Literature DB >> 31671481

The win ratio: Impact of censoring and follow-up time and use with nonproportional hazards.

Gaohong Dong1, Bo Huang2, Yu-Wei Chang3, Yodit Seifu4, James Song5, David C Hoaglin6.   

Abstract

The win ratio has been studied methodologically and applied in data analysis and in designing clinical trials. Researchers have pointed out that the results depend on follow-up time and censoring time, which are sometimes used interchangeably. In this article, we distinguish between follow-up time and censoring time, show theoretically the impact of censoring on the win ratio, and illustrate the impact of follow-up time. We then point out that, if the treatment has long-term benefit from a more important but less frequent endpoint (eg, death), the win ratio can show that benefit by following patients longer, avoiding masking by more frequent but less important outcomes, which occurs in conventional time-to-first-event analyses. For the situation of nonproportional hazards, we demonstrate that the win ratio can be a good alternative to methods such as landmark survival rate, restricted mean survival time, and weighted log-rank tests.
© 2019 John Wiley & Sons, Ltd.

Entities:  

Keywords:  hazard ratio; landmark survival rate; log-rank test; prioritized pairwise comparisons; restricted mean survival time

Mesh:

Year:  2019        PMID: 31671481     DOI: 10.1002/pst.1977

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  2 in total

1.  The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring.

Authors:  Gaohong Dong; Lu Mao; Bo Huang; Margaret Gamalo-Siebers; Jiuzhou Wang; GuangLei Yu; David C Hoaglin
Journal:  J Biopharm Stat       Date:  2020-06-17       Impact factor: 1.051

2.  Statistical models for composite endpoints of death and non-fatal events: a review.

Authors:  Lu Mao; KyungMann Kim
Journal:  Stat Biopharm Res       Date:  2021-07-06       Impact factor: 1.586

  2 in total

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