Modelling placebo response in depression trials using a longitudinal model with informative dropout

Dropouts are common events in longitudinal studies in depression. Ignoring missing information may lead to biased and inconsistent assessment of study results. A non-linear model was recently developed to describe the time-course of HAMD-17 clinical score in the placebo arms of antidepressant clinical trials. In this paper we complemented this model by introducing an informative dropout component to jointly estimate HAMD-17 time-course and dropout mechanism. The aims of this work were to: (a) characterise typical placebo response in depression trials in presence of dropouts, (b) explore which dropout mechanism better describe the time-varying probability of a subject to dropout from the trial, and (c) define a framework for the development of clinical trial simulation in depression. A meta-analytic approach was used on placebo data collected in 6 clinical trials including 695 subjects suffering from Major Depressive Disorders. Alternative hypotheses for missingness were evaluated using different hazard models. The Missing Not At Random performed statistically (p < 0.01) better than Missing At Random, that in turn performed better (p < 0.01) than Missing Completely At Random model. This finding provided new insights on the validity of the analyses currently used in many longitudinal clinical trials to support the registration of a new medicinal product. (C) 2008 Elsevier B.V. All rights reserved.