Performance of the Self-Controlled Case Series With Active Comparators for Drug Safety Signal Detection Using the French Administrative Healthcare Database (SNDS)
Abstract
Background: The self controlled case series (SCCS) is one of the most promising methods for drug safety signal detection using real world data (RWD), and incorporating active comparators could potentially improve its performance by addressing time-varying confounding by indication. The 'Système National des Données de Santé' (SNDS) is a large nationwide administrative claims database, which has not been used extensively for drug safety signal detection. While comparable in size to other RWD sources, it is unclear to what extent the performance of SCCS correlates with that in other sources.
Objectives: This study aims to evaluate the performance of the SCCS with and without active comparators for signal detection in the French administrative healthcare database SNDS.
Methods: We applied the SCCS to macrolide and fluoroquinolone antibiotics, using amoxicillin as the active comparator. Amoxicillin was chosen as an active comparator with similar indications. 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. The observation period lasted 2 years, with a 30-day risk window after each dispensing. Diagnostic performance was measured using sensitivity and specificity with respect to the product labels.
Results: The sensitivity and specificity of the SCCS without…
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Evidence Hub reads this as a case series, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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