z-logo
open-access-imgOpen Access
Many-to-one comparisons after safety selection in multi-arm clinical trials
Author(s) -
Gerald Hlavin,
Lisa V. Hampson,
Franz König
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0180131
Subject(s) - type i and type ii errors , sample size determination , selection (genetic algorithm) , clinical trial , computer science , medicine , multiple comparisons problem , statistical power , null hypothesis , false discovery rate , word error rate , statistics , mathematics , artificial intelligence , biochemistry , chemistry , gene
In phase II platform trials, ‘many-to-one’ comparisons are performed when K experimental treatments are compared with a common control to identify the most promising treatment(s) to be selected for Phase III trials. However, when sample sizes are limited, such as when the disease of interest is rare, only a single Phase II/III trial addressing both treatment selection and confirmatory efficacy testing may be feasible. In this paper, we suggest a two-step safety selection and testing procedure for such seamless trials. At the end of the study, treatments are first screened on the basis of safety, and those deemed to be sufficiently safe are then taken forwards for efficacy testing against a common control. All safety and efficacy evaluations are therefore performed at the end of the study, when for each patient all safety and efficacy data are available. If confirmatory conclusions are to be drawn from the trial, strict control of the family-wise error rate (FWER) is essential. However, to avoid unnecessary losses in power, no type I error rate should be “wasted” on comparisons which are no longer of interest because treatments have been dropped due to safety concerns. We investigate the impact on power and FWER control of multiplicity adjustments which correct efficacy tests only for the number of safe selected treatments instead of adjusting for all K null hypotheses the trial begins testing. We derive conditions under which strict control of the FWER can be achieved. Procedures using the estimated association between safety and efficacy outcomes are developed for the case when the correlation between endpoints is unknown. The operating characteristics of the proposed procedures are assessed via simulation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here