ArticleBiometrics2022
Restricted mean survival time as a function of restriction time.
Article in Biometrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Time-Dependent Comparative Effectiveness of First-Line Treatment for Metastatic Clear Cell Renal Cell Carcinoma: A Restricted Mean Survival Time-Based Network Meta-analysis.Targeted oncology · 2026Pooled it
- Re-evaluating Treatments for Advanced Urothelial Carcinoma Using Restricted Mean Survival Time: A Systematic Review and Network Meta-analysis.European urology open science · 2026Review
- Estimands and Doubly Robust Estimation for Cluster-Randomized Trials With Survival Outcomes.Statistics in medicine · 2026Article
- While-alive regression analysis of composite survival endpoints.Biostatistics (Oxford, England) · 2025Article
- GTsurvival: A Hybrid GCN-Neural Decision Tree Model for Restricted Mean Survival Time Prediction with Complex Censored Data.Entropy (Basel, Switzerland) · 2025Article
- Long-Term Survival in Patients With Low-Risk Cervical Cancer After Simple, Modified, or Radical Hysterectomy.JAMA network open · 2025Article
- Modeling the Restricted Mean Survival Time Using Pseudo-Value Random Forests.Statistics in medicine · 2025Article
- 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
- Article
- Restricted mean survival time regression model with time-dependent covariates.Statistics in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Restricted mean survival time (RMST) is a clinically interpretable and meaningful survival metric that has gained popularity in recent years. Several methods are available for regression modeling of RMST, most based on pseudo-observations or what is essentially an inverse-weighted complete-case analysis. No existing RMST regression method allows for the covariate effects to be expressed as functions over time. This is a considerable limitation, in light of the many hazard regression methods that do accommodate such effects. To address this void in the literature, we propose RMST methods that permit estimating time-varying effects. In particular, we propose an inference framework for directly modeling RMST as a continuous function of L. Large-sample properties are derived. Simulation studies are performed to evaluate the performance of the methods in finite sample sizes. The proposed framework is applied to kidney transplant data obtained from the Scientific Registry of Transplant Recipients.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.