Depicting Risperidone Safety Profiles in Clinical Trials Across Different Diagnoses Using a Dopamine D2-Based Pharmacological Class Effect Query Defined by FAERS

Current methods are not designed to relate the incidence of individual adverse events reported in clinical trials to the plurality of adverse events accumulated in spontaneous reporting databases during real-world use. We have previously reported on a pharmacological class-effect query of clinical trial data defined by a disproportionality analysis of the US Food and Drug Administration Adverse Event Reporting System (FAERS) post-marketing data. The aim of the current analysis was to apply a dopamine D2-based pharmacological class-effect query to clinical trial safety data of an atypical antipsychotic tested across different patient populations. Patient-level adverse event data (n = 4400) from controlled clinical trials of the antipsychotic risperidone in schizophrenia, bipolar disorder, Alzheimer’s disease psychosis, and autism were obtained through the Yale University Open Data Access (YODA) project. An Empirical Bayes Geometric Mean analysis was performed, and a three-fold threshold incidence level was applied to determine if a preferred term met criteria for being an antipsychotic class-related adverse event. In pooled data from seven trials of adult schizophrenia, class-specific adverse events were identified in 49