Testing the Hypothesis that Matters for Multiple Primary Endpoints

Abstract

In clinical trials with multiple primary endpoints, the effectiveness of a treatment may be established using either a composite endpoint or by employing a decision rule based on the individual endpoints. In this paper, the latter method is examined. Emphasis is placed on the careful selection of primary endpoints and the need to specify the clinical objectives and statistical decision rules in advance. It is argued that Bonferroni-type adjustments are appropriate only in the case of a nonspecific hypothesis. Since requiring an intervention to demonstrate positive effects in several primary endpoints is more stringent than requiring an effect in any, some upward adjustment of individual α-levels should be allowed. In addition, physiologic/symptomatic classification of endpoints with separate decision rules for each may also be warranted in certain circumstances. An example is presented.