Mining and analysis of adverse drug events signals of colchicine based on FDA adverse event database
Xu Shuai-min
Cui Wei-qi
Song Wei-juan
Wang Yan-hong
Zhao Yang
Abstract：Objective To provide references for clinically safe and rational drug use by mining and analyzing adverse drug event signals associated with colchicine. Methods Reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN) methods of measures of disproportionality were performed to mine and analyze the data of colchicine-related ad-verse drug events (ADE) reports in the US FDA adverse event reporting system (FAERS) database from January 2004 to September 2023. Results A total of 163 ADE risk signals of preferred terms (PT) were filtered out after data processing,involving 19 system organ class (SOC),mainly focusing on gastrointestinal disorders,injury poisoning and procedural complications,musculoskeletal and connective tissue disorders. The risk signals not recorded in the instruction were mainly focused on infections and infestations,psychiatric disorders,and blood and lymphatic system disorders. Conclusion The therapeutic window of colchicine is narrow,and vigilance is required for its drug toxicity and interactions,particularly in patients with liver and kidney dysfunction or when com-bined with CYP3A4 or P-glycoprotein (P-gp) inhibitors. Attention should be paid to risk signals not listed in the drug inserts,such as multiple organ dysfunction syndrome,pneumonia,hypotension,and suicide attempt in addition to the common ADEs such as vomit-ing,diarrhea,abdominal pain,neuromyopathy,and myopathy.
Keywords：ColchicineAdverse drug eventSignal miningDisproportionality measuresUS FDA adverse event reporting system database
Publication Date：2024-12-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 841-845 )