Literature DB >> 1645642

Conditional power for arbitrary survival curves to decide whether to extend a clinical trial.

W G Henderson1, S G Fisher, L Weber, K E Hammermeister, G Sethi.   

Abstract

This article describes a computer simulation methodology to calculate conditional power for comparing two arbitrary survival curves as an aid in deciding whether or not to extend a clinical trial. The method is a modification of that by Halpern and Brown, which computes unconditional power for comparing arbitrary survival curves at the beginning of a study. The advantage of this method is that it permits conditional power calculations for comparisons of distribution-free survival curves. Power is computed for two commonly used statistical tests, the log-rank test and Gehan's generalization of the Wilcoxon test, and for a modified Kolmogorov-Smirnov test, which is particularly sensitive to crossing survival curves. This method for estimating conditional power should be useful in the situation in which a decision must be made regarding the benefit of continuing a clinical trial. The application of this method is shown using VA Cooperative Study No. 90, "Prognosis and Outcome Following Heart Valve Replacement."

Mesh:

Year:  1991        PMID: 1645642     DOI: 10.1016/0197-2456(91)90027-j

Source DB:  PubMed          Journal:  Control Clin Trials        ISSN: 0197-2456


  2 in total

1.  When to stop a clinical trial.

Authors:  S J Pocock
Journal:  BMJ       Date:  1992-07-25

2.  Estimation of conditional power for cluster-randomized trials with interval-censored endpoints.

Authors:  Kaitlyn Cook; Rui Wang
Journal:  Biometrics       Date:  2020-09-12       Impact factor: 1.701

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.