SynthesisBMC medical research methodology2017
Self-controlled designs in pharmacoepidemiology involving electronic healthcare databases: a systematic review.
Synthesis in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
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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
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods for drug safety signal detection using routinely collected observational electronic health care data: A systematic review.Pharmacoepidemiology and drug safety · 2023Pooled it
- Cardiopulmonary hospitalization risks from wildfire-specific and non-wildfire PMNature communications · 2026Article
- Drug-specific risks of acute kidney injury associated with triple whammy therapy: a nationwide self-controlled case series study in Japan.Journal of pharmaceutical health care and sciences · 2026Article
- Prescription sequence symmetry analysis of voriconazole-associated hypomagnesemia in pediatric patients with hematologic diseases.Frontiers in pharmacology · 2026Article
- Screening criteria of potentially inappropriate medications and associations of exposure timing with incident hospital admissions among older adults in a rural community hospital.BMC geriatrics · 2025Article
- Acute cardiovascular effects associated with the use of prescription medications: A Danish nationwide screening study.British journal of clinical pharmacology · 2025Article
- Sequential Epidemiological Analyses of Real-World Data: A Tool for Prospective Drug Safety Surveillance from the Rofecoxib Example.Drug safety · 2025Article
- Effect of intravitreal Bevacizumab on coagulation profile of patients with diabetic retinopathy.Pakistan journal of medical sciences · 2025Article
- Association Between Pneumonia Risk and Anticholinergic Burden Among Patients with Different Frailty Levels.Clinical epidemiology · 2025Article
- Triptan use in elderly over 65 years and the risk of hospitalization for serious vascular events.The journal of headache and pain · 2024Article
- The COVID-19 Vaccine Safety Research Center: a cornerstone for strengthening safety evidence for COVID-19 vaccination in the Republic of Korea.Osong public health and research perspectives · 2024Article
- Article
- A Novel Randomized Trial Protocol for Evaluating Wound Healing Interventions.Advances in wound care · 2023Article
- Article
- Bias in case-crossover studies of medications due to persistent use: A simulation study.Pharmacoepidemiology and drug safety · 2020Article
- A plea to stop using the case-control design in retrospective database studies.Statistics in medicine · 2019Article
- Article
- Measurement error and misclassification in electronic medical records: methods to mitigate bias.Current epidemiology reports · 2018Article
- The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE).BMJ (Clinical research ed.) · 2018Article
- Analysis of Observational Self-matched Data to Examine Acute Triggers of Outcome Events with Abrupt Onset.Epidemiology (Cambridge, Mass.) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundObservational studies are widely used in pharmacoepidemiology. Several designs can be used, in particular self-controlled designs (case-crossover and self-controlled case series). These designs offer the advantage of controlling for time-invariant confounders, which may not be collected in electronic healthcare databases. They are particularly useful in pharmacoepidemiology involving healthcare database. To be valid, they require the presence of some characteristics (key validity assumptions), and in such situations, these designs should be preferred. We aimed at describing the appropriate use and reporting of the key validity assumptions in self-controlled design studies.
methodsArticles published between January 2011 and December 2014, and describing a self-controlled study design involving electronic healthcare databases were retrieved. The appropriate use (fulfilment of key assumptions) was studied in terms of major (abrupt onset event, rare or recurrent event, and intermittent exposure) and minor assumptions (those for which the design can be adapted).
resultsAmong the 107 articles describing a self-controlled design, 35/53 (66%) case-crossover studies, and 48/55 (87%) self-controlled case series fulfilled the major validity assumptions for use of the design; 4/35 and 14/48 respectively did not fulfill the minor assumptions. Overall, 31/53 (58%) case-crossover studies and 34/55 (62%) self-controlled case series fulfilled both major and minor assumptions. The reporting of the methodology or the results was appropriate, except for power calculation.
conclusionsSelf-controlled designs were not appropriately used in34% and 13% of the articles we reviewed that described a case-crossover or a self-controlled case series design, respectively. We encourage better use of these designs in situations in which major validity assumptions are fulfilled (i.e., for which they are recommended), accounting for situations for which the design can be adapted.
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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.