ArticleProceedings of the National Academy of Sciences of the United States of America2018
Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 8 of them syntheses that pooled it.
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
104 citing papers in PubMed, 8 syntheses or guidelines pooled it, 157 citations in OpenAlex.
- Differences in clinical features between axial psoriatic arthritis and axial spondyloarthritis: a systematic review and meta-analysis of observational studies.Frontiers in medicine · 2026Pooled it
- Use of sensitivity analyses to assess uncontrolled confounding from unmeasured variables in observational, active comparator pharmacoepidemiologic studies: a systematic review.American journal of epidemiology · 2025Pooled it
- Ranitidine Use and Incident Cancer in a Multinational Cohort.JAMA network open · 2023Pooled it
- Pooled it
- Comparative risk of thrombosis with thrombocytopenia syndrome or thromboembolic events associated with different covid-19 vaccines: international network cohort study from five European countries and the US.BMJ (Clinical research ed.) · 2022Pooled it
- ODACH: a one-shot distributed algorithm for Cox model with heterogeneous multi-center data.Scientific reports · 2022Pooled it
- Repurposing anti-inflammasome NRTIs for improving insulin sensitivity and reducing type 2 diabetes development.Nature communications · 2020Pooled it
- Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis.Lancet (London, England) · 2019Pooled it
- Observational methods for COVID-19 vaccine effectiveness research: an empirical evaluation and target trial emulation.International journal of epidemiology · 2024Trial
- Evaluating large-scale propensity score adjustment when sample size is small.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Methylphenidate and Long-Term Risk of Cardiovascular Diseases: A Nationwide Cohort Study.Pharmacoepidemiology and drug safety · 2026Article
- GLP-1 Receptor Agonists and Risk of Skin Cancer in Adults With Type 2 Diabetes: A Target Trial Emulation.Diabetes, obesity & metabolism · 2026Article
- Association of Herpes Simplex Virus Type-1 With Dementia Outcomes: Longitudinal Retrospective Cohort Study Using Real-World Electronic Health Record Data.JMIR formative research · 2026Article
- Negative controls and how to use them: a guidance paper.International journal of epidemiology · 2026Article
- Empirical-Null Calibration Challenges Comparative CNS Safety Signals for Androgen-Receptor Pathway Inhibitors: A FAERS Re-Analysis.Pharmaceuticals (Basel, Switzerland) · 2026Article
- How Negative Controls Are Used in Pharmacoepidemiology: A Methodological Scoping Review of Real-World Observational Studies of Glucagon-Like Peptide-1 Receptor Agonists.Pharmacoepidemiology and drug safety · 2026Article
- Real-world performance of large-scale propensity score adjustment strategies: Matching, weighting, and stratification.Research square · 2026Article
- Comparative Cardiovascular Effectiveness of Glucagon-Like Peptide 1 Receptor Agonists and Sodium-Glucose Cotransporter 2 Inhibitors in Diabetes Mellitus.Journal of the American College of Cardiology · 2026Article
- Association of serum lipid levels with incident periodontitis in a multicenter study.Clinical oral investigations · 2026Article
- Comparison of Cardiovascular Events in Patients Receiving Concomitant Clopidogrel and Proton Pump Inhibitors Classified by CYP2C19 Inhibitory Potency.Arteriosclerosis, thrombosis, and vascular biology · 2026Observational
44 more citing papers are in PubMed but not listed here.
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 at 4 institutions in 1 country.
Funding
Abstract
Observational healthcare data, such as electronic health records and administrative claims, offer potential to estimate effects of medical products at scale. Observational studies have often been found to be nonreproducible, however, generating conflicting results even when using the same database to answer the same question. One source of discrepancies is error, both random caused by sampling variability and systematic (for example, because of confounding, selection bias, and measurement error). Only random error is typically quantified but converges to zero as databases become larger, whereas systematic error persists independent from sample size and therefore, increases in relative importance. Negative controls are exposure-outcome pairs, where one believes no causal effect exists; they can be used to detect multiple sources of systematic error, but interpreting their results is not always straightforward. Previously, we have shown that an empirical null distribution can be derived from a sample of negative controls and used to calibrate
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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.