Sensitivity analysis for unmeasured confounding in estimating the difference in restricted mean survival time

The difference in restricted mean survival time has been increasingly used as an alternative measure to the hazard ratio in survival analysis. Although some statistical methods have been developed for estimating the difference in restricted mean survival time adjusted for measured confounders in observational studies, the impact of unmeasured confounding on the estimate has rarely been assessed. We develop a novel sensitivity analysis for the estimate of the difference in restricted mean survival time with respect to unmeasured confounding. After formulating the sensitivity analysis problem as an optimization problem, we explain how to obtain the sensitivity range of the difference in restricted mean survival time efficiently and assess its uncertainty using the percentile bootstrap confidence interval. Analytic results are provided for some important survival settings. Simulation studies show that the proposed methods perform well in various settings. We illustrate the proposed sensitivity analysis method by analyzing data from the German Breast Cancer Study Group study.

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Publication Details

Journal
Statistical Methods in Medical Research
Published
2024-10-07
DOI
https://doi.org/10.1177/09622802241280782
Citations
1
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
1.13

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article

Sensitivity analysis for unmeasured confounding in estimating the difference in restricted mean survival time

Woojoo Lee, Ji Hoon Park, Seungjae Lee
1 citations
Statistical Methods in Medical Research
Health Systems, Economic Evaluations, Quality of Life
1.13
article

Sensitivity analysis for unmeasured confounding in estimating the difference in restricted mean survival time

Woojoo Lee, Ji Hoon Park, Seungjae Lee
article en
1 citations

Abstract

The difference in restricted mean survival time has been increasingly used as an alternative measure to the hazard ratio in survival analysis. Although some statistical methods have been developed for estimating the difference in restricted mean survival time adjusted for measured confounders in observational studies, the impact of unmeasured confounding on the estimate has rarely been assessed. We develop a novel sensitivity analysis for the estimate of the difference in restricted mean survival time with respect to unmeasured confounding. After formulating the sensitivity analysis problem as an optimization problem, we explain how to obtain the sensitivity range of the difference in restricted mean survival time efficiently and assess its uncertainty using the percentile bootstrap confidence interval. Analytic results are provided for some important survival settings. Simulation studies show that the proposed methods perform well in various settings. We illustrate the proposed sensitivity analysis method by analyzing data from the German Breast Cancer Study Group study.

Statistical Methods in Medical ResearchVol. 33(11-12)
Seoul National University (KR), Seoul National University Bundang Hospital (KR)
National Research Foundation of Korea
Climate action
Openalex Percentile: Top 11%
Health Systems, Economic Evaluations, Quality of Life
1.13
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