Active Safety Monitoring of Newly Marketed Medications in a Distributed Data Network: Application of a Semi-Automated Monitoring System
Year: 2012
Type: article
Study design: Observational Study
Abstract: We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic health-care data. In a retrospective analysis, we show that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). Over >5 years of monitoring, rate differences (RDs) in comparisons of rosuvastatin with atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% confidence interval (CI): -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI: -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin with azithromycin was 0.3 cases per 1,000 person-years (95% CI: -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for the three drug-outcome pairs.
Authors: J J Gagne, R J Glynn, J A Rassen, A M Walker, G W Daniel, G Sridhar, S Schneeweiss
Language: English
Subfield: Toxicology
Domain: Life Sciences
Open Access status: green
Awards: Analyzing Complex Healthcare Data to Determine Causality of Observed Drug Effects, G1249985205, G2175213164, G4750251080, Assessment of Treatment Effects in High-Dimensional, Routine Care Claims Data, "Stopping Rules" for Drug Safety Monitoring Using Healthcare Databases, COMPARATIVE EFFECTIVENESS METHODS FOR EVALUATION OF IN-HOSPITAL EXPOSURES, Effectiveness studies with securely pooled healthcare data and adjusted analyses
OpenAlex ID: W2152628670