Resampling-based methods for the analysis of multiple endpoints in clinical trials

✍ Scribed by Peter Reitmeir; Gernot Wassmer

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 95 KB
• Volume: 18
• Category: Article
• ISSN: 0277-6715
• DOI: 10.1002/(sici)1097-0258(19991230)18:24<3453::aid-sim283>3.0.co;2-z

✦ Synopsis

We consider multivariate tests for comparing two treatments with multiple endpoints. The test decision is drawn from the simultaneous consideration of the univariate tests for the single endpoints. A general class of these tests, called cut-o! tests, can be given, which, however, can lead to highly conservative procedures because the dependencies among the endpoints are not taken into account. In applying resampling-based methods considerable improvements for these tests can be achieved. Resampling-based cut-o! tests are proposed which are sensitive against a treatment di!erence in a single endpoint, in a subgroup of endpoints, or in all endpoints. The results of Monte Carlo simulations demonstrate that a remarkable gain in statistical power as compared to the crude simultaneous consideration can be reached. In particular, for the multivariate one-sided test situation the proposed tests can be recommended. As an example the application of the tests is demonstrated by data from a clinical trial.