Lifetime Data Analysis最新文献_第8页

Integrative analysis of high-dimensional RCT and RWD subject to censoring and hidden confounding. 高维RCT与RWD的综合分析。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-04-29 DOI: 10.1007/s10985-025-09654-1

Xin Ye, Shu Yang, Xiaofei Wang, Yanyan Liu

{"title":"Integrative analysis of high-dimensional RCT and RWD subject to censoring and hidden confounding.","authors":"Xin Ye, Shu Yang, Xiaofei Wang, Yanyan Liu","doi":"10.1007/s10985-025-09654-1","DOIUrl":"10.1007/s10985-025-09654-1","url":null,"abstract":"In this study, we focus on estimating the heterogeneous treatment effect (HTE) for survival outcome. The outcome is subject to censoring and the number of covariates is high-dimensional. We utilize data from both the randomized controlled trial (RCT), considered as the gold standard, and real-world data (RWD), possibly affected by hidden confounding factors. To achieve a more efficient HTE estimate, such integrative analysis requires great insight into the data generation mechanism, particularly the accurate characterization of unmeasured confounding effects/bias. With this aim, we propose a penalized-regression-based integrative approach that allows for the simultaneous estimation of parameters, selection of variables, and identification of the existence of unmeasured confounding effects. The consistency, asymptotic normality, and efficiency gains are rigorously established for the proposed estimate. Finally, we apply the proposed method to estimate the HTE of lobar/sublobar resection on the survival of lung cancer patients. The RCT is a multicenter non-inferiority randomized phase 3 trial, and the RWD comes from a clinical oncology cancer registry in the United States. The analysis reveals that the unmeasured confounding exists and the integrative approach does enhance the efficiency for the HTE estimation.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":" ","pages":"473-497"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12317910/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144003384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating network structures in recurrent event data with discrete observation times. 研究具有离散观测时间的循环事件数据中的网络结构。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-05-23 DOI: 10.1007/s10985-025-09656-z

Yufeng Xia, Yangkuo Li, Xiaobing Zhao, Xuan Xu

引用次数: 0

Regression analysis of a graphical proportional hazards model for informatively left-truncated current status data. 信息左截断当前状态数据的图形比例风险模型的回归分析。

IF 1 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-05-10 DOI: 10.1007/s10985-025-09655-0

Mengyue Zhang, Shishu Zhao, Shuying Wang, Xiaolin Xu

{"title":"Regression analysis of a graphical proportional hazards model for informatively left-truncated current status data.","authors":"Mengyue Zhang, Shishu Zhao, Shuying Wang, Xiaolin Xu","doi":"10.1007/s10985-025-09655-0","DOIUrl":"10.1007/s10985-025-09655-0","url":null,"abstract":"In survival analysis, researchers commonly focus on variable selection issues in real-world data, particularly when complex network structures exist among covariates. Additionally, due to factors such as data collection costs and delayed entry, real-world data often exhibit censoring and truncation phenomena.This paper addresses left-truncated current status data by employing a copula-based approach to model the relationship between censoring time and failure time. Based on this, we investigate the problem of variable selection in the context of complex network structures among covariates. To this end, we integrate Markov Random Field (MRF) with the Proportional Hazards (PH) model, and extend the latter to more flexibly characterize the correlation structure among covariates. For solving the constructed model, we propose a penalized optimization method and utilize spline functions to estimate the baseline hazard function. Through numerical simulation experiments and case studies of clinical trial data, we comprehensively evaluate the effectiveness and performance of the proposed model and its parameter inference strategy. This evaluation not only demonstrates the robustness of the proposed model in handling complex disease data but also further verifies the high precision and reliability of the parameter estimation method.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":" ","pages":"498-542"},"PeriodicalIF":1.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian bivariate cure rate models using Gaussian copulas. 基于高斯copuls的贝叶斯二元治愈率模型。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-06-25 DOI: 10.1007/s10985-025-09660-3

Seoyoon Cho, Matthew A Psioda, Joseph G Ibrahim

{"title":"Bayesian bivariate cure rate models using Gaussian copulas.","authors":"Seoyoon Cho, Matthew A Psioda, Joseph G Ibrahim","doi":"10.1007/s10985-025-09660-3","DOIUrl":"10.1007/s10985-025-09660-3","url":null,"abstract":"We propose a joint model for multiple time-to-event outcomes where the outcomes have a cure structure. When a subset of a population is not susceptible to an event of interest, traditional survival models cannot accommodate this type of phenomenon. For example, for patients with melanoma, certain modern treatment options can reduce the mortality and relapse rates. Traditional survival models assume the entire population is at risk for the event of interest, i.e., has a non-zero hazard at all times. However, cure rate models allow a portion of the population to be risk-free of the event of interest. Our proposed model uses a novel truncated Gaussian copula to jointly model bivariate time-to-event outcomes of this type. In oncology studies, multiple time-to-event outcomes (e.g., overall survival and relapse-free or progression-free survival) are typically of interest. Therefore, multivariate methods to analyze time-to-event outcomes with a cure structure are potentially of great utility. We formulate a joint model directly on the time-to-event outcomes (i.e., unconditional on whether an individual is cured or not). Dependency between the time-to-event outcomes is modeled via the correlation matrix of the truncated Gaussian copula. A Markov Chain Monte Carlo procedure is proposed for model fitting. Simulation studies and a real data analysis using a melanoma clinical trial data are presented to illustrate the performance of the method and the proposed model is compared to independent models.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":" ","pages":"658-673"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144486712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation and variable selection for semiparametric transformation models with length-biased survival data. 具有长度偏倚生存数据的半参数转换模型的估计和变量选择。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-07-16 DOI: 10.1007/s10985-025-09661-2

Jih-Chang Yu, Yu-Jen Cheng

{"title":"Estimation and variable selection for semiparametric transformation models with length-biased survival data.","authors":"Jih-Chang Yu, Yu-Jen Cheng","doi":"10.1007/s10985-025-09661-2","DOIUrl":"10.1007/s10985-025-09661-2","url":null,"abstract":"In this study, we investigate estimation and variable selection for semiparametric transformation models with length-biased survival data-a special case of left truncation commonly encountered in the social sciences and cancer prevention trials. To correct for sampling bias, conventional methods such as conditional likelihood, martingale estimating equations, and composite likelihood have been proposed. However, these methods may be less efficient due to their reliance on only partial information from the full likelihood. In contrast, we adopt a full-likelihood approach under the semiparametric transformation model and propose a unified and more efficient nonparametric maximum likelihood estimator (NPMLE). To perform variable selection, we incorporate an adaptive least absolute shrinkage and selection operator (ALASSO) penalty into the full likelihood. We show that when the NPMLE is used as the initial value, the resulting one-step ALASSO estimator-offering a simplified version of the Newton-Raphson method-achieves oracle properties. Theoretical properties of the proposed methods are established using empirical process techniques. The performance of the methods is evaluated through simulation studies and illustrated with a real data application.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":" ","pages":"674-701"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144643970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wild bootstrap for counting process-based statistics: a martingale theory-based approach. 野生自举计数过程为基础的统计：一个基于鞅理论的方法。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-07-28 DOI: 10.1007/s10985-025-09659-w

Marina T Dietrich, Dennis Dobler, Mathisca C M de Gunst

引用次数: 0

Design and analysis of individually randomized group-treatment trials with time to event outcomes. 随机分组治疗试验的设计和分析。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-07-01 Epub Date: 2025-06-03 DOI: 10.1007/s10985-025-09657-y

Sin-Ho Jung

{"title":"Design and analysis of individually randomized group-treatment trials with time to event outcomes.","authors":"Sin-Ho Jung","doi":"10.1007/s10985-025-09657-y","DOIUrl":"10.1007/s10985-025-09657-y","url":null,"abstract":"In a typical individually randomized group-treatment (IRGT) trial, subjects are randomized between a control arm and an experimental arm. While the subjects randomized to the control arm are treated individually, those in the experimental arm are assigned to one of clusters for group treatment. By sharing some common frailties, the outcomes of subjects in the same groups tend to be dependent, whereas those in the control arm are independent. In this paper, we consider IRGT trials with time to event outcomes. We modify the two-sample log-rank test to compare the survival data from TRGT trials, and derive its sample size formula. The proposed sample size formula requires specification of marginal survival distributions for the two arms, bivariate survival distribution and cluster size distribution for the experimental arm, and accrual period or accrual rate together with additional follow-up period. In a sample size calculation, either the cluster sizes are given and the number of clusters is calculated or the number of clusters is given at the time of study open and the required accrual period to determine the cluster sizes is calculated. Simulations and a real data example show that the proposed test statistic controls the type I error rate and the formula provides accurately powered sample sizes. Also proposed are optimal designs minimizing the total sample size or the total cost when the cost per subject is different between two treatment arms.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":" ","pages":"574-594"},"PeriodicalIF":1.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144217400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantile regression under dependent censoring with unknown association. 关联未知的相关审查下的分位数回归。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-04-01 Epub Date: 2025-03-16 DOI: 10.1007/s10985-025-09647-0

Myrthe D'Haen, Ingrid Van Keilegom, Anneleen Verhasselt

{"title":"Quantile regression under dependent censoring with unknown association.","authors":"Myrthe D'Haen, Ingrid Van Keilegom, Anneleen Verhasselt","doi":"10.1007/s10985-025-09647-0","DOIUrl":"10.1007/s10985-025-09647-0","url":null,"abstract":"The study of survival data often requires taking proper care of the censoring mechanism that prohibits complete observation of the data. Under right censoring, only the first occurring event is observed: either the event of interest, or a competing event like withdrawal of a subject from the study. The corresponding identifiability difficulties led many authors to imposing (conditional) independence or a fully known dependence between survival and censoring times, both of which are not always realistic. However, recent results in survival literature showed that parametric copula models allow identification of all model parameters, including the association parameter, under appropriately chosen marginal distributions. The present paper is the first one to apply such models in a quantile regression context, hence benefiting from its well-known advantages in terms of e.g. robustness and richer inference results. The parametric copula is supplemented with a likewise parametric, yet flexible, enriched asymmetric Laplace distribution for the survival times conditional on the covariates. Its asymmetric Laplace basis provides its close connection to quantiles, while the extension with Laguerre orthogonal polynomials ensures sufficient flexibility for increasing polynomial degrees. The distributional flavour of the quantile regression presented, comes with advantages of both theoretical and computational nature. All model parameters are proven to be identifiable, consistent, and asymptotically normal. Finally, performance of the model and of the proposed estimation procedure is assessed through extensive simulation studies as well as an application on liver transplant data.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":" ","pages":"253-299"},"PeriodicalIF":1.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lifetime analysis with monotonic degradation: a boosted first hitting time model based on a homogeneous gamma process. 具有单调退化的寿命分析：一种基于均匀伽马过程的改进的首次撞击时间模型。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-04-01 Epub Date: 2025-04-05 DOI: 10.1007/s10985-025-09648-z

Clara Bertinelli Salucci, Azzeddine Bakdi, Ingrid Kristine Glad, Bo Henry Lindqvist, Erik Vanem, Riccardo De Bin

引用次数: 0

Total time on test-based goodness-of-fit statistics for the reciprocal property in fatigue-life models. 疲劳寿命模型中互反特性的基于试验的拟合优度统计的总时间。

IF 1.5 3区数学

Lifetime Data Analysis Pub Date : 2025-04-01 Epub Date: 2025-04-26 DOI: 10.1007/s10985-025-09653-2

Cecilia Castro, Marta Azevedo, Víctor Leiva, Luís Meira-Machado

{"title":"Total time on test-based goodness-of-fit statistics for the reciprocal property in fatigue-life models.","authors":"Cecilia Castro, Marta Azevedo, Víctor Leiva, Luís Meira-Machado","doi":"10.1007/s10985-025-09653-2","DOIUrl":"10.1007/s10985-025-09653-2","url":null,"abstract":"We propose a new goodness-of-fit procedure designed to verify the reciprocal property that characterizes the fatigue-life or Birnbaum-Saunders (BS) distribution. Under this property, scaling a random variable that takes positive values by its median results in the same distribution as its reciprocal, a feature frequently encountered in reliability and survival studies. Our procedure employs total time on test (TTT) curves to compare the behavior of the observed data and its reciprocal counterpart, capturing both local and global discrepancies through supremum- and area-based statistics. We establish the theoretical validity of these statistics under mild assumptions, showing that they deliver accurate inference for moderate to large samples. Simulation evidence indicates that our TTT-based procedures are sensitive to subtle departures from log-symmetry, particularly when the distribution underlying the data has heavier or lighter tails than the assumed one. Illustrative real data examples further reveal how overlooking deviations from the reciprocal property can distort reliability estimates and predictions of failure times, showing the practical importance of the new goodness-of-fit procedure. Overall, our findings strengthen the BS framework and provide robust tools for model validation and selection when log-symmetric modeling assumptions are in place.","PeriodicalId":49908,"journal":{"name":"Lifetime Data Analysis","volume":"31 2","pages":"422-441"},"PeriodicalIF":1.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0