A Bayesian Analysis in the Presence of Covariates for Multivariate Survival Data: An example of Application

In this paper, we introduce a Bayesian analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different ""frailties"" or latent variables are considered to capture the correlation among the survival times for the same individual. We assume Weibull or generalized Gamma distributions considering right censored lifetime data. We develop the Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods.

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.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

On the unification of long-term survival models

In this paper we extend the long-term survival model proposed by Chen et al. [Chen, M.-H., Ibrahim, J.G., Sinha, D., 1999. A new Bayesian model for survival data with a surviving fraction. journal of the American Statistical Association 94, 909-919] via the generating function of a real sequence introduced by Feller [Feller, W., 1968. An Introduction to Probability Theory and its Applications, third ed., vol. 1, Wiley, New York]. A direct consequence of this new formulation is the unification of the long-term survival models proposed by Berkson and Gage [Berkson, J., Gage, R.P., 1952. Survival cure for cancer patients following treatment. journal of the American Statistical Association 47, 501-515] and Chen et al. (see citation above). Also, we show that the long-term survival function formulated in this paper satisfies the proportional hazards property if, and only if, the number of competing causes related to the occurrence of an event of interest follows a Poisson distribution. Furthermore, a more flexible model than the one proposed by Yin and Ibrahim [Yin, G., Ibrahim, J.G., 2005. Cure rate models: A unified approach. The Canadian journal of Statistics 33, 559-570] is introduced and, motivated by Feller`s results, a very useful competing index is defined. (c) 2008 Elsevier B.V. All rights reserved.

Celecoxib prevents tumor growth in an animal model by a COX-2 independent mechanism

Nonsteroidal antiinflammatory drugs (NSAIDs) have been shown to reduce cell growth in several tumors. Among these possible antineoplastic drugs are cyclooxygenase-2 (COX-2)-selective drugs, such as celecoxib, in which antitumoral mechanisms were evaluated in rats bearing Walker-256 (W256) tumor. W256 carcinosarcoma cells were inoculated subcutaneously (10(7) cells/rat) in rats submitted to treatment with celecoxib (25 mg kg(-1)) or vehicle for 14 days. Tumor growth, body-weight gain, and survival data were evaluated. The mechanisms, such as COX-2 expression and activity, oxidative stress, by means of enzymes and lipoperoxidation levels, and apoptosis mediators were also investigated. A reduction in tumor growth and an increased weight gain were observed. Celecoxib provided a higher incidence of survival compared with the control group. Cellular effects are probably COX-2 independent, because neither enzyme expression nor its activity, measured by tumoral PGE(2), showed significant difference between groups. It is probable that this antitumor action is dependent on an apoptotic way, which has been evaluated by the expression of the antiapoptotic protein Bcl-xL, in addition to the cellular changes observed by electronic microscopy. Celecoxib has also a possible involvement with redox homeostasis, because its administration caused significant changes in the activity of oxidative enzymes, such as catalase and superoxide dismutase. These results confirm the antitumor effects of celecoxib in W256 cancer model, contributing to elucidating its antitumoral mechanism and corroborating scientific literature about its effect on other types of cancer.

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.

Deviance residuals in generalised log-gamma regression models with censored observations

In this article, we compare three residuals based on the deviance component in generalised log-gamma regression models with censored observations. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. For all cases studied, the empirical distributions of the proposed residuals are in general symmetric around zero, but only a martingale-type residual presented negligible kurtosis for the majority of the cases studied. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for the martingale-type residual in generalised log-gamma regression models with censored data. A lifetime data set is analysed under log-gamma regression models and a model checking based on the martingale-type residual is performed.

COM-Poisson cure rate survival models and an application to a cutaneous melanoma data

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow the Conway-Maxwell Poisson distribution. This model includes as special cases some of the well-known cure rate models discussed in the literature. Next, we discuss the maximum likelihood estimation of the parameters of this cure rate survival model. Finally, we illustrate the usefulness of this model by applying it to a real cutaneous melanoma data. (C) 2009 Elsevier B.V. All rights reserved.

Density and survival rate of Culex quinquefasciatus at Parque Ecologico do Tiete, Sao Paulo, Brazil

Parity rate, gonotrophic cycle length, and density of a Culex quinquefasciatus female population was estimated at the Parque Ecologico do Tiete (PET), Sao Paulo, Brazil. Adult Cx. quinquefasciatus females were collected from vegetation along the edges of a polluted drainage canal with the use of a battery-powered backpack aspirator from September to November 2005 and from February to April 2006. We examined 255 Cx. quinquefasciatus ovaries to establish the parity rate of 0.22 and determined the gonotrophic cycle length under laboratory conditions to be 3 and 4 days. From these data, we calculated the Cx. quinquefasciatus survival rate to be 0.60 and 0.68 per day. Density of the Cx. quinquefasciatus female (5.71 females per m(2)) was estimated based on a population size of 28,810 individuals divided by the sampled area of 5,040 m(2). Results of all experiments indicate medium survivorship and high density of the Cx. quinquefasciatus female population. This species is epidemiologically relevant in the PET area and should be a target of the vector control program of Sao Paulo municipality.

Do individuals in better condition survive for longer? Field survival estimates according to male alternative reproductive tactics and sex

There is a gap in terms of the supposed survival differences recorded in the field according to individual condition. This is partly due to our inability to assess survival in the wild. Here we applied modern statistical techniques to field-gathered data in two damselfly species whose males practice alternative reproductive tactics (ARTs) and whose indicators of condition in both sexes are known. In Paraphlebia zoe, there are two ART: a larger black-winged (BW) male which defends mating territories and a smaller hyaline-winged (HW) male that usually acts as a satellite. In this species, condition in both morphs is correlated with body size. In Calopteryx haemorrhoidalis, males follow tactics according to their condition with males in better condition practicing a territorial ART. In addition, in this species, condition correlates positively with wing pigmentation in both sexes. Our prediction for both species was that males practicing the territorial tactic will survive less longer than males using a nonterritorial tactic, and larger or more pigmented animals will survive for longer. In P. zoe, BW males survived less than females but did not differ from HW males, and not necessarily larger individuals survived for longer. In fact, size affected survival but only when group identity was analysed, showing a positive relationship in females and a slightly negative relationship in both male morphs. For C. haemorrhoidalis, survival was larger for more pigmented males and females, but size was not a good survival predictor. Our results partially confirm assumptions based on the maintenance of ARTs. Our results also indicate that female pigmentation, correlates with a fitness component - survival - as proposed by recent sexual selection ideas applied to females.

Immobilized Kidney 28-kDa Endostatin- Related (KES28kDa) Fragment Promotes Endothelial Cell Survival

Background/Objective: Renal ischemia-hypoxia is a leading cause of acute kidney injury (AKI). Ischemia causes extracellular matrix breakdown of the tubular basement membrane. Endostatin (ES) is the C-terminal fragment of collagen XVIII generated by proteolytic cleavage. Recent studies have demonstrated that ES expression is upregulated in ischemic kidneys. The present study aimed to characterize ES from ischemic kidneys. Methods: Ischemic renal failure was induced via 45 min of occlusion of the left renal artery and vein. After the ischemic period, blood was collected. Kidneys were harvested and used for immunohistochemical testing and protein extraction. Three-step purification was used. Soluble and immobilized purified ES were tested in cell viability and adhesion assays. Results: The soluble KES28kDa inhibited endothelial cell proliferation: 25 versus 12.5 mu g (p < 0.05); 12.5 versus 3.15 mu g (p < 0.05). Immobilization of KES28kDa supports endothelial cell survival over the control p = 0.021). Human umbilical vein endothelial cells plated on immobilized KES28kDa showed an increase in membrane ruffles and stress fibers. Conclusion: These data demonstrate the local synthesis of a 28-kDa ES-related fragment following AKI and suggest its role in endothelium survival. Copyright (C) 2010 S. Karger AG, Basel

Corneal graft survival after therapeutic keratoplasty for Acanthamoeba keratitis

Purpose: To describe corneal graft survival and visual outcome after therapeutic penetrating keratoplasty in patients with Acanthamoeba keratitis (AK) that is unresponsive to clinical treatment. Methods: Retrospective study. Thirty-two patients with AK who underwent therapeutic penetrating keratoplasty (tPK) from August 1996 to August 2005 were included. Data relating to clinical features, visual acuity, surgical technique, graft survival and complications were collected. Graft survival was evaluated by the Kaplan-Meier method and comparisons were performed using the Log-rank test. Results: Most patients (62.5%) were female. Mean age [+/- standard deviation (SD)] was 35 (+/- 13) years (range 15-68 years). All patients were contact lens wearers. Eighteen patients (56%) presented paralytic mydriasis and glaucoma during the treatment. Thirteen patients (40%) developed glaucoma after surgery; eight of them (61%) required a second PK because of graft failure. Of the 32 keratoplasty eyes, 56.2% presented graft failure at any follow-up point. Forty-five per cent of graft failures occurred before the 12 month follow-up, so 55% remained clear in the first year after surgery. Twelve patients underwent a second PK; seven of them failed and 45% were clear at 1 year. Two patients presented graft recurrence of amoebic infection. There was no significant difference in graft survival when eyes with or without mydriasis were compared (P = 0.40). Eyes with glaucoma presented a significantly shorter graft survival (P = 0.01). Conclusion: Penetrating keratoplasty is a treatment option for eyes that are unresponsive to clinical treatment infections. However, graft survival is poor; postoperative glaucoma is frequent and is associated with shorter graft survival.

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.

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.