Designing and analysing clinical trials in mental health: an evidence synthesis approach

Abstract

Objective: When planning a clinical study, evidence on the treatment effect is often available from previous studies. However, this evidence is mostly ignored for the analysis of the new study. This is unfortunate, since using it could lead to a smaller study without compromising power. We describe a design that addresses this issue.

Methods: We use a Bayesian meta-analytic model to incorporate the available evidence in the analysis of the new study. The shrinkage estimate for the new study integrates the evidence from the other studies. At the planning phase of the study, it allows a statistically justified reduction of the sample size.

Results: The design is illustrated using data from an Food and Drug Administration (FDA) review of lurasidone for the treatment of schizophrenia. Three studies inform the meta-analysis before the new study is conducted. Results from an additional phase III study, which were not available at the time of the FDA review, are then used for the actual analysis.

Conclusions: In the presence of reliable and relevant evidence, the design offers a way to conduct a smaller study without compromising power. It therefore fills a gap between the assessment of evidence and its actual use in the design and analysis of studies.

Keywords: MENTAL HEALTH; STATISTICS & RESEARCH METHODS.

Figure 1

Meta-analysis of the 6 weeks change from baseline in Clinical Global Impressions—Severity Scale (CGI-S), lurasidone versus placebo. Shown is the difference in the 6 weeks CGI-S change from baseline (lurasidone vs placebo) with negative values favouring lurasidone. No effect corresponds to a value of zero, which is indicated by the dotted line. The straight lines with the squares are the study-specific results. The diamonds represent the overall and the predicted effect. The predicted effect (results in bold) corresponds to the effect that we would expect in a next study. For the between-trial heterogeneity, the typical (median) value and the 95% interval are given. The 0.13 indicates moderate heterogeneity, and the interval ranges from very small to substantial-to-large heterogeneity.

Figure 2

Meta-analysis of the 6 weeks change from baseline in Clinical Global Impressions—Severity Scale (CGI-S), lurasidone versus placebo, including studies D1050049, D1050196, D1050229 and D1050233. Shown is the difference in the 6 weeks CGI-S change from baseline (lurasidone vs placebo) with negative values favouring lurasidone. No effect corresponds to a value of zero, which is indicated by the dotted line. The straight lines with the squares are the study-specific results. The dotted grey lines with the rotated squares represent the shrinkage estimates. These correspond to the estimates for each study incorporating the data from the other studies. The diamond represents the overall effect. For the between-trial heterogeneity, the typical (median) value and the 95% interval are given. The 0.14 indicates moderate heterogeneity, and the interval ranges from very small to substantial-to-large heterogeneity.