Left-censored dementia incidences in estimating cohort effects
AbstractWe estimate the dementia incidence hazard in Germany for the birth cohorts 1900 until 1954 from a simple sample of Germany ’s largest health insurance company. Followed from 2004 to 2012, 36,000 uncensored dementia incidences are observed and further 200,000 right-censored insurants included. From a multiplicative hazard model we find a positive and linear trend in the dementia hazard over the cohorts. The main focus of the study is on 11,000 left-censored persons who have already suffered from the disease in 2004. After including the left-censored observations, the slope of the trend declines markedly due to Sim...
Source: Lifetime Data Analysis - September 11, 2020 Category: Statistics Source Type: research
Measuring the temporal prognostic utility of a baseline risk score
AbstractIn the time-to-event setting, the concordance probability assesses the relative level of agreement between a model-based risk score and the survival time of a patient. While it provides a measure of discrimination over the entire follow-up period of a study, the probability does not provide information on the longitudinal durability of a baseline risk score. It is possible that a baseline risk model is able to segregate short-term from long-term survivors but unable to maintain its discriminatory strength later in the follow-up period. As a consequence, this would motivate clinicians to re-evaluate the risk score l...
Source: Lifetime Data Analysis - July 23, 2020 Category: Statistics Source Type: research
Extensions of the absolute standardized hazard ratio and connections with measures of explained variation and variable importance
AbstractThe absolute standardized hazard ratio (ASHR) is a scale-invariant scalar measure of the strength of association of a vector of covariates with the risk of an event. It is derived from proportional hazards regression. The ASHR is useful for making comparisons among different sets of covariates. Extensions of the ASHR concept and practical considerations regarding its computation are discussed. These include a new method to conduct preliminary checks for collinearity among covariates, a partial ASHR to evaluate the association with event risk of some of the covariates conditioning on others, and the ASHR for interac...
Source: Lifetime Data Analysis - July 22, 2020 Category: Statistics Source Type: research
Statistical analysis of clustered mixed recurrent-event data with application to a cancer survivor study
AbstractIn long-term follow-up studies on recurrent events, the observation patterns may not be consistent over time. During some observation periods, subjects may be monitored continuously so that each event occurence time is known. While during the other observation periods, subjects may be monitored discretely so that only the number of events in each period is known. This results in mixed recurrent-event and panel-count data. In these data, there is dependence among within-subject events. Furthermore, if the data are collected from multiple centers, then there is another level of dependence among within-center subjects...
Source: Lifetime Data Analysis - July 11, 2020 Category: Statistics Source Type: research
Subtleties in the interpretation of hazard contrasts
AbstractThe hazard ratio is one of the most commonly reported measures of treatment effect in randomised trials, yet the source of much misinterpretation. This point was made clear by Hern án (Epidemiology (Cambridge, Mass) 21(1):13–15, 2010) in a commentary, which emphasised that the hazard ratio contrasts populations of treated and untreated individuals who survived a given period of time, populations that will typically fail to be comparable—even in a randomised trial—as a r esult of different pressures or intensities acting on different populations. The commentary has been very influential, but also a source of ...
Source: Lifetime Data Analysis - July 10, 2020 Category: Statistics Source Type: research
Correction to: Nonparametric estimators of survival function under the mixed case interval-censored model with left truncation
The original version of this article unfortunately contains mistakes. It has been corrected with this Correction (Source: Lifetime Data Analysis)
Source: Lifetime Data Analysis - July 8, 2020 Category: Statistics Source Type: research
Generalized mean residual life models for case-cohort and nested case-control studies
AbstractMean residual life (MRL) is the remaining life expectancy of a subject who has survived to a certain time point and can be used as an alternative to hazard function for characterizing the distribution of a time-to-event variable. Inference and application of MRL models have primarily focused on full-cohort studies. In practice, case-cohort and nested case-control designs have been commonly used within large cohorts that have long follow-up and study rare diseases, particularly when studying costly molecular biomarkers. They enable prospective inference as the full-cohort design with significant cost-saving benefits...
Source: Lifetime Data Analysis - June 10, 2020 Category: Statistics Source Type: research
Nonparametric and semiparametric estimators of restricted mean survival time under length-biased sampling
AbstractRestricted mean survival time is often of direct interest in epidemiologic studies involving censored survival time. In this article, we propose the nonparametric and semiparametric estimators of the mean restricted to the preassigned interval with censored length-biased data. Based on the peculiarity of length-biased data, the auxiliary information that truncation time and residual time have the same distribution is taken into account for improving estimation efficiency. For two-sample comparison, we construct two tests which are easy to implement. We also derive the asymptotic properties for the proposed estimato...
Source: Lifetime Data Analysis - April 15, 2020 Category: Statistics Source Type: research
Analysis of the time-varying Cox model for the cause-specific hazard functions with missing causes
AbstractThis paper studies the Cox model with time-varying coefficients for cause-specific hazard functions when the causes of failure are subject to missingness. Inverse probability weighted and augmented inverse probability weighted estimators are investigated. The latter is considered as a two-stage estimator by directly utilizing the inverse probability weighted estimator and through modeling available auxiliary variables to improve efficiency. The asymptotic properties of the two estimators are investigated. Hypothesis testing procedures are developed to test the null hypotheses that the covariate effects are zero and...
Source: Lifetime Data Analysis - April 8, 2020 Category: Statistics Source Type: research
Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data
AbstractInterval-censored data often arise naturally in medical, biological, and demographical studies. As a matter of routine, the Cox proportional hazards regression is employed to fit such censored data. The related work in the framework of additive hazards regression, which is always considered as a promising alternative, remains to be investigated. We propose a sieve maximum likelihood method for estimating regression parameters in the additive hazards regression with case II interval-censored data, which consists of right-, left- and interval-censored observations. We establish the consistency and the asymptotic norm...
Source: Lifetime Data Analysis - March 9, 2020 Category: Statistics Source Type: research
Estimation of treatment effects and model diagnostics with two-way time-varying treatment switching: an application to a head and neck study
AbstractTreatment switching frequently occurs in clinical trials due to ethical reasons. Intent-to-treat analysis without adjusting for switching yields biased and inefficient estimates of the treatment effects. In this paper, we propose a class of semiparametric semi-competing risks transition survival models to accommodate two-way time-varying switching. Theoretical properties of the proposed method are examined. An efficient expectation –maximization algorithm is derived to obtain maximum likelihood estimates and model diagnostic tools. Existing software is used to implement the algorithm. Simulation studies are condu...
Source: Lifetime Data Analysis - March 2, 2020 Category: Statistics Source Type: research
Semiparametric regression and risk prediction with competing risks data under missing cause of failure
AbstractThe cause of failure in cohort studies that involve competing risks is frequently incompletely observed. To address this, several methods have been proposed for the semiparametric proportional cause-specific hazards model under a missing at random assumption. However, these proposals provide inference for the regression coefficients only, and do not consider the infinite dimensional parameters, such as the covariate-specific cumulative incidence function. Nevertheless, the latter quantity is essential for risk prediction in modern medicine. In this paper we propose a unified framework for inference about both the r...
Source: Lifetime Data Analysis - January 24, 2020 Category: Statistics Source Type: research
Nonparametric estimators of survival function under the mixed case interval-censored model with left truncation
AbstractIt is well known that the nonparametric maximum likelihood estimator (NPMLE) can severely underestimate the survival probabilities at early times for left-truncated and interval-censored (LT-IC) data. For arbitrarily truncated and censored data, Pan and Chappel (JAMA Stat Probab Lett 38:49 –57,1998a, Biometrics 54:1053 –1060,1998b) proposed a nonparametric estimator of the survival function, called the iterative Nelson estimator (INE). Their simulation study showed that the INE performed well in overcoming the under-estimation of the survival function from the NPMLE for LT-IC data. In this article, we revisit t...
Source: Lifetime Data Analysis - January 12, 2020 Category: Statistics Source Type: research
Cumulative risk regression in case –cohort studies using pseudo-observations
AbstractCase –cohort studies are useful when information on certain risk factors is difficult or costly to ascertain. Particularly, a case–cohort study may be well suited in situations where several case series are of interest, e.g. in studies with competing risks, because the same sub-cohort may serve as a comparison group for all case series. Previous analyses of this kind of sampled cohort data most often involved estimation of rate ratios based on a Cox regression model. However, with competing risks this method will not provide parameters that directly describe the association between covariates a nd cumulative ri...
Source: Lifetime Data Analysis - January 12, 2020 Category: Statistics Source Type: research
Multiple event times in the presence of informative censoring: modeling and analysis by copulas
AbstractMotivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distrib...
Source: Lifetime Data Analysis - November 14, 2019 Category: Statistics Source Type: research
