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Eur J Pharm Sci. 2009 Jan 31;36(1):4-10. doi: 10.1016/j.ejps.2008.10.025. Epub 2008 Nov 8.

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

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Clinical Pharmacology Modelling & Simulation, GlaxoSmithKline, Verona, Italy.


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.

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