A case-control study on the clinical characteristics of granisetron-related arrhythmias and the development of a predictive nomogram.

BACKGROUND:Automatic monitoring and assessment are increasingly employed in drug safety evaluations using hospital information system data. The increasing concern about granisetron-related arrhythmias requires real-world studies to improve our understanding of its safety. AIM:This study aimed to analyze the incidence, clinical characteristics, and risk factors of granisetron-related arrhythmias in hospitalized patients using real-world data obtained from the Adverse Drug Event Active Surveillance and Assessment System-II (ADE-ASAS-II) and concurrently aimed to develop and validate a nomogram to predict the occurrence of arrhythmias. METHOD:Retrospective automatic monitoring of inpatients using granisetron was conducted in a Chinese hospital from January 1, 2017, to December 31, 2021, to determine the incidence of arrhythmias using ADE-ASAS- II. Propensity score matching was used to balance confounders and analyze clinical characteristics. Based on risk factors identified through logistic regression analysis, a prediction nomogram was established and internally validated using the Bootstrap method. RESULTS:Arrhythmias occurred in 178 of 72,508 cases taking granisetron with an incidence of 0.3%. Independent risk factors for granisetron-related arrhythmias included medication duration, comorbid cardiovascular disease, concomitant use of other 5-hydroxytryptamine 3 receptor antagonists, alanine aminotransferase > 40 U/L, and blood urea nitrogen > 7.5 mmol/L. The nomogram demonstrated good differentiation and calibration, with enhanced clinical benefit observed when the risk threshold ranged from 0.10 to 0.82. CONCLUSION:The nomogram, based on the five identified independent risk factors, may be valuable in predicting the risk of granisetron-related arrhythmias in the administered population, offering significant clinical applications.