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There is a current demand for "safety signal" screening, not only for single drugs but also for drug-drug interactions. The detection of drug-drug interaction signals using the proportional reporting ratio ( PRR ) has been reported, such as through using the combination risk ratio ( CRR ). However, the CRR does not consider the overlap between the lower limit of the 95% confidence interval of the PRR of concomitant-use drugs and the upper limit of the 95% confidence interval of the PRR of single drugs. In this study, we proposed the concomitant signal score ( CSS ), with the improved detection criteria, to overcome the issues associated with the CRR . "Hypothetical" true data were generated through a combination of signals detected using three detection algorithms. The signal detection accuracy of the analytical model under investigation was verified using machine learning indicators. The CSS presented improved signal detection when the number of reports was ≥3, with respect to the following metrics: accuracy ( CRR : 0.752 → CSS : 0.817), Youden's index ( CRR : 0.555 → CSS : 0.661), and F -measure ( CRR : 0.780 → CSS : 0.820). The proposed model significantly improved the accuracy of signal detection for drug-drug interactions using the PRR .

Improved Detection Criteria for Detecting Drug-Drug Interaction Signals Using the Proportional Reporting Ratio