ArticleJournal of clinical epidemiology2020
Prior event rate ratio adjustment produced estimates consistent with randomized trial: a diabetes case study.
Article in Journal of clinical epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed, 17 citations in OpenAlex.
- Strategy to Control Biases in Prior Event Rate Ratio Method, With Application to Palliative Care in Patients With Advanced Cancer.Statistics in medicine · 2026Article
- Retrospective Analysis of Adverse Drug Reactions in Patients with Type 2 Diabetes Mellitus and Development of a Risk Prediction Model.International journal of general medicine · 2026Article
- Triangulating Instrumental Variable, confounder adjustment and difference-in-difference methods for comparative effectiveness research in observational data.Wellcome open research · 2025Article
- Two assumptions of the prior event rate ratio approach for controlling confounding can be evaluated by self-controlled case series and dynamic random intercept modeling.Journal of clinical epidemiology · 2024Article
- The State of Use and Utility of Negative Controls in Pharmacoepidemiologic Studies.American journal of epidemiology · 2024Review
- Use of Bisphosphonates and the Risk of Skin Ulcer: A National Cohort Study Using Data from the French Health Care Claims Database.Drug safety · 2023Article
- The Effect of Buprenorphine on Human Immunodeficiency Virus Viral Suppression.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Impact of influenza vaccination on amoxicillin prescriptions in older adults: A retrospective cohort study using primary care data.PloS one · 2021Article
- Precision Medicine in Type 2 Diabetes: Using Individualized Prediction Models to Optimize Selection of Treatment.Diabetes · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
objectivesElectronic health records (EHR) provide a valuable resource for assessing drug side-effects, but treatments are not randomly allocated in routine care creating the potential for bias. We conduct a case study using the Prior Event Rate Ratio (PERR) Pairwise method to reduce unmeasured confounding bias in side-effect estimates for two second-line therapies for type 2 diabetes, thiazolidinediones, and sulfonylureas. STUDY DESIGN AND SETTINGS: Primary care data were extracted from the Clinical Practice Research Datalink (n = 41,871). We utilized outcomes from the period when patients took first-line metformin to adjust for unmeasured confounding. Estimates for known side-effects and a negative control outcome were compared with the A Diabetes Outcome Progression Trial (ADOPT) trial (n = 2,545).
resultsWhen on metformin, patients later prescribed thiazolidinediones had greater risks of edema, HR 95% CI 1.38 (1.13, 1.68) and gastrointestinal side-effects (GI) 1.47 (1.28, 1.68), suggesting the presence of unmeasured confounding. Conventional Cox regression overestimated the risk of edema on thiazolidinediones and identified a false association with GI. The PERR Pairwise estimates were consistent with ADOPT: 1.43 (1.10, 1.83) vs. 1.39 (1.04, 1.86), respectively, for edema, and 0.91 (0.79, 1.05) vs. 0.94 (0.80, 1.10) for GI.
conclusionThe PERR Pairwise approach offers potential for enhancing postmarketing surveillance of side-effects from EHRs but requires careful consideration of assumptions.
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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 Socratic graph.