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In clinical follow-up studies with a time-to-event end point, the difference in the restricted mean survival time (RMST) is a suitable substitute for the hazard ratio (HR). However, the RMST only measures the survival of patients over a…

Methodology · Statistics 2023-06-27 Zijing Yang , Chengfeng Zhang , Yawen Hou , Zheng Chen

The difference in restricted mean survival time (RMST) is a clinically meaningful measure to quantify treatment effect in randomized controlled trials, especially when the proportional hazards assumption does not hold. Several frequentist…

Restricted mean survival time (RMST) is an intuitive summary statistic for time-to-event random variables, and can be used for measuring treatment effects. Compared to hazard ratio, its estimation procedure is robust against the…

Methodology · Statistics 2023-05-25 Ruizhe Chen , Sanjib Basu , Qian Shi

In clinical or epidemiological follow-up studies, methods based on time scale indicators such as the restricted mean survival time (RMST) have been developed to some extent. Compared with traditional hazard rate indicator system methods,…

Methodology · Statistics 2022-05-26 Chengfeng Zhang , Hongji Wu , Baoyi Huang , Hao Yuan , Yawen Hou , Zheng Chen

The restricted mean survival time (RMST) has become a popular measure to summarize event times in longitudinal studies. Defined as the area under the survival function up to a time horizon $\tau$ > 0, the RMST can be interpreted as the life…

Methodology · Statistics 2024-11-05 Alina Schenk , Vanessa Basten , Matthias Schmid

Covariate adjustment is desired by both practitioners and regulators of randomized clinical trials because it improves precision for estimating treatment effects. However, covariate adjustment presents a particular challenge in…

Methodology · Statistics 2023-07-20 Yunfan Li , Jessica L. Ross , Aaron M. Smith , David P. Miller

Restricted mean survival time (RMST) offers a compelling nonparametric alternative to hazard ratios for right-censored time-to-event data, particularly when the proportional hazards assumption is violated. By capturing the total event-free…

Methodology · Statistics 2025-01-28 Jinghao Sun , Douglas E. Schaubel , Eric J. Tchetgen Tchetgen

The restricted mean survival time (RMST) is a widely used quantity in survival analysis due to its straightforward interpretation. For instance, predicting the time to event based on patient attributes is of great interest when analyzing…

Statistics Theory · Mathematics 2025-03-11 Ariane Cwiling , Vittorio Perduca , Olivier Bouaziz

Investigating the causal relationship between exposure and the time-to-event outcome is an important topic in biomedical research. Previous literature has discussed the potential issues of using the hazard ratio as a marginal causal effect…

Methodology · Statistics 2022-05-05 Zihan Lin , Ai Ni , Bo Lu

The restricted mean survival time (RMST) model has been garnering attention as a way to provide a clinically intuitive measure: the mean survival time. RMST models, which use methods based on pseudo time-to-event values and inverse…

Methodology · Statistics 2024-06-11 Keisuke Hanada , Masahiro Kojima

Restricted mean survival time (RMST) is gaining attention as a measure to quantify the treatment effect on survival outcomes in randomized clinical trials. Several methods to determine sample size based on the RMST-based tests have been…

Methodology · Statistics 2022-12-19 Satoshi Hattori , Hajime Uno

Comparing survival experiences of different groups of data is an important issue in several applied problems. A typical example is where one wishes to investigate treatment effects. Here we propose a new Bayesian approach based on…

Methodology · Statistics 2024-07-17 Alan Riva-Palacio , Fabrizio Leisen , Antonio Lijoi

Restricted mean survival time (RMST) models have gained popularity when analyzing time-to-event outcomes because RMST models offer more straightforward interpretations of treatment effects with fewer assumptions than hazard ratios commonly…

Methodology · Statistics 2023-10-23 Kaiyuan Hua , Xiaofei Wang , Hwanhee Hong

Many medical decisions involve the use of dynamic information collected on individual patients toward predicting likely transitions in their future health status. If accurate predictions are developed, then a prognostic mode can identify…

Methodology · Statistics 2018-02-22 Aasthaa Bansal , Patrick J. Heagerty

In medicine, researchers often seek to infer the effects of a given treatment on patients' outcomes. However, the standard methods for causal survival analysis make simplistic assumptions about the data-generating process and cannot capture…

Machine Learning · Computer Science 2022-10-28 Prayag Chatha , Yixin Wang , Zhenke Wu , Jeffrey Regier

The restricted mean survival time (RMST) is the mean survival time in the study population followed up to a specific time point, and is simply the area under the survival curve up to the specific time point. The difference between two RMSTs…

Methodology · Statistics 2025-09-18 Peter Zhang , Brent Logan , Michael Martens

In large observational studies, the case-cohort design is commonly used to reduce the cost associated with covariate measurement. For survival outcomes, literature has suggested that the restricted mean survival time (RMST) be a more…

Methodology · Statistics 2026-05-08 Andy Ni , Wei-En Lu , Bo Lu

The use of the non-parametric Restricted Mean Survival Time endpoint (RMST) has grown in popularity as trialists look to analyse time-to-event outcomes without the restrictions of the proportional hazards assumption. In this paper, we…

Methodology · Statistics 2023-11-06 Emily Alger , David S. Robertson , Abigail J. Burdon

Background: Effective allocation of limited donor lungs in cystic fibrosis (CF) requires accurate survival predictions, so that high-risk patients may be prioritized for transplantation. In practice, decisions about allocation are made…

Applications · Statistics 2017-06-30 Aasthaa Bansal , Nicole Mayer-Hamblett , Christopher H. Goss , Patrick J. Heagerty

Biomarker-guided designs are increasingly used to evaluate personalized treatments based on patients' biomarker status in Phase II and III clinical trials. With adaptive enrichment, these designs can improve the efficiency of evaluating the…

Methodology · Statistics 2024-06-11 Kaiyuan Hua , Hwanhee Hong , Xiaofei Wang
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