Study design features affecting outcome in antidepressant trials

Background issue in the approval process of antidepressants is the inconsistency of results between antidepressant clinical phase III trials. Identifying factors influencing efficacy data is needed to facilitate interpretation of the results. s iewed data packages submitted as new drug applications to Swissmedic focusing on pivotal, short-term antidepressant trials. Included studies used HAMD-17 or HAMD-21 as primary measures and enrolled patients aged 18–65 years with a diagnosis of major depression. Due to the hierarchical structure of the data a mixed-effect regression model has been applied with responder rates as primary outcome criterion. Random intercepts were estimated for the different trials, while study design factors were assigned as explanatory fixed effects. s nal dataset was based upon 35 study reports with a total of N = 10,835 patients. Significant results were found for study arm (placebo vs. active compound, p < 0.001), sample size (p = 0.002), duration of treatment (p = 0.024), two or more active treatment arms (p = 0.022) and the individual drug (p = 0.029). Furthermore, a tendency to an association with the outcome was observed for baseline disease severity (p = 0.077) and possibility of dosing adaptation (p = 0.076). tions strict confidentiality agreements, individual drugs are not reported here. Further research should consider additional variables that might have an impact on the results of antidepressant trials. sions cy data in antidepressant trials is significantly affected by various factors. These factors and their potentially confounding role have to be considered in the interpretation of the results.