patients at a single center during 2000 to 2003 originally used in model development. We then compared the distribution of predicted risk among these patients with that among patients in 2004 to 2006. Finally, we constructed a VLAD chart of risk-adjusted outcomes for the latter period. Among 1083 patients between April 2000 and March 2003, the risk model performed well at predicted risks above 3%, underestimated mortality at 2% to 3% predicted risk, and overestimated mortality below 2% predicted risk. There was little difference in the distribution of predicted risk among these patients and among 903 patients between June 2004 and October 2006. Outcomes for the more recent period were appreciably better than those expected according to the risk model. This finding cannot be explained by any apparent bias in the risk model combined with changes in case-mix. Risk models can, and hopefully do, become out of date. There is scope for complacency in the risk-adjusted audit if the risk model used is not regularly recalibrated to reflect changing standards and expectations.

DIFFERENTIAL IMPACT OF HLA-A, HLA-B AND HLA-DR COMPATIBILITY ON THE RENAL ALLOGRAFT SURVIVAL

Directory of Open Access Journals (Sweden)

V. Y. Abramov

2012-01-01

Full Text Available We studied the long-term results of 532 deceased donor kidney transplantations to investigate the impact of HLA match on the survival of renal allograft. All transplants were performed in our center in 1996–2009 and moni- tored prospectively for 1–14 years. We found, the survival of 58 kidneys grafted with 0–2 mismatch for HLA- ABDR to be significantly better (Plogrank = 0,016 than the survival of the kidneys grafted with 3–6 HLA-ABDR mismatch. The full compatibility for HLA-A (n = 75 did not influence the long-term survival (Plogrank = 0,48. The absence of HLA-DR mismatch had a beneficial effect for survival of 68 kidneys (Plogrank = 0,07. Eighteen cases with the full HLA-B compatibility between graft and recipient demonstrated excellent long-term survival (Plogrank = 0,007. HLA-B compatibility influenced significantly (P = 0,042 the survival of transplanted kidney in the Cox regression model adjusted for donor and recipient age, panel-reactive antibody level, re-transplant, and immunosuppression protocol. The data obtained support the conclusion, that HLA compatibility should be one of the criteria of deceased donor kidney allocation. 

Value-based contracting innovated Medicare advantage healthcare delivery and improved survival.

Science.gov (United States)

Mandal, Aloke K; Tagomori, Gene K; Felix, Randell V; Howell, Scott C

2017-02-01

In Medicare Advantage (MA) with its CMS Hierarchical Condition Categories (CMS-HCC) payment model, CMS reimburses private plans (Medicare Advantage Organizations [MAOs]) with prospective, monthly, health-based or risk-adjusted, capitated payments. The effect of this payment methodology on healthcare delivery remains debatable. How value-based contracting generates cost efficiencies and improves clinical outcomes in MA is studied. A difference in contracting arrangements between an MAO and 2 provider groups facilitated an intervention-control, preintervention-postintervention, difference-in-differences approach among statistically similar, elderly, community-dwelling MA enrollees within one metropolitan statistical area. Starting in 2009, for intervention-group MA enrollees, the MAO and a provider group agreed to full-risk capitation combined with a revenue gainshare. The gainshare was based on increases in the Risk Adjustment Factor (RAF), which modified the CMS-HCC payments. For the control group, the MAO continued to reimburse another provider group through fee-for-service. RAF, utilization, and survival were followed until December 31, 2012. The intervention group's mean RAF increased significantly (P based visits (P based care for these MA enrollees with multiple comorbidities, a 6% survival benefit with a 32.8% lower hazard of death (P Value-based contracting can drive utilization patterns and improve clinical outcomes among chronically ill, elderly MA members.

Analyzing sickness absence with statistical models for survival data

DEFF Research Database (Denmark)

Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars

2007-01-01

OBJECTIVES: Sickness absence is the outcome in many epidemiologic studies and is often based on summary measures such as the number of sickness absences per year. In this study the use of modern statistical methods was examined by making better use of the available information. Since sickness...... absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...

Prognostic factors associated with the survival of oral and pharyngeal carcinoma in Taiwan

International Nuclear Information System (INIS)

Chen, Ping-Ho; Tu, Hung-Pin; Ko, Ying-Chin; Shieh, Tien-Yu; Ho, Pei-Shan; Tsai, Chi-Cheng; Yang, Yi-Hsin; Lin, Ying-Chu; Ko, Min-Shan; Tsai, Pei-Chien; Chiang, Shang-Lun

2007-01-01

In Taiwan, a distinct ethnic group variation in incidence and mortality rates has been suggested for most carcinomas. Our aim is to identify the role of prognostic factors associated with the survival of oral and pharyngeal carcinoma in Taiwan. Taiwan Cancer Registry records of 9039 subjects diagnosed with oral and pharyngeal carcinoma were analyzed. The population was divided into three ethnic groups by residence, which were Taiwanese aborigines, Hakka and Hokkien communities. Five-year survival rates were estimated by Kaplan-Meier methods. Ethnic curves differed significantly by log-rank test; therefore separate models for Taiwanese aborigines, Hakka and Hokkien were carried out. The Cox multivariate proportional hazards model was used to examine the role of prognostic factors on ethnic survival. The five-year survival rates of oral and pharyngeal carcinoma were significantly poorer for Hokkien community (53.9%) and Taiwanese aborigines community (58.1%) compared with Hakka community (60.5%). The adjusted hazard ratio of Taiwanese aborigines versus Hakka was 1.07 (95%CI, 0.86–1.33) for oral and pharyngeal carcinoma mortality, and 1.16 (95%CI, 1.01–1.33) for Hokkien versus Hakka. Males had significantly poor prognosis than females. Subjects with tongue and/or mouth carcinoma presented the worst prognosis, whereas lip carcinoma had the best prognosis. Subjects with verrucous carcinoma had better survival than squamous cell carcinoma. Prognosis was the worst in elderly subjects, and subjects who underwent surgery had the highest survival rate. Our study presented that predictive variables in oral and pharyngeal carcinoma survival have been: ethnic groups, period of diagnosis, gender, diagnostic age, anatomic site, morphologic type, and therapy

Biochemical Control With Radiotherapy Improves Overall Survival in Intermediate and High-Risk Prostate Cancer Patients Who Have an Estimated 10-Year Overall Survival of >90%

International Nuclear Information System (INIS)

Herbert, Christopher; Liu, Mitchell; Tyldesley, Scott; Morris, W. James; Joffres, Michel; Khaira, Mandip; Kwan, Winkle; Moiseenko, Vitali; Pickles, Thomas

2012-01-01

Purpose: To identify subgroups of patients with carcinoma of the prostate treated with radical radiotherapy that have improved overall survival when disease is biochemically controlled. Methods and Materials: A cohort of 1,060 prostate cancer patients treated with radical radiotherapy was divided into nine subgroups based on National Comprehensive Cancer Network risk category and estimated 10-year overall survival (eOS 10y) derived from the age adjusted Charlson Comorbidity Index. Patients with and without biochemical control were compared with respect to overall survival. Actuarial estimates of overall survival were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of overall survival. Results: Median follow-up was 125 months (range, 51–176 months). Only the subgroups with high or intermediate risk disease and an eOS 10y of >90% had a statistically significantly improved overall survival when prostate cancer was biochemically controlled. In all other groups, biochemical control made no significant difference to overall survival. In the subgroup with high-risk disease and eOS 10y >90%, actuarial overall survival was 86.3% (95% confidence interval [CI] 78.5%–94.1%) and 62.1% (95% CI 52.9%–71.3%) for patients with biochemical control and biochemical relapse respectively (p = 0.002). In the intermediate risk group with eOS >90%, actuarial overall survival was 95.3% (95% CI 89.0%–100%) and 79.8% (95% CI 68.0%–91.6%) for biochemically controlled and biochemically relapsed patients (p = 0.033). On multivariate analysis, National Comprehensive Cancer Network risk group (p = 0.005), biochemical control (p = 0.033) and eOS 10y (p 90%.

Association of a Locus in the CAMTA1 Gene With Survival in Patients With Sporadic Amyotrophic Lateral Sclerosis.

Science.gov (United States)

Fogh, Isabella; Lin, Kuang; Tiloca, Cinzia; Rooney, James; Gellera, Cinzia; Diekstra, Frank P; Ratti, Antonia; Shatunov, Aleksey; van Es, Michael A; Proitsi, Petroula; Jones, Ashley; Sproviero, William; Chiò, Adriano; McLaughlin, Russell Lewis; Sorarù, Gianni; Corrado, Lucia; Stahl, Daniel; Del Bo, Roberto; Cereda, Cristina; Castellotti, Barbara; Glass, Jonathan D; Newhouse, Steven; Dobson, Richard; Smith, Bradley N; Topp, Simon; van Rheenen, Wouter; Meininger, Vincent; Melki, Judith; Morrison, Karen E; Shaw, Pamela J; Leigh, P Nigel; Andersen, Peter M; Comi, Giacomo P; Ticozzi, Nicola; Mazzini, Letizia; D'Alfonso, Sandra; Traynor, Bryan J; Van Damme, Philip; Robberecht, Wim; Brown, Robert H; Landers, John E; Hardiman, Orla; Lewis, Cathryn M; van den Berg, Leonard H; Shaw, Christopher E; Veldink, Jan H; Silani, Vincenzo; Al-Chalabi, Ammar; Powell, John

2016-07-01

Amyotrophic lateral sclerosis (ALS) is a devastating adult-onset neurodegenerative disorder with a poor prognosis and a median survival of 3 years. However, a significant proportion of patients survive more than 10 years from symptom onset. To identify gene variants influencing survival in ALS. This genome-wide association study (GWAS) analyzed survival in data sets from several European countries and the United States that were collected by the Italian Consortium for the Genetics of ALS and the International Consortium on Amyotrophic Lateral Sclerosis Genetics. The study population included 4256 patients with ALS (3125 [73.4%] deceased) with genotype data extended to 7 174 392 variants by imputation analysis. Samples of DNA were collected from January 1, 1993, to December 31, 2009, and analyzed from March 1, 2014, to February 28, 2015. Cox proportional hazards regression under an additive model with adjustment for age at onset, sex, and the first 4 principal components of ancestry, followed by meta-analysis, were used to analyze data. Survival distributions for the most associated genetic variants were assessed by Kaplan-Meier analysis. Among the 4256 patients included in the analysis (2589 male [60.8%] and 1667 female [39.2%]; mean [SD] age at onset, 59 [12] years), the following 2 novel loci were significantly associated with ALS survival: at 10q23 (rs139550538; P = 1.87 × 10-9) and in the CAMTA1 gene at 1p36 (rs2412208, P = 3.53 × 10-8). At locus 10q23, the adjusted hazard ratio for patients with the rs139550538 AA or AT genotype was 1.61 (95% CI, 1.38-1.89; P = 1.87 × 10-9), corresponding to an 8-month reduction in survival compared with TT carriers. For rs2412208 CAMTA1, the adjusted hazard ratio for patients with the GG or GT genotype was 1.17 (95% CI, 1.11-1.24; P = 3.53 × 10-8), corresponding to a 4-month reduction in survival compared with TT carriers. This GWAS robustly identified 2 loci at genome-wide levels of

Exploring location influences on firm survival rates using parametric duration models

NARCIS (Netherlands)

Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.; Timmermans, H.J.P.; Vries, de B.

2010-01-01

Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and

Exploring location influences on firm survival rates using parametric duration models

NARCIS (Netherlands)

Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.

2011-01-01

Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and

A Unified Model of Geostrophic Adjustment and Frontogenesis

Science.gov (United States)

Taylor, John; Shakespeare, Callum

2013-11-01

Fronts, or regions with strong horizontal density gradients, are ubiquitous and dynamically important features of the ocean and atmosphere. In the ocean, fronts are associated with enhanced air-sea fluxes, turbulence, and biological productivity, while atmospheric fronts are associated with some of the most extreme weather events. Here, we describe a new mathematical framework for describing the formation of fronts, or frontogenesis. This framework unifies two classical problems in geophysical fluid dynamics, geostrophic adjustment and strain-driven frontogenesis, and provides a number of important extensions beyond previous efforts. The model solutions closely match numerical simulations during the early stages of frontogenesis, and provide a means to describe the development of turbulence at mature fronts.

Effect of the spray volume adjustment model on the efficiency of fungicides and residues in processing tomato

Energy Technology Data Exchange (ETDEWEB)

Ratajkiewicz, H.; Kierzek, R.; Raczkowski, M.; Hołodyńska-Kulas, A.; Łacka, A.; Wójtowicz, A.; Wachowiak, M.

2016-11-01

This study compared the effects of a proportionate spray volume (PSV) adjustment model and a fixed model (300 L/ha) on the infestation of processing tomato with potato late blight (Phytophthora infestans (Mont.) de Bary) (PLB) and azoxystrobin and chlorothalonil residues in fruits in three consecutive seasons. The fungicides were applied in alternating system with or without two spreader adjuvants. The proportionate spray volume adjustment model was based on the number of leaves on plants and spray volume index. The modified Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method was optimized and validated for extraction of azoxystrobin and chlorothalonil residue. Gas chromatography with a nitrogen and phosphorus detector and an electron capture detector were used for the analysis of fungicides. The results showed that higher fungicidal residues were connected with lower infestation of tomato with PLB. PSV adjustment model resulted in lower infestation of tomato than the fixed model (300 L/ha) when fungicides were applied at half the dose without adjuvants. Higher expected spray interception into the tomato canopy with the PSV system was recognized as the reasons of better control of PLB. The spreader adjuvants did not have positive effect on the biological efficacy of spray volume application systems. The results suggest that PSV adjustment model can be used to determine the spray volume for fungicide application for processing tomato crop. (Author)

Effect of the spray volume adjustment model on the efficiency of fungicides and residues in processing tomato

Directory of Open Access Journals (Sweden)

Henryk Ratajkiewicz

2016-08-01

Full Text Available This study compared the effects of a proportionate spray volume (PSV adjustment model and a fixed model (300 L/ha on the infestation of processing tomato with potato late blight (Phytophthora infestans (Mont. de Bary (PLB and azoxystrobin and chlorothalonil residues in fruits in three consecutive seasons. The fungicides were applied in alternating system with or without two spreader adjuvants. The proportionate spray volume adjustment model was based on the number of leaves on plants and spray volume index. The modified Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS method was optimized and validated for extraction of azoxystrobin and chlorothalonil residue. Gas chromatography with a nitrogen and phosphorus detector and an electron capture detector were used for the analysis of fungicides. The results showed that higher fungicidal residues were connected with lower infestation of tomato with PLB. PSV adjustment model resulted in lower infestation of tomato than the fixed model (300 L/ha when fungicides were applied at half the dose without adjuvants. Higher expected spray interception into the tomato canopy with the PSV system was recognized as the reasons of better control of PLB. The spreader adjuvants did not have positive effect on the biological efficacy of spray volume application systems. The results suggest that PSV adjustment model can be used to determine the spray volume for fungicide application for processing tomato crop.

Nivolumab versus Cabozantinib: Comparing Overall Survival in Metastatic Renal Cell Carcinoma.

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Witold Wiecek

Full Text Available Renal-cell carcinoma (RCC affects over 330,000 new patients every year, of whom 1/3 present with metastatic RCC (mRCC at diagnosis. Most mRCC patients treated with a first-line agent relapse within 1 year and need second-line therapy. The present study aims to compare overall survival (OS between nivolumab and cabozantinib from two recent pivotal studies comparing, respectively, each one of the two emerging treatments against everolimus in patients who relapse following first-line treatment. Comparison is traditionally carried out using the Bucher method, which assumes proportional hazard. Since OS curves intersected in one of the pivotal studies, models not assuming proportional hazards were also considered to refine the comparison. Four Bayesian parametric survival network meta-analysis models were implemented on overall survival (OS data digitized from the Kaplan-Meier curves reported in the studies. Three models allowing hazard ratios (HR to vary over time were assessed against a fixed-HR model. The Bucher method favored cabozantinib, with a fixed HR for OS vs. nivolumab of 1.09 (95% confidence interval: [0.77, 1.54]. However, all models with time-varying HR showed better fits than the fixed-HR model. The log-logistic model fitted the data best, exhibiting a HR for OS initially favoring cabozantinib, the trend inverting to favor nivolumab after month 5 (95% credible interval <1 from 10 months. The initial probability of cabozantinib conferring superior OS was 54%, falling to 41.5% by month 24. Numerical differences in study-adjusted OS estimates between the two treatments remained small. This study evidences that HR for OS of nivolumab vs. cabozantinib varies over time, favoring cabozantinib in the first months of treatment but nivolumab afterwards, a possible indication that patients with poor prognosis benefit more from cabozantinib in terms of survival, nivolumab benefiting patients with better prognosis. More evidence, including real

Risk-adjusted performance evaluation in three academic thoracic surgery units using the Eurolung risk models.

Science.gov (United States)

Pompili, Cecilia; Shargall, Yaron; Decaluwe, Herbert; Moons, Johnny; Chari, Madhu; Brunelli, Alessandro

2018-01-03

The objective of this study was to evaluate the performance of 3 thoracic surgery centres using the Eurolung risk models for morbidity and mortality. This was a retrospective analysis performed on data collected from 3 academic centres (2014-2016). Seven hundred and twenty-one patients in Centre 1, 857 patients in Centre 2 and 433 patients in Centre 3 who underwent anatomical lung resections were analysed. The Eurolung1 and Eurolung2 models were used to predict risk-adjusted cardiopulmonary morbidity and 30-day mortality rates. Observed and risk-adjusted outcomes were compared within each centre. The observed morbidity of Centre 1 was in line with the predicted morbidity (observed 21.1% vs predicted 22.7%, P = 0.31). Centre 2 performed better than expected (observed morbidity 20.2% vs predicted 26.7%, P models were successfully used as risk-adjusting instruments to internally audit the outcomes of 3 different centres, showing their applicability for future quality improvement initiatives. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Identifying an Inciting Antigen Is Associated With Improved Survival in Patients With Chronic Hypersensitivity Pneumonitis

Science.gov (United States)

Swigris, Jeffrey J.; Forssén, Anna V.; Tourin, Olga; Solomon, Joshua J.; Huie, Tristan J.; Olson, Amy L.; Brown, Kevin K.

2013-01-01

Background: The cornerstone of hypersensitivity pneumonitis (HP) management is having patients avoid the inciting antigen (IA). Often, despite an exhaustive search, an IA cannot be found. The objective of this study was to examine whether identifying the IA impacts survival in patients with chronic HP. Methods: We used the Kaplan-Meier method to display, and the log-rank test to compare, survival curves of patients with well-characterized chronic HP stratified on identification of an IA exposure. A Cox proportional hazards (PH) model was used to identify independent predictors in time-to-death analysis. Results: Of 142 patients, 67 (47%) had an identified IA, and 75 (53%) had an unidentified IA. Compared with survivors, patients who died (n = 80, 56%) were older, more likely to have smoked, had lower total lung capacity % predicted and FVC % predicted, had higher severity of dyspnea, were more likely to have pulmonary fibrosis, and were less likely to have an identifiable IA. In a Cox PH model, the inability to identify an IA (hazard ratio [HR], 1.76; 95% CI, 1.01-3.07), older age (HR, 1.04; 95% CI, 1.01-1.07), the presences of pulmonary fibrosis (HR, 2.43; 95% CI, 1.36-4.35), a lower FVC% (HR, 1.36; 95% CI, 1.10-1.68), and a history of smoking (HR, 2.01; 95% C1, 1.15-3.50) were independent predictors of shorter survival. After adjusting for mean age, presence of fibrosis, mean FVC%, mean diffusing capacity of the lung for carbon monoxide (%), and history of smoking, survival was longer for patients with an identified IA exposure than those with an unidentified IA exposure (median, 8.75 years vs 4.88 years; P = .047). Conclusions: Among patients with chronic HP, when adjusting for a number of potentially influential predictors, including the presence of fibrosis, the inability to identify an IA was independently associated with shortened survival. PMID:23828161

Adjustments of the TaD electron density reconstruction model with GNSS-TEC parameters for operational application purposes

Directory of Open Access Journals (Sweden)

Belehaki Anna

2012-12-01

Full Text Available Validation results on the latest version of TaD model (TaDv2 show realistic reconstruction of the electron density profiles (EDPs with an average error of 3 TECU, similar to the error obtained from GNSS-TEC calculated paremeters. The work presented here has the aim to further improve the accuracy of the TaD topside reconstruction, adjusting the TEC parameter calculated from TaD model with the TEC parameter calculated by GNSS transmitting RINEX files provided by receivers co-located with the Digisondes. The performance of the new version is tested during a storm period demonstrating further improvements in respect to the previous version. Statistical comparison of modeled and observed TEC confirms the validity of the proposed adjustment. A significant benefit of the proposed upgrade is that it facilitates the real-time implementation of TaD. The model needs a reliable measure of the scale height at the peak height, which is supposed to be provided by Digisondes. Oftenly, the automatic scaling software fails to correctly calculate the scale height at the peak, Hm, due to interferences in the receiving signal. Consequently the model estimated topside scale height is wrongly calculated leading to unrealistic results for the modeled EDP. The proposed TEC adjustment forces the model to correctly reproduce the topside scale height, despite the inaccurate values of Hm. This adjustment is very important for the application of TaD in an operational environment.

Body mass index, weight change, and survival in non-Hodgkin lymphoma patients in Connecticut women.

Science.gov (United States)

Han, Xuesong; Stevens, June; Bradshaw, Patrick T

2013-01-01

Evidence is emerging that obesiy and weight gain may affect the prognosis of several types of cancer. We investigated the impact of body mass index (BMI) as well as pre-and postdiagnosis weight changes on non-Hodgkin lymphoma (NHL) prognosis. A cohort of 573 female incident NHL cases diagnosed during 1996-2000 in Connecticut was followed for a median of 7.8 yr. Self-reported height and weight at 3 time points before and after diagnosis were collected. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using proportional hazard models adjusting for factors believed to be associated with overall survival of NHL. Underweight (BMI treatment were found to have a poorer survival.

Statistical modelling of survival data with random effects h-likelihood approach

CERN Document Server

Ha, Il Do; Lee, Youngjo

2017-01-01

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to research...

Adjustment of regional regression models of urban-runoff quality using data for Chattanooga, Knoxville, and Nashville, Tennessee

Science.gov (United States)

Hoos, Anne B.; Patel, Anant R.

1996-01-01

Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.

Remote Sensing-based Methodologies for Snow Model Adjustments in Operational Streamflow Prediction

Science.gov (United States)

Bender, S.; Miller, W. P.; Bernard, B.; Stokes, M.; Oaida, C. M.; Painter, T. H.

2015-12-01

Water management agencies rely on hydrologic forecasts issued by operational agencies such as NOAA's Colorado Basin River Forecast Center (CBRFC). The CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate research-oriented, remotely-sensed snow data into CBRFC operations and to improve the accuracy of CBRFC forecasts. The partnership has yielded valuable analysis of snow surface albedo as represented in JPL's MODIS Dust Radiative Forcing in Snow (MODDRFS) data, across the CBRFC's area of responsibility. When dust layers within a snowpack emerge, reducing the snow surface albedo, the snowmelt rate may accelerate. The CBRFC operational snow model (SNOW17) is a temperature-index model that lacks explicit representation of snowpack surface albedo. CBRFC forecasters monitor MODDRFS data for emerging dust layers and may manually adjust SNOW17 melt rates. A technique was needed for efficient and objective incorporation of the MODDRFS data into SNOW17. Initial development focused in Colorado, where dust-on-snow events frequently occur. CBRFC forecasters used retrospective JPL-CBRFC analysis and developed a quantitative relationship between MODDRFS data and mean areal temperature (MAT) data. The relationship was used to generate adjusted, MODDRFS-informed input for SNOW17. Impacts of the MODDRFS-SNOW17 MAT adjustment method on snowmelt-driven streamflow prediction varied spatially and with characteristics of the dust deposition events. The largest improvements occurred in southwestern Colorado, in years with intense dust deposition events. Application of the method in other regions of Colorado and in "low dust" years resulted in minimal impact. The MODDRFS-SNOW17 MAT technique will be implemented in CBRFC operations in late 2015, prior to spring 2016 runoff. Collaborative investigation of remote sensing-based adjustment methods for the CBRFC operational hydrologic forecasting environment will continue over the next several years.

Repatriation Adjustment: Literature Review

Directory of Open Access Journals (Sweden)

Gamze Arman

2009-12-01

Full Text Available Expatriation is a widely studied area of research in work and organizational psychology. After expatriates accomplish their missions in host countries, they return to their countries and this process is called repatriation. Adjustment constitutes a crucial part in repatriation research. In the present literature review, research about repatriation adjustment was reviewed with the aim of defining the whole picture in this phenomenon. Present research was classified on the basis of a theoretical model of repatriation adjustment. Basic frame consisted of antecedents, adjustment, outcomes as main variables and personal characteristics/coping strategies and organizational strategies as moderating variables.

Models of traumatic experiences and children's psychological adjustment: the roles of perceived parenting and the children's own resources and activity.

Science.gov (United States)

Punamäki, R L; Qouta, S; el Sarraj, E

1997-08-01

The relations between traumatic events, perceived parenting styles, children's resources, political activity, and psychological adjustment were examined among 108 Palestinian boys and girls of 11-12 years of age. The results showed that exposure to traumatic events increased psychological adjustment problems directly and via 2 mediating paths. First, the more traumatic events children had experienced, the more negative parenting they experienced. And, the poorer they perceived parenting, the more they suffered from high neuroticism and low self-esteem. Second, the more traumatic events children had experienced, the more political activity they showed, and the more active they were, the more they suffered from psychological adjustment problems. Good perceived parenting protected children's psychological adjustment by making them less vulnerable in two ways. First, traumatic events decreased their intellectual, creative, and cognitive resources, and a lack of resources predicted many psychological adjustment problems in a model excluding perceived parenting. Second, political activity increased psychological adjustment problems in the same model, but not in the model including good parenting.

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

Racial residential segregation, socioeconomic disparities, and the White-Black survival gap

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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

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.

Differential impact of obesity and diabetes mellitus on survival after liver resection for colorectal cancer metastases.

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Amptoulach, Sousana; Gross, Gillis; Kalaitzakis, Evangelos

2015-12-01

Data on the potential effect of obesity and diabetes mellitus on survival after liver resection due to colorectal cancer (CRC) metastases are very limited. Patients undergoing liver resection for CRC metastases in a European institution in 2004-2011 were retrospectively enrolled. Relevant data, such as body mass index, extent of resection, chemotherapy, and perioperative outcome, were collected from medical records. The relation of obesity and diabetes mellitus with overall and disease-free survival was assessed using adjusted Cox models. Thirty of 207 patients (14.4%) included in the study were obese (BMI ≥30 kg/m(2)) and 25 (12%) had diabetes mellitus. Major hepatectomy was performed in 46%. Although both obese patients and those with diabetes had higher American Society of Anesthesiologist scores (P diabetes was significantly related to primary tumor characteristics, liver metastasis features, extent or radicality of resection, extrahepatic disease at hepatectomy, preoperative or postoperative oncologic therapy, or perioperative outcome (P > 0.05 for all). Patients were followed up for a median of 39 mo posthepatectomy (interquartile range, 13-56 mo). After adjustment for confounders, obesity was an independent predictor of improved (hazard ratio, 0.305, 95% confidence interval, 0.103-0.902) and diabetes of worse overall survival (hazard ratio, 3.298, 95% confidence interval, 1.306-8.330). Obese patients with diabetes had also worse disease-free survival compared with the rest of the cohort (P diabetes mellitus has a negative impact on prognosis. Copyright © 2015 Elsevier Inc. All rights reserved.

A Four-Part Model of Autonomy during Emerging Adulthood: Associations with Adjustment

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Lamborn, Susie D.; Groh, Kelly

2009-01-01

We found support for a four-part model of autonomy that links connectedness, separation, detachment, and agency to adjustment during emerging adulthood. Based on self-report surveys of 285 American college students, expected associations among the autonomy variables were found. In addition, agency, as measured by self-reliance, predicted lower…

Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

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Liu, Gang; Dong, Chuanpeng; Wang, Xing; Hou, Guojun; Zheng, Yu; Xu, Huilin; Zhan, Xiaohui; Liu, Lei

2017-11-17

Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than those in high-risk group. This finding was further validated in five other independent datasets (GSE14333, GSE17536, GSE17537, GSE33113, and GSE37892). Besides, associations between clinicopathological information and risk score were analyzed. A nomogram including risk score was plotted to facilitate the utilization of risk score. The risk score model is also demonstrated to be effective on predicting both overall and recurrence-free survival of chemotherapy received patients. After performing Gene Set Enrichment Analysis (GSEA) between high and low risk groups, we found that several cell-cell interaction KEGG pathways were identified. Funnel plot results showed that there was no publication bias in these datasets. In summary, by utilizing the regulatory activity in stage II and III colorectal carcinoma, the risk score successfully predicts the survival of 1021 stage II/III CRC patients in six independent datasets.

Adjusting kinematics and kinetics in a feedback-controlled toe walking model

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Olenšek Andrej

2012-08-01

Full Text Available Abstract Background In clinical gait assessment, the correct interpretation of gait kinematics and kinetics has a decisive impact on the success of the therapeutic programme. Due to the vast amount of information from which primary anomalies should be identified and separated from secondary compensatory changes, as well as the biomechanical complexity and redundancy of the human locomotion system, this task is considerably challenging and requires the attention of an experienced interdisciplinary team of experts. The ongoing research in the field of biomechanics suggests that mathematical modeling may facilitate this task. This paper explores the possibility of generating a family of toe walking gait patterns by systematically changing selected parameters of a feedback-controlled model. Methods From the selected clinical case of toe walking we identified typical toe walking characteristics and encoded them as a set of gait-oriented control objectives to be achieved in a feedback-controlled walking model. They were defined as fourth order polynomials and imposed via feedback control at the within-step control level. At the between-step control level, stance leg lengthening velocity at the end of the single support phase was adaptively adjusted after each step so as to facilitate gait velocity control. Each time the gait velocity settled at the desired value, selected intra-step gait characteristics were modified by adjusting the polynomials so as to mimic the effect of a typical therapeutical intervention - inhibitory casting. Results By systematically adjusting the set of control parameters we were able to generate a family of gait kinematic and kinetic patterns that exhibit similar principal toe walking characteristics, as they were recorded by means of an instrumented gait analysis system in the selected clinical case of toe walking. We further acknowledge that they to some extent follow similar improvement tendencies as those which one can

Measurement of the Economic Growth and Add-on of the R.M. Solow Adjusted Model

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Ion Gh. Rosca

2007-08-01

Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans model etc., the R.M. Solow model is part of the category which characterizes the economic growth.The paper aim is the economic growth measurement and add-on of the R.M. Solow adjusted model.

A comparative study of generalized linear mixed modelling and artificial neural network approach for the joint modelling of survival and incidence of Dengue patients in Sri Lanka

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Hapugoda, J. C.; Sooriyarachchi, M. R.

2017-09-01

Survival time of patients with a disease and the incidence of that particular disease (count) is frequently observed in medical studies with the data of a clustered nature. In many cases, though, the survival times and the count can be correlated in a way that, diseases that occur rarely could have shorter survival times or vice versa. Due to this fact, joint modelling of these two variables will provide interesting and certainly improved results than modelling these separately. Authors have previously proposed a methodology using Generalized Linear Mixed Models (GLMM) by joining the Discrete Time Hazard model with the Poisson Regression model to jointly model survival and count model. As Aritificial Neural Network (ANN) has become a most powerful computational tool to model complex non-linear systems, it was proposed to develop a new joint model of survival and count of Dengue patients of Sri Lanka by using that approach. Thus, the objective of this study is to develop a model using ANN approach and compare the results with the previously developed GLMM model. As the response variables are continuous in nature, Generalized Regression Neural Network (GRNN) approach was adopted to model the data. To compare the model fit, measures such as root mean square error (RMSE), absolute mean error (AME) and correlation coefficient (R) were used. The measures indicate the GRNN model fits the data better than the GLMM model.

The effect of referral for cardiac rehabilitation on survival following acute myocardial infarction

DEFF Research Database (Denmark)

Lewinter, Christian; Bland, John M; Crouch, Simon

2014-01-01

BACKGROUND: International guidelines recommend referral for cardiac rehabilitation (CR) after acute myocardial infarction (AMI). However, the impact on long-term survival after CR referral has not been adjusted by time-variance. We compared the effects of CR referral after hospitalization for AMI......% CI, 0.66 to 0.96, p = 0.02 in 2003) when patients entered the model at three months after discharge and had a common exit at 90 months. Significant positive and negative predictors for CR referral were beta-blocker prescription (+), reperfusion (+) and age (-) in 1995, and reperfusion...... (+), revascularization (+), heart failure (HF) (+), antiplatelets (+), angiotensin-converting-enzyme inhibitor (ACE-I) (+), statins (+), diabetes (-), and the modified Global Registry of Acute Cardiac Events (GRACE) risk score (-) in 2003. CONCLUSIONS: CR referral was associated with improved survival in 2003...

Regional variations in cancer survival: Impact of tumour stage, socioeconomic status, comorbidity and type of treatment in Norway.

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Skyrud, Katrine Damgaard; Bray, Freddie; Eriksen, Morten Tandberg; Nilssen, Yngvar; Møller, Bjørn

2016-05-01

Cancer survival varies by place of residence, but it remains uncertain whether this reflects differences in tumour, patient and treatment characteristics (including tumour stage, indicators of socioeconomic status (SES), comorbidity and information on received surgery and radiotherapy) or possibly regional differences in the quality of delivered health care. National population-based data from the Cancer Registry of Norway were used to identify cancer patients diagnosed in 2002-2011 (n = 258,675). We investigated survival from any type of cancer (all cancer sites combined), as well as for the six most common cancers. The effect of adjusting for prognostic factors on regional variations in cancer survival was examined by calculating the mean deviation, defined by the mean absolute deviation of the relative excess risks across health services regions. For prostate cancer, the mean deviation across regions was 1.78 when adjusting for age and sex only, but decreased to 1.27 after further adjustment for tumour stage. For breast cancer, the corresponding mean deviations were 1.34 and 1.27. Additional adjustment for other prognostic factors did not materially change the regional variation in any of the other sites. Adjustment for tumour stage explained most of the regional variations in prostate cancer survival, but had little impact for other sites. Unexplained regional variations after adjusting for tumour stage, SES indicators, comorbidity and type of treatment in Norway may be related to regional inequalities in the quality of cancer care. © 2015 UICC.

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.

Ants avoid superinfections by performing risk-adjusted sanitary care.

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Konrad, Matthias; Pull, Christopher D; Metzler, Sina; Seif, Katharina; Naderlinger, Elisabeth; Grasse, Anna V; Cremer, Sylvia

2018-03-13

Being cared for when sick is a benefit of sociality that can reduce disease and improve survival of group members. However, individuals providing care risk contracting infectious diseases themselves. If they contract a low pathogen dose, they may develop low-level infections that do not cause disease but still affect host immunity by either decreasing or increasing the host's vulnerability to subsequent infections. Caring for contagious individuals can thus significantly alter the future disease susceptibility of caregivers. Using ants and their fungal pathogens as a model system, we tested if the altered disease susceptibility of experienced caregivers, in turn, affects their expression of sanitary care behavior. We found that low-level infections contracted during sanitary care had protective or neutral effects on secondary exposure to the same (homologous) pathogen but consistently caused high mortality on superinfection with a different (heterologous) pathogen. In response to this risk, the ants selectively adjusted the expression of their sanitary care. Specifically, the ants performed less grooming and more antimicrobial disinfection when caring for nestmates contaminated with heterologous pathogens compared with homologous ones. By modulating the components of sanitary care in this way the ants acquired less infectious particles of the heterologous pathogens, resulting in reduced superinfection. The performance of risk-adjusted sanitary care reveals the remarkable capacity of ants to react to changes in their disease susceptibility, according to their own infection history and to flexibly adjust collective care to individual risk.

Survival of Poliovirus in Flowing Turbid Seawater Treated with Ultraviolet Light

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Hill, W. F.; Hamblet, F. E.; Akin, E. W.

1967-01-01

The effectiveness of a model ultraviolet (UV) radiation unit for treating flowing turbid seawater contaminated with poliovirus was determined. At a turbidity of 70 ppm, the observed survival ratios ranged from 1.9 × 10-3 (99.81% reduction) to 1.5 × 10-4 (99.98% reduction) at flow rates ranging from 25 to 15 liters/min; no virus was recovered at flow rates of 10 and 5 liters/min. At a turbidity of 240 ppm, the observed survival ratios ranged from 3.2 × 10-2 (96.80% reduction) to 2.1 × 10-4 (99.98% reduction) at flow rates ranging from 25 to 5 liters/min. As expected, turbidity had an adverse influence on the effectiveness of UV radiation; however, by adjusting the flow rate of the seawater through the treatment unit, adequate disinfection was shown to be predictable. Images Fig. 1 PMID:4291955

Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

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White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

The impact of intraoperative opioid use on survival after oral cancer surgery.

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Patino, Miguel A; Ramirez, Rafael E; Perez, Carlos A; Feng, Lei; Kataria, Pranav; Myers, Jeffrey; Cata, Juan P

2017-11-01

To investigate the impact of opioid use on cancer recurrence after oral cancer surgery. We hypothesized that the amount of opioids administered during oral cancer surgery is an independent predictor of recurrence free survival (RFS) and overall survival (OS). After Institutional Review Board approval, we collected demographic, tumor related, intraoperative and survival data of patients who had oral cancer surgery. Multivariable Cox proportional hazards models were used to determine the impact of important covariates on RFS and OS. 268 patients were included. After adjusting for significant covariates, the amount of opioids administered during surgery was not an independent predictor of RFS (HR: 1.27 [CI 95%, 0.838-1.924], p=0.26). However, we observed an association between opioid consumption and shorter OS (HR=1.77, [CI 95%=0.995-3.149]. p=0.05). High requirements of opioids during surgery increase the risk of recurrence and mortality by 27% and 77%, although the association is not statically significant. Copyright © 2017 Elsevier Ltd. All rights reserved.

September-March survival of female northern pintails radiotagged in San Joaquin Valley, California

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Fleskes, J.P.; Jarvis, R.L.; Gilmer, D.S.

2002-01-01

To improve understanding of pintail ecology, we radiotagged 191 hatch-year (HY) and 228 after-hatch-year (AHY) female northern pintails (Anas acuta) in the San Joaquin Valley (SJV), and studied their survival throughout central California, USA, during September-March, 1991-1994. We used adjusted Akaike Information Criterion (AICc) values to contrast known-fate models and examine variation in survival rates relative to year, interval, wintering region (AJV, other central California), pintail age, body mass at capture, capture date, capture area, and radio type. The best-fitting model included only interval x year and age x body mass; the next 2 best-fitting models also included wintering region and capture date. Hunting caused 83% of the mortalities we observed, and survival was consistently lower during hunting than nonhunting intervals. Nonhunting and hunting mortality during early winter was highest during the 1991-1992 drought year. Early-winter survival improved during the study along with habitat conditions in the Grassland Ecological Area (EA), where most radiotagged pintails spent early winter. Survival was more closely related to body mass at capture for HY than AHY pintails, even after accounting for the later arrival (based on capture date) of HY pintails, suggesting HY pintails are less adept at improving their condition. Thus, productivity estimates based on harvest age ratios may be biased if relative vulnerability of HY and AHY pintails is assumed to be constant because fall body condition of pintails may vary greatly among years. Cumulative winter survival was 75.6% (95% CI = 68.3% to 81.7%) for AHY and 65.4% (56.7% to 73.1%) for HY female pintails. Daily odds of survival in the cotton-agriculture landscape of the SJV were -21.3% (-40.3% to +3.7%) lower than in the rice-agriculture landscape of the Sacramento Valley (SACV) and other central California areas. Higher hunting mortality may be 1 reason pintails have declined more in SJV than in SACV.

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...

Drought and Cooler Temperatures Are Associated with Higher Nest Survival in Mountain Plovers

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Victoria J. Dreitz

2012-06-01

Full Text Available Native grasslands have been altered to a greater extent than any other biome in North America. The habitats and resources needed to support breeding performance of grassland birds endemic to prairie ecosystems are currently threatened by land management practices and impending climate change. Climate models for the Great Plains prairie region predict a future of hotter and drier summers with strong multiyear droughts and more frequent and severe precipitation events. We examined how fluctuations in weather conditions in eastern Colorado influenced nest survival of an avian species that has experienced recent population declines, the Mountain Plover (Charadrius montanus. Nest survival averaged 27.2% over a 7-yr period (n = 936 nests and declined as the breeding season progressed. Nest survival was favored by dry conditions and cooler temperatures. Projected changes in regional precipitation patterns will likely influence nest survival, with positive influences of predicted declines in summer rainfall yet negative effects of more intense rain events. The interplay of climate change and land use practices within prairie ecosystems may result in Mountain Plovers shifting their distribution, changing local abundance, and adjusting fecundity to adapt to their changing environment.

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

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Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

2016-03-01

One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi

Radiation Therapy Administration and Survival in Stage I/II Extranodal Marginal Zone B-Cell Lymphoma of Mucosa-Associated Lymphoid Tissue

Energy Technology Data Exchange (ETDEWEB)

Olszewski, Adam J., E-mail: adam_olszewski@brown.edu; Desai, Amrita

2014-03-01

Purpose: To determine the factors associated with the use of radiation therapy and associated survival outcomes in early-stage marginal zone lymphoma of the mucosa-associated lymphoid tissue (MALT). Methods and Materials: We extracted data on adult patients with stage I/II MALT lymphoma diagnoses between 1998 and 2010 recorded in the Surveillance, Epidemiology, and End Results (SEER) database. We studied factors associated with radiation therapy administration in a logistic regression model and described the cumulative incidence of lymphoma-related death (LRD) according to receipt of the treatment. The association of radiation therapy with survival was explored in multivariate models with adjustment for immortal time bias. Results: Of the 7774 identified patients, 36% received radiation therapy as part of the initial course of treatment. Older patients; black or Hispanic men; white, Hispanic, and black women; and socioeconomically disadvantaged and underinsured patients had a significantly lower chance of receiving radiation therapy. Radiation therapy administration was associated with a lower chance of LRD in most sites. In cutaneous, ocular, and salivary MALT lymphomas, the 5-year estimate of LRD after radiation therapy was 0%. The association of radiation therapy with overall survival in different lymphoma sites was heterogeneous, and statistically significant in cutaneous (hazard ratio 0.45, P=.009) and ocular (hazard ratio 0.47, P<.0001) locations after multivariate adjustment. Conclusions: Demographic factors are associated with the use of radiation therapy in MALT lymphoma. Clinicians should be sensitive to those disparities because the administration of radiation therapy may be associated with improved survival, particularly in cutaneous and ocular lymphomas.

Radiation Therapy Administration and Survival in Stage I/II Extranodal Marginal Zone B-Cell Lymphoma of Mucosa-Associated Lymphoid Tissue

International Nuclear Information System (INIS)

Olszewski, Adam J.; Desai, Amrita

2014-01-01

Purpose: To determine the factors associated with the use of radiation therapy and associated survival outcomes in early-stage marginal zone lymphoma of the mucosa-associated lymphoid tissue (MALT). Methods and Materials: We extracted data on adult patients with stage I/II MALT lymphoma diagnoses between 1998 and 2010 recorded in the Surveillance, Epidemiology, and End Results (SEER) database. We studied factors associated with radiation therapy administration in a logistic regression model and described the cumulative incidence of lymphoma-related death (LRD) according to receipt of the treatment. The association of radiation therapy with survival was explored in multivariate models with adjustment for immortal time bias. Results: Of the 7774 identified patients, 36% received radiation therapy as part of the initial course of treatment. Older patients; black or Hispanic men; white, Hispanic, and black women; and socioeconomically disadvantaged and underinsured patients had a significantly lower chance of receiving radiation therapy. Radiation therapy administration was associated with a lower chance of LRD in most sites. In cutaneous, ocular, and salivary MALT lymphomas, the 5-year estimate of LRD after radiation therapy was 0%. The association of radiation therapy with overall survival in different lymphoma sites was heterogeneous, and statistically significant in cutaneous (hazard ratio 0.45, P=.009) and ocular (hazard ratio 0.47, P<.0001) locations after multivariate adjustment. Conclusions: Demographic factors are associated with the use of radiation therapy in MALT lymphoma. Clinicians should be sensitive to those disparities because the administration of radiation therapy may be associated with improved survival, particularly in cutaneous and ocular lymphomas

Comparison of hypertabastic survival model with other unimodal hazard rate functions using a goodness-of-fit test.

Science.gov (United States)

Tahir, M Ramzan; Tran, Quang X; Nikulin, Mikhail S

2017-05-30

We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Factors affecting 30-month survival in lung cancer patients.

Science.gov (United States)

Mahesh, P A; Archana, S; Jayaraj, B S; Patil, Shekar; Chaya, S K; Shashidhar, H P; Sunitha, B S; Prabhakar, A K

2012-10-01

Age adjusted incidence rate of lung cancer in India ranges from 7.4 to 13.1 per 100,000 among males and 3.9 to 5.8 per 100,000 among females. The factors affecting survival in lung cancer patients in India are not fully understood. The current study was undertaken to evaluate the factors affecting survival in patients diagnosed with lung cancer attending a tertiary care cancer institute in Bangalore, Karnataka, India. Consecutive patients with primary lung cancer attending Bangalore Institute of Oncology, a tertiary care centre at Bangalore, between 2006 and 2009 were included. Demographic, clinical, radiological data were collected retrospectively from the medical records. A total of 170 consecutive subjects (128 males, 42 females) diagnosed to have lung cancer; 151 non-small cell lung cancer (NSCLC) and 19 small cell lung cancer (SCLC) were included. A higher proportion of never-smokers (54.1%) were observed, mostly presenting below the age of 60 yr. Most subjects were in stage IV and III at the time of diagnosis. More than 50 per cent of patients presented with late stage lung cancer even though the duration of symptoms is less than 2 months. The 30-month overall survival rates for smokers and never-smokers were 32 and 49 per cent, respectively. No significant differences were observed in 30 month survival based on age at presentation, gender and type of lung cancer. Cox proportional hazards model identified never-smokers and duration of symptoms less than 1 month as factors adversely affecting survival. Our results showed that lung cancer in Indians involved younger subjects and associated with poorer survival as compared to other ethnic population. Studies on large sample need to be done to evaluate risk factors in lung cancer patients.

Positive Adjustment Among American Repatriated Prisoners of the Vietnam War: Modeling the Long-Term Effects of Captivity.

Science.gov (United States)

King, Daniel W; King, Lynda A; Park, Crystal L; Lee, Lewina O; Kaiser, Anica Pless; Spiro, Avron; Moore, Jeffrey L; Kaloupek, Danny G; Keane, Terence M

2015-11-01

A longitudinal lifespan model of factors contributing to later-life positive adjustment was tested on 567 American repatriated prisoners from the Vietnam War. This model encompassed demographics at time of capture and attributes assessed after return to the U.S. (reports of torture and mental distress) and approximately 3 decades later (later-life stressors, perceived social support, positive appraisal of military experiences, and positive adjustment). Age and education at time of capture and physical torture were associated with repatriation mental distress, which directly predicted poorer adjustment 30 years later. Physical torture also had a salutary effect, enhancing later-life positive appraisals of military experiences. Later-life events were directly and indirectly (through concerns about retirement) associated with positive adjustment. Results suggest that the personal resources of older age and more education and early-life adverse experiences can have cascading effects over the lifespan to impact well-being in both positive and negative ways.

Survival of captive-reared Hispaniolan Parrots released in Parque Nacional del Este, Dominican Republic

Science.gov (United States)

Collazo, J.A.; White, T.H.; Vilella, F.J.; Guerrero, S.A.

2003-01-01

We report first-year survival rates of 49 captive-reared Hispaniolan Parrots (Amazona ventralis) released in Parque Nacional del Este, Dominican Republic. Our goal was to learn about factors affecting postrelease survival. Specifically, we tested if survival was related to movements and whether modifying prerelease protocols influenced survival rates. We also estimated survival in the aftermath of Hurricane Georges (22 September 1998). Twenty-four parrots, fitted with radio-transmitters, were released between 14 September and 12 December 1997. Twenty-five more were released between 29 June and 16 September 1998. First-year survival rates were 30% in 1997 and 29% in 1998. Survival probability was related to bird mobility. In contrast to birds released in 1997, none of the 25 parrots released in 1998 suffered early postrelease mortality (i.e., 3-5 days after release). Two adjustments to prerelease protocols (increased exercise and reduced blood sampling) made in 1998 may have contributed to differences in mobility and survival between years. The reduction of early postrelease mortality in 1998 was encouraging, as was the prospect for higher first-year survival (e.g., 30% to 65%). Only one death was attributed to the immediate impact of the hurricane. Loss of foraging resources was likely a major contributor to ensuing mortality. Birds increased their mobility, presumably in search of food. Survival rates dropped 23% in only eight weeks posthurricane. This study underscores the value of standardized prerelease protocols, and of estimating survival and testing for factors that might influence it. Inferences from such tests will provide the best basis to make adjustments to a release program.

A survival model for fractionated radiotherapy with an application to prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Zaider, Marco [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)]. E-mail: Zaiderm@mskcc.org; Zelefsky, Michael J.; Leibel, Steven A. [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Hanin, Leonid G. [Department of Mathematics, Idaho State University, Pocatello, ID (United States); Tsodikov, Alexander D.; Yakovlev, Andrei Y. [Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (United States)

2001-10-01

This paper explores the applicability of a mechanistic survival model, based on the distribution of clonogens surviving a course of fractionated radiation therapy, to clinical data on patients with prostate cancer. The study was carried out using data on 1100 patients with clinically localized prostate cancer who were treated with three-dimensional conformal radiation therapy. The patients were stratified by radiation dose (group 1: <67.5 Gy; group 2: 67.5-72.5 Gy; group 3: 72.5-77.5 Gy; group 4: 77.5-87.5 Gy) and prognosis category (favourable, intermediate and unfavourable as defined by pre-treatment PSA and Gleason score). A relapse was recorded when tumour recurrence was diagnosed or when three successive prostate specific antigen (PSA) elevations were observed from a post-treatment nadir PSA level. PSA relapse-free survival was used as the primary end point. The model, which is based on an iterated Yule process, is specified in terms of three parameters: the mean number of tumour clonogens that survive the treatment, the mean of the progression time of post-treatment tumour development and its standard deviation. The model parameters were estimated by the maximum likelihood method. The fact that the proposed model provides an excellent description both of the survivor function and of the hazard rate is prima facie evidence of the validity of the model because closeness of the two survivor functions (empirical and model-based) does not generally imply closeness of the corresponding hazard rates. The estimated cure probabilities for the favourable group are 0.80, 0.74 and 0.87 (for dose groups 1-3, respectively); for the intermediate group: 0.25, 0.51, 0.58 and 0.78 (for dose groups 1-4, respectively) and for the unfavourable group: 0.0, 0.27, 0.33 and 0.64 (for dose groups 1-4, respectively). The distribution of progression time to tumour relapse was found to be independent of prognosis group but dependent on dose. As the dose increases the mean progression

The Survival Processing Effect with Intentional Learning of Ad Hoc Categories

Directory of Open Access Journals (Sweden)

Anastasiya Savchenko

2014-04-01

Full Text Available Previous studies have shown that memory is adapted to remember information when it is processed in a survival context. This study investigates how procedural changes in Marinho (2012 study might have led to her failure to replicate the survival mnemonic advantage. In two between-subjects design experiments, participants were instructed to learn words from ad hoc categories and to rate their relevance to a survival or a control scenario. No survival advantage was obtained in either experiment. The Adjusted Ratio of Clustering (ARC scores revealed that including the category labels made the participants rely more on the category structure of the list. Various procedural aspects of the conducted experiments are discussed as possible reasons underlying the absence of the survival effect.

Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States

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Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.

2007-01-01

Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…

Development and Validation of Perioperative Risk-Adjustment Models for Hip Fracture Repair, Total Hip Arthroplasty, and Total Knee Arthroplasty.

Science.gov (United States)

Schilling, Peter L; Bozic, Kevin J

2016-01-06

Comparing outcomes across providers requires risk-adjustment models that account for differences in case mix. The burden of data collection from the clinical record can make risk-adjusted outcomes difficult to measure. The purpose of this study was to develop risk-adjustment models for hip fracture repair (HFR), total hip arthroplasty (THA), and total knee arthroplasty (TKA) that weigh adequacy of risk adjustment against data-collection burden. We used data from the American College of Surgeons National Surgical Quality Improvement Program to create derivation cohorts for HFR (n = 7000), THA (n = 17,336), and TKA (n = 28,661). We developed logistic regression models for each procedure using age, sex, American Society of Anesthesiologists (ASA) physical status classification, comorbidities, laboratory values, and vital signs-based comorbidities as covariates, and validated the models with use of data from 2012. The derivation models' C-statistics for mortality were 80%, 81%, 75%, and 92% and for adverse events were 68%, 68%, 60%, and 70% for HFR, THA, TKA, and combined procedure cohorts. Age, sex, and ASA classification accounted for a large share of the explained variation in mortality (50%, 58%, 70%, and 67%) and adverse events (43%, 45%, 46%, and 68%). For THA and TKA, these three variables were nearly as predictive as models utilizing all covariates. HFR model discrimination improved with the addition of comorbidities and laboratory values; among the important covariates were functional status, low albumin, high creatinine, disseminated cancer, dyspnea, and body mass index. Model performance was similar in validation cohorts. Risk-adjustment models using data from health records demonstrated good discrimination and calibration for HFR, THA, and TKA. It is possible to provide adequate risk adjustment using only the most predictive variables commonly available within the clinical record. This finding helps to inform the trade-off between model performance and data

Price adjustment for traditional Chinese medicine procedures: Based on a standardized value parity model.

Science.gov (United States)

Wang, Haiyin; Jin, Chunlin; Jiang, Qingwu

2017-11-20

Traditional Chinese medicine (TCM) is an important part of China's medical system. Due to the prolonged low price of TCM procedures and the lack of an effective mechanism for dynamic price adjustment, the development of TCM has markedly lagged behind Western medicine. The World Health Organization (WHO) has emphasized the need to enhance the development of alternative and traditional medicine when creating national health care systems. The establishment of scientific and appropriate mechanisms to adjust the price of medical procedures in TCM is crucial to promoting the development of TCM. This study has examined incorporating value indicators and data on basic manpower expended, time spent, technical difficulty, and the degree of risk in the latest standards for the price of medical procedures in China, and this study also offers a price adjustment model with the relative price ratio as a key index. This study examined 144 TCM procedures and found that prices of TCM procedures were mainly based on the value of medical care provided; on average, medical care provided accounted for 89% of the price. Current price levels were generally low and the current price accounted for 56% of the standardized value of a procedure, on average. Current price levels accounted for a markedly lower standardized value of acupuncture, moxibustion, special treatment with TCM, and comprehensive TCM procedures. This study selected a total of 79 procedures and adjusted them by priority. The relationship between the price of TCM procedures and the suggested price was significantly optimized (p based on a standardized value parity model is a scientific and suitable method of price adjustment that can serve as a reference for other provinces and municipalities in China and other countries and regions that mainly have fee-for-service (FFS) medical care.

Modeling the kinetics of survival of Staphylococcus aureus in regional yogurt from goat's milk.

Science.gov (United States)

Bednarko-Młynarczyk, E; Szteyn, J; Białobrzewski, I; Wiszniewska-Łaszczych, A; Liedtke, K

2015-01-01

The aim of this study was to determine the kinetics of the survival of the test strain of Staphylococcus aureus in the product investigated. Yogurt samples were contaminated with S. aure to an initial level of 10(3)-10(4) cfu/g. The samples were then stored at four temperatures: 4, 6, 20, 22°C. During storage, the number of S. aureus forming colonies in a gram of yogurt was determined every two hours. Based on the results of the analysis culture the curves of survival were plotted. Three primary models were selected to describe the kinetics of changes in the count of bacteria: Cole's model, a modified model of Gompertz and the model of Baranyi and Roberts. Analysis of the model fit carried out based on the average values of Pearson's correlation coefficient, between the modeled and measured values, showed that the Cole's model had the worst fit. The modified Gompertz model showed the count of S. aureus as a negative value. These drawbacks were not observed in the model of Baranyi and Roberts. For this reason, this model best reflects the kinetics of changes in the number of staphylococci in yogurt.

A complete generalized adjustment criterion

NARCIS (Netherlands)

Perković, Emilija; Textor, Johannes; Kalisch, Markus; Maathuis, Marloes H.

2015-01-01

Covariate adjustment is a widely used approach to estimate total causal effects from observational data. Several graphical criteria have been developed in recent years to identify valid covariates for adjustment from graphical causal models. These criteria can handle multiple causes, latent

Effect of Warfarin Treatment on Survival of Patients With Pulmonary Arterial Hypertension (PAH) in the Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL).

Science.gov (United States)

Preston, Ioana R; Roberts, Kari E; Miller, Dave P; Sen, Ginny P; Selej, Mona; Benton, Wade W; Hill, Nicholas S; Farber, Harrison W

2015-12-22

Long-term anticoagulation is recommended in idiopathic pulmonary arterial hypertension (IPAH). In contrast, limited data support anticoagulation in pulmonary arterial hypertension (PAH) associated with systemic sclerosis (SSc-PAH). We assessed the effect of warfarin anticoagulation on survival in IPAH and SSc-PAH patients enrolled in Registry to Evaluate Early and Long-term PAH Disease Management (REVEAL), a longitudinal registry of group I PAH. Patients who initiated warfarin on study (n=187) were matched 1:1 with patients never on warfarin, by enrollment site, etiology, and diagnosis status. Descriptive analyses were conducted to compare warfarin users and nonusers by etiology. Survival analyses with and without risk adjustment were performed from the time of warfarin initiation or a corresponding quarterly update in matched pairs to avoid immortal time bias. Time-varying covariate models were used as sensitivity analyses. Mean warfarin treatment was 1 year; mean international normalized ratios were 1.9 (IPAH) and 2.0 (SSc-PAH). Two-thirds of patients initiating warfarin discontinued treatment before the last study assessment. There was no survival difference with warfarin in IPAH patients (adjusted hazard ratio, 1.37; P=0.21) or in SSc-PAH patients (adjusted hazard ratio, 1.60; P=0.15) in comparison with matched controls. However, SSc-PAH patients receiving warfarin within the previous year (hazard ratio, 1.57; P=0.031) or any time postbaseline (hazard ratio, 1.49; P=0.046) had increased mortality in comparison with warfarin-naïve patients. No significant survival advantage was observed in IPAH patients who started warfarin. In SSc-PAH patients, long-term warfarin was associated with poorer survival than in patients not receiving warfarin, even after adjusting for confounders. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00370214. © 2015 The Authors.

Development of a model for case-mix adjustment of pressure ulcer prevalence rates.

NARCIS (Netherlands)

Bours, G.J.J.W.; Halfens, J.; Berger, M.P.; Abu-Saad, H.H.; Grol, R.P.T.M.

2003-01-01

BACKGROUND: Acute care hospitals participating in the Dutch national pressure ulcer prevalence survey use the results of this survey to compare their outcomes and assess their quality of care regarding pressure ulcer prevention. The development of a model for case-mix adjustment is essential for the

Outcomes and long-term survival of coronary artery surgery: The controversial role of opium as risk marker

Science.gov (United States)

Najafi, Mahdi; Jahangiry, Leila; Mortazavi, Seyedeh Hamideh; Jalali, Arash; Karimi, Abbasali; Bozorgi, Ali

2016-01-01

AIM To study survival in isolated coronary artery bypass graft (CABG) patients and to evaluate the impact of preoperative chronic opium consumption on long-term outcome. METHODS Cohort of 566 isolated CABG patients as Tehran Heart Center cardiac output measurement was conducted. Daily evaluation until discharge as well as 4- and 12-mo and 6.5-year follow-up information for survival status were fulfilled for all patients. Long-term 6.5-year overall and opium-stratified survival, adjusted survival curves based on opium consumption as well as possible predictors of all-cause mortality using multiple cox regression were determined by statistical analysis. RESULTS Six point five-year overall survival was 91.8%; 86.6% in opium consumers and 92.7% in non-opium consumers (P = 0.035). Patients with positive history of opium consumption significantly tended to have lower ejection fraction (EF), higher creatinine level and higher prevalence of myocardial infarction. Multiple predictors of all-cause mortality included age, body mass index, EF, diabetes mellitus and cerebrovascular accident. The hazard ratio (HR) of 2.09 for the risk of mortality in opium addicted patients with a borderline P value (P = 0.052) was calculated in this model. Further adjustment with stratification based on smoking and opium addiction reduced the HR to 1.20 (P = 0.355). CONCLUSION Simultaneous impact of smoking as a confounding variable in most of the patients prevents from definitive judgment on the role of opium as an independent contributing factor in worse long-term survival of CABG patients in addition to advanced age, low EF, diabetes mellitus and cerebrovascular accident. Meanwhile, our findings do not confirm any cardio protective role for opium to improve outcome in coronary patients with the history of smoking. Further studies are needed to clarify pure effect of opium and warrant the aforementioned findings. PMID:27957254

Models for cell survival with low LET radiation

International Nuclear Information System (INIS)

Payne, M.G.; Garrett, W.R.

1975-01-01

A model for cell survival under low LET irradiation was developed in which the cell is considered to have N 0 -independent sensitive sites, each of which can exist in either an undamaged state (state A) or one of two damaged states. Radiation can change the sensitive sites from the undamaged state to either of two damaged states. The first damaged state (state B) can either be repaired or be promoted on the second damaged state (state C), which is irreparable. The promotion from the first damaged state to the second can occur due to any of the following: (1) further radiation damage, (2) an abortive attempt to repair the site, or (3) the arrival at a part of the cell cycle where the damage is ''fixed.'' Subject to the further assumptions that radiation damage can occur either indirectly (i.e., through radiation products) or due to direct interaction, and that repair of the first damaged state is a one-step process, expressions can be derived for P(N/sub A/, N/sub B/,t) = probability that after time t a cell will have N/sub A/ sites in state A and N/sub B/ in state B. The problem of determining P(N/sub A/, N/sub B/, t) is formulated for arbitrary time dependences of the radiation field and of all rate coefficients. A large family of cell-survival models can be described by interpreting the sensitive sites in different ways and by making different choices of rate coefficients and of the combinations of numbers of sites in different states that will lead to cell death. (U.S.)

Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

Science.gov (United States)

Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

2017-10-01

Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (PLearning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that

Pregnancy associated nasopharyngeal carcinoma: A retrospective case-control analysis of maternal survival outcomes

International Nuclear Information System (INIS)

Cheng, Yi-Kan; Zhang, Fan; Tang, Ling-Long; Chen, Lei; Zhou, Guan-Qun; Zeng, Mu-Sheng; Kang, Tie-Bang; Jia, Wei-Hua; Shao, Jian-Yong; Mai, Hai-Qiang; Guo, Ying; Ma, Jun

2015-01-01

Background: Pregnancy-associated nasopharyngeal carcinoma (PANPC) has been associated with poor survival. Recent advances in radiation technology and imaging techniques, and the introduction of chemotherapy have improved survival in nasopharyngeal carcinoma (NPC); however, it is not clear whether these changes have improved survival in PANPC. Therefore, the purpose of this study was to compare five-year maternal survival in patients with PANPC and non-pregnant patients with NPC. Methods: After adjusting for age, stage and chemotherapy mode, we conducted a retrospective case-control study among 36 non-metastatic PANPC patients and 36 non-pregnant NPC patients (control group) who were treated at our institution between 2000 and 2010. Results: The median age of both groups was 30 years (range, 23–35 years); median follow-up for all patients was 70 months. Locoregionally-advanced disease accounted for 83.3% of all patients with PANPC and 92.9% of patients who developed NPC during pregnancy. In both the PANPC and control groups, 31 patients (86.1%) received chemotherapy and all patients received definitive radiotherapy. The five-year rates for overall survival (70% vs. 78%, p = 0.72), distant metastasis-free survival (79% vs. 76%, p = 0.77), loco-regional relapse-free survival (97% vs. 91%, p = 0.69) and disease-free survival (69% vs. 74%, p = 0.98) were not significantly different between the PANPC and control groups. Multivariate analysis using a Cox proportional hazards model revealed that only N-classification was significantly associated with five-year OS. Conclusion: This study demonstrates that, in the modern treatment era, pregnancy itself may not negatively influence survival outcomes in patients with NPC; however, pregnancy may delay the diagnosis of NPC

Survival predictability of lean and fat mass in men and women undergoing maintenance hemodialysis.

Science.gov (United States)

Noori, Nazanin; Kovesdy, Csaba P; Dukkipati, Ramanath; Kim, Youngmee; Duong, Uyen; Bross, Rachelle; Oreopoulos, Antigone; Luna, Amanda; Benner, Debbie; Kopple, Joel D; Kalantar-Zadeh, Kamyar

2010-11-01

Larger body size is associated with greater survival in maintenance hemodialysis (MHD) patients. It is not clear how lean body mass (LBM) and fat mass (FM) compare in their associations with survival across sex in these patients. We examined the hypothesis that higher FM and LBM are associated with greater survival in MHD patents irrespective of sex. In 742 MHD patients, including 31% African Americans with a mean (± SD) age of 54 ± 15 y, we categorized men (n = 391) and women (n = 351) separately into 4 quartiles of near-infrared interactance-measured LBM and FM. Cox proportional hazards models estimated death hazard ratios (HRs) (and 95% CIs), and cubic spline models were used to examine associations with mortality over 5 y (2001-2006). After adjustment for case-mix and inflammatory markers, the highest quartiles of FM and LBM were associated with greater survival in women: HRs of 0.38 (95% CI: 0.20, 0.71) and 0.34 (95% CI: 0.17, 0.67), respectively (reference: first quartile). In men, the highest quartiles of FM and percentage FM (FM%) but not of LBM were associated with greater survival: HRs of 0.51 (95% CI: 0.27, 0.96), 0.45 (95% CI: 0.23, 0.88), and 1.17 (95% CI: 0.60, 2.27), respectively. Cubic spline analyses showed greater survival with higher FM% and higher "FM minus LBM percentiles" in both sexes, whereas a higher LBM was protective in women. In MHD patients, higher FM in both sexes and higher LBM in women appear to be protective. The survival advantage of FM appears to be superior to that of LBM. Clinical trials to examine the outcomes of interventions that modify body composition in MHD patients are indicated.

Survival Outcome After Stereotactic Body Radiation Therapy and Surgery for Stage I Non-Small Cell Lung Cancer: A Meta-Analysis

International Nuclear Information System (INIS)

Zheng, Xiangpeng; Schipper, Matthew; Kidwell, Kelley; Lin, Jules; Reddy, Rishindra; Ren, Yanping; Chang, Andrew; Lv, Fanzhen; Orringer, Mark; Spring Kong, Feng-Ming

2014-01-01

Purpose: This study compared treatment outcomes of stereotactic body radiation therapy (SBRT) with those of surgery in stage I non-small cell lung cancer (NSCLC). Methods and Materials: Eligible studies of SBRT and surgery were retrieved through extensive searches of the PubMed, Medline, Embase, and Cochrane library databases from 2000 to 2012. Original English publications of stage I NSCLC with adequate sample sizes and adequate SBRT doses were included. A multivariate random effects model was used to perform a meta-analysis to compare survival between treatments while adjusting for differences in patient characteristics. Results: Forty SBRT studies (4850 patients) and 23 surgery studies (7071 patients) published in the same period were eligible. The median age and follow-up duration were 74 years and 28.0 months for SBRT patients and 66 years and 37 months for surgery patients, respectively. The mean unadjusted overall survival rates at 1, 3, and 5 years with SBRT were 83.4%, 56.6%, and 41.2% compared to 92.5%, 77.9%, and 66.1% with lobectomy and 93.2%, 80.7%, and 71.7% with limited lung resections. In SBRT studies, overall survival improved with increasing proportion of operable patients. After we adjusted for proportion of operable patients and age, SBRT and surgery had similar estimated overall and disease-free survival. Conclusions: Patients treated with SBRT differ substantially from patients treated with surgery in age and operability. After adjustment for these differences, OS and DFS do not differ significantly between SBRT and surgery in patients with operable stage I NSCLC. A randomized prospective trial is warranted to compare the efficacy of SBRT and surgery

Survival Outcome After Stereotactic Body Radiation Therapy and Surgery for Stage I Non-Small Cell Lung Cancer: A Meta-Analysis

Energy Technology Data Exchange (ETDEWEB)

Zheng, Xiangpeng [Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai (China); Schipper, Matthew [Department of Radiation Oncology, the University of Michigan, Ann Arbor, Michigan (United States); Department of Biostatistics, the University of Michigan, Ann Arbor, Michigan (United States); Kidwell, Kelley [Department of Biostatistics, the University of Michigan, Ann Arbor, Michigan (United States); Lin, Jules; Reddy, Rishindra [Department of Surgery, Section of Thoracic Surgery, University of Michigan, Ann Arbor, Michigan (United States); Ren, Yanping [Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai (China); Chang, Andrew [Department of Surgery, Section of Thoracic Surgery, University of Michigan, Ann Arbor, Michigan (United States); Lv, Fanzhen [Department of Thoracic Surgery, Huadong Hospital, Fudan University, Shanghai (China); Orringer, Mark [Department of Surgery, Section of Thoracic Surgery, University of Michigan, Ann Arbor, Michigan (United States); Spring Kong, Feng-Ming, E-mail: Fkong@gru.edu [Department of Radiation Oncology, the University of Michigan, Ann Arbor, Michigan (United States)

2014-11-01

Purpose: This study compared treatment outcomes of stereotactic body radiation therapy (SBRT) with those of surgery in stage I non-small cell lung cancer (NSCLC). Methods and Materials: Eligible studies of SBRT and surgery were retrieved through extensive searches of the PubMed, Medline, Embase, and Cochrane library databases from 2000 to 2012. Original English publications of stage I NSCLC with adequate sample sizes and adequate SBRT doses were included. A multivariate random effects model was used to perform a meta-analysis to compare survival between treatments while adjusting for differences in patient characteristics. Results: Forty SBRT studies (4850 patients) and 23 surgery studies (7071 patients) published in the same period were eligible. The median age and follow-up duration were 74 years and 28.0 months for SBRT patients and 66 years and 37 months for surgery patients, respectively. The mean unadjusted overall survival rates at 1, 3, and 5 years with SBRT were 83.4%, 56.6%, and 41.2% compared to 92.5%, 77.9%, and 66.1% with lobectomy and 93.2%, 80.7%, and 71.7% with limited lung resections. In SBRT studies, overall survival improved with increasing proportion of operable patients. After we adjusted for proportion of operable patients and age, SBRT and surgery had similar estimated overall and disease-free survival. Conclusions: Patients treated with SBRT differ substantially from patients treated with surgery in age and operability. After adjustment for these differences, OS and DFS do not differ significantly between SBRT and surgery in patients with operable stage I NSCLC. A randomized prospective trial is warranted to compare the efficacy of SBRT and surgery.

Exploration of location influences on firm survival rates using parametric duration models

NARCIS (Netherlands)

Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.

2011-01-01

This study explored the influences of location on business firm survival rates with the use of parametric duration models applied to a data set. Of the variables included, those found to be the most significant were accessibility to infrastructure supply, regional effects, demographic and economic

Selective histone deacetylase 6 inhibition prolongs survival in a lethal two-hit model.

Science.gov (United States)

Cheng, Xin; Liu, Zhengcai; Liu, Baoling; Zhao, Ting; Li, Yongqing; Alam, Hasan B

2015-07-01

Hemorrhagic shock (HS) followed by a subsequent insult ("second hit") often initiates an exaggerated systemic inflammatory response and multiple organ failure. We have previously demonstrated that valproic acid, a pan histone deacetylase inhibitor, could improve survival in a rodent "two-hit" model. In the present study, our goal was to determine whether selective inhibition of histone deacetylase 6 with Tubastatin A (Tub-A) could prolong survival in a two-hit model where HS was followed by sepsis from cecal ligation and puncture (CLP). C57Bl/6J mice were subjected to sublethal HS (30% blood loss) and then randomly divided into two groups (n = 13 per group) such as Tub-A group (treatment) and vehicle (VEH) group (control). The Tub-A group was given an intraperitoneal injection of Tub-A (70 mg/kg) dissolved in dimethyl sulfoxide (DMSO). The VEH group was injected with DMSO (1 μl/g body weight). After 24 h, all mice were subjected CLP followed immediately by another dose of Tub-A or DMSO. Survival was monitored for 10 d. In a parallel study, peritoneal irrigation fluid and liver tissue from Tub-A- or DMSO-treated mice were collected 3 h after CLP. Enzyme-linked immunosorbent assay was performed to quantify activity of the myeloperoxidase and concentrations of tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6) in the peritoneal irrigation fluid. RNA was isolated from the liver tissue, and real-time polymerase chain reaction was performed to measure relative messenger RNA levels of TNF-α and IL-6. Treatment with Tub-A significantly improved survival compared with that of the control (69.2% versus 15.4%). In addition, Tub-A significantly suppressed myeloperoxidase activity (169.9 ± 8.4 ng/mL versus 70.4 ± 17.4 ng/mL; P hit model. Copyright © 2015 Elsevier Inc. All rights reserved.

Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

Science.gov (United States)

Borup, Morten; Grum, Morten; Linde, Jens Jørgen; Mikkelsen, Peter Steen

2016-08-01

Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5-30 min of rain data recorded by multiple rain gauges and propagating the rainfall estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable, well defined, 64 ha urban catchment, for nine overflow generating rain events. The dynamically adjusted radar data perform best when the aggregation period is as small as 10-20 min, in which case it performs much better than static adjusted radar data and data from rain gauges situated 2-3 km away.

Analysis of survival in breast cancer patients by using different parametric models

Science.gov (United States)

Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

2017-09-01

In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

Effects of marital status on survival of hepatocellular carcinoma by race/ethnicity and gender.

Science.gov (United States)

Wu, Wenrui; Fang, Daiqiong; Shi, Ding; Bian, Xiaoyuan; Li, Lanjuan

2018-01-01

It is well demonstrated that being married is associated with a better prognosis in multiple types of cancer. However, whether the protective effect of marital status varied across race/ethnicity and gender in patients with hepatocellular carcinoma remains unclear. Therefore, we aimed to evaluate the roles of race/ethnicity and gender in this relationship. We identified eligible patients from Surveillance, Epidemiology and End Results (SEER) database during 2004-2012. Overall and cancer-specific survival differences across marital status were compared by Kaplan-Meier curves. We also estimated crude hazard ratios (CHRs) and adjusted hazard ratios (AHRs) with 95% confidence intervals (CIs) for marital status associated with survival by race/ethnicity and gender in Cox proportional hazard models. A total of 12,168 eligible patients diagnosed with hepatocellular carcinoma were included. We observed that married status was an independent protective prognostic factor for overall and cancer-specific survival. In stratified analyses by race/ethnicity, the AHR of overall mortality (unmarried vs married) was highest for Hispanic (AHR =1.25, 95% CI, 1.13-1.39; P married patients obtained better survival advantages. Race/ethnicity and gender could influence the magnitude of associations between marital status and risk of mortality.

Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

Science.gov (United States)

Forutan, M; Ansari Mahyari, S; Sargolzaei, M

2015-02-01

Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection. © 2014 Blackwell Verlag GmbH.

A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

International Nuclear Information System (INIS)

Chow, Edward; Fung, KinWah; Panzarella, Tony; Bezjak, Andrea; Danjoux, Cyril; Tannock, Ian

2002-01-01

Purpose: To develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic. Methods and Materials: Sixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model. Results: Six prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS ≤13 (n=133); 67%, 41%, and 20% for patients with SPS 14-19 (n=129); and 36%, 18%, and 4% for patients with SPS ≥20 (n=133) (p<0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (≤3 risk factors) (n=98); 68%, 47%, and 24% (4 risk factors) (n=117); and 46%, 24%, and 11% (≥5 factors) (n=180) (p<0.0001). Conclusion: Clinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use

Analysis of DNA repair gene polymorphisms and survival in low-grade and anaplastic gliomas

DEFF Research Database (Denmark)

Berntsson, Shala Ghaderi; Wibom, Carl; Sjöström, Sara

2011-01-01

different DNA repair genes (ATM, NEIL1, NEIL2, ERCC6 and RPA4) which were associated with survival. Finally, these eight genetic variants were adjusted for treatment, malignancy grade, patient age and gender, leaving one variant, rs4253079, mapped to ERCC6, with a significant association to survival (OR 0...

Metformin Increases Overall Survival in Patients with Diabetes Undergoing Surgery for Colorectal Cancer

DEFF Research Database (Denmark)

Fransgaard, Tina; Thygesen, Lau Caspar; Gögenur, Ismail

2015-01-01

-Meier estimator and the Cox regression model adjusted for important clinical risk factors were used. RESULTS: A total of 30,493 patients were included in the study, of which 3391 were diagnosed with diabetes and 1962 were treated with metformin. The adjusted HR of all-cause mortality for the diabetes group was 1......BACKGROUND: Emerging evidence suggests that metformin decreases the risk of developing colorectal cancer in patients with diabetes, but only few studies have examined potential survival benefits after surgery for colorectal cancer (CRC). The purpose of the study was to examine the association......'s National Clinical Database (DCCG). The Danish National Patient Register (NPR) records all hospital contacts in Denmark, and the diagnosis of diabetes was identified by combining NPR data with use of antidiabetic drugs identified through the Danish National Prescription Registry and DCCG. The Kaplan...

Melanoma survival is superior in females across all tumour stages but is influenced by age.

Science.gov (United States)

Khosrotehrani, Kiarash; Dasgupta, Paramita; Byrom, Lisa; Youlden, Danny R; Baade, Peter D; Green, Adele C

2015-10-01

Among patients with invasive melanoma, females are known to have higher survival than males globally. However, this survival advantage has not been explored in thin melanomas, the most common form of the disease. In addition, it is unclear if this advantage is true across all age groups. We aimed to compare melanoma survival between males and females by clinical stage and within age groups. Melanomas from 1995 to 2008 were extracted from the Queensland Cancer Registry and the Surveillance, Epidemiology, and End Results (SEER) Program, and melanoma-specific deaths were ascertained up to 2011. Flexible parametric survival models compared survival between groups. The Queensland cohort of 28,979 patients experienced 1712 melanoma deaths and the SEER cohort of 57,402 patients included 6929 melanoma deaths. Survival rates were in favour of females across nearly all tumour stages, including thin invasive tumours in both cohorts after adjusting for demographic and clinical factors [odds ratio (OR) death female:male for stage I melanoma = 0.64 in Queensland; and OR = 0.79 in the US, both P age categories. In particular, the survival advantage was inconsistent in females with stage I melanoma aged under 60. Females with melanoma have a survival advantage over males including in stage I melanomas. However, this advantage is dependent on age at diagnosis, suggesting an underlying biological mechanism influenced by age that exists from the very early stages of the disease.

A model of survival following pre-hospital cardiac arrest based on the Victorian Ambulance Cardiac Arrest Register.

Science.gov (United States)

Fridman, Masha; Barnes, Vanessa; Whyman, Andrew; Currell, Alex; Bernard, Stephen; Walker, Tony; Smith, Karen L

2007-11-01

This study describes the epidemiology of sudden cardiac arrest patients in Victoria, Australia, as captured via the Victorian Ambulance Cardiac Arrest Register (VACAR). We used the VACAR data to construct a new model of out-of-hospital cardiac arrest (OHCA), which was specified in accordance with observed trends. All cases of cardiac arrest in Victoria that were attended by Victorian ambulance services during the period of 2002-2005. Overall survival to hospital discharge was 3.8% among 18,827 cases of OHCA. Survival was 15.7% among 1726 bystander witnessed, adult cardiac arrests of presumed cardiac aetiology, presenting in ventricular fibrillation or ventricular tachycardia (VF/VT), where resuscitation was attempted. In multivariate logistic regression analysis, bystander CPR, cardiac arrest (CA) location, response time, age and sex were predictors of VF/VT, which, in turn, was a strong predictor of survival. The same factors that affected VF/VT made an additional contribution to survival. However, for bystander CPR, CA location and response time this additional contribution was limited to VF/VT patients only. There was no detectable association between survival and age younger than 60 years or response time over 15min. The new model accounts for relationships among predictors of survival. These relationships indicate that interventions such as reduced response times and bystander CPR act in multiple ways to improve survival.

Increased Severe Trauma Patient Volume is Associated With Survival Benefit and Reduced Total Health Care Costs: A Retrospective Observational Study Using a Japanese Nationwide Administrative Database.

Science.gov (United States)

Endo, Akira; Shiraishi, Atsushi; Fushimi, Kiyohide; Murata, Kiyoshi; Otomo, Yasuhiro

2017-06-07

The aim of this study was to evaluate the associations of severe trauma patient volume with survival benefit and health care costs. The effect of trauma patient volume on survival benefit is inconclusive, and reports on its effects on health care costs are scarce. We conducted a retrospective observational study, including trauma patients who were transferred to government-approved tertiary emergency hospitals, or hospitals with an intensive care unit that provided an equivalent quality of care, using a Japanese nationwide administrative database. We categorized hospitals according to their annual severe trauma patient volumes [1 to 50 (reference), 51 to 100, 101 to 150, 151 to 200, and ≥201]. We evaluated the associations of volume categories with in-hospital survival and total cost per admission using a mixed-effects model adjusting for patient severity and hospital characteristics. A total of 116,329 patients from 559 hospitals were analyzed. Significantly increased in-hospital survival rates were observed in the second, third, fourth, and highest volume categories compared with the reference category [94.2% in the highest volume category vs 88.8% in the reference category, adjusted odds ratio (95% confidence interval, 95% CI) = 1.75 (1.49-2.07)]. Furthermore, significantly lower costs (in US dollars) were observed in the second and fourth categories [mean (standard deviation) for fourth vs reference = $17,800 ($17,378) vs $20,540 ($32,412), adjusted difference (95% CI) = -$2559 (-$3896 to -$1221)]. Hospitals with high volumes of severe trauma patients were significantly associated with a survival benefit and lower total cost per admission.

Cooking frequency may enhance survival in Taiwanese elderly.

Science.gov (United States)

Chen, Rosalind Chia-Yu; Lee, Meei-Shyuan; Chang, Yu-Hung; Wahlqvist, Mark L

2012-07-01

To investigate the association between cooking behaviour and long-term survival among elderly Taiwanese. Cohort study. The duration of follow-up was the interval between the date of interview and the date of death or 31 December 2008, when censored for survivors. Information used included demographics, socio-economic status, health behaviours, cooking frequencies, physical function, cognitive function, nutrition knowledge awareness, eating out habits and food and nutrient intakes. These data were linked to death records. Cox proportional-hazards models were used to evaluate cooking frequency on death from 1999 to 2008 with related covariate adjustments. Elderly Nutrition and Health Survey in Taiwan, 1999-2000. Nationally representative free-living elderly people aged ≥65 years (n 1888). During a 10-year follow-up, 695 participants died. Those who cooked most frequently were younger, women, unmarried, less educated, non-drinkers of alcohol, non-smokers, without chewing difficulty, had spouse as dinner companion, normal cognition, who walked or shopped more than twice weekly, who ate less meat and more vegetables. Highly frequent cooking (>5 times/week, compared with never) predicted survival (hazard ratio (HR) = 0·47; 95 % CI, 0·36, 0·61); with adjustment for physical function, cognitive function, nutrition knowledge awareness and other covariates, HR was 0·59 (95 % CI, 0·41, 0·86). Women benefited more from cooking more frequently than did men, with decreased HR, 51 % v. 24 %, when most was compared with least. A 2-year delay in the assessment of survivorship led to similar findings. Cooking behaviour favourably predicts survivorship. Highly frequent cooking may favour women more than men.

Calculating the 30-day survival rate in acute myocardial infarction: should we use the treatment chain or the hospital catchment model?

Directory of Open Access Journals (Sweden)

Jan Norum

2017-12-01

Full Text Available Introduction: Acute myocardial infarction (AMI is a potentially deadly disease and significant efforts have been concentrated on improving hospital performance. A 30-day survival rate has become a key quality of care indicator. In Northern Norway, some patients undergoing AMI are directly transferred to the Regional Cardiac Intervention Center at the University Hospital of North Norway in Tromsø. Here, coronary angiography and percutaneous coronary intervention is performed. Consequently, local hospitals may be bypassed in the treatment chain, generating differences in case mix, and making the treatment chain model difficult to interpret. We aimed to compare the treatment chain model with an alternative based on patients’ place of living. Methods: Between 2013 and 2015, a total of 3,155 patients were registered in the Norwegian Patient Registry database. All patients were categorized according to their local hospital’s catchment area. The method of Guo-Romano, with an indifference interval of 0.02, was used to test whether a hospital was an outlier or not. We adjusted for age, sex, comorbidity, and number of prior hospitalizations. Conclusions: We revealed the 30-day AMI survival figure ranging between 88.0% and 93.5% (absolute difference 5.5% using the hospital catchment method. The treatment chain rate ranged between 86.0% and 94.0% (absolute difference 8.0%. The latter figure is the one published as the National Quality of Care Measure in Norway. Local hospitals may get negative attention even though their catchment area is well served. We recommend the hospital catchment method as the first choice when measuring equality of care.

Quality Adjusted Life Years and Trade Off Exercises : exploring methodology and validity

NARCIS (Netherlands)

Verschuuren, Marieke

2006-01-01

Quality Adjusted Life Years (QALYs) are a popular outcome measure in cost-effectiveness analyses. QALYs are computed by multiplying follow-up or survival by a scaling factor reflecting health related quality of life, and as such capture quantity and quality gains simultaneously. Issues with regard

A Threshold Model of Social Support, Adjustment, and Distress after Breast Cancer Treatment

Science.gov (United States)

Mallinckrodt, Brent; Armer, Jane M.; Heppner, P. Paul

2012-01-01

This study examined a threshold model that proposes that social support exhibits a curvilinear association with adjustment and distress, such that support in excess of a critical threshold level has decreasing incremental benefits. Women diagnosed with a first occurrence of breast cancer (N = 154) completed survey measures of perceived support…

Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

Science.gov (United States)

Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

2016-01-01

Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

Science.gov (United States)

Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V.; Tkachenko, N. P.

2015-12-01

The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.

DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

Energy Technology Data Exchange (ETDEWEB)

Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V., E-mail: Yu.Kuyanov@gmail.com; Tkachenko, N. P. [Institute for High Energy Physics, National Research Center Kurchatov Institute, COMPAS Group (Russian Federation)

2015-12-15

The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.

DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

International Nuclear Information System (INIS)

Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V.; Tkachenko, N. P.

2015-01-01

The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available

Animal reintroductions: an innovative assessment of survival

Science.gov (United States)

Muths, Erin L.; Bailey, Larissa L.; Watry, Mary Kay

2014-01-01

Quantitative evaluations of reintroductions are infrequent and assessments of milestones reached before a project is completed, or abandoned due to lack of funding, are rare. However, such assessments, which are promoted in adaptive management frameworks, are critical. Quantification can provide defensible estimates of biological success, such as the number of survivors from a released cohort, with associated cost per animal. It is unlikely that the global issues of endangered wildlife and population declines will abate, therefore, assurance colonies and reintroductions are likely to become more common. If such endeavors are to be successful biologically or achieve adequate funding, implementation must be more rigorous and accountable. We use a novel application of a multistate, robust design capture-recapture model to estimate survival of reintroduced tadpoles through metamorphosis (i.e., the number of individuals emerging from the pond) and thereby provide a quantitative measure of effort and success for an "in progress" reintroduction of toads. Our data also suggest that tadpoles released at later developmental stages have an increased probability of survival and that eggs laid in the wild hatched at higher rates than eggs laid by captive toads. We illustrate how an interim assessment can identify problems, highlight successes, and provide information for use in adjusting the effort or implementing a Decision-Theoretic adaptive management strategy.

The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models.

Science.gov (United States)

Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J

2009-06-01

We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.

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...

Adjustment modes in the trajectory of progressive multiple sclerosis: a qualitative study and conceptual model.

Science.gov (United States)

Bogosian, Angeliki; Morgan, Myfanwy; Bishop, Felicity L; Day, Fern; Moss-Morris, Rona

2017-03-01

We examined cognitive and behavioural challenges and adaptations for people with progressive multiple sclerosis (MS) and developed a preliminary conceptual model of changes in adjustment over time. Using theoretical sampling, 34 semi-structured interviews were conducted with people with MS. Participants were between 41 and 77 years of age. Thirteen were diagnosed with primary progressive MS and 21 with secondary progressive MS. Data were analysed using a grounded theory approach. Participants described initially bracketing the illness off and carrying on their usual activities but this became problematic as the condition progressed and they employed different adjustment modes to cope with increased disabilities. Some scaled back their activities to live a more comfortable life, others identified new activities or adapted old ones, whereas at times, people disengaged from the adjustment process altogether and resigned to their condition. Relationships with partners, emotional reactions, environment and perception of the environment influenced adjustment, while people were often flexible and shifted among modes. Adjusting to a progressive condition is a fluid process. Future interventions can be tailored to address modifiable factors at different stages of the condition and may involve addressing emotional reactions concealing/revealing the condition and perceptions of the environment.

The comparison of proportional hazards and accelerated failure time models in analyzing the first birth interval survival data

Science.gov (United States)

Faruk, Alfensi

2018-03-01

Survival analysis is a branch of statistics, which is focussed on the analysis of time- to-event data. In multivariate survival analysis, the proportional hazards (PH) is the most popular model in order to analyze the effects of several covariates on the survival time. However, the assumption of constant hazards in PH model is not always satisfied by the data. The violation of the PH assumption leads to the misinterpretation of the estimation results and decreasing the power of the related statistical tests. On the other hand, the accelerated failure time (AFT) models do not assume the constant hazards in the survival data as in PH model. The AFT models, moreover, can be used as the alternative to PH model if the constant hazards assumption is violated. The objective of this research was to compare the performance of PH model and the AFT models in analyzing the significant factors affecting the first birth interval (FBI) data in Indonesia. In this work, the discussion was limited to three AFT models which were based on Weibull, exponential, and log-normal distribution. The analysis by using graphical approach and a statistical test showed that the non-proportional hazards exist in the FBI data set. Based on the Akaike information criterion (AIC), the log-normal AFT model was the most appropriate model among the other considered models. Results of the best fitted model (log-normal AFT model) showed that the covariates such as women’s educational level, husband’s educational level, contraceptive knowledge, access to mass media, wealth index, and employment status were among factors affecting the FBI in Indonesia.

Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

DEFF Research Database (Denmark)

Borup, Morten; Grum, Morten; Linde, Jens Jørgen

2016-01-01

estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable......Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling...... overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5–30 min of rain data recorded by multiple rain gauges and propagating the rainfall...

Relationship between crown placement and the survival of endodontically treated teeth.

Science.gov (United States)

Aquilino, Steven A; Caplan, Daniel J

2002-03-01

Crowns have been considered the restoration of choice for endodontically treated teeth, but their selection has been based primarily on anecdotal evidence. This study tested the hypothesis that crown placement (coronal coverage) is associated with improved survival of endodontically treated teeth when preaccess, endodontic, and restorative factors are controlled. A University of Iowa College of Dentistry treatment database was used to identify permanent teeth that had undergone initial obturation between July 1, 1985, and December 31, 1987. Study patients were restricted to persons with at least 1 dental visit in each 2-year interval from 1985 to 1996; a simple random sample of 280 patients (n = 400 teeth) was selected. Dental charts, radiographs, and computerized databases were examined to ascertain variables of interest and to verify study inclusion criteria. Kaplan-Meier survival estimates were generated for the 203 teeth that satisfied study inclusion criteria. Multivariate Cox proportional hazards regression models were developed, with standard errors adjusted to account for clustering of teeth within patients. When tooth type and radiographic evidence of caries at access were controlled, the final Cox model showed that endodontically treated teeth not crowned after obturation were lost at a 6.0 times greater rate than teeth crowned after obturation (95% confidence interval: 3.2 to 11.3). Within the limitations of this study, a strong association between crown placement and the survival of endodontically treated teeth was observed. These results may impact treatment planning if long-term tooth retention is the primary goal.

Modeling the decline of the Porcupine Caribou Herd, 1989-1998: the importance of survival vs. recruitment

Directory of Open Access Journals (Sweden)

Stephen M. Arthur

2003-04-01

Full Text Available The Porcupine caribou (Rangifer tarandus granti herd increased from approximately 100 000 animals during the 1970s to 178 000 in 1989, then declined to 129 000 by 1998. Our objective was to model the dynamics of this herd and investigate the potential that lower calf recruitment, as was observed during 1991-1993, produced the observed population changes. A deterministic model was prepared using estimates of birth and survival rates that reproduced the pattern of population growth from 1971-1989. Then, parameters were changed to simulate effects of lower calf recruitment and adult survival. Reducing recruitment for 3 years caused an immediate reduction in population size, but the population began to recover in 5-6 years. Even a dramatic temporary reduction in recruitment did not explain the continuing decline after 1995. In contrast, a slight but persistent reduction in adult survival caused a decline that closely followed the observed pattern. This suggests that survival of adults, and perhaps calves, has declined since the late 1980s.

Individual fluorouracil dose adjustment in FOLFOX based on pharmacokinetic follow-up compared with conventional body-area-surface dosing: a phase II, proof-of-concept study.

Science.gov (United States)

Capitain, Olivier; Asevoaia, Andreaa; Boisdron-Celle, Michele; Poirier, Anne-Lise; Morel, Alain; Gamelin, Erick

2012-12-01

To compare the efficacy and safety of pharmacokinetically (PK) guided fluorouracil (5-FU) dose adjustment vs. standard body-surface-area (BSA) dosing in a FOLFOX (folinic acid, fluorouracil, oxaliplatin) regimen in metastatic colorectal cancer (mCRC). A total of 118 patients with mCRC were administered individually determined PK-adjusted 5-FU in first-line FOLFOX chemotherapy. The comparison arm consisted of 39 patients, and these patients were also treated with FOLFOX with 5-FU by BSA. For the PK-adjusted arm 5-FU was monitored during infusion, and the dose for the next cycle was based on a dose-adjustment chart to achieve a therapeutic area under curve range (5-FU(ODPM Protocol)). The objective response rate was 69.7% in the PK-adjusted arm, and median overall survival and median progression-free survival were 28 and 16 months, respectively. In the traditional patients who received BSA dosage, objective response rate was 46%, and overall survival and progression-free survival were 22 and 10 months, respectively. Grade 3/4 toxicity was 1.7% for diarrhea, 0.8% for mucositis, and 18% for neutropenia in the dose-monitored group; they were 12%, 15%, and 25%, respectively, in the BSA group. Efficacy and tolerability of PK-adjusted FOLFOX dosing was much higher than traditional BSA dosing in agreement with previous reports for 5-FU monotherapy PK-adjusted dosing. Analysis of these results suggests that PK-guided 5-FU therapy offers added value to combination therapy for mCRC. Copyright © 2012 Elsevier Inc. All rights reserved.

Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

Science.gov (United States)

Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

2009-04-01

Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

DNA-mediated adjuvant immunotherapy extends survival in two different mouse models of myeloid malignancies.

Science.gov (United States)

Le Pogam, Carole; Patel, Satyananda; Gorombei, Petra; Guerenne, Laura; Krief, Patricia; Omidvar, Nader; Tekin, Nilgun; Bernasconi, Elena; Sicre, Flore; Schlageter, Marie-Helene; Chopin, Martine; Noguera, Maria-Elena; West, Robert; Abu, Ansu; Mathews, Vikram; Pla, Marika; Fenaux, Pierre; Chomienne, Christine; Padua, Rose Ann

2015-10-20

We have previously shown that a specific promyelocytic leukemia-retinoic acid receptor alpha (PML-RARA) DNA vaccine combined with all-trans retinoic acid (ATRA) increases the number of long term survivors with enhanced immune responses in a mouse model of acute promyelocytic leukemia (APL). This study reports the efficacy of a non-specific DNA vaccine, pVAX14Flipper (pVAX14), in both APL and high risk myelodysplastic syndrome (HR-MDS) models. PVAX14 is comprised of novel immunogenic DNA sequences inserted into the pVAX1 therapeutic plasmid. APL mice treated with pVAX14 combined with ATRA had increased survival comparable to that obtained with a specific PML-RARA vaccine. Moreover, the survival advantage correlated with decreased PML-RARA transcript levels and increase in anti-RARA antibody production. In HR-MDS mice, pVAX14 significantly improved survival and reduced biomarkers of leukemic transformation such as phosphorylated mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK) 1. In both preclinical models, pVAX14 vaccine significantly increased interferon gamma (IFNγ) production, memory T-cells (memT), reduced the number of colony forming units (CFU) and increased expression of the adapter molecule signalling to NF-κB, MyD88. These results demonstrate the adjuvant properties of pVAX14 providing thus new approaches to improve clinical outcome in two different models of myeloid malignancies, which may have potential for a broader applicability in other cancers.

Modelling survival and connectivity of Mnemiopsis leidyi in the south-western North Sea and Scheldt estuaries

DEFF Research Database (Denmark)

van der Molen, J.; van Beek, J.; Augustine, Starrlight

2015-01-01

Three different models were applied to study the reproduction, survival and dispersal of Mnemiopsis leidyi in the Scheldt estuaries and the southern North Sea: a high-resolution particle tracking model with passive particles, a low-resolution particle tracking model with a reproduction model coup...

Prediction of survival in patients with Stage IV kidney cancer

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L. V. Mirilenko

2015-01-01

Full Text Available The efficiency of treatment was evaluated and the predictors of adjusted survival (AS were identified in patients with disseminated kidney cancer treated at the Republican Research and Practical Center for Oncology and Medical Radiology in 1999 to 2011 (A.E. Okeanov, P.I. Moiseev, L.F. Levin. Malignant tumors in Belarus, 2001–2012. Edited by O.G. Sukonko. Seven factors (regional lymph node metastases; distant bone metastases; a high-grade tumor; sarcomatous tumor differentiation; hemoglobin levels of < 125 g/l in women and < 150 g/l in men; an erythrocyte sedimentation rate of 40 mm/h; palliative surgery were found to have an independent, unfavorable impact on AS. A multidimensional model was built to define what risk group low (no more than 2 poor factors, moderate (3–4 poor factors, and high (more than 4 poor factors the patients with Stage IV kidney cancer belonged to. In these groups, the median survival was 34.7, 17.2, and 4.0 months and 3-year AS rates were 48.6, 24.6, and 3.2 %, respectively. 

Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

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Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Dimick, Justin B; Wang, Edward; Chow, Warren B; Ko, Clifford Y; Bilimoria, Karl Y

2012-05-01

The measurement of hospital quality based on outcomes requires risk adjustment. The c-statistic is a popular tool used to judge model performance, but can be limited, particularly when evaluating specific operations in focused populations. Our objectives were to examine the interpretation and relevance of the c-statistic when used in models with increasingly similar case mix and to consider an alternative perspective on model calibration based on a graphical depiction of model fit. From the American College of Surgeons National Surgical Quality Improvement Program (2008-2009), patients were identified who underwent a general surgery procedure, and procedure groups were increasingly restricted: colorectal-all, colorectal-elective cases only, and colorectal-elective cancer cases only. Mortality and serious morbidity outcomes were evaluated using logistic regression-based risk adjustment, and model c-statistics and calibration curves were used to compare model performance. During the study period, 323,427 general, 47,605 colorectal-all, 39,860 colorectal-elective, and 21,680 colorectal cancer patients were studied. Mortality ranged from 1.0% in general surgery to 4.1% in the colorectal-all group, and serious morbidity ranged from 3.9% in general surgery to 12.4% in the colorectal-all procedural group. As case mix was restricted, c-statistics progressively declined from the general to the colorectal cancer surgery cohorts for both mortality and serious morbidity (mortality: 0.949 to 0.866; serious morbidity: 0.861 to 0.668). Calibration was evaluated graphically by examining predicted vs observed number of events over risk deciles. For both mortality and serious morbidity, there was no qualitative difference in calibration identified between the procedure groups. In the present study, we demonstrate how the c-statistic can become less informative and, in certain circumstances, can lead to incorrect model-based conclusions, as case mix is restricted and patients become

The Complexity of Survival: Asylum Seekers, Resilience and Religion

DEFF Research Database (Denmark)

Buch-Hansen, Gitte; Lorensen, Marlene Ringgaard

to a simple instrument to obtain asylum. In this article, we show how his recommendation ignores the complexity of motives involved in the change of religious affiliation. By our adjustment of Bourdieu’s theory of social capital, we demonstrate how conversion is also a way of existential survival...

A track-event theory of cell survival

Energy Technology Data Exchange (ETDEWEB)

Besserer, Juergen; Schneider, Uwe [Zuerich Univ. (Switzerland). Inst. of Physics; Radiotherapy Hirslanden, Zuerich (Switzerland)

2015-09-01

When fractionation schemes for hypofractionation and stereotactic body radiotherapy are considered, a reliable cell survival model at high dose is needed for calculating doses of similar biological effectiveness. In this work a simple model for cell survival which is valid also at high dose is developed from Poisson statistics. An event is defined by two double strand breaks (DSB) on the same or different chromosomes. An event is always lethal due to direct lethal damage or lethal binary misrepair by the formation of chromosome aberrations. Two different mechanisms can produce events: one-track events (OTE) or two-track-events (TTE). The target for an OTE is always a lethal event, the target for an TTE is one DSB. At least two TTEs on the same or different chromosomes are necessary to produce an event. Both, the OTE and the TTE are statistically independent. From the stochastic nature of cell kill which is described by the Poisson distribution the cell survival probability was derived. It was shown that a solution based on Poisson statistics exists for cell survival. It exhibits exponential cell survival at high dose and a finite gradient of cell survival at vanishing dose, which is in agreement with experimental cell studies. The model fits the experimental data nearly as well as the three-parameter formula of Hug-Kellerer and is only based on two free parameters. It is shown that the LQ formalism is an approximation of the model derived in this work. It could be also shown that the derived model predicts a fractionated cell survival experiment better than the LQ-model. It was shown that cell survival can be described with a simple analytical formula on the basis of Poisson statistics. This solution represents in the limit of large dose the typical exponential behavior and predicts cell survival after fractionated dose application better than the LQ-model.

A track-event theory of cell survival

International Nuclear Information System (INIS)

Besserer, Juergen; Schneider, Uwe

2015-01-01

When fractionation schemes for hypofractionation and stereotactic body radiotherapy are considered, a reliable cell survival model at high dose is needed for calculating doses of similar biological effectiveness. In this work a simple model for cell survival which is valid also at high dose is developed from Poisson statistics. An event is defined by two double strand breaks (DSB) on the same or different chromosomes. An event is always lethal due to direct lethal damage or lethal binary misrepair by the formation of chromosome aberrations. Two different mechanisms can produce events: one-track events (OTE) or two-track-events (TTE). The target for an OTE is always a lethal event, the target for an TTE is one DSB. At least two TTEs on the same or different chromosomes are necessary to produce an event. Both, the OTE and the TTE are statistically independent. From the stochastic nature of cell kill which is described by the Poisson distribution the cell survival probability was derived. It was shown that a solution based on Poisson statistics exists for cell survival. It exhibits exponential cell survival at high dose and a finite gradient of cell survival at vanishing dose, which is in agreement with experimental cell studies. The model fits the experimental data nearly as well as the three-parameter formula of Hug-Kellerer and is only based on two free parameters. It is shown that the LQ formalism is an approximation of the model derived in this work. It could be also shown that the derived model predicts a fractionated cell survival experiment better than the LQ-model. It was shown that cell survival can be described with a simple analytical formula on the basis of Poisson statistics. This solution represents in the limit of large dose the typical exponential behavior and predicts cell survival after fractionated dose application better than the LQ-model.

Standard model group: Survival of the fittest

Science.gov (United States)

Nielsen, H. B.; Brene, N.

1983-09-01

The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some "world (gauge) group". We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

Standard model group: survival of the fittest

International Nuclear Information System (INIS)

Nielsen, H.B.; Brene, N.

1983-01-01

Th essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapse is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property. (orig.)

Estimation of group means when adjusting for covariates in generalized linear models.

Science.gov (United States)

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

Patient survival and surgical re-intervention predictors for intracapsular hip fractures.

Science.gov (United States)

González Quevedo, David; Mariño, Iskandar Tamimi; Sánchez Siles, Juan Manuel; Escribano, Esther Romero; Granero Molina, Esther Judith; Enrique, David Bautista; Smoljanović, Tomislav; Pareja, Francisco Villanueva

2017-08-01

Choosing between total hip replacement (THR) and partial hip replacement (PHR) for patients with intracapsular hip fractures is often based on subjective factors. Predicting the survival of these patients and risk of surgical re-intervention is essential to select the most adequate implant. We conducted a retrospective cohort study on mortality of patients over 70 years with intracapsular hip fractures who were treated between January 2010 and December 2013, with either PHR or THR. Patients' information was withdrawn from our local computerized database. The age-adjusted Charlson comorbidity index (ACCI) and American Society of Anesthesiologists (ASA) score were calculated for all patients. The patients were followed for 2 years after surgery. Survival and surgical re-intervention rates were compared between the two groups using a Multivariate Cox proportional hazard model. A total of 356 individuals were included in this study. At 2 years of follow-up, 221 (74.4%) of the patients with ACCI score≤7 were still alive, in contrast to only 20 (29.0%) of those with ACCI score>7. In addition, 201 (76.2%) of the patients with ASA score≤3 were still alive after 2 years, compared to 30 (32.6%) of individuals with ASA >3. Patients with the ACCI score>7, and ASA score>3 had a significant increase in all-cause 2-year mortality (adjusted hazard ratio of 3.2, 95% CI 2.2-4.6; and 3.12, 95% CI 2.2-4.5, respectively). Patients with an ASA score>3 had a quasi-significant increase in the re-intervention risk (adjusted hazard ratio 2.2, 95% CI 1.0-5.1). The sensitivity, specificity, positive predictive value and negative predictive values of ACCI in predicting 2-year mortality were 39.2%, 91.1%, 71%, and 74.4%, respectively. On the other hand, the sensitivity, specificity, positive predictive value and negative predictive values of ASA score in predicting 2-year mortality were 49.6%, 79.1%, 67.4%, and 76.1%, respectively. Both ACCI and ASA scales were able to predict the 2-year

Modeling nest-survival data: a comparison of recently developed methods that can be implemented in MARK and SAS

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Rotella, J. J.

2004-06-01

Full Text Available Estimating nest success and evaluating factors potentially related to the survival rates of nests are key aspects of many studies of avian populations. A strong interest in nest success has led to a rich literature detailing a variety of estimation methods for this vital rate. In recent years, modeling approaches have undergone especially rapid development. Despite these advances, most researchers still employ Mayfield’s ad-hoc method (Mayfield, 1961 or, in some cases, the maximum-likelihood estimator of Johnson (1979 and Bart & Robson (1982. Such methods permit analyses of stratified data but do not allow for more complex and realistic models of nest survival rate that include covariates that vary by individual, nest age, time, etc. and that may be continuous or categorical. Methods that allow researchers to rigorously assess the importance of a variety of biological factors that might affect nest survival rates can now be readily implemented in Program MARK and in SAS’s Proc GENMOD and Proc NLMIXED. Accordingly, use of Mayfield’s estimator without first evaluating the need for more complex models of nest survival rate cannot be justified. With the goal of increasing the use of more flexible methods, we first describe the likelihood used for these models and then consider the question of what the effective sample size is for computation of AICc. Next, we consider the advantages and disadvantages of these different programs in terms of ease of data input and model construction; utility/flexibility of generated estimates and predictions; ease of model selection; and ability to estimate variance components. An example data set is then analyzed using both MARK and SAS to demonstrate implementation of the methods with various models that contain nest-, group- (or block-, and time-specific covariates. Finally, we discuss improvements that would, if they became available, promote a better general understanding of nest survival rates.

Helplessness/hopelessness, minimization and optimism predict survival in women with invasive ovarian cancer: a role for targeted support during initial treatment decision-making?

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Price, Melanie A; Butow, Phyllis N; Bell, Melanie L; deFazio, Anna; Friedlander, Michael; Fardell, Joanna E; Protani, Melinda M; Webb, Penelope M

2016-06-01

Women with advanced ovarian cancer generally have a poor prognosis but there is significant variability in survival despite similar disease characteristics and treatment regimens. The aim of this study was to determine whether psychosocial factors predict survival in women with ovarian cancer, controlling for potential confounders. The sample comprised 798 women with invasive ovarian cancer recruited into the Australian Ovarian Cancer Study and a subsequent quality of life study. Validated measures of depression, optimism, minimization, helplessness/hopelessness, and social support were completed 3-6 monthly for up to 2 years. Four hundred nineteen women (52.5 %) died over the follow-up period. Associations between time-varying psychosocial variables and survival were tested using adjusted Cox proportional hazard models. There was a significant interaction of psychosocial variables measured prior to first progression and overall survival, with higher optimism (adjusted hazard ratio per 1 standard deviation (HR) = 0.80, 95 % confidence interval (CI) 0.65-0.97), higher minimization (HR = 0.79, CI 0.66-0.94), and lower helplessness/hopelessness (HR = 1.40, CI 1.15-1.71) associated with longer survival. After disease progression, these variables were not associated with survival (optimism HR = 1.10, CI 0.95-1.27; minimization HR = 1.12, CI 0.95-1.31; and helplessness/hopelessness HR = 0.86, CI 0.74-1.00). Depression and social support were not associated with survival. In women with invasive ovarian cancer, psychosocial variables prior to disease progression appear to impact on overall survival, suggesting a preventive rather than modifying role. Addressing psychosocial responses to cancer and their potential impact on treatment decision-making early in the disease trajectory may benefit survival and quality of life.

Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

Science.gov (United States)

Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

Modeling of pathogen survival during simulated gastric digestion.

Science.gov (United States)

Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

2011-02-01

The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens.

Learning Survival Models with On-Line Simulation Activities in the Actuarial Science Degree

Directory of Open Access Journals (Sweden)

Antonio Fernandez-Morales

2011-03-01

Full Text Available The aim of this paper is to describe an on-line survival laboratory designed to enhance teaching and learning in the Statistics courses of the Actuarial Science Degree of the Uni-versity of Málaga. The objective of the on-line survival lab is to help students through a guided program of simulation activities with the understanding of the most important statistical concepts of the stochastic modeling of human survival, from an Actuarial point of view. The graphical interactive simulator is implemented as Java applets for the web version, and as a Javascript animation for a lite iPhone/iPod touch version. Finally, the results of a survey carried out at the end of the course are discussed to have a preliminary assessment of the students’ satisfaction with the resources, and their perception about the usefulness for their learning process.

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

An Optic Nerve Crush Injury Murine Model to Study Retinal Ganglion Cell Survival

Science.gov (United States)

Tang, Zhongshu; Zhang, Shuihua; Lee, Chunsik; Kumar, Anil; Arjunan, Pachiappan; Li, Yang; Zhang, Fan; Li, Xuri

2011-01-01

Injury to the optic nerve can lead to axonal degeneration, followed by a gradual death of retinal ganglion cells (RGCs), which results in irreversible vision loss. Examples of such diseases in human include traumatic optic neuropathy and optic nerve degeneration in glaucoma. It is characterized by typical changes in the optic nerve head, progressive optic nerve degeneration, and loss of retinal ganglion cells, if uncontrolled, leading to vision loss and blindness. The optic nerve crush (ONC) injury mouse model is an important experimental disease model for traumatic optic neuropathy, glaucoma, etc. In this model, the crush injury to the optic nerve leads to gradual retinal ganglion cells apoptosis. This disease model can be used to study the general processes and mechanisms of neuronal death and survival, which is essential for the development of therapeutic measures. In addition, pharmacological and molecular approaches can be used in this model to identify and test potential therapeutic reagents to treat different types of optic neuropathy. Here, we provide a step by step demonstration of (I) Baseline retrograde labeling of retinal ganglion cells (RGCs) at day 1, (II) Optic nerve crush injury at day 4, (III) Harvest the retinae and analyze RGC survival at day 11, and (IV) Representative result. PMID:21540827

The Mediating Role of Psychological Adjustment between Peer Victimization and Social Adjustment in Adolescence.

Science.gov (United States)

Romera, Eva M; Gómez-Ortiz, Olga; Ortega-Ruiz, Rosario

2016-01-01

There is extensive scientific evidence of the serious psychological and social effects that peer victimization may have on students, among them internalizing problems such as anxiety or negative self-esteem, difficulties related to low self-efficacy and lower levels of social adjustment. Although a direct relationship has been observed between victimization and these effects, it has not yet been analyzed whether there is a relationship of interdependence between all these measures of psychosocial adjustment. The aim of this study was to examine the relationship between victimization and difficulties related to social adjustment among high school students. To do so, various explanatory models were tested to determine whether psychological adjustment (negative self-esteem, social anxiety and social self-efficacy) could play a mediating role in this relationship, as suggested by other studies on academic adjustment. The sample comprised 2060 Spanish high school students (47.9% girls; mean age = 14.34). The instruments used were the scale of victimization from European Bullying Intervention Project Questionnaire , the negative scale from Rosenberg Self-Esteem Scale, Social Anxiety Scale for Adolescents and a general item about social self-efficacy, all of them self-reports. Structural equation modeling was used to analyze the data. The results confirmed the partial mediating role of negative self-esteem, social anxiety and social self-efficacy between peer victimization and social adjustment and highlight the importance of empowering victimized students to improve their self-esteem and self-efficacy and prevent social anxiety. Such problems lead to the avoidance of social interactions and social reinforcement, thus making it difficult for these students to achieve adequate social adjustment.

The Mediating Role of Psychological Adjustment between Peer Victimization and Social Adjustment in Adolescence

Directory of Open Access Journals (Sweden)

Eva M. Romera

2016-11-01

Full Text Available There is extensive scientific evidence of the serious psychological and social effects that peer victimization may have on students, among them internalizing problems such as anxiety or negative self-esteem, difficulties related to low self-efficacy and lower levels of social adjustment. Although a direct relationship has been observed between victimization and these effects, it has not yet been analyzed whether there is a relationship of interdependence between all these measures of psychosocial adjustment. The aim of this study was to examine the relationship between victimization and difficulties related to social adjustment among high school students. To do so, various explanatory models were tested to determine whether psychological adjustment (negative self-esteem, social anxiety and social self-efficacy could play a mediating role in this relationship, as suggested by other studies on academic adjustment. The sample comprised 2060 Spanish high school students (47.9% girls; mean age = 14.34. The instruments used were the scale of victimization from European Bullying Intervention Project Questionnaire, the negative scale from Rosenberg Self-Esteem Scale, Social Anxiety Scale for Adolescents and a general item about social self-efficacy, all of them self-reports. Structural equation modeling was used to analyze the data. The results confirmed the partial mediating role of negative self-esteem, social anxiety and social self-efficacy between peer victimization and social adjustment and highlight the importance of empowering victimized students to improve their self-esteem and self-efficacy and prevent social anxiety. Such problems lead to the avoidance of social interactions and social reinforcement, thus making it difficult for these students to achieve adequate social adjustment.

Network ties and survival

DEFF Research Database (Denmark)

Acheampong, George; Narteh, Bedman; Rand, John

2017-01-01

Poultry farming has been touted as one of the major ways by which poverty can be reduced in low-income economies like Ghana. Yet, anecdotally there is a high failure rate among these poultry farms. This current study seeks to understand the relationship between network ties and survival chances...... of small commercial poultry farms (SCPFs). We utilize data from a 2-year network survey of SCPFs in rural Ghana. The survival of these poultry farms are modelled using a lagged probit model of farms that persisted from 2014 into 2015. We find that network ties are important to the survival chances...... but this probability reduces as the number of industry ties increases but moderation with dynamic capability of the firm reverses this trend. Our findings show that not all network ties aid survival and therefore small commercial poultry farmers need to be circumspect in the network ties they cultivate and develop....

Modeling the survivability of brucella to exposure of Ultraviolet radiation and temperature

Science.gov (United States)

Howe, R.

Accumulated summation of daily Ultra Violet-B (UV-B = 290? to 320 ? ) data? from The USDA Ultraviolet Radiation Monitoring Program show good correlation (R^2 = 77%) with daily temperature data during the five month period from February through June, 1998. Exposure of disease organisms, such as brucella to the effects of accumulated UV-B radiation, can be modeled for a 5 month period from February through June, 1998. Estimates of a lethal dosage for brucell of UV-B in the environment is dependent on minimum/maximum temperature and Solar Zenith Angle for the time period. The accumulated increase in temperature over this period also effects the decomposition of an aborted fetus containing brucella. Decomposition begins at some minimum daily temperature at 27 to 30 degrees C and peaks at 39 to 40C. It is useful to view the summation of temperature as a threshold for other bacteria growth, so that accumulated temperature greater than some value causes decomposition through competition with other bacteria and brucella die from the accumulated effects of UV-B, temperature and organism competition. Results of a study (Cook 1998) to determine survivability of brucellosis in the environment through exposure of aborted bovine fetuses show no one cause can be attributed to death of the disease agent. The combination of daily increase in temperature and accumulated UV-B radiation reveal an inverse correlation to survivability data and can be modeled as an indicator of brucella survivability in the environment in arid regions.

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.

Asymmetric adjustment

NARCIS (Netherlands)

2010-01-01

A method of adjusting a signal processing parameter for a first hearing aid and a second hearing aid forming parts of a binaural hearing aid system to be worn by a user is provided. The binaural hearing aid system comprises a user specific model representing a desired asymmetry between a first ear

Impact of forced vital capacity loss on survival after the onset of chronic lung allograft dysfunction.

Science.gov (United States)

Todd, Jamie L; Jain, Rahil; Pavlisko, Elizabeth N; Finlen Copeland, C Ashley; Reynolds, John M; Snyder, Laurie D; Palmer, Scott M

2014-01-15

Emerging evidence suggests a restrictive phenotype of chronic lung allograft dysfunction (CLAD) exists; however, the optimal approach to its diagnosis and clinical significance is uncertain. To evaluate the hypothesis that spirometric indices more suggestive of a restrictive ventilatory defect, such as loss of FVC, identify patients with distinct clinical, radiographic, and pathologic features, including worse survival. Retrospective, single-center analysis of 566 consecutive first bilateral lung recipients transplanted over a 12-year period. A total of 216 patients developed CLAD during follow-up. CLAD was categorized at its onset into discrete physiologic groups based on spirometric criteria. Imaging and histologic studies were reviewed when available. Survival after CLAD diagnosis was assessed using Kaplan-Meier and Cox proportional hazards models. Among patients with CLAD, 30% demonstrated an FVC decrement at its onset. These patients were more likely to be female, have radiographic alveolar or interstitial changes, and histologic findings of interstitial fibrosis. Patients with FVC decline at CLAD onset had significantly worse survival after CLAD when compared with those with preserved FVC (P model including baseline demographic and clinical factors (P < 0.0001; adjusted hazard ratio, 2.73; 95% confidence interval, 1.86-4.04). At CLAD onset, a subset of patients demonstrating physiology more suggestive of restriction experience worse clinical outcomes. Further study of the biologic mechanisms underlying CLAD phenotypes is critical to improving long-term survival after lung transplantation.

Survival of fishes after impingement on traveling screens at Hudson River power plants

International Nuclear Information System (INIS)

Muessig, P.H.; Hutchison, J.B.; King, L.R.; Ligotino, R.J.; Daley, M.

1988-01-01

The survival of Hudson River fishes, juveniles and adults, after they had been impinged on continuously rotated traveling screens at the Bowline Point and Danskammer Point power plants was examined. Survival of principal species was similar at the two plants, and estimates of survival improved as monitoring stress was reduced. Adjusted for survival of control fish, survival over 84-108 h after fish were recovered from the screens was highest for Atlantic tomcod, striped bass, and white perch (50-90%) and lowest for bay anchovy, alewife, and blueback herring; other species showed intermediate survival. Survival of striped bass and white perch was positively correlated with water temperature in winter and with conductivity in spring and fall. Continual rotation of the screens, which shortens the average time that fish are impinged, increased survival over that associated with intermittent rotation. 24 refs., 9 figs., 4 tabs

Overweight or obese BMI is associated with earlier, but not later survival after common acute illnesses.

Science.gov (United States)

Prescott, Hallie C; Chang, Virginia W

2018-02-06

Obesity has been associated with improved short-term mortality following common acute illness, but its relationship with longer-term mortality is unknown. Observational study of U.S. Health and Retirement Study (HRS) participants with federal health insurance (fee-for-service Medicare) coverage, hospitalized with congestive heart failure (N = 4287), pneumonia (N = 4182), or acute myocardial infarction (N = 2001), 1996-2012. Using cox proportional hazards models, we examined the association between overweight or obese BMI (BMI ≥ 25.0 kg/m 2 ) and mortality to 5 years after hospital admission, adjusted for potential confounders measured at the same time as BMI, including age, race, sex, education, partnership status, income, wealth, and smoking status. Body mass index (BMI) was calculated from self-reported height and weight collected at the HRS survey prior to hospitalization (a median 1.1 year prior to hospitalization). The referent group was patients with a normal BMI (18.5 to BMI was associated with lower mortality at 1 year after hospitalization for congestive heart failure, pneumonia, and acute myocardial infarction-with adjusted hazard ratios of 0.68 (95% CI 0.59-0.79), 0.74 (95% CI: 0.64-0.84), and 0.65 (95%CI: 0.53-0.80), respectively. Among participants who lived to one year, however, subsequent survival was similar between patients with normal versus overweight/obese BMI. In older Americans, overweight or obese BMI was associated with improved survival following hospitalization for congestive heart failure, pneumonia, and acute myocardial infarction. This association, however, is limited to the shorter-term. Conditional on surviving to one year, we did not observe a survival advantage associated with excess weight.

The empty wagons adjustment algorithm of Chinese heavy-haul railway

International Nuclear Information System (INIS)

Zhang, Jinchuan; Yang, Hao; Wei, Yuguang; Shang, Pan

2016-01-01

The paper studied the problem of empty wagons adjustment of Chinese heavy-haul railway. Firstly, based on the existing study of the empty wagons adjustment of heavy-haul railway in the world, Chinese heavy-haul railway was analyzed, especially the mode of transportation organization and characteristics of empty wagons adjustment. Secondly, the optimization model was set up to solve the empty wagons adjustment of heavy-haul railway and the model took the minimum idling period as the function goal. Finally, through application and solution of one case, validity and practicability of model and algorithm had been proved. So, the model could offer decision support to transport enterprises on adjusting empty wagons.

Changing Pattern in Malignant Mesothelioma Survival

Directory of Open Access Journals (Sweden)

Jennifer Faig

2015-02-01

Full Text Available Survival for mesothelioma has been shown to be poor, with marginal improvement over time. Recent advances in the understanding of pathophysiology and treatment of mesothelioma may impact therapy to improve survival that may not be evident from available clinical trials that are often small and not randomized. Therapies may affect survival differently based on mesothelioma location (pleural vs peritoneal. Data are conflicting regarding the effect of asbestos exposure on mesothelioma location. OBJECTIVES: We examined survival in a large cohort of mesothelioma subjects analyzed by tumor location and presence and mode of asbestos exposure. METHODS: Data were analyzed from cases (n = 380 diagnosed with mesothelioma from 1992 to 2012. Cases were either drawn from treatment referrals, independent medical evaluation for medical legal purposes, or volunteers who were diagnosed with mesothelioma. Subjects completed an occupational medical questionnaire, personal interview with the examining physician, and physician review of the medical record. RESULTS: This study reports better survival for mesothelioma than historical reports. Survival for peritoneal mesothelioma was longer than that for pleural mesothelioma (hazard ratio = 0.36, 95% confidence interval = 0.24-0.54, P < .001 after adjusting for gender and age at diagnosis. Non-occupational cases were more likely to be 1 diagnosed with peritoneal mesothelioma, 2 female, 3 exposed, and 4 diagnosed at a younger age and to have a 5 shorter latency compared to occupational cases (P < .001. CONCLUSION: Peritoneal mesothelioma was more likely associated with non-occupational exposure, thus emphasizing the importance of exposure history in enhancing early diagnosis and treatment impact.

Estimating the average treatment effect on survival based on observational data and using partly conditional modeling.

Science.gov (United States)

Gong, Qi; Schaubel, Douglas E

2017-03-01

Treatments are frequently evaluated in terms of their effect on patient survival. In settings where randomization of treatment is not feasible, observational data are employed, necessitating correction for covariate imbalances. Treatments are usually compared using a hazard ratio. Most existing methods which quantify the treatment effect through the survival function are applicable to treatments assigned at time 0. In the data structure of our interest, subjects typically begin follow-up untreated; time-until-treatment, and the pretreatment death hazard are both heavily influenced by longitudinal covariates; and subjects may experience periods of treatment ineligibility. We propose semiparametric methods for estimating the average difference in restricted mean survival time attributable to a time-dependent treatment, the average effect of treatment among the treated, under current treatment assignment patterns. The pre- and posttreatment models are partly conditional, in that they use the covariate history up to the time of treatment. The pre-treatment model is estimated through recently developed landmark analysis methods. For each treated patient, fitted pre- and posttreatment survival curves are projected out, then averaged in a manner which accounts for the censoring of treatment times. Asymptotic properties are derived and evaluated through simulation. The proposed methods are applied to liver transplant data in order to estimate the effect of liver transplantation on survival among transplant recipients under current practice patterns. © 2016, The International Biometric Society.

Heterogeneity in the Speed of Adjustment toward Target Leverage

DEFF Research Database (Denmark)

Elsas, Ralf; Florysiak, David

2011-01-01

Estimating the speed of adjustment toward target leverage using the standard partial adjustment model assumes that all firms within the sample adjust at the same (average) pace. Dynamic capital structure theory predicts heterogeneity in adjustment speed due to firm-specific adjustment costs. Appl...

42 CFR 422.310 - Risk adjustment data.

Science.gov (United States)

2010-10-01

... that are used in the development and application of a risk adjustment payment model. (b) Data... (CONTINUED) MEDICARE PROGRAM MEDICARE ADVANTAGE PROGRAM Payments to Medicare Advantage Organizations § 422... risk adjustment factors used to adjust payments, as required under §§ 422.304(a) and (c). CMS also may...

Alternative Payment Models Should Risk-Adjust for Conversion Total Hip Arthroplasty: A Propensity Score-Matched Study.

Science.gov (United States)

McLawhorn, Alexander S; Schairer, William W; Schwarzkopf, Ran; Halsey, David A; Iorio, Richard; Padgett, Douglas E

2017-12-06

For Medicare beneficiaries, hospital reimbursement for nonrevision hip arthroplasty is anchored to either diagnosis-related group code 469 or 470. Under alternative payment models, reimbursement for care episodes is not further risk-adjusted. This study's purpose was to compare outcomes of primary total hip arthroplasty (THA) vs conversion THA to explore the rationale for risk adjustment for conversion procedures. All primary and conversion THAs from 2007 to 2014, excluding acute hip fractures and cancer patients, were identified in the National Surgical Quality Improvement Program database. Conversion and primary THA patients were matched 1:1 using propensity scores, based on preoperative covariates. Multivariable logistic regressions evaluated associations between conversion THA and 30-day outcomes. A total of 2018 conversions were matched to 2018 primaries. There were no differences in preoperative covariates. Conversions had longer operative times (148 vs 95 minutes, P reimbursement models shift toward bundled payment paradigms, conversion THA appears to be a procedure for which risk adjustment is appropriate. Copyright © 2017 Elsevier Inc. All rights reserved.

Exact results for survival probability in the multistate Landau-Zener model

International Nuclear Information System (INIS)

Volkov, M V; Ostrovsky, V N

2004-01-01

An exact formula is derived for survival probability in the multistate Landau-Zener model in the special case where the initially populated state corresponds to the extremal (maximum or minimum) slope of a linear diabatic potential curve. The formula was originally guessed by S Brundobler and V Elzer (1993 J. Phys. A: Math. Gen. 26 1211) based on numerical calculations. It is a simple generalization of the expression for the probability of diabatic passage in the famous two-state Landau-Zener model. Our result is obtained via analysis and summation of the entire perturbation theory series

Coordination Motor Skills of Military Pilots Subjected to Survival Training.

Science.gov (United States)

Tomczak, Andrzej

2015-09-01

Survival training of military pilots in the Polish Army gains significance because polish pilots have taken part in more and more military missions. Prolonged exercise of moderate intensity with restricted sleep or sleep deprivation is known to deteriorate performance. The aim of the study was thus to determine the effects of a strenuous 36-hour exercise with restricted sleep on selected motor coordination and psychomotor indices. Thirteen military pilots aged 30-56 years were examined twice: pretraining and posttraining. The following tests were applied: running motor adjustment (15-m sprint, 3 × 5-m shuttle run, 15-m slalom, and 15-m squat), divided attention, dynamic body balance, handgrip strength differentiation. Survival training resulted in significant decreases in maximum handgrip strength (from 672 to 630 N), corrected 50% max handgrip (from 427 to 367 N), error 50% max (from 26 to 17%), 15-m sprint (from 5.01 to 4.64 m·s), and 15-m squat (2.20 to 1.98 m·s). The training improvements took place in divided attention test (from 48.2 to 57.2%). The survival training applied to pilots only moderately affected some of their motor adjustment skills, the divided attention, and dynamic body balance remaining unaffected or even improved. Further studies aimed at designing a set of tests for coordination motor skills and of soldiers' capacity to fight for survival under conditions of isolation are needed.

Evolution Scenarios at the Romanian Economy Level, Using the R.M. Solow Adjusted Model

Directory of Open Access Journals (Sweden)

Stelian Stancu

2008-06-01

Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans model etc., the R.M. Solow model is part of the category which characterizes the economic growth. The paper proposes the presentation of the R.M. Solow adjusted model with specific simulation characteristics and economic growth scenario. Considering these aspects, there are presented the values obtained at the economy level, behind the simulations, about the ratio Capital on the output volume, Output volume on employee, equal with the current labour efficiency, as well as the Labour efficiency value.

An approach to the drone fleet survivability assessment based on a stochastic continues-time model

Science.gov (United States)

Kharchenko, Vyacheslav; Fesenko, Herman; Doukas, Nikos

2017-09-01

An approach and the algorithm to the drone fleet survivability assessment based on a stochastic continues-time model are proposed. The input data are the number of the drones, the drone fleet redundancy coefficient, the drone stability and restoration rate, the limit deviation from the norms of the drone fleet recovery, the drone fleet operational availability coefficient, the probability of the drone failure-free operation, time needed for performing the required tasks by the drone fleet. The ways for improving the recoverable drone fleet survivability taking into account amazing factors of system accident are suggested. Dependencies of the drone fleet survivability rate both on the drone stability and the number of the drones are analysed.

The combined effect of individual and neighborhood socioeconomic status on nasopharyngeal cancer survival.

Directory of Open Access Journals (Sweden)

Ting-Shou Chang

Full Text Available BACKGROUND: The relationship between individual and neighborhood socioeconomic status (SES and mortality rates in patients with nasopharyngeal carcinoma (NPC is unknown. This population-based study aimed to examine the association between SES and survival of patients with NPC in Taiwan. MATERIALS AND METHODS: A population-based follow-up study was conducted of 4691 patients diagnosed with NPC between 2002 and 2006. Each patient was traced to death or for 5 years. Individual SES was defined by enrollee job category. Neighborhood SES was based on household income dichotomized into advantaged and disadvantaged areas. Cox proportional hazards model was used to compare the death-free survival rates between the different SES groups after adjusting for possible confounding factors and risk factors. RESULTS: In NPC patients below the age of 65 years, 5-year overall survival rates were worst for those with low individual SES living in disadvantaged neighborhoods. After adjusting for patient characteristics (age, gender, Charlson Comorbidity Index Score, NPC patients with low individual SES residing in disadvantaged neighborhoods were found to have a 2-fold higher risk of mortality than patients with high individual SES residing in advantaged neighborhoods. We found no significant difference in mortality rates between different SES groups in NPC patients aged 65 and above. CONCLUSIONS: Our findings indicate that NPC patients with low individual SES who live in disadvantaged neighborhoods have the higher risk of mortality than their more privileged counterparts. Public health strategies and welfare policies would be well advised to try to offset the inequalities in health care and pay more attention to addressing the needs of this vulnerable group.

Estimation of age- and stage-specific Catalan breast cancer survival functions using US and Catalan survival data

Science.gov (United States)

2009-01-01

Background During the last part of the 1990s the chance of surviving breast cancer increased. Changes in survival functions reflect a mixture of effects. Both, the introduction of adjuvant treatments and early screening with mammography played a role in the decline in mortality. Evaluating the contribution of these interventions using mathematical models requires survival functions before and after their introduction. Furthermore, required survival functions may be different by age groups and are related to disease stage at diagnosis. Sometimes detailed information is not available, as was the case for the region of Catalonia (Spain). Then one may derive the functions using information from other geographical areas. This work presents the methodology used to estimate age- and stage-specific Catalan breast cancer survival functions from scarce Catalan survival data by adapting the age- and stage-specific US functions. Methods Cubic splines were used to smooth data and obtain continuous hazard rate functions. After, we fitted a Poisson model to derive hazard ratios. The model included time as a covariate. Then the hazard ratios were applied to US survival functions detailed by age and stage to obtain Catalan estimations. Results We started estimating the hazard ratios for Catalonia versus the USA before and after the introduction of screening. The hazard ratios were then multiplied by the age- and stage-specific breast cancer hazard rates from the USA to obtain the Catalan hazard rates. We also compared breast cancer survival in Catalonia and the USA in two time periods, before cancer control interventions (USA 1975–79, Catalonia 1980–89) and after (USA and Catalonia 1990–2001). Survival in Catalonia in the 1980–89 period was worse than in the USA during 1975–79, but the differences disappeared in 1990–2001. Conclusion Our results suggest that access to better treatments and quality of care contributed to large improvements in survival in Catalonia. On

Permintaan Beras di Provinsi Jambi (Penerapan Partial Adjustment Model

Directory of Open Access Journals (Sweden)

Wasi Riyanto

2013-07-01

Full Text Available The purpose of this study is to determine the effect of price of rice, flour prices, population, income of population and demand of rice for a year earlier on rice demand, demand rice elasticity and rice demand prediction in Jambi Province. This study uses secondary data, including time series data for 22 years from 1988 until 2009. The study used some variables, consist of rice demand (Qdt, the price of rice (Hb, the price of wheat flour (Hg, population (Jp, the income of the population (PDRB and demand for rice the previous year (Qdt-1. The make of this study are multiple regression and dynamic analysis  a Partial Adjustment Model, where the demand for rice is the dependent variable and the price of rice, flour prices, population, income population and demand of rice last year was the independent variable. Partial Adjustment Model analysis results showed that the effect of changes in prices of rice  and flour are not significant  to  changes in demand for rice. The population and demand of rice the previous year has positive and significant impact on demand for rice, while revenues have negative and significant population of rice demand. Variable price of rice, earning population and the price of flour is inelastic the demand of rice, because rice is not a normal good but as a necessity so that there is no substitution of goods (replacement of rice with other commodities in Jambi Province. Based on the analysis, it is recommended to the government to be able to control the rate of population increase given the variable number of people as one of the factors that affect demand for rice.It is expected that the  government also began  to  socialize  in a lifestyle  of  non-rice food consumption to control the increasing amount of demand for rice. Last suggestion, the government developed a diversification of staple foods other than rice. Keywords: Demand, Rice, Income Population

PERMINTAAN BERAS DI PROVINSI JAMBI (Penerapan Partial Adjustment Model

Directory of Open Access Journals (Sweden)

Wasi Riyanto

2013-07-01

Full Text Available The purpose of this study is to determine the effect of price of rice, flour prices, population, income of population and demand of rice for a year earlier on rice demand, demand rice elasticity and rice demand prediction in Jambi Province. This study uses secondary data, including time series data for 22 years from 1988 until 2009. The study used some variables, consist of rice demand (Qdt, the price of rice (Hb, the price of wheat flour (Hg, population (Jp, the income of the population (PDRB and demand for rice the previous year (Qdt-1. The make of this study are multiple regression and dynamic analysis a Partial Adjustment Model, where the demand for rice is the dependent variable and the price of rice, flour prices, population, income population and demand of rice last year was the independent variable. Partial Adjustment Model analysis results showed that the effect of changes in prices of rice and flour are not significant to changes in demand for rice. The population and demand of rice the previous year has positive and significant impact on demand for rice, while revenues have negative and significant population of rice demand. Variable price of rice, earning population and the price of flour is inelastic the demand of rice, because rice is not a normal good but as a necessity so that there is no substitution of goods (replacement of rice with other commodities in Jambi Province. Based on the analysis, it is recommended to the government to be able to control the rate of population increase given the variable number of people as one of the factors that affect demand for rice.It is expected that the government also began to socialize in a lifestyle of non-rice food consumption to control the increasing amount of demand for rice. Last suggestion, the government developed a diversification of staple foods other than rice.

Extremely low-frequency magnetic fields and survival from childhood acute lymphoblastic leukemia

DEFF Research Database (Denmark)

Schüz, J; Grell, K; Kinsey, S

2012-01-01

A previous US study reported poorer survival in children with acute lymphoblastic leukemia (ALL) exposed to extremely low-frequency magnetic fields (ELF-MF) above 0.3 μT, but based on small numbers. Data from 3073 cases of childhood ALL were pooled from prospective studies conducted in Canada......, Denmark, Germany, Japan, UK and US to determine death or relapse up to 10 years from diagnosis. Adjusting for known prognostic factors, we calculated hazard ratios (HRs) and 95% confidence intervals (CI) for overall survival and event-free survival for ELF-MF exposure categories and by 0.1 μT increases...

Predicting water main failures using Bayesian model averaging and survival modelling approach

International Nuclear Information System (INIS)

Kabir, Golam; Tesfamariam, Solomon; Sadiq, Rehan

2015-01-01

To develop an effective preventive or proactive repair and replacement action plan, water utilities often rely on water main failure prediction models. However, in predicting the failure of water mains, uncertainty is inherent regardless of the quality and quantity of data used in the model. To improve the understanding of water main failure, a Bayesian framework is developed for predicting the failure of water mains considering uncertainties. In this study, Bayesian model averaging method (BMA) is presented to identify the influential pipe-dependent and time-dependent covariates considering model uncertainties whereas Bayesian Weibull Proportional Hazard Model (BWPHM) is applied to develop the survival curves and to predict the failure rates of water mains. To accredit the proposed framework, it is implemented to predict the failure of cast iron (CI) and ductile iron (DI) pipes of the water distribution network of the City of Calgary, Alberta, Canada. Results indicate that the predicted 95% uncertainty bounds of the proposed BWPHMs capture effectively the observed breaks for both CI and DI water mains. Moreover, the performance of the proposed BWPHMs are better compare to the Cox-Proportional Hazard Model (Cox-PHM) for considering Weibull distribution for the baseline hazard function and model uncertainties. - Highlights: • Prioritize rehabilitation and replacements (R/R) strategies of water mains. • Consider the uncertainties for the failure prediction. • Improve the prediction capability of the water mains failure models. • Identify the influential and appropriate covariates for different models. • Determine the effects of the covariates on failure

Standard model group: survival of the fittest

Energy Technology Data Exchange (ETDEWEB)

Nielsen, H.B. (Niels Bohr Inst., Copenhagen (Denmark); Nordisk Inst. for Teoretisk Atomfysik, Copenhagen (Denmark)); Brene, N. (Niels Bohr Inst., Copenhagen (Denmark))

1983-09-19

The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapse is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

Standard model group survival of the fittest

International Nuclear Information System (INIS)

Nielsen, H.B.; Brene, N.

1983-02-01

The essential content of this note is related to random dynamics. The authors speculate that the world seen through a sub Planck scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. It is seen that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. It is further argued that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property. (Auth.)

Association of the Timing of Pregnancy With Survival in Women With Breast Cancer

Science.gov (United States)

Iqbal, Javaid; Amir, Eitan; Rochon, Paula A.; Giannakeas, Vasily; Sun, Ping

2017-01-01

Importance Increasing numbers of women experience pregnancy around the time of, or after, a diagnosis of breast cancer. Understanding the effect of pregnancy on survival in women with breast cancer will help in the counseling and treatment of these women. Objective To compare the overall survival of women diagnosed with breast cancer during pregnancy or in the postpartum period with that of women who had breast cancer but did not become pregnant. Design, Setting, and Participants This population-based, retrospective cohort study linked health administrative databases in Ontario, Canada, comprising 7553 women aged 20 to 45 years at the time of diagnosis with invasive breast cancer, from January 1, 2003, to December 31, 2014. Exposures Any pregnancy in the period from 5 years before, until 5 years after, the index date of the diagnosis of breast cancer. Women were classified into the following 4 exposure groups: no pregnancy (the referent), pregnancy before breast cancer, pregnancy-associated breast cancer, and pregnancy following breast cancer. Main Outcomes and Measures Five-year actuarial survival rates for all exposure groups, age-adjusted and multivariable hazard ratios [HRs] of pregnancy for overall survival for all exposure groups, and time-dependent hazard ratios for women with pregnancy following breast cancer. Results Among the 7553 women in the study (mean age at diagnosis, 39.1 years; median, 40 years; range, 20-44 years) the 5-year actuarial survival rate was 87.5% (95% CI, 86.5%-88.4%) for women with no pregnancy, 85.3% (95% CI, 82.8%-87.8%) for women with pregnancy before breast cancer (age-adjusted hazard ratio, 1.03; 95% CI, 0.85-1.27; P = .73), and 82.1% (95% CI, 78.3%-85.9%) for women with pregnancy-associated breast cancer (age-adjusted hazard ratio, 1.18; 95% CI, 0.91-1.53; P = .20). The 5-year actuarial survival rate was 96.7% (95% CI, 94.1%-99.3%) for women who had pregnancy 6 months or more after diagnosis of breast cancer, vs 87

Incorporating Comorbidity Within Risk Adjustment for UK Pediatric Cardiac Surgery.

Science.gov (United States)

Brown, Katherine L; Rogers, Libby; Barron, David J; Tsang, Victor; Anderson, David; Tibby, Shane; Witter, Thomas; Stickley, John; Crowe, Sonya; English, Kate; Franklin, Rodney C; Pagel, Christina

2017-07-01

When considering early survival rates after pediatric cardiac surgery it is essential to adjust for risk linked to case complexity. An important but previously less well understood component of case mix complexity is comorbidity. The National Congenital Heart Disease Audit data representing all pediatric cardiac surgery procedures undertaken in the United Kingdom and Ireland between 2009 and 2014 was used to develop and test groupings for comorbidity and additional non-procedure-based risk factors within a risk adjustment model for 30-day mortality. A mixture of expert consensus based opinion and empiric statistical analyses were used to define and test the new comorbidity groups. The study dataset consisted of 21,838 pediatric cardiac surgical procedure episodes in 18,834 patients with 539 deaths (raw 30-day mortality rate, 2.5%). In addition to surgical procedure type, primary cardiac diagnosis, univentricular status, age, weight, procedure type (bypass, nonbypass, or hybrid), and era, the new risk factor groups of non-Down congenital anomalies, acquired comorbidities, increased severity of illness indicators (eg, preoperative mechanical ventilation or circulatory support) and additional cardiac risk factors (eg, heart muscle conditions and raised pulmonary arterial pressure) all independently increased the risk of operative mortality. In an era of low mortality rates across a wide range of operations, non-procedure-based risk factors form a vital element of risk adjustment and their presence leads to wide variations in the predicted risk of a given operation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

Science.gov (United States)

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient. The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, pcase-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

A new multivariate zero-adjusted Poisson model with applications to biomedicine.

Science.gov (United States)

Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

2018-05-25

Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Modeling the ecological impacts of Flaming Gorge Dam operations

International Nuclear Information System (INIS)

Yin, S.C.L.; LaGory, K.E.; Hayse, J.W.; Hlohowskyj, I.; Van Lonkhuyzen, R.A.; Cho, H.E.

1996-01-01

Hydropower operations at Flaming Gorge Dam on the Green River in Utah, US, can produce rapid downstream changes in flow and stage during a day. These changes can, in turn, affect ecological resources below the dam, including riparian vegetation, trout, and endangered fish. Four hydropower operational scenarios featuring varying degrees of hydropower-induced flow fluctuation were evaluated with hydrologic models and multispectral aerial videography of the river. Year-round high fluctuations would support the least amount of stable spawning habitat for trout and nursery habitat for endangered fish, and would have the greatest potential for reducing growth and over winter survival of fish. Seasonally, adjusted moderate fluctuation and seasonally adjusted steady flow scenarios could increase food production and over winter survival and would provide the greatest amount of spawning and nursery habitat for fish. The year-round high fluctuation, seasonally adjusted high fluctuation, and seasonally adjusted moderate fluctuation scenarios would result in a 5% decrease in upper riparian zone habitat. the seasonally adjusted steady flow scenario would result in an 8% increase in upper riparian zone habitat. Lower riparian zone habitat would increase by about 17% for year-round and seasonally adjusted high fluctuating flow scenarios but decrease by about 24% and 69% for seasonally adjusted moderate fluctuating and steady flow scenarios, respectively

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

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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.

Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

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Astuti Thamrin, Sri; Taufik, Irfan

2018-03-01

Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

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.

Organochlorine insecticides DDT and chlordane in relation to survival following breast cancer.

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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.

The relationship between the C-statistic of a risk-adjustment model and the accuracy of hospital report cards: a Monte Carlo Study.

Science.gov (United States)

Austin, Peter C; Reeves, Mathew J

2013-03-01

Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards. To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards. Monte Carlo simulations were used to examine this issue. We examined the influence of 3 factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada. The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact. The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card.

Twenty-Five Year Survival of Children with Intellectual Disability in Western Australia.

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Bourke, Jenny; Nembhard, Wendy N; Wong, Kingsley; Leonard, Helen

2017-09-01

To investigate survival up to early adulthood for children with intellectual disability and compare their risk of mortality with that of children without intellectual disability. This was a retrospective cohort study of all live births in Western Australia between January 1, 1983 and December 31, 2010. Children with an intellectual disability (n = 10 593) were identified from the Western Australian Intellectual Disability Exploring Answers Database. Vital status was determined from linkage to the Western Australian Mortality database. Kaplan-Meier product limit estimates and 95% CIs were computed by level of intellectual disability. Hazard ratios (HRs) and 95% CIs were calculated from Cox proportional hazard regression models adjusting for potential confounders. After adjusting for potential confounders, compared with those without intellectual disability, children with intellectual disability had a 6-fold increased risk of mortality at 1-5 years of age (adjusted HR [aHR] = 6.0, 95%CI: 4.8, 7.6), a 12-fold increased risk at 6-10 years of age (aHR = 12.6, 95% CI: 9.0, 17.7) and a 5-fold increased risk at 11-25 years of age (aHR = 4.9, 95% CI: 3.9, 6.1). Children with severe intellectual disability were at even greater risk. No difference in survival was observed for Aboriginal children with intellectual disability compared with non-Aboriginal children with intellectual disability. Although children with intellectual disability experience higher mortality at all ages compared with those without intellectual disability, the greatest burden is for those with severe intellectual disability. However, even children with mild to moderate intellectual disability have increased risk of death compared with unaffected children. Copyright © 2017 Elsevier Inc. All rights reserved.

Model for breast cancer survival: relative prognostic roles of axillary nodal status, TNM stage, estrogen receptor concentration, and tumor necrosis.

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Shek, L L; Godolphin, W

1988-10-01

The independent prognostic effects of certain clinical and pathological variables measured at the time of primary diagnosis were assessed with Cox multivariate regression analysis. The 859 patients with primary breast cancer, on which the proportional hazards model was based, had a median follow-up of 60 months. Axillary nodal status (categorized as N0, N1-3 or N4+) was the most significant and independent factor in overall survival, but inclusion of TNM stage, estrogen receptor (ER) concentration and tumor necrosis significantly improved survival predictions. Predictions made with the model showed striking subset survival differences within stage: 5-year survival from 36% (N4+, loge[ER] = 0, marked necrosis) to 96% (N0, loge[ER] = 6, no necrosis) in TNM I, and from 0 to 70% for the same categories in TNM IV. Results of the model were used to classify patients into four distinct risk groups according to a derived hazard index. An 8-fold variation in survival was seen with the highest (greater than 3) to lowest index values (less than 1). Each hazard index level included patients with varied combinations of the above factors, but could be considered to denote the same degree of risk of breast cancer mortality. A model with ER concentration, nodal status, and tumor necrosis was found to best predict survival after disease recurrence in 369 patients, thus confirming the enduring biological significance of these factors.

Pretreatment Evaluation of Microcirculation by Dynamic Contrast-Enhanced Magnetic Resonance Imaging Predicts Survival in Primary Rectal Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

DeVries, Alexander Friedrich [Department of Radio-Oncology, Academic Teaching Hospital Feldkirch, Feldkirch (Austria); Piringer, Gudrun, E-mail: gudrun.piringer@hotmail.com [Department of Oncology, Wels-Grieskirchen Medical Hospital, Wels (Austria); Kremser, Christian; Judmaier, Werner [Department of Radiology, Innsbruck Medical University, Innsbruck (Austria); Saely, Christoph Hubert [Department of Medicine and Cardiology, Academic Teaching Hospital Feldkirch, Feldkirch (Austria); Lukas, Peter [Department of Radio-Oncology, Innsbruck Medical University, Innsbruck (Austria); Öfner, Dietmar [Department of Surgery, Paracelsus Medical University, Salzburg (Austria)

2014-12-01

Purpose: To investigate the prognostic value of the perfusion index (PI), a microcirculatory parameter estimated from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which integrates information on both flow and permeability, to predict overall survival and disease-free survival in patients with primary rectal cancer. Methods and Materials: A total of 83 patients with stage cT3 rectal cancer requiring neoadjuvant chemoradiation were investigated with DCE-MRI before start of therapy. Contrast-enhanced dynamic T{sub 1} mapping was obtained, and a simple data analysis strategy based on the calculation of the maximum slope of the tissue concentration–time curve divided by the maximum of the arterial input function was used as a measure of tumor microcirculation (PI), which integrates information on both flow and permeability. Results: In 39 patients (47.0%), T downstaging (ypT0-2) was observed. During a mean (±SD) follow-up period of 71 ± 29 months, 58 patients (69.9%) survived, and disease-free survival was achieved in 45 patients (54.2%). The mean PI (PImean) averaged over the group of nonresponders was significantly higher than for responders. Additionally, higher PImean in age- and gender-adjusted analyses was strongly predictive of therapy nonresponse. Most importantly, PImean strongly and significantly predicted disease-free survival (unadjusted hazard ratio [HR], 1.85 [ 95% confidence interval, 1.35-2.54; P<.001)]; HR adjusted for age and sex, 1.81 [1.30-2.51]; P<.001) as well as overall survival (unadjusted HR 1.42 [1.02-1.99], P=.040; HR adjusted for age and sex, 1.43 [1.03-1.98]; P=.034). Conclusions: This analysis identifies PImean as a novel biomarker that is predictive for therapy response, disease-free survival, and overall survival in patients with primary locally advanced rectal cancer.

Predictors of survival among HIV-positive children on ART in ...

African Journals Online (AJOL)

... 16(4): 335–343. Open Access article distributed in terms of the Creative Commons Attribution License ... and adjusted hazard ratios respectively. The results reveal ... Children who were initiated early on ART had higher survival probability over time (HR: 0.35 [95% ..... workers they will have desirable clinical outcomes.

Pre-End-Stage Renal Disease Care and Early Survival among Incident Dialysis Patients in the US Military Health System.

Science.gov (United States)

Nee, Robert; Fisher, Evan; Yuan, Christina M; Agodoa, Lawrence Y; Abbott, Kevin C

2017-01-01

Previous reports showed an increased early mortality after chronic dialysis initiation among the end-stage renal disease (ESRD) population. We hypothesized that ESRD patients in the Military Health System (MHS) would have greater access to pre-ESRD care and hence better survival rates during this early high-risk period. In this retrospective cohort study, using the US Renal Data System database, we identified 1,256,640 patients initiated on chronic dialysis from January 2, 2004 through December 31, 2014, from which a bootstrap sample of 3,984 non-MHS incident dialysis patients were compared with 996 MHS patients. We assessed care by a nephrologist and dietitian, erythropoietin administration, and vascular access use at dialysis initiation as well as all-cause mortality as outcome variables. MHS patients were significantly more likely to have had pre-ESRD nephrology care (adjusted OR [aOR] 2.9; 95% CI 2.3-3.7) and arteriovenous fistula used at dialysis initiation (aOR 2.2; 95% CI 1.7-2.7). Crude mortality rates peaked between the 4th and the 8th week for both cohorts but were reduced among MHS patients. The baseline adjusted Cox model showed significantly lower death rates among MHS vs. non-MHS patients at 6, 9, and 12 months. This survival advantage among MHS patients was attenuated after further adjustment for pre-ESRD nephrology care and dialysis vascular access. MHS patients had improved survival within the first 12 months compared to the general ESRD population, which may be explained in part by differences in pre-ESRD nephrology care and vascular access types. © 2017 S. Karger AG, Basel.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

Directory of Open Access Journals (Sweden)

Ping Yu

Full Text Available A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke.The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient.The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82, and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84. Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008.The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

Economic analysis of coal price-electricity price adjustment in China based on the CGE model

International Nuclear Information System (INIS)

He, Y.X.; Zhang, S.L.; Yang, L.Y.; Wang, Y.J.; Wang, J.

2010-01-01

In recent years, coal price has risen rapidly, which has also brought a sharp increase in the expenditures of thermal power plants in China. Meantime, the power production price and power retail price have not been adjusted accordingly and a large number of thermal power plants have incurred losses. The power industry is a key industry in the national economy. As such, a thorough analysis and evaluation of the economic influence of the electricity price should be conducted before electricity price adjustment is carried out. This paper analyses the influence of coal price adjustment on the electric power industry, and the influence of electricity price adjustment on the macroeconomy in China based on computable general equilibrium models. The conclusions are as follows: (1) a coal price increase causes a rise in the cost of the electric power industry, but the influence gradually descends with increase in coal price; and (2) an electricity price increase has an adverse influence on the total output, Gross Domestic Product (GDP), and the Consumer Price Index (CPI). Electricity price increases have a contractionary effect on economic development and, consequently, electricity price policy making must consequently consider all factors to minimize their adverse influence.

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...

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

A metallic solution model with adjustable parameter for describing ternary thermodynamic properties from its binary constituents

International Nuclear Information System (INIS)

Fang Zheng; Qiu Guanzhou

2007-01-01

A metallic solution model with adjustable parameter k has been developed to predict thermodynamic properties of ternary systems from those of its constituent three binaries. In the present model, the excess Gibbs free energy for a ternary mixture is expressed as a weighted probability sum of those of binaries and the k value is determined based on an assumption that the ternary interaction generally strengthens the mixing effects for metallic solutions with weak interaction, making the Gibbs free energy of mixing of the ternary system more negative than that before considering the interaction. This point is never considered in the models currently reported, where the only difference in a geometrical definition of molar values of components is considered that do not involve thermodynamic principles but are completely empirical. The current model describes the results of experiments very well, and by adjusting the k value also agrees with those from models used widely in the literature. Three ternary systems, Mg-Cu-Ni, Zn-In-Cd, and Cd-Bi-Pb are recalculated to demonstrate the method of determining k and the precision of the model. The results of the calculations, especially those in Mg-Cu-Ni system, are better than those predicted by the current models in the literature

Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy requiring IVC filter placement.

Science.gov (United States)

Huang, Steven Y; Odisio, Bruno C; Sabir, Sharjeel H; Ensor, Joe E; Niekamp, Andrew S; Huynh, Tam T; Kroll, Michael; Gupta, Sanjay

2017-07-01

Our purpose was to develop a predictive model for short-term survival (i.e. filter placement in patients with venous thromboembolism (VTE) and solid malignancy. Clinical and laboratory parameters were retrospectively reviewed for patients with solid malignancy who received a filter between January 2009 and December 2011 at a tertiary care cancer center. Multivariate Cox proportional hazards modeling was used to assess variables associated with 6 month survival following filter placement in patients with VTE and solid malignancy. Significant variables were used to generate a predictive model. 397 patients with solid malignancy received a filter during the study period. Three variables were associated with 6 month survival: (1) serum albumin [hazard ratio (HR) 0.496, P filter placement can be predicted from three patient variables. Our predictive model could be used to help physicians decide whether a permanent or retrievable filter may be more appropriate as well as to assess the risks and benefits for filter retrieval within the context of survival longevity in patients with cancer.

Assessing survivability to support power grid investment decisions

International Nuclear Information System (INIS)

Koziolek, Anne; Avritzer, Alberto; Suresh, Sindhu; Menasché, Daniel S.; Diniz, Morganna; Souza e Silva, Edmundo de; Leão, Rosa M.; Trivedi, Kishor; Happe, Lucia

2016-01-01

The reliability of power grids has been subject of study for the past few decades. Traditionally, detailed models are used to assess how the system behaves after failures. Such models, based on power flow analysis and detailed simulations, yield accurate characterizations of the system under study. However, they fall short on scalability. In this paper, we propose an efficient and scalable approach to assess the survivability of power systems. Our approach takes into account the phased-recovery of the system after a failure occurs. The proposed phased-recovery model yields metrics such as the expected accumulated energy not supplied between failure and full recovery. Leveraging the predictive power of the model, we use it as part of an optimization framework to assist in investment decisions. Given a budget and an initial circuit to be upgraded, we propose heuristics to sample the solution space in a principled way accounting for survivability-related metrics. We have evaluated the feasibility of this approach by applying it to the design of a benchmark distribution automation circuit. Our empirical results indicate that the combination of survivability and power flow analysis can provide meaningful investment decision support for power systems engineers. - Highlights: • We propose metrics and models for scalable survivability analysis of power systems. • The survivability model captures the system phased-recovery, from failure to repair. • The survivability model is used as a building block of an optimization framework. • Heuristics assist in investment options accounting for survivability-related metrics.

Prognostic Factors for Survival in Patients with Gastric Cancer using a Random Survival Forest

Science.gov (United States)

Adham, Davoud; Abbasgholizadeh, Nategh; Abazari, Malek

2017-01-01

Background: Gastric cancer is the fifth most common cancer and the third top cause of cancer related death with about 1 million new cases and 700,000 deaths in 2012. The aim of this investigation was to identify important factors for outcome using a random survival forest (RSF) approach. Materials and Methods: Data were collected from 128 gastric cancer patients through a historical cohort study in Hamedan-Iran from 2007 to 2013. The event under consideration was death due to gastric cancer. The random survival forest model in R software was applied to determine the key factors affecting survival. Four split criteria were used to determine importance of the variables in the model including log-rank, conversation?? of events, log-rank score, and randomization. Efficiency of the model was confirmed in terms of Harrell’s concordance index. Results: The mean age of diagnosis was 63 ±12.57 and mean and median survival times were 15.2 (95%CI: 13.3, 17.0) and 12.3 (95%CI: 11.0, 13.4) months, respectively. The one-year, two-year, and three-year rates for survival were 51%, 13%, and 5%, respectively. Each RSF approach showed a slightly different ranking order. Very important covariates in nearly all the 4 RSF approaches were metastatic status, age at diagnosis and tumor size. The performance of each RSF approach was in the range of 0.29-0.32 and the best error rate was obtained by the log-rank splitting rule; second, third, and fourth ranks were log-rank score, conservation of events, and the random splitting rule, respectively. Conclusion: Low survival rate of gastric cancer patients is an indication of absence of a screening program for early diagnosis of the disease. Timely diagnosis in early phases increases survival and decreases mortality. Creative Commons Attribution License

Computer-aided system of evaluation for population-based all-in-one service screening (CASE-PASS): from study design to outcome analysis with bias adjustment.

Science.gov (United States)

Chen, Li-Sheng; Yen, Amy Ming-Fang; Duffy, Stephen W; Tabar, Laszlo; Lin, Wen-Chou; Chen, Hsiu-Hsi

2010-10-01

Population-based routine service screening has gained popularity following an era of randomized controlled trials. The evaluation of these service screening programs is subject to study design, data availability, and the precise data analysis for adjusting bias. We developed a computer-aided system that allows the evaluation of population-based service screening to unify these aspects and facilitate and guide the program assessor to efficiently perform an evaluation. This system underpins two experimental designs: the posttest-only non-equivalent design and the one-group pretest-posttest design and demonstrates the type of data required at both the population and individual levels. Three major analyses were developed that included a cumulative mortality analysis, survival analysis with lead-time adjustment, and self-selection bias adjustment. We used SAS AF software to develop a graphic interface system with a pull-down menu style. We demonstrate the application of this system with data obtained from a Swedish population-based service screen and a population-based randomized controlled trial for the screening of breast, colorectal, and prostate cancer, and one service screening program for cervical cancer with Pap smears. The system provided automated descriptive results based on the various sources of available data and cumulative mortality curves corresponding to the study designs. The comparison of cumulative survival between clinically and screen-detected cases without a lead-time adjustment are also demonstrated. The intention-to-treat and noncompliance analysis with self-selection bias adjustments are also shown to assess the effectiveness of the population-based service screening program. Model validation was composed of a comparison between our adjusted self-selection bias estimates and the empirical results on effectiveness reported in the literature. We demonstrate a computer-aided system allowing the evaluation of population-based service screening

Lung cancer: Incidence and survival in Rabat, Morocco.

Science.gov (United States)

Lachgar, A; Tazi, M A; Afif, M; Er-Raki, A; Kebdani, T; Benjaafar, N

2016-12-01

Lung cancer is the most common cancer worldwide, but epidemiologic data from developing countries are lacking. This article reports lung cancer incidence and survival in Rabat, the capital of Morocco. All lung cancer cases diagnosed between 2005 and 2008 were analyzed using data provided by the Rabat Cancer Registry. The standardized rate was reported using age adjustment with respect to the world standard population, and the observed survival rates were calculated using the Kaplan-Meier method. Three hundred fifty-one cases were registered (314 males and 37 females), aged 27-90 years (median, 59 years). The most common pathological type was adenocarcinoma (40.2%) followed by squamous cell carcinoma (31.9%); the majority of cases were diagnosed at stage IV (52%). The age-standardized incidence rate was 25.1 and 2.7 per 100,000 for males and females, respectively, and the overall observed survival rates at 1 and 5 years were 31.7% and 3.4%, respectively. The clinical stage of disease was the only independent predictor of survival. The survival rate of lung cancer in Rabat is very poor. This finding explains the need for measures to reduce the prevalence of tobacco and to improve diagnostic and therapeutic facilities for lung cancer. Copyright © 2016. Published by Elsevier Masson SAS.

Sodium nitroprusside enhanced cardiopulmonary resuscitation improves short term survival in a porcine model of ischemic refractory ventricular fibrillation.

Science.gov (United States)

Yannopoulos, Demetris; Bartos, Jason A; George, Stephen A; Sideris, George; Voicu, Sebastian; Oestreich, Brett; Matsuura, Timothy; Shekar, Kadambari; Rees, Jennifer; Aufderheide, Tom P

2017-01-01

Sodium nitroprusside (SNP) enhanced CPR (SNPeCPR) demonstrates increased vital organ blood flow and survival in multiple porcine models. We developed a new, coronary occlusion/ischemia model of prolonged resuscitation, mimicking the majority of out-of-hospital cardiac arrests presenting with shockable rhythms. SNPeCPR will increase short term (4-h) survival compared to standard 2015 Advanced Cardiac Life Support (ACLS) guidelines in an ischemic refractory ventricular fibrillation (VF), prolonged CPR model. Sixteen anesthetized pigs had the ostial left anterior descending artery occluded leading to ischemic VF arrest. VF was untreated for 5min. Basic life support was performed for 10min. At minute 10 (EMS arrival), animals received either SNPeCPR (n=8) or standard ACLS (n=8). Defibrillation (200J) occurred every 3min. CPR continued for a total of 45min, then the balloon was deflated simulating revascularization. CPR continued until return of spontaneous circulation (ROSC) or a total of 60min, if unsuccessful. SNPeCPR animals received 2mg of SNP at minute 10 followed by 1mg every 5min until ROSC. Standard ACLS animals received 0.5mg epinephrine every 5min until ROSC. Primary endpoints were ROSC and 4-h survival. All SNPeCPR animals (8/8) achieved sustained ROSC versus 2/8 standard ACLS animals within one hour of resuscitation (p=0.04). The 4-h survival was significantly improved with SNPeCPR compared to standard ACLS, 7/8 versus 1/8 respectively, p=0.0019. SNPeCPR significantly improved ROSC and 4-h survival compared with standard ACLS CPR in a porcine model of prolonged ischemic, refractory VF cardiac arrest. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Development and External Validation of Prognostic Model for 2-Year Survival of Non-Small-Cell Lung Cancer Patients Treated With Chemoradiotherapy

International Nuclear Information System (INIS)

Dehing-Oberije, Cary; Yu Shipeng; De Ruysscher, Dirk; Meersschout, Sabine; Van Beek, Karen; Lievens, Yolande; Van Meerbeeck, Jan; De Neve, Wilfried; Rao, Bharat Ph.D.; Weide, Hiska van der; Lambin, Philippe

2009-01-01

Purpose: Radiotherapy, combined with chemotherapy, is the treatment of choice for a large group of non-small-cell lung cancer (NSCLC) patients. Recent developments in the treatment of these patients have led to improved survival. However, the clinical TNM stage is highly inaccurate for the prediction of survival, and alternatives are lacking. The objective of this study was to develop and validate a prediction model for survival of NSCLC patients, treated with chemoradiotherapy. Patients and Methods: The clinical data from 377 consecutive inoperable NSCLC patients, Stage I-IIIB, treated radically with chemoradiotherapy were collected. A prognostic model for 2-year survival was developed, using 2-norm support vector machines. The performance of the model was expressed as the area under the curve of the receiver operating characteristic and assessed using leave-one-out cross-validation, as well as two external data sets. Results: The final multivariate model consisted of gender, World Health Organization performance status, forced expiratory volume in 1 s, number of positive lymph node stations, and gross tumor volume. The area under the curve, assessed by leave-one-out cross-validation, was 0.74, and application of the model to the external data sets yielded an area under the curve of 0.75 and 0.76. A high- and low-risk group could be clearly identified using a risk score based on the model. Conclusion: The multivariate model performed very well and was able to accurately predict the 2-year survival of NSCLC patients treated with chemoradiotherapy. The model could support clinicians in the treatment decision-making process.

Breast implants following mastectomy in women with early-stage breast cancer: prevalence and impact on survival

International Nuclear Information System (INIS)

Le, Gem M; O'Malley, Cynthia D; Glaser, Sally L; Lynch, Charles F; Stanford, Janet L; Keegan, Theresa HM; West, Dee W

2005-01-01

Few studies have examined the effect of breast implants after mastectomy on long-term survival in breast cancer patients, despite growing public health concern over potential long-term adverse health effects. We analyzed data from the Surveillance, Epidemiology and End Results Breast Implant Surveillance Study conducted in San Francisco–Oakland, in Seattle–Puget Sound, and in Iowa. This population-based, retrospective cohort included women younger than 65 years when diagnosed with early or unstaged first primary breast cancer between 1983 and 1989, treated with mastectomy. The women were followed for a median of 12.4 years (n = 4968). Breast implant usage was validated by medical record review. Cox proportional hazards models were used to estimate hazard rate ratios for survival time until death due to breast cancer or other causes for women with and without breast implants, adjusted for relevant patient and tumor characteristics. Twenty percent of cases received postmastectomy breast implants, with silicone gel-filled implants comprising the most common type. Patients with implants were younger and more likely to have in situ disease than patients not receiving implants. Risks of breast cancer mortality (hazard ratio, 0.54; 95% confidence interval, 0.43–0.67) and nonbreast cancer mortality (hazard ratio, 0.59; 95% confidence interval, 0.41–0.85) were lower in patients with implants than in those patients without implants, following adjustment for age and year of diagnosis, race/ethnicity, stage, tumor grade, histology, and radiation therapy. Implant type did not appear to influence long-term survival. In a large, population-representative sample, breast implants following mastectomy do not appear to confer any survival disadvantage following early-stage breast cancer in women younger than 65 years old

Impact of geographic area level on measuring socioeconomic disparities in cancer survival in New South Wales, Australia: A period analysis.

Science.gov (United States)

Stanbury, Julia F; Baade, Peter D; Yu, Yan; Yu, Xue Qin

2016-08-01

Area-based socioeconomic measures are widely used in health research. In theory, the larger the area used the more individual misclassification is introduced, thus biasing the association between such area level measures and health outcomes. In this study, we examined the socioeconomic disparities in cancer survival using two geographic area-based measures to see if the size of the area matters. We used population-based cancer registry data for patients diagnosed with one of 10 major cancers in New South Wales (NSW), Australia during 2004-2008. Patients were assigned index measures of socioeconomic status (SES) based on two area-level units, census Collection District (CD) and Local Government Area (LGA) of their address at diagnosis. Five-year relative survival was estimated using the period approach for patients alive during 2004-2008, for each socioeconomic quintile at each area-level for each cancer. Poisson-regression modelling was used to adjust for socioeconomic quintile, sex, age-group at diagnosis and disease stage at diagnosis. The relative excess risk of death (RER) by socioeconomic quintile derived from this modelling was compared between area-units. We found extensive disagreement in SES classification between CD and LGA levels across all socioeconomic quintiles, particularly for more disadvantaged groups. In general, more disadvantaged patients had significantly lower survival than the least disadvantaged group for both CD and LGA classifications. The socioeconomic survival disparities detected by CD classification were larger than those detected by LGA. Adjusted RER estimates by SES were similar for most cancers when measured at both area levels. We found that classifying patient SES by the widely used Australian geographic unit LGA results in underestimation of survival disparities for several cancers compared to when SES is classified at the geographically smaller CD level. Despite this, our RER of death estimates derived from these survival