ArticleDrug safety2017
Evaluation of the Case-Crossover (CCO) Study Design for Adverse Drug Event Detection.
Article in Drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- The Extent and Magnitude of Bias in Case-Crossover Studies of Real-World Non-transient Medications Patterns: A Simulation Study with Real-World Examples.Drug safety · 2026Article
- Medications influencing the risk of fall-related injuries in older adults: case-control and case-crossover design studies.BMC geriatrics · 2023Article
- Using Simulated Data to Assess Case-Crossover Designs for Studying Less Transient Effects of Drugs.Drug safety · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe case-crossover (CCO) design was originally intended to study exposures characterized as intermittent with acute effects. The performance of the CCO design is not well characterized under alternative exposure and outcome relationships.
objectiveThe purpose of this study was to evaluate the ability of the CCO to identify simulated treatment effects under different drug exposures and outcomes relationships while varying the duration of the 1:1 matched risk and control windows.
methodsThe simulated data were obtained from the Observational Medical Dataset Simulator, version 2 (OSIM2). The area under the receiver operator characteristic curve (AUC) was calculated to compare CCO performance across outcome types, simulated relative risk (RR), and duration of risk and control windows.
resultsThe AUC for acute outcomes was higher for shorter risk and control windows and improved with higher simulated RR. For example, the AUC for the simulated RR of 4 was 0.95 for a 30-day window length and 0.78 for a 360-day window length. The AUC for the accumulative outcomes increased with longer risk and control windows and stronger simulated RR. For example, the AUC for the simulated RR of 4 was 0.85 for a 360-day window length and 0.23 for a 30-day window length. Risk and control window lengths did not appear to sufficiently alter the AUC for insidious onset outcomes.
conclusionsThe CCO performed best for acute-onset outcomes, but may be useful for exploring adverse outcomes with accumulative effects. Careful consideration must be given to the hypothesized drug exposure and outcome distribution because specification of risk and control window duration affects CCO performance.
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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.