• multi-regional schizophrenia trials;
  • ANCOVA model;
  • recursive partitioning


In recent years, we have seen an increasing trend of foreign data as part of clinical trial data submitted in new drug applications (NDA) to US Food and Drug Administration (FDA). To understand the design and analysis characteristics, we studied schizophrenia multi-regional clinical trials (MRCTs). The schizophrenia data set consisted of a total of 12 585 patients collected from 33 clinical trials with 63.8% patients from North America, the largest region. The data set constituted 10 schizophrenia drug programs in support of NDAs submitted to FDA from December 1993 to December 2005.

Two main objectives were pursued. First, we investigated some study design issues including potential heterogeneity of treatment effect via meta analysis and placebo response pattern over time. Second, we performed empirical modeling in two ways, supervised and unsupervised, to explain potential impact of baseline covariates on treatment effect in MRCTs.

Based on our analysis results, placebo response appeared to increase over time and primarily attributed to US region. On average, the observed treatment effect in the US was generally smaller than non-US region. Both supervised and unsupervised empirical modeling selected baseline Positive and Negative Syndrome Scale total score as one of the most important covariates explaining a treatment effect. Region also played a role in explaining potential treatment effect heterogeneity. When baseline body weight was considered as a covariate in an empiric model, our results indicated that it alone did not seem to be an important factor in explaining regional difference. Published in 2010 by John Wiley & Sons, Ltd.