Domperidone increases harmful cardiac events in Parkinson's disease: A Bayesian re-analysis of an observational study
Gisèle Nakhlé1, James M Brophy2, Christel Renoux3
1CHUM Research Center, Pavillon S, 850, St-Denis St., Montreal, Quebec, Canada; The Canadian Network for Observational Drug Effect Studies (CNODES), Jewish General Hospital, 3755 Chemin de la Côte-Sainte-Catherine H-485, Montreal, Quebec Canada; University of Montreal, 2900 Edouard Montpetit Blvd, Montreal, Quebec Canada.
Objectives:
To assess the risks of ventricular tachyarrhythmia/sudden cardiac death (VT/SCD) with domperidone use in Parkinson's disease (PD).
Study Designs And Settings:
Using Bayesian methods, results from an observationalstudy were combined with prior beliefs to calculate posterior probabilities of increasedrelative risk (RR)) of VT/SCD with use of domperidone compared to non-use and ofharm, defined as risk exceeding 15%. The analyses were carried with normallydistributed priors (log (RR)): uninformative (N(0,10)) or informative (N(0.53,179)),derived from a meta-analysis (OR (95%CI):1.70 (1.47-1.97)). Sensitivity analyses used:different priors' strengths, different priors, and Bayesian meta-analysis RESULTS: The uninformative prior yielded a RR: 1.23 (95% credible interval (CrI):0.94-1.62), like the published frequentist RR: 1.22 (95% CI:0.99-1.50), with 69% probabilityof harm. With an informative prior weighted at 100%, 50% and 10%, the RR were 1.63(1.41-1.88), 1.57 (1.31-1.91) and 1.39 (1.10-1.93), respectively. The correspondingprobabilities of harm were 100%, 99%, and 94%, respectively.
Conclusion:
While both the frequentist and Bayesian approaches with anuninformative prior were unable to reach a definitive conclusion concerning thearrhythmic risk of domperidone in PD patients, the Bayesian analysis with informativepriors showed a high probability of increased risk that was robust to multiple priorsensitivity analyses.
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