ArticleStatistics in medicine2022
Restricted mean survival time regression model with time-dependent covariates.
Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Early use of albumin may increase the risk of sepsis-associated acute kidney injury in sepsis patients: a target trial emulation.Military Medical Research · 2025Article
- Eight-Year Outcomes of Cardiosphere-Derived Cells in Single Ventricle Congenital Heart Disease.Journal of the American Heart Association · 2024Article
- Time-varying effect in older patients with early-stage breast cancer: a model considering the competing risks based on a time scale.Frontiers in oncology · 2024Article
- Restricted mean survival time regression model with time-dependent covariates.Statistics in medicine · 2022Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
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, the RMST is easier to interpret and does not require the proportional hazard assumption. To date, regression models based on the RMST are indirect or direct models of the RMST and baseline covariates. However, time-dependent covariates are becoming increasingly common in follow-up studies. Based on the inverse probability of censoring weighting (IPCW) method, we developed a regression model of the RMST and time-dependent covariates. Through Monte Carlo simulation, we verified the estimation performance of the regression parameters of the proposed model. Compared with the time-dependent Cox model and the fixed (baseline) covariate RMST model, the time-dependent RMST model has a better prediction ability. Finally, an example of heart transplantation was used to verify the above conclusions.
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