Combining mortality and longitudinal measures in clinical trials
Abstract
Clinical trials often assess therapeutic benefit on the basis of an event such as death or the diagnosis of disease. Usually, there are several additional longitudinal measures of clinical status which are collected to be used in the treatment comparison. This paper proposes a simple non-parametric test which combines a time to event measure and a longitudinal measure so that a substantial treatment difference on either of the measures will reject the null hypothesis. The test is applied on AIDS prophylaxis and paediatric trials.
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
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