Performance of the Self-Controlled Case Series With Active Comparators for Drug Safety Signal Detection Using...

Despite testing of epidemiological methods in US Claims databases for signal detection, such data sources have not become a routine capability. The Self Controlled Case Series (SCCS) is one of the most promising methods for drug safety signal detection using Real World Data, and incorporating active comparators could potentially improve its performance by addressing confounding by indication.

This study aims to evaluate the performance of the SCCS with and without active comparators for signal detection using US Merative MarketScan Commercial Claims and Medicare databases.

We applied the SCCS to macrolide and fluoroquinolone antibiotics, using amoxicillin and cefalexin as active comparators. In total, 7 drugs and 30 outcomes from all organ classes were selected. We developed a reference set of 104 positive controls and 58 negative controls, using a taxonomy framework to ensure the selected drug outcome pairs are theoretically well suited to the SCCS design. A two-year observation period with a 30-day risk window after each dispensing was used. Diagnostic performance was measured using sensitivity and specificity with respect to the product labels.

The SCCS without active comparators achieved sensitivities of 0.73 and 0.72 and specificities of 0.68 and 0.62 in commercial and Medicare claims, respectively, for pairs with sufficient power. Active comparators increased specificity up to 0.84 and 0.86, respectively, in Commercial Claims and Medicare but decreased sensitivity to 0.45 and 0.36.

MarketScan databases are potentially suitable for drug safety signal detection due to their large size and information contained. Using a carefully designed reference set of drug-outcome pairs well suited to the study design, the SCCS, while imperfect, performed comparably to optimal settings identified in previously published studies. Active comparators did not enhance overall performance but showed improved specificity by better controlling confounding by indication at the cost of reduced sensitivity.