Identification of drug combinations to reduce the risk of pioglitazone-related bladder cancer using the FDA adverse event reporting system database.

Abstract

Background: Emerging studies have uncovered the innovative pharmacological characteristics of pioglitazone (PLZ). However, concerns regarding the potential link to an increased risk of bladder cancer (BC) had constrained its clinical application.

Research design and methods: BC reports associated with PLZ and drug combinations containing PLZ from 1 January 2004 to 30 September 2024 were identified from the Food and Drug Administration Adverse Event Reporting System (FAERS) database. Reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN) method was applied to mine adverse drug event signals.

Results: Of 144 combinations, 15 showed an IC025 greater than 3, denoting a strong signal; 44 had an IC025 between 1.5 and 3, indicating moderate signal intensity; 36 had an IC025 between 0 and 1.5, pointing to a weak signal; and 49 had an IC025 less than 0, suggesting no apparent related signal. Importantly, the IC025 values for all drug combinations did not surpass the value observed when PLZ was used as monotherapy.

Conclusions: Through comprehensive data mining, 14 PTs associated with BC were identified, indicating that specific medication combinations might mitigate the risk of PLZ-related BC. Our findings offer valuable insights for guiding decisions on PLZ combination therapies.