Background: Early prediction and accurate characterization of risk for serious liver injury associated with newly marketed drugs remains an important challenge for clinicians, the pharmaceutical industry, and regulators. To date, a biomarker that specifically indicates exposure to a drug as the etiologic cause of liver injury has not been identified.
Objectives: Using cumulative proportional reporting ratios (PRRs), we investigated 'real-time' profiles of a set of pharmaceuticals, over the first 3 years of US marketing, for the signaling of clinically serious drug-induced liver injury (DILI) in a large spontaneous-reporting database.
Methods: Using report counts of hepatic failure or clinically serious liver injury obtained from the FDA Adverse Events Reporting System (FAERS) database, PRRs of adverse drug event terms were calculated by division of counts of domestic reports of these events by counts of all serious adverse events for each of 13 selected drugs associated with a broad range of hepatotoxic risk (including three linked to only rare instances of clinically apparent liver injury) with reference to all other drugs in the database. Drug-specific cumulative PRRs were measured at successive intervals (calendar quarters) using cumulative tallies of FAERS reports to generate time-based profiles over the initial 3 years of US marketing.
Results: In the set of drugs analyzed, those with no known hepatotoxic risk demonstrated time-based cumulative PRR profiles that approximate the background rates of hepatic failure and serious liver injury reported in the entire FAERS database. In contrast, those that were removed from marketing or subjected to marketing restrictions due to their potential to cause liver injury were associated with profiles of rapidly rising cumulative PRRs that were greater than 5 within the first 10 million domestic prescriptions or the first four quarters of US marketing. The systematic tracking and identification of rising PRRs for DILI associated with newly marketed pharmaceutical and biological agents is a valuable tool for identification of safety signals within the FAERS database.
Limitations: Disproportionality profiling of spontaneous reports in FAERS (e.g., cumulative PRR measurements), which signals an association between a recently marketed drug and liver injury, is not a method to quantitatively measure drug-related risk. Regulatory actions in response to emerging drug safety concerns often depend on an accurate assessment of risks using multiple sources of data and the consideration of overall benefits and risks of the agent. Causality must be determined through analysis of individual cases to exclude other etiologies of liver injury.
Conclusion: The FAERS database can be used to advance empiric hepatotoxicity time-trending reporting levels for newly marketed agents in order to rapidly identify recently launched potential hepatotoxic agents and initiate further evaluation.