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Bayesian transformation models for multivariate survival data

Filho, Mário de Castro Andrade; Chen, Ming-Hui; Ibrahim, Joseph G.; Klein, John P.
Fonte: John Wiley and Sons; Malden Publicador: John Wiley and Sons; Malden
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
58.544463%
In this paper, we propose a general class of Gamma frailty transformation models for multivariate survival data. The transformation class includes the commonly used proportional hazards and proportional odds models. The proposed class also includes a family of cure rate models. Under an improper prior for the parameters, we establish propriety of the posterior distribution. A novel Gibbs sampling algorithm is developed for sampling from the observed data posterior distribution. A simulation study is conducted to examine the properties of the proposed methodology. An application to a data set from a cord blood transplantation study is also reported.; CNPq; U.S. National Institutes of Health; Center for International Blood and Marrow Transplant Research; US National Cancer Institute; National Heart, Lung, and Blood Institute; National Institute of Allergy and Infectious Diseases; National Institute of Allergy and Infectious Diseases

Tests of proportional hazards and proportional odds models for grouped survival data

Colosimo, E. A.; Chalita, LVAS; Demetrio, CGB
Fonte: International Biometric Soc Publicador: International Biometric Soc
Tipo: Artigo de Revista Científica Formato: 1233-1240
Português
Relevância na Pesquisa
58.544463%
In this paper, we derive score test statistics to discriminate between proportional hazards and proportional odds models for grouped survival data. These models are embedded within a power family transformation in order to obtain the score tests. In simple cases, some small-sample results are obtained for the score statistics using Monte Carlo simulations. Score statistics have distributions well approximated by the chi-squared distribution. Real examples illustrate the proposed tests.

Incorporating Validation Subsets into Discrete Proportional Hazards Models for Mismeasured Outcomes

Magaret, Amalia S.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 20/11/2008 Português
Relevância na Pesquisa
58.315986%
Standard proportional hazards methods are inappropriate for mismeasured outcomes. Previous work has shown that outcome mismeasurement can bias estimation of hazard ratios for covariates. We previously developed an Adjusted Proportional Hazards method that can produce accurate hazard ratio estimates when outcome measurement is either non-sensitive or non-specific. That method requires that mismeasurement rates (the sensitivity and specificity of the diagnostic test) are known. Here, we develop an approach to handle unknown mismeasurement rates. We consider the case where the true failure status is known for a subset of subjects (the validation set) until the time of observed failure or censoring. Five methods of handling these mismeasured outcomes are described and compared. The first uses only subjects on whom complete data are available (validation subset) while the second uses only mismeasured outcomes (naive method). Three other methods include available data from both validated and non-validated subjects. Through simulation, we show that inclusion of the non-validated subjects can improve efficiency relative to use of the complete case data only; and that inclusion of some true outcomes (the validation subset) can reduce bias relative to use of mismeasured outcomes only. We also compare the performance of the validation methods proposed using an example dataset.

PROPORTIONAL HAZARDS MODELS WITH CONTINUOUS MARKS

Sun, Yanqing; Gilbert, Peter B.; McKeague, Ian W.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 01/02/2009 Português
Relevância na Pesquisa
58.535015%
For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541–554]. This article studies an extension of this approach to allow a continuum of competing risks, in which the cause of failure is replaced by a continuous mark only observed at the failure time. We develop inference for the proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazard depends nonparametrically on both time and mark. This work is motivated by the need to assess HIV vaccine efficacy, while taking into account the genetic divergence of infecting HIV viruses in trial participants from the HIV strain that is contained in the vaccine, and adjusting for covariate effects. Mark-specific vaccine efficacy is expressed in terms of one of the regression functions in the mark-specific proportional hazards model. The new approach is evaluated in simulations and applied to the first HIV vaccine efficacy trial.

Causal interactions in the proportional hazards model

VanderWeele, Tyler J.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /09/2011 Português
Relevância na Pesquisa
58.49172%
The paper relates estimation and testing for additive interaction in proportional hazards models to causal interactions within the counterfactual framework. A definition of a causal interaction for time-to-event outcomes is given that generalizes existing definitions for dichotomous outcomes. Conditions are given concerning the relative excess risk due to interaction in proportional hazards models that imply the presence of a causal interaction at some point in time. Further results are given that allow for assessing the range of times and baseline survival probabilities for which parameter estimates indicate that a causal interaction is present, and for deriving lower bounds on the prevalence of such causal interactions. An interesting feature of the time-to-event setting is that causal interactions can disappear as time progresses i.e. whether a causal interaction is present depends on the follow-up time. The results are illustrated by hypothetical and data analysis examples.

Pseudo-partial likelihood for proportional hazards models with biased-sampling data

TSAI, WEI YANN
Fonte: Oxford University Press Publicador: Oxford University Press
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
68.58377%
We obtain a pseudo-partial likelihood for proportional hazards models with biased-sampling data by embedding the biased-sampling data into left-truncated data. The log pseudo-partial likelihood of the biased-sampling data is the expectation of the log partial likelihood of the left-truncated data conditioned on the observed data. In addition, asymptotic properties of the estimator that maximize the pseudo-partial likelihood are derived. Applications to length-biased data, biased samples with right censoring and proportional hazards models with missing covariates are discussed.

Global Partial Likelihood for Nonparametric Proportional Hazards Models

Chen, Kani; Guo, Shaojun; Sun, Liuquan; Wang, Jane-Ling
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
58.315986%
As an alternative to the local partial likelihood method of Tibshirani and Hastie and Fan, Gijbels, and King, a global partial likelihood method is proposed to estimate the covariate effect in a nonparametric proportional hazards model, λ(t|x) = exp{ψ(x)}λ0(t). The estimator, ψ̂(x), reduces to the Cox partial likelihood estimator if the covariate is discrete. The estimator is shown to be consistent and semiparametrically efficient for linear functionals of ψ(x). Moreover, Breslow-type estimation of the cumulative baseline hazard function, using the proposed estimator ψ̂(x), is proved to be efficient. The asymptotic bias and variance are derived under regularity conditions. Computation of the estimator involves an iterative but simple algorithm. Extensive simulation studies provide evidence supporting the theory. The method is illustrated with the Stanford heart transplant data set. The proposed global approach is also extended to a partially linear proportional hazards model and found to provide efficient estimation of the slope parameter. This article has the supplementary materials online.

A simulation study of finite-sample properties of marginal structural Cox proportional hazards models

Westreich, Daniel; Cole, Stephen R.; Schisterman, Enrique F.; Platt, Robert W.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
68.64042%
Motivated by a previously published study of HIV treatment, we simulated data subject to time-varying confounding affected by prior treatment to examine some finite-sample properties of marginal structural Cox proportional hazards models. We compared (a) unadjusted, (b) regression-adjusted, (c) unstabilized and (d) stabilized marginal structural (inverse probability-of-treatment [IPT] weighted) model estimators of effect in terms of bias, standard error, root mean squared error (MSE) and 95% confidence limit coverage over a range of research scenarios, including relatively small sample sizes and ten study assessments. In the base-case scenario resembling the motivating example, where the true hazard ratio was 0.5, both IPT-weighted analyses were unbiased while crude and adjusted analyses showed substantial bias towards and across the null. Stabilized IPT-weighted analyses remained unbiased across a range of scenarios, including relatively small sample size; however, the standard error was generally smaller in crude and adjusted models. In many cases, unstabilized weighted analysis showed a substantial increase in standard error compared to other approaches. Root MSE was smallest in the IPT-weighted analyses for the base-case scenario. In situations where time-varying confounding affected by prior treatment was absent...

Parameter orthogonality in mixed regression models for survival data

Hutton, J.; Solomon, P.
Fonte: Royal Statistical Society Publicador: Royal Statistical Society
Tipo: Artigo de Revista Científica
Publicado em //1997 Português
Relevância na Pesquisa
69.006816%
The implications of parameter orthogonality for the robustness of survival regression models are considered. The question of which of the proportional hazards or the accelerated life families of models would be more appropriate for analysis is usually ignored, and the proportional hazards family is applied, particularly in medicine, for convenience. Accelerated life models have conventionally been used in reliability applications. We propose a one-parameter family mixture survival model which includes both the accelerated life and the proportional hazards models. By orthogonalizing relative to the mixture parameter, we can show that, for small effects of the covariates, the regression parameters under the alternative families agree to within a constant. This recovers a known misspecification result. We use notions of parameter orthogonality to explore robustness to other types of misspecification including misspecified base-line hazards. The results hold in the presence of censoring. We also study the important question of when proportionality matters.; J. L. Hutton and P. J. Solomon

Childhood Socioeconomic Position, Gender, Adult Body Mass Index, and Incidence of Type 2 Diabetes Mellitus Over 34 Years in the Alameda County Study

Maty, S.; Lynch, J.; Raghunathan, T.; Kaplan, G.
Fonte: Amer Public Health Assoc Inc Publicador: Amer Public Health Assoc Inc
Tipo: Artigo de Revista Científica
Publicado em //2008 Português
Relevância na Pesquisa
68.1358%
Objectives. We examined the association between childhood socioeconomic position and incidence of type 2 diabetes and the effects of gender and adult body mass index (BMI). Methods. We studied 5913 participants in the Alameda County Study from 1965 to 1999 who were diabetes free at baseline (1965). Cox proportional hazards models estimated diabetes risk associated with childhood socioeconomic position and combined childhood socioeconomic position–adult BMI categories in pooled and gender-stratified samples. Demographic confounders and potential pathway components (physical inactivity, smoking, alcohol consumption, hypertension, depression, health care access) were included as covariates. Results. Low childhood socioeconomic position was associated with excess diabetes risk, especially among women. Race and body composition accounted for some of this excess risk. The association between childhood socioeconomic position and diabetes incidence differed by adult BMI category in the pooled and women-only groups. Adjustment for race and behaviors attenuated the risk attributable to low childhood socioeconomic position among the obese group only. Conclusions. Childhood socioeconomic position was a robust predictor of incident diabetes, especially among women. A cumulative risk effect was observed for both childhood socioeconomic position and adult BMI...

Survival of Australian women with invasive epithelial ovarian cancer: a population-based study

Anuradha, S.; Webb, P.M.; Blomfield, P.; Brand, A.H.; Friedlander, M.; Leung, Y.; Obermair, A.; Oehler, M.K.; Quinn, M.; Steer, C.; Jordan, S.J.
Fonte: MJA Group Australia Publicador: MJA Group Australia
Tipo: Artigo de Revista Científica
Publicado em //2014 Português
Relevância na Pesquisa
68.1358%
OBJECTIVE: To describe survival patterns in a nationally complete cohort of Australian women with epithelial ovarian cancer, by sociodemographic and clinical factors. DESIGN, SETTING AND PARTICIPANTS: All 1192 women diagnosed with invasive epithelial ovarian cancer in 2005 were identified through state-based cancer registries. We obtained detailed information from their medical records in 2009 and updated survival data in 2012. MAIN OUTCOME MEASURES: Crude 3-year, 5-year and 7-year survival rates; 3-year and 5-year conditional survival; and hazard ratios (HRs) for the association of participant and cancer characteristics with survival, from multivariable Cox proportional hazards models. RESULTS: Overall crude 5-year survival was 35% (95% CI, 33%-38%). Conditional survival increased moderately for women who lived beyond a year from diagnosis, although for women alive 2 years after diagnosis, the probability of surviving a further 5 years was still only 53% (95% CI, 49%-57%). Increasing age and disease stage were most strongly associated with poor survival. After adjusting for these, survival was significantly worse for women with carcinosarcomas (HRadj, 2.1 [95% CI, 1.3-3.2]), clear cell (HRadj, 1.7 [95% CI, 1.2-2.3]) and mucinous (HRadj...

Using Cox's proportional hazard models to implement optimal strategies: An example from behavioural ecology

Tenhumberg, B.; Keller, M.; Possingham, H.
Fonte: Pergamon-Elsevier Science Ltd Publicador: Pergamon-Elsevier Science Ltd
Tipo: Artigo de Revista Científica
Publicado em //2001 Português
Relevância na Pesquisa
78.395767%
Simple behavioural rules, or “rules of thumb”, which lead to behaviour that closely approximates an optimal strategy, have generated a lot of recent interest in the field of foraging behaviour. In this paper, we derive rules of thumb from a stochastic simulation model in which the foragers behave optimally. We use a particular biological system: the patch leaving behaviour of a parasitoid. We simulate parasitoids whose patch leaving behaviour is determined by a stochastic dynamic programming (SDP) model, while allowing parasitoids to make mistakes in their estimation of host density when arriving in a patch. We use Cox's proportional hazards models to obtain statistical rules of thumb from the simulated behaviour. This represents the first use of a proportional hazard approximation to generate rules of thumb from a complex optimal strategy.; http://www.elsevier.com/wps/find/journaldescription.cws_home/623/description#description

Lower age at menarche affects survival in older Australian women: results from the Australian Longitudinal Study of Ageing

Giles, L.; Glonek, G.; Moore, V.; Davies, M.; Luszcz, M.
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em //2010 Português
Relevância na Pesquisa
68.1358%
Background: While menarche indicates the beginning of a woman's reproductive life, relatively little is known about the association between age at menarche and subsequent morbidity and mortality. We aimed to examine the effect of lower age at menarche on all-cause mortality in older Australian women over 15 years of follow-up. Methods: Data were drawn from the Australian Longitudinal Study of Ageing (n = 1,031 women aged 65-103 years). We estimated the hazard ratio (HR) associated with lower age at menarche using Cox proportional hazards models, and adjusted for a broad range of reproductive, demographic, health and lifestyle covariates. Results: During the follow-up period, 673 women (65%) died (average 7.3 years (SD 4.1) of follow-up for decedents). Women with menses onset < 12 years of age (10.7%; n = 106) had an increased hazard of death over the follow-up period (adjusted HR 1.28; 95%CI 0.99-1.65) compared with women who began menstruating aged ≥ 12 years (89.3%; n = 883). However, when age at menarche was considered as a continuous variable, the adjusted HRs associated with the linear and quadratic terms for age at menarche were not statistically significant at a 5% level of significance (linear HR 0.76; 95%CI 0.56 - 1.04; quadratic HR 1.01; 95%CI 1.00-1.02). Conclusion: Women with lower age at menarche may have reduced survival into old age. These results lend support to the known associations between earlier menarche and risk of metabolic disease in early adulthood. Strategies to minimise earlier menarche...

Optimal and Robust Designs of Step-stress Accelerated Life Testing Experiments for Proportional Hazards Models

Huang, Wan-yi
Fonte: Brock University Publicador: Brock University
Tipo: Electronic Thesis or Dissertation
Português
Relevância na Pesquisa
78.315986%
Accelerated life testing (ALT) is widely used to obtain reliability information about a product within a limited time frame. The Cox s proportional hazards (PH) model is often utilized for reliability prediction. My master thesis research focuses on designing accelerated life testing experiments for reliability estimation. We consider multiple step-stress ALT plans with censoring. The optimal stress levels and times of changing the stress levels are investigated. We discuss the optimal designs under three optimality criteria. They are D-, A- and Q-optimal designs. We note that the classical designs are optimal only if the model assumed is correct. Due to the nature of prediction made from ALT experimental data, attained under the stress levels higher than the normal condition, extrapolation is encountered. In such case, the assumed model cannot be tested. Therefore, for possible imprecision in the assumed PH model, the method of construction for robust designs is also explored.

Sobrevivência de mulheres com câncer de mama sob a perspectiva dos modelos de riscos competitivos; Survival of women with breast cancer in the perspective of competing risks models

Rosemeire de Olanda Ferraz
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 11/02/2015 Português
Relevância na Pesquisa
68.37154%
O objetivo deste estudo é identificar os fatores associados ao tempo de sobrevida do câncer de mama, como idade, estadiamento e extensão do tumor, utilizando modelos de riscos proporcionais de Cox e de riscos competitivos de Fine-Gray. E também propor um modelo de regressão paramétrico para ajustar o tempo de sobrevida na presença dos riscos competitivos. É um estudo de coorte retrospectivo de base-populacional referente a 524 mulheres diagnosticadas com câncer de mama no período de 1993 a 1995, acompanhadas até 2011, residentes no município de Campinas/SP. Um ponto de corte para a variável contínua da idade foi escolhido utilizando-se modelos de Cox. Nos ajustes de modelos simples e múltiplo de Fine-Gray e de Cox, a idade não foi significativa quando o óbito por câncer de mama foi o evento de interesse. As curvas de sobrevivências estimadas por Kaplan-Meier evidenciaram diferenças expressivas nas probabilidades comparando-se os óbitos por câncer de mama e por riscos competitivos. As curvas de sobrevida por câncer de mama não apresentaram diferenças significativas quando comparadas as categorias de idades, segundo teste de log rank. Os modelos de Fine-Gray e Cox identificaram praticamente as mesmas covariáveis influenciando no tempo de sobrevida para ambos eventos de interesse...

Proportional Hazards Models and Age-Period-Cohort Analysis of Cancer Rates

Rosenberg, Philip S.; Anderson, William F.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 20/05/2010 Português
Relevância na Pesquisa
58.535015%
Age-period-cohort (APC) analysis is widely used in cancer epidemiology to model trends in cancer rates. We develop methods for comparative APC analysis of two independent cause-specific hazard rates assuming that an APC model holds for each one. We construct linear hypothesis tests to determine whether the two hazards are absolutely proportional or proportional after stratification by cohort, period, or age. When a given proportional hazards model appears adequate, we derive simple expressions for the relative hazards using identifiable APC parameters. To demonstrate the utility of these new methods, we analyze cancer incidence rates in the United States in blacks versus whites for selected cancers, using data from the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. The examples illustrate that each type of proportionality may be encountered in practice.

Estimation of Stratified Mark-Specific Proportional Hazards Models with Missing Marks

Sun, Yanqing; Gilbert, Peter B.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /03/2012 Português
Relevância na Pesquisa
58.315986%
An objective of randomized placebo-controlled preventive HIV vaccine efficacy trials is to assess the relationship between the vaccine effect to prevent infection and the genetic distance of the exposing HIV to the HIV strain represented in the vaccine construct. Motivated by this objective, recently a mark-specific proportional hazards model with a continuum of competing risks has been studied, where the genetic distance of the transmitting strain is the continuous `mark' defined and observable only in failures. A high percentage of genetic marks of interest may be missing for a variety of reasons, predominantly due to rapid evolution of HIV sequences after transmission before a blood sample is drawn from which HIV sequences are measured. This research investigates the stratified mark-specific proportional hazards model with missing marks where the baseline functions may vary with strata. We develop two consistent estimation approaches, the first based on the inverse probability weighted complete-case (IPW) technique, and the second based on augmenting the IPW estimator by incorporating auxiliary information predictive of the mark. We investigate the asymptotic properties and finite-sample performance of the two estimators, and show that the augmented IPW estimator...

Proportional hazards models with continuous marks

Sun, Yanqing; Gilbert, Peter B.; McKeague, Ian W.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 03/03/2009 Português
Relevância na Pesquisa
58.535015%
For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541--554]. This article studies an extension of this approach to allow a continuum of competing risks, in which the cause of failure is replaced by a continuous mark only observed at the failure time. We develop inference for the proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazard depends nonparametrically on both time and mark. This work is motivated by the need to assess HIV vaccine efficacy, while taking into account the genetic divergence of infecting HIV viruses in trial participants from the HIV strain that is contained in the vaccine, and adjusting for covariate effects. Mark-specific vaccine efficacy is expressed in terms of one of the regression functions in the mark-specific proportional hazards model. The new approach is evaluated in simulations and applied to the first HIV vaccine efficacy trial.; Comment: Published in at http://dx.doi.org/10.1214/07-AOS554 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

A sensitivity analysis for causal parameters in structural proportional hazards models

Goetghebeur, E.; Loeys, T.
Fonte: Universidade Autônoma de Barcelona Publicador: Universidade Autônoma de Barcelona
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //2003 Português
Relevância na Pesquisa
78.49172%
Deviations from assigned treatment occur often in clinical trials. In such a setting, the traditional intent-to-treat analysis does not measure biological efficacy but rather programmatic effectiveness. For all-or-nothing compliance situation, Loeys and Goetghebeur (2003) recently proposed a Structural Proportional Hazards method. It allows for causal estimation in the complier subpopulation provided the exclusion restriction holds: randomization per se has no effect unless exposure has changed. This assumption is typically made with structural models for noncompliance but questioned when the trial is not blinded. In this paper we extend the structural PH model to allow for an effect of randomization per se. This enables analyzing sensitivity of conclusions to deviations from the exclusion restriction. In a colo-rectal cancer trial we find the causal estimator of the effect of an arterial device implantation to be remarkably insensitive to such deviations.

Survival analysis for recurrent event data:an application to childhood infectious diseases

Kelly, Patrick; Lim, Lynette
Fonte: John Wiley & Sons Inc Publicador: John Wiley & Sons Inc
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
58.44102%
Many extensions of survival models based on the Cox proportional hazards approach have been proposed to handle clustered or multiple event data. Of particular note are five Cox-based models for recurrent event data: Andersen and Gill (AG); Wei, Lin and Weissfeld (WLW); Prentice, Williams and Peterson, total time (PWP-CP) and gap time (PWP-GT); and Lee, Wei and Amato (LWA). Some authors have compared these models by observing differences that arise from fitting the models to real and simulated data. However, no attempt has been made to systematically identify the components of the models that are appropriate for recurrent event data. We propose a systematic way of characterizing such Cox-based models using four key components: risk intervals; baseline hazard; risk set, and correlation adjustment. From the definitions of risk interval and risk set there are conceptually seven such Cox-based models that are permissible, five of which are those previously identified. The two new variant models are termed the 'total time - restricted' (TT-R) and 'gap time - unrestricted' (GT-UR) models. The aim of the paper is to determine which models are appropriate for recurrent event data using the key components. The models are fitted to simulated data sets and to a data set of childhood recurrent infectious diseases. The LWA model is not appropriate for recurrent event data because it allows a subject to be at risk several times for the same event. The WLW model overestimates treatment effect and is not recommended. We conclude that PWP-GT and TT-R are useful models for analysing recurrent event data...