ArticlePharmacoepidemiology and drug safety2026
Performance of the Self-Controlled Case Series for Drug Safety Signal Detection: A Multi-Database Study.
Article in Pharmacoepidemiology and drug safety, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Performance of the Self-Controlled Case Series for Drug Safety Signal Detection: A Multi-Database Study.Pharmacoepidemiology and drug safety · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundDifferences in performance of the Self-Controlled Case Series (SCCS) for signal detection have been reported across different databases. However, there has been limited comparative analysis of performance and it remains unknown whether combinations of databases could enable more effective signal detection.
objectivesThis study aims to compare the performance of the SCCS for signal detection across several data sources, and to determine whether combinations of databases can improve SCCS performance.
methodsWe applied the SCCS to macrolides and fluoroquinolone antibiotics, in four databases: Merative MarketScan Commercial Claims and Medicare, the Clinical Practice Research Datalink (CPRD) Aurum and the Système National des Données de Santé. 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, specificity and area under the receiver operating curve (AUC) with respect to the product labels, both for individual and combinations of databases.
resultsThe sensitivity of the SCCS ranged from 0.57-0.89 across individual databases, and the specificity from 0.43-0.77 when limited to drug-outcome pairs sufficiently powered. The combination of all databases achieved the maximum sensitivity of 0.89 (0.41 specificity) for the full reference set, and a sensitivity of 1 (0.35 specificity) for drug outcome pairs with enough power. Whilst AUCs ranged from 0.66 to 0.71 across individual databases, the highest performing combination was CPRD plus MarketScan Commercial Claims (0.76 AUC).
conclusionsUsing a carefully designed reference set of drug-outcome pairs well suited to the study design, the SCCS performance varied substantially by database due to differences in population, reporting, healthcare and coding systems and prescribing patterns. Multi-database studies showed increased performance of SCCS for signal detection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.