Doubly valid and doubly sharp sensitivity analysis to unobserved confounding for survival outcomes

2026-09-16

AI Summary

研究针对生存结果中未观察到的混杂因素，提出了一种基于边际敏感性模型的双有效双锐化敏感性分析方法，以估计因果治疗效应。

Abstract

Time-to-event outcomes are central in oncology and rare diseases, where treatment effects are often summarized by differences in survival curves or Restricted Mean Survival Time (RMST). In real-world data, estimating these causal effects relies on the absence of unobserved confounding, an assumption that is rarely satisfied. We develop a sensitivity analysis framework for causal treatment effects with survival outcomes under the Marginal Sensitivity Model (MSM). We introduce doubly valid and doubly sharp (DVDS) bounds for differences in survival functions and RMST, extending recent DVDS results to the time-to-event setting while accounting for informative censoring. In practice, our method yields tighter bounds and improved computational efficiency compared to a previous approach from the literature, on simulated and real data. For tractability, we assume independence between censoring and unobserved confounding, a limit that should be addressed in future works.

Problem

• unobserved confounding
• survival outcomes
• causal treatment effects
• sensitivity analysis
• marginal sensitivity model

Innovation

• Doubly Valid and Doubly Sharp (DVDS) Bounds
• Marginal Sensitivity Model (MSM)
• Survival Outcomes
• Restricted Mean Survival Time (RMST)
• Informative Censoring