Header

UZH-Logo

Maintenance Infos

A mixed approach for proving non-inferiority in clinical trials with binary endpoints


Rousson, V; Seifert, Burkhardt (2008). A mixed approach for proving non-inferiority in clinical trials with binary endpoints. Biometrical Journal, 50(2):190-204.

Abstract

When a new treatment is compared to an established one in a randomized clinical trial, it is standard practice to statistically test for non-inferiority rather than for superiority. When the endpoint is binary, one usually compares two treatments using either an odds-ratio or a difference of proportions. In this paper, we propose a mixed approach which uses both concepts. One first defines the non-inferiority margin using an odds-ratio and one ultimately proves non-inferiority statistically using a difference of proportions. The mixed approach is shown to be more powerful than the conventional odds-ratio approach when the efficacy of the established treatment is known (with good precision) and high (e.g. with more than 56% of success). The gain of power achieved may lead in turn to a substantial reduction in the sample size needed to prove non-inferiority. The mixed approach can be generalized to ordinal endpoints.

Abstract

When a new treatment is compared to an established one in a randomized clinical trial, it is standard practice to statistically test for non-inferiority rather than for superiority. When the endpoint is binary, one usually compares two treatments using either an odds-ratio or a difference of proportions. In this paper, we propose a mixed approach which uses both concepts. One first defines the non-inferiority margin using an odds-ratio and one ultimately proves non-inferiority statistically using a difference of proportions. The mixed approach is shown to be more powerful than the conventional odds-ratio approach when the efficacy of the established treatment is known (with good precision) and high (e.g. with more than 56% of success). The gain of power achieved may lead in turn to a substantial reduction in the sample size needed to prove non-inferiority. The mixed approach can be generalized to ordinal endpoints.

Statistics

Citations

16 citations in Web of Science®
16 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

2 downloads since deposited on 05 Nov 2008
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2008
Deposited On:05 Nov 2008 15:30
Last Modified:05 Apr 2016 12:29
Publisher:Wiley-Blackwell
ISSN:0323-3847
Publisher DOI:https://doi.org/10.1002/bimj.200710410
PubMed ID:18311852

Download