Joint modeling of dropout and outcome in three pivotal clinical trials of schizophrenia

Background: Dropout is a serious challenge to clinical trials in psychiatry, yet standard outcome analyses with mixed models do not account for dropout, while joint modeling uses dropout from a survival model to adjust the outcome from a mixed model, but is untested in clinical trials of schizophrenia. Aims: To compare mixed and joint modeling in three acute phase pivotal placebo controlled trials of schizophrenia. Method: Data were reanalyzed on 611 in-patients with acute schizophrenia who participated in three pivotal randomized controlled trials that compared placebo with olanzapine or risperidone (dropout rates placebo: 62.6% and medication: 37.4%). The outcome measures were BPRS or PANSS total change scores. Mixed-effects models for repeated measures and joint models were computed and compared to examine the time-treatment interaction. Effect size comparisons were made. Results: Antipsychotic treatment was superior to placebo across analyses. Time treatment interactions were significant (p< .05) for the mixed (beta = 2.33) and joint models (beta = 2.62). Compared with mixed modeling, joint modeling reduced the estimated change score for treatment (21.24 vs 19.74) and placebo (1.64 vs - 1.11). The effect size differences between placebo and treatment groups were greater for joint (ES = .89) than mixed modeling (ES = 0.83). Sensitivity analysis replicated this trend of results in each of the three trials. Conclusion: Compared to mixed modeling, joint modeling results in a greater separation between treatment and placebo groups. This offers preliminary evidence that joint modeling may be useful in the analysis of antipsychotic placebo controlled RCTs.