Evidence map›Paper›PMID 41235709›Full record

ArticlePharmacoepidemiology and drug safety2025

Performance of the Self-Controlled Case Series With Active Comparators for Drug Safety Signal Detection Using the French Administrative Healthcare Database (SNDS).

Astrid Coste, Angel Y S Wong, François Haguinet, Andrew Bate, Ian J Douglas

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Article in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Astrid CosteDepartment of Non-Communicable Diseases Epidemiology, LSHTM, London, UK.ORCID 0000-0003-4207-7447
Angel Y S WongDepartment of Non-Communicable Diseases Epidemiology, LSHTM, London, UK.ORCID 0000-0002-8618-7333
François HaguinetGSK, Wavre, Belgium.
Andrew BateDepartment of Non-Communicable Diseases Epidemiology, LSHTM, London, UK.ORCID 0000-0003-3151-3653
Ian J DouglasDepartment of Non-Communicable Diseases Epidemiology, LSHTM, London, UK.

Funding

GlaxoSmithKline
6 · The paper itself

Abstract

backgroundThe 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.

objectivesThis study aims to evaluate the performance of the SCCS with and without active comparators for signal detection in the French administrative healthcare database SNDS.

methodsWe 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.

resultsThe sensitivity and specificity of the SCCS without active comparator were 0.89 and 0.43, respectively, when limited to pairs with satisfactory power. Specificity increased up to 0.91 with active comparators; however, sensitivity decreased to 0.52.

conclusionsThe SNDS is a useful data source for signal detection, particularly for outcomes captured in hospitals. Using a carefully designed reference set of drug-outcome pairs well suited to the study design, the SCCS achieved satisfactory performance for signal detection in this database. In this study, the use of active comparators improved overall performance at the expense of greatly reduced sensitivity.

Indexed as

Adverse Drug Reaction Reporting SystemsAnti-Bacterial AgentsDatabases, FactualDrug-Related Side Effects and Adverse ReactionsAmoxicillinFluoroquinolonesFranceHumansMacrolidesPharmacovigilanceAmoxicillinAnti-Bacterial AgentsFluoroquinolonesMacrolidesclaims datapharmacoepidemiologypharmacovigilancereal‐world dataself‐controlled case seriessignal detection

Identifiers

PMID41235709
PMCPMC12616763

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