| アブストラクト | BACKGROUND AND OBJECTIVE: 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 D(2)-based pharmacological class-effect query to clinical trial safety data of an atypical antipsychotic tested across different patient populations. METHODS: 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. RESULTS: In pooled data from seven trials of adult schizophrenia, class-specific adverse events were identified in 49% of patients treated with risperidone; in 49% of risperidone-treated patients in two trials in adolescent schizophrenia; in 65% of risperidone-treated patients in four trials in adult bipolar disorder; in 50% of risperidone-treated patients in two trials in adolescent schizophrenia; in 36% of risperidone-treated patients in one trial in Alzheimer's disease; and in 94% of risperidone-treated patients in one trial in autism. CONCLUSIONS: The cumulative curves of class-specific adverse events in risperidone clinical trials of schizophrenia were similar to those first reported for other atypical antipsychotic drugs. However, the class-specific adverse event curves were notably lower for Alzheimer's disease and higher for autism, suggesting that the diagnostic indication may have an important effect on the cumulative class-specific side-effect burden. |
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| ジャーナル名 | Clinical drug investigation |
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| Pubmed追加日 | 2022/11/10 |
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| 投稿者 | Hopkins, Seth C; Ogirala, Ajay; Zeni, Courtney; Worden, MaryAlice; Koblan, Kenneth S |
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| 組織名 | Sunovion Pharmaceuticals Inc., 84 Waterford Drive, Marlborough, MA, 01752, USA.;seth.hopkins@sunovion.com. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/36350559/ |
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