The polysurvival model with long-term survivors

Long-term survival models have historically been considered for analyzing time-to-event data with long-term survivors fraction. However, situations in which a fraction (1 - p) of systems is subject to failure from independent competing causes of failure, while the remaining proportion p is cured or has not presented the event of interest during the time period of the study, have not been fully considered in the literature. In order to accommodate such situations, we present in this paper a new long-term survival model. Maximum likelihood estimation procedure is discussed as well as interval estimation and hypothesis tests. A real dataset illustrates the methodology.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

On Causal Mediation Analysis with a Survival Outcome

Suppose that having established a marginal total effect of a point exposure on a time-to-event outcome, an investigator wishes to decompose this effect into its direct and indirect pathways, also know as natural direct and indirect effects, mediated by a variable known to occur after the exposure and prior to the outcome. This paper proposes a theory of estimation of natural direct and indirect effects in two important semiparametric models for a failure time outcome. The underlying survival model for the marginal total effect and thus for the direct and indirect effects, can either be a marginal structural Cox proportional hazards model, or a marginal structural additive hazards model. The proposed theory delivers new estimators for mediation analysis in each of these models, with appealing robustness properties. Specifically, in order to guarantee ignorability with respect to the exposure and mediator variables, the approach, which is multiply robust, allows the investigator to use several flexible working models to adjust for confounding by a large number of pre-exposure variables. Multiple robustness is appealing because it only requires a subset of working models to be correct for consistency; furthermore, the analyst need not know which subset of working models is in fact correct to report valid inferences. Finally, a novel semiparametric sensitivity analysis technique is developed for each of these models, to assess the impact on inference, of a violation of the assumption of ignorability of the mediator.

Mixture Cure Survival Models with Dependent Censoring

A number of authors have studies the mixture survival model to analyze survival data with nonnegligible cure fractions. A key assumption made by these authors is the independence between the survival time and the censoring time. To our knowledge, no one has studies the mixture cure model in the presence of dependent censoring. To account for such dependence, we propose a more general cure model which allows for dependent censoring. In particular, we derive the cure models from the perspective of competing risks and model the dependence between the censoring time and the survival time using a class of Archimedean copula models. Within this framework, we consider the parameter estimation, the cure detection, and the two-sample comparison of latency distribution in the presence of dependent censoring when a proportion of patients is deemed cured. Large sample results using the martingale theory are obtained. We applied the proposed methodologies to the SEER prostate cancer data.

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

Impact of number of vessels disease on outcome of patients with stable coronary artery disease: 5-year follow-up of the medical, angioplasty, and bypass surgery study (MASS)

Objective: To evaluate whether the number of vessels disease has an impact on clinical outcomes as well as on therapeutic results accordingly to medical, percutaneous, or surgery treatment in chronic coronary artery disease. Methods: We evaluated 825 individuals enrolled in MASS study, a randomized study to compare treatment options for single or multivessel coronary artery disease with preserved left ventricular function, prospectively followed during 5 years. The incidence of overall mortality and the composite end-point of death, myocardial infarction, and refractory angina were compared in three groups: single vessel disease (SVD n = 214), two-vessel disease (2VD n = 253) and three-vessel disease (3VD n = 358). The relationship between baseline variables and the composite end-point was assessed using a Cox proportional hazards survival model. Results: Most baseline characteristics were similar among groups, except age (younger in SVD and older in 3VD, p < 0.001), lower incidence of hypertension in SVD (p < 0.0001), and lower levels of total and LDL-cholesterol in 3VD (p = 0.004 and p = 0.005, respectively). There were no statistical differences in composite end-point in 5 years among groups independent of the kind of treatment; however, there was a higher mortality rate in 3VD (p < 0.001). When we stratified our analysis for each treatment option, bypass surgery was associated with a tower number of composite end-point in all groups (SVD p < 0.001, 2VD p = 0.002, 3VD p < 0.001). In multivariate analysis, we found higher mortality risk in 3VD comparing to SVD (p = 0.005, HR 3.14, 95%Cl 1.4-7.0). Conclusion: Three-vessel disease was associated with worse prognosis compared to single-or two-vessel disease in patients with stable coronary disease and preserved ventricular function at 5-year follow-up. In addition, event-free survival rates were higher after bypass surgery, independent of the number of vessels diseased in these subsets of patients. (c) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Cerebral impedance and neurological outcome following a mild or severe hypoxic/ischemic episode in neonatal piglets

Multi-frequency bio-impedance has the potential to identify infants at risk of poor neurodevelopmental outcome following hypoxia by detecting cerebral edema. This study investigated the relationship between the severity of an hypoxic/ischemic episode, neurological outcome following the hypoxia and non-invasively measured cerebral bioelectrical impedance in piglets. One-day-old piglets were anaesthetised and ventilated. Hypoxia was induced by reducing the inspired oxygen concentration to 3-5%. Severe hypoxia was defined as hypoxia resulting in at least 30 min of low amplitude EEG (

Penetrance of marked cognitive impairment in older male carriers of the FMR1 gene premutation.

BACKGROUND: Male carriers of the FMR1 premutation are at risk of developing the fragile X-associated tremor/ataxia syndrome (FXTAS), a newly recognised and largely under-diagnosed late onset neurodegenerative disorder. Patients affected with FXTAS primarily present with cerebellar ataxia and intention tremor. Cognitive decline has also been associated with the premutation, but the lack of data on its penetrance is a growing concern for clinicians who provide genetic counselling. METHODS: The Mattis Dementia Rating Scale (MDRS) was administered in a double blind fashion to 74 men aged 50 years or more recruited from fragile X families (35 premutation carriers and 39 intrafamilial controls) regardless of their clinical manifestation. Based on previous publications, marked cognitive impairment was defined by a score <or=123 on the MDRS. RESULTS: Both logistic and survival models confirmed that in addition to age and education level, premutation size plays a significant (p<0.01 and p<0.03 for logistic and survival model, respectively) role in cognitive impairment. The estimated penetrance of marked cognitive impairment in our sample (adjusted for the mean age 63.4 years and mean education level 9.7 years) for midsize/large (70-200 CGG) and small (55-69 CGG) premutation alleles was 33.3% (relative risk (RR) 6.5; p = 0.01) and 5.9% (RR 1.15; p = 0.9) respectively. Penetrance in the control group was 5.1%. CONCLUSIONS: Male carriers of midsize to large premutation alleles had a sixfold increased risk of developing cognitive decline and the risk increases with allele size. In addition, it was observed that cognitive impairment may precede motor symptoms. These data provide guidance for genetic counselling although larger samples are required to refine these estimates.

Primate adult brain cell autotransplantation, a pilot study in asymptomatic MPTP-treated monkeys.

Autologous brain cell transplantation might be useful for repairing lesions and restoring function of the central nervous system. We have demonstrated that adult monkey brain cells, obtained from cortical biopsy and kept in culture for a few weeks, exhibit neural progenitor characteristics that make them useful for brain repair. Following MPTP treatment, primates were dopamine depleted but asymptomatic. Autologous cultured cells were reimplanted into the right caudate nucleus of the donor monkey. Four months after reimplantation, histological analysis by stereology and TH immunolabeling showed that the reimplanted cells successfully survived, bilaterally migrated in the whole striatum, and seemed to have a neuroprotection effect over time. These results may add a new strategy to the field of brain neuroprotection or regeneration and could possibly lead to future clinical applications.

Comparison of clinical and angiographic prognostic risk scores in elderly patients presenting with acute coronary syndrome and referred for percutaneous coronary intervention.

BACKGROUND: Multiple risk prediction models have been validated in all-age patients presenting with acute coronary syndrome (ACS) and treated with percutaneous coronary intervention (PCI); however, they have not been validated specifically in the elderly. METHODS: We calculated the GRACE (Global Registry of Acute Coronary Events) score, the logistic EuroSCORE, the AMIS (Acute Myocardial Infarction Swiss registry) score, and the SYNTAX (Synergy between Percutaneous Coronary Intervention with TAXUS and Cardiac Surgery) score in a consecutive series of 114 patients ≥75 years presenting with ACS and treated with PCI within 24 hours of hospital admission. Patients were stratified according to score tertiles and analysed retrospectively by comparing the lower/mid tertiles as an aggregate group with the higher tertile group. The primary endpoint was 30-day mortality. Secondary endpoints were the composite of death and major adverse cardiovascular events (MACE) at 30 days, and 1-year MACE-free survival. Model discrimination ability was assessed using the area under receiver operating characteristic curve (AUC). RESULTS: Thirty-day mortality was higher in the upper tertile compared with the aggregate lower/mid tertiles according to the logistic EuroSCORE (42% vs 5%; odds ratio [OR] = 14, 95% confidence interval [CI] = 4-48; p <0.001; AUC = 0.79), the GRACE score (40% vs 4%; OR = 17, 95% CI = 4-64; p <0.001; AUC = 0.80), the AMIS score (40% vs 4%; OR = 16, 95% CI = 4-63; p <0.001; AUC = 0.80), and the SYNTAX score (37% vs 5%; OR = 11, 95% CI = 3-37; p <0.001; AUC = 0.77). CONCLUSIONS: In elderly patients presenting with ACS and referred to PCI within 24 hours of admission, the GRACE score, the EuroSCORE, the AMIS score, and the SYNTAX score predicted 30 day mortality. The predictive value of clinical scores was improved by using them in combination.

Destructive weighted Poisson cure rate models

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 a compound weighted Poisson distribution. This model is more flexible in terms of dispersion than the promotion time cure model. Moreover, it gives an interesting and realistic interpretation of the biological mechanism of the occurrence of event of interest as it includes a destructive process of the initial risk factors in a competitive scenario. In other words, what is recorded is only from the undamaged portion of the original number of risk factors.

Escolhas individuais e bem-estar financeiro: três ensaios utilizando microdados

Como orientar políticas públicas de modo a promover o bem-estar da população? Para responder a essa questão a comunidade acadêmica tem enfocado a necessidade de se conhecer melhor as escolhas de consumo individuais. Essa tendência encontra apoio no número, cada vez maior, de bases de microdados disponibilizadas pelos órgãos governamentais e iniciativa privada. O presente trabalho analisa as escolhas dos brasileiros com relação às decisões de financiamento e de oferta de trabalho. O estudo é dividido em três ensaios empíricos distintos. Como a contratação de crédito em mercados informais é motivada pelo déficit de educação financeira é o foco do primeiro ensaio. Considerando mais de 2.000 observações sobre tomadas de crédito, utiliza-se um modelo logit multinomial para estimar a propensão à tomada de crédito na informalidade em contraste com o crédito bancário. Os resultados indicam que a educação financeira pode ter uma relevância maior para a seleção de financiamentos informais do que a restrição de crédito. O segundo ensaio analisa o comportamento de uso de cartões de crédito dentre 1.458 jovens adultos residentes no Brasil, EUA ou França. Um modelo de equações estruturais é utilizado para incorporar relações entre as variáveis latentes. O modelo validado pelo estudo representa uma situação em que o bem-estar financeiro é afetado pela forma com que o indivíduo utiliza o cartão de crédito que, por sua vez, é afetado pelo sentimento de comparação social e pela autoconfiança financeira, essa última sendo impactada também pela educação financeira recebida dos pais. Na comparação entre grupos encontramos evidências de que a comparação social tem um efeito mais forte sobre os jovens brasileiros e que homens são mais dependentes da educação dos pais do que as mulheres. No último ensaio a população pobre brasileira é analisada em relação a um suposto efeito preguiça, que seria causado pela diminuição de oferta de trabalho das famílias que recebem o benefício financeiro do governo via o Programa Bolsa Família. Um modelo de sobrevivência foi usado para comparar a duração no emprego entre beneficiários do programa e um grupo controle, utilizando uma base de dados com mais de 3 milhões de indivíduos. A hipótese de um efeito preguiça é rejeitada. O risco de desligamento do emprego para os beneficiários do Bolsa Família é medido como sendo de 7% a 10% menor, o que é capaz de anular, por exemplo, o maior risco de saída do emprego causado pela presença de filhos pequenos na composição familiar. Uma vez que a rotatividade no emprego dificulta o recebimento de aposentadorias por tempo de contribuição, pode-se concluir que o programa de transferência de renda brasileiro terá um impacto positivo sobre o bem-estar financeiro futuro do trabalhador.

Biomechanical and histologic analysis in aortic endoprosthesis using fibrin glue

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação genética da reconcepção de fêmeas primíparas da raça Nelore

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)