Experimental enhancement of corticosterone levels positively affects subsequent male survival.

Corticosterone is an important hormone of the stress response that regulates physiological processes and modifies animal behavior. While it positively acts on locomotor activity, it may negatively affect reproduction and social activity. This suggests that corticosterone may promote behaviors that increase survival at the cost of reproduction. In this study, we experimentally investigate the link between corticosterone levels and survival in adult common lizards (Lacerta vivipara) by comparing corticosterone-treated with placebo-treated lizards. We experimentally show that corticosterone enhances energy expenditure, daily activity, food intake, and it modifies the behavioral time budget. Enhanced appetite of corticosterone-treated individuals compensated for increased energy expenditure and corticosterone-treated males showed increased survival. This suggests that corticosterone may promote behaviors that reduce stress and it shows that corticosterone per se does not reduce but directly or indirectly increases longer-term survival. This suggests that the production of corticosterone as a response to a stressor may be an adaptive mechanism that even controls survival.

Education, tobacco smoking, alcohol consumption, and IL-2 and IL-6 gene polymorphisms in the survival of head and neck cancer

The association of education, tobacco smoking, alcohol consumption, and interleukin-2 (IL-2 +114 and -384) and -6 (IL-6 -174) DNA polymorphisms with head and neck squamous cell carcinoma (HNSCC) was investigated in a cohort study of 445 subjects. IL-2 and IL-6 genotypes were determined by real-time PCR. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (95%CI) of disease-specific survival according to anatomical sites of the head and neck. Mean age was 56 years and most patients were males (87.6%). Subjects with 5 or more years of schooling had better survival in larynx cancer. Smoking had no effect on HNSCC survival, but alcohol consumption had a statistically significant effect on larynx cancer. IL-2 gene +114 G/T (HR = 0.52; 95%CI = 0.15-1.81) and T/T (HR = 0.22; 95%CI = 0.02-3.19) genotypes were associated with better survival in hypopharynx cancer. IL-2 +114 G/T was a predictor of poor survival in oral cavity/oropharynx cancer and larynx cancer (HR = 1.32; 95%CI = 0.61-2.85). IL-2 -384 G/T was associated with better survival in oral cavity/oropharynx cancer (HR = 0.80; 95%CI = 0.45-1.42) and hypopharynx cancer (HR = 0.68; 95%CI = 0.21-2.20), but an inverse relationship was observed for larynx cancer. IL-6 -174 G/C was associated with better survival in hypopharynx cancer (HR = 0.68; 95%CI = 0.26-1.78) and larynx cancer (HR = 0.93; 95%CI = 0.42-2.07), and C/C reduced mortality in larynx cancer. In general, our results are similar to previous reports on the value of education, smoking, alcohol consumption, and IL-2 and IL-6 genetic polymorphisms for the prognosis of HNSCC, but the risks due to these variables are small and estimates imprecise.

Assessment of a five-year survival on hemodialysis in Brazil: a cohort of 3,082 incident patients

Brazil has the third largest contingent of patients on maintenance hemodialysis (HD) worldwide. However, little is known regarding survival rate and predictors of mortality risk in that population, which are the purposes of this study. A total of 3,082 patients incident on HD, from 2000 to 2004, at 25 dialysis facilities distributed among 7 out of 26 states of Brazil were followed-up until 2009. Patients were 52 ± 16 years-old, 57.8% men, and 20.4%, diabetics. The primary outcome was all causes of mortality. Data were censored at five years of follow-up. The global five-year survival rate was 58.2%. In the Cox proportional model, variables associated with risk of death were: age (hazard ratio - HR = 1.44 per decade, p < 0.0001), diabetes (HR = 1.51, p < 0.0001), serum albumin (HR = 0.76 per g/dL, p = 0.001), creatinine (HR = 0.92 per mg/dL, p < 0.0001), and phosphorus (HR = 1.06 per mg/dL, p = 0.04). The present results show that the mortality rate on HD in this Brazilian cohort was relatively low, but the population is younger and with a lower prevalence of diabetes than the ones reported for developed countries.

‘Modeling and Analysis of Competing Risks Data’

there has been much research on analyzing various forms of competing risks data. Nevertheless, there are several occasions in survival studies, where the existing models and methodologies are inadequate for the analysis competing risks data. ldentifiabilty problem and various types of and censoring induce more complications in the analysis of competing risks data than in classical survival analysis. Parametric models are not adequate for the analysis of competing risks data since the assumptions about the underlying lifetime distributions may not hold well. Motivated by this, in the present study. we develop some new inference procedures, which are completely distribution free for the analysis of competing risks data.

Comparison of survival rates of captive-reared and wild-bred Mauritius kestrels (Falco punctatus) in a re-introduced population

Re-introduction is a technique widely used in the conservation of threatened bird species. With advances in aviculture the use of captive-produced individuals as the release stock is becoming more commonplace, and ideally, survival of captive-produced, released individuals should be no different from their wild-bred counterparts. During the late 1980s the Critically Endangered Mauritius kestrel (Falco punctatus) was successfully re-introduced into the Bambous mountain range, Mauritius, some 30 years after its local extinction. Between 1987 and 2001 the developing population was closely monitored enabling us to construct re-sighting histories for 88 released and 284 wild-bred kestrels. We used age-structured models in the survival analysis software program MARK to determine if an individual's origin influenced its subsequent survival. Our analysis indicated no compelling evidence for reduced survival among juvenile captive-reared and released individuals, relative to their wild-bred counterparts, across the majority of cohorts and only limited evidence of a cohort-specific effect. This study illustrates that despite the lack of a formal experimental approach it is still feasible to conduct an assessment of re-introduction outcomes and techniques.

Bayesian analysis of an inverse Gaussian correlated frailty model

In survival analysis frailty is often used to model heterogeneity between individuals or correlation within clusters. Typically frailty is taken to be a continuous random effect, yielding a continuous mixture distribution for survival times. A Bayesian analysis of a correlated frailty model is discussed in the context of inverse Gaussian frailty. An MCMC approach is adopted and the deviance information criterion is used to compare models. As an illustration of the approach a bivariate data set of corneal graft survival times is analysed. (C) 2006 Elsevier B.V. All rights reserved.

Comparison of survival rates of captive-reared and wild-bred Mauritius kestrels (falco punctatus) in a re-introduced population

Re-introduction is a technique widely used in the conservation of threatened bird species. With advances in aviculture the use of captive-produced individuals as the release stock is becoming more commonplace, and ideally, survival of captive-produced, released individuals should be no different from their wild-bred counterparts. During the late 1980s the Critically Endangered Mauritius kestrel (Falco punctatus) was successfully re-introduced into the Bambous mountain range, Mauritius, some 30 years after its local extinction. Between 1987 and 2001 the developing population was closely monitored enabling us to construct re-sighting histories for 88 released and 284 wild-bred kestrels. We used age-structured models in the survival analysis software program MARK to determine if an individual's origin influenced its subsequent survival. Our analysis indicated no compelling evidence for reduced survival among juvenile captive-reared and released individuals, relative to their wild-bred counterparts, across the majority of cohorts and only limited evidence of a cohort-specific effect. This study illustrates that despite the lack of a formal experimental approach it is still feasible to conduct an assessment of re-introduction outcomes and techniques. (C) 2003 Elsevier Ltd. All rights reserved.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

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

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. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.

A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes

We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, for a given vector of covariates. Approaches based on semiparametric and parametric (exponential and Weibull distributions) methodologies are considered. A simulation study is conducted to evaluate the performance of the proposed estimator and the jackknife resampling method is used to estimate the variance of such estimator. An application to a real data set is also included.