An IPCW Adjusted Win Statistics Approach in Clinical Trials Incorporating Equivalence Margins to Define Ties

Fuente: arXiv
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Autores principales: Cui, Ying, Huang, Bo, Dong, Gaohong, Uozumi, Ryuji, Tian, Lu
Formato: Preprint
Publicado: 2025
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author Cui, Ying
Huang, Bo
Dong, Gaohong
Uozumi, Ryuji
Tian, Lu
author_facet Cui, Ying
Huang, Bo
Dong, Gaohong
Uozumi, Ryuji
Tian, Lu
contents In clinical trials, multiple outcomes of different priorities commonly occur as the patient's response may not be adequately characterized by a single outcome. Win statistics are appealing summary measures for between-group difference at more than one endpoint. When defining the result of pairwise comparisons of a time-to-event endpoint, it is desirable to allow ties to account for incomplete follow-up and not clinically meaningful difference in endpoints of interest. In this paper, we propose a class of win statistics for time-to-event endpoints with a user-specified equivalence margin. These win statistics are identifiable in the presence of right-censoring and do not depend on the censoring distribution. We then develop estimation and inference procedures for the proposed win statistics based on inverse-probability-of-censoring {weighting} (IPCW) adjustment to handle right-censoring. We conduct extensive simulations to investigate the operational characteristics of the proposed procedure in the finite sample setting. A real oncology trial is used to illustrate the proposed approach.
format Preprint
id arxiv_https___arxiv_org_abs_2506_03050
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An IPCW Adjusted Win Statistics Approach in Clinical Trials Incorporating Equivalence Margins to Define Ties
Cui, Ying
Huang, Bo
Dong, Gaohong
Uozumi, Ryuji
Tian, Lu
Methodology
Applications
92B15
In clinical trials, multiple outcomes of different priorities commonly occur as the patient's response may not be adequately characterized by a single outcome. Win statistics are appealing summary measures for between-group difference at more than one endpoint. When defining the result of pairwise comparisons of a time-to-event endpoint, it is desirable to allow ties to account for incomplete follow-up and not clinically meaningful difference in endpoints of interest. In this paper, we propose a class of win statistics for time-to-event endpoints with a user-specified equivalence margin. These win statistics are identifiable in the presence of right-censoring and do not depend on the censoring distribution. We then develop estimation and inference procedures for the proposed win statistics based on inverse-probability-of-censoring {weighting} (IPCW) adjustment to handle right-censoring. We conduct extensive simulations to investigate the operational characteristics of the proposed procedure in the finite sample setting. A real oncology trial is used to illustrate the proposed approach.
title An IPCW Adjusted Win Statistics Approach in Clinical Trials Incorporating Equivalence Margins to Define Ties
topic Methodology
Applications
92B15
url https://arxiv.org/abs/2506.03050