ArticleDrug safety2020
Channeling Bias in the Analysis of Risk of Myocardial Infarction, Stroke, Gastrointestinal Bleeding, and Acute Renal Failure with the Use of Paracetamol Compared with Ibuprofen.
Article in Drug safety, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed, 15 citations in OpenAlex.
- Assessing Covariate Balance With Small Sample Sizes.Statistics in medicine · 2025Article
- Assessing Covariate Balance with Small Sample Sizes.medRxiv : the preprint server for health sciences · 2025Article
- Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes: A Multinational, Federated Analysis of LEGEND-T2DM.Journal of the American College of Cardiology · 2024Article
- Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab: An Observational Health Data Sciences and Informatics Network Study.Ophthalmology. Retina · 2024Observational
- The State of Use and Utility of Negative Controls in Pharmacoepidemiologic Studies.American journal of epidemiology · 2024Review
- A Principled Approach to Characterize and Analyze Partially Observed Confounder Data from Electronic Health Records.Clinical epidemiology · 2024Article
- Conducting and interpreting disproportionality analyses derived from spontaneous reporting systems.Frontiers in drug safety and regulation · 2023Review
- Adjusting for indirectly measured confounding using large-scale propensity score.Journal of biomedical informatics · 2022Article
- Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionObservational studies estimating severe outcomes for paracetamol versus ibuprofen use have acknowledged the specific challenge of channeling bias. A previous study relying on negative controls suggested that using large-scale propensity score (LSPS) matching may mitigate bias better than models using limited lists of covariates.
objectiveThe aim was to assess whether using LSPS matching would enable the evaluation of paracetamol, compared to ibuprofen, and increased risk of myocardial infarction, stroke, gastrointestinal (GI) bleeding, or acute renal failure. STUDY DESIGN AND
settingIn a new-user cohort study, we used two propensity score model strategies for confounder controls. One replicated the approach of controlling for a hand-picked list. The second used LSPSs based on all available covariates for matching. Positive and negative controls assessed residual confounding and calibrated confidence intervals. The data source was the Clinical Practices Research Datalink (CPRD).
resultsA substantial proportion of negative controls were statistically significant after propensity score matching on the publication covariates, indicating considerable systematic error. LSPS adjustment was less biased, but residual error remained. The calibrated estimates resulted in very wide confidence intervals, indicating large uncertainty in effect estimates once residual error was incorporated.
conclusionsFor paracetamol versus ibuprofen, when using LSPS methods in the CPRD, it is only possible to distinguish true effects if those effects are large (hazard ratio > 2). Due to their smaller hazard ratios, the outcomes under study cannot be differentiated from null effects (represented by negative controls) even if there were a true effect. Based on these data, we conclude that we are unable to determine whether paracetamol is associated with an increased risk of myocardial infarction, stroke, GI bleeding, and acute renal failure compared to ibuprofen, due to residual confounding.
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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.