Abstract
Objective To explore the clinical safety of lopinavir/ritonavir (LPV/r) by mining the risk signals of adverse events (AEs) related to LPV/r for the safe application of the drug in the treatment of novel coronavirus pneumonia (COVID-19). Methods The risk signals related to LPV/r in AE reports of US FDA Adverse Event Reporting System (FAERS) from the first quarter of 2010 to the third quarter of 2019 were mined by reporting odds ratio (ROR). An AE with reports more than 3 and 95% confidence interval (CI) lower limit of ROR greater than 1 was defined as a positive signal. AEs were counted and classified using the preferred system organ class (SOC) and preferred term (PT) of Medical Dictionary for Regulatory Activities (MedDRA). The PTs of top 50 adverse event reports and signal strength were selected and analyzed. Results From the first quarter of 2010 to the third quarter of 2019, a total of 13 335 AE reports with LPV/r as the primary suspicious drug were reported in the FAERS database. Four hundred and fifty-five AE risk signals with reports more than 3 and the 95%CI lower limit of ROR greater than 1 were detected, involving 7 718 AE reports. The top 2 system organs involved in AE reports were injury, poisoning and procedural complications [13.6% (1 051/7 718)] and pregnancy, puerperium and perinatal conditions [11.7% (899/7 718)]. However, 998 (95.0%) of 1051 AE reports involved in injury, poisoning and procedural complications were related to drug exposure during pregnancy. The system organ with the highest signals was congenital, familial and genetic disorders [16.3% (74/455)]. In addition, 144 AEs caused by drug interactions were detected, which ranked the 7th in the AE reports. Conclusions The risk signals of fetal, neonatal and infant abnormalities related to LPV/r during pregnancy were detected, suggesting that attention should be paid to the risk of using LPV/r in pregnant women and infants. The interaction between LPV/r and other drugs was also worthy of attention. Key words: Lopinavir; Ritonavir; Coronavirus; Coronavirus infections; Adverse drug reaction reporting systems; United States Food and Drug Administration; Signal processing, computer-assisted
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