Brand vs generic adverse event reporting patterns: An authorized generic-controlled evaluation of cardiovascular medications.

WHAT IS KNOWN AND OBJECTIVE: Some public scepticism exists about generics in terms of whether brand and generic drugs produce identical outcomes. This study explores whether adverse event (AE) reporting patterns are similar between brand and generic drugs, using authorized generics (AGs) as a control for possible generic drug perception biases. METHODS: Events reported to the FDA Adverse Event Reporting System from the years 2004-2015 were analysed. Drugs were classified as brand, AG or generic based on drug and manufacturer names. Reports were included if amlodipine, losartan, metoprolol extended release (ER) or simvastatin were listed as primary or secondary suspect drugs. Disproportionality analyses using the reporting odds ratio (ROR) assessed the relative rate of reporting labelled AEs compared to reporting these AEs with all other drugs. The Breslow-Day test compared RORs across brand, AG and generic. Interrupted time series analysis evaluated the impact of generic entry on reporting trends. RESULTS AND DISCUSSION: Generics accounted for significant percentages of total U.S. reports, but AGs accounted for smaller percentages of reports, including for amlodipine (14.26%), losartan (1.48%), metoprolol ER (0.35%) and simvastatin (0.70%). Whereas the RORs were significantly different for multiple brand vs generic comparisons, the AG vs generic comparisons yielded fewer statistically significant findings. Namely, only the ROR for AG differed from generic for amlodipine with peripheral oedema (P < .01). WHAT IS NEW AND CONCLUSION: Inconsistent reporting patterns were observed more between brand and generic compared with AG and generic. Use of AGs as a control for perception biases against generics is useful, but this approach can be limited by small AG report numbers. Requiring the manufacturer name to be printed on the prescription bottle or packaging could improve the accuracy of assignment for products being reported.

Duke Scholars

Author David Page Biostatistics & Bioinformatics, Division of Biostatistics