ArticleTherapeutic advances in drug safety2013
Does design matter? Systematic evaluation of the impact of analytical choices on effect estimates in observational studies.
Article in Therapeutic advances in drug safety, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 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
14 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Grilling the data: application of specification curve analysis to red meat and all-cause mortality.Journal of clinical epidemiology · 2024Pooled it
- Methods for drug safety signal detection using routinely collected observational electronic health care data: A systematic review.Pharmacoepidemiology and drug safety · 2023Pooled it
- Field-wide meta-analyses of observational associations can map selective availability of risk factors and the impact of model specifications.Journal of clinical epidemiology · 2016Pooled it
- The Mortality Risk of Proton Pump Inhibitors in 1.9 Million US Seniors: An Extended Cox Survival Analysis.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2022Trial
- Illustrating an Adaptive Prespecification Framework for Observational Research: Target Trial Emulations Comparing Immunomodulator Treatments for COVID-19.Epidemiology (Cambridge, Mass.) · 2025Article
- Automating assignment of HIV+ patients into phenogroups from demography bound phenotype attack rates.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Evaluating the performance of temporal pattern discovery: new application using statins and rhabdomyolysis in OMOP databases.BMC medical informatics and decision making · 2022Article
- Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.Clinical pharmacology and therapeutics · 2022Article
- Computational drug repositioning of atorvastatin for ulcerative colitis.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities.Statistics in medicine · 2020Article
- Article
- Referral for Specialist Follow-up and Its Association With Post-discharge Mortality Among Patients With Systolic Heart Failure (from the National Heart Failure Audit for England and Wales).The American journal of cardiology · 2017Article
- Feasibility and utility of applications of the common data model to multiple, disparate observational health databases.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Variation in choice of study design: findings from the Epidemiology Design Decision Inventory and Evaluation (EDDIE) survey.Drug safety · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinical studies that use observational databases, such as administrative claims and electronic health records, to evaluate the effects of medical products have become commonplace. These studies begin by selecting a particular study design, such as a case control, cohort, or self-controlled design, and different authors can and do choose different designs for the same clinical question. Furthermore, published papers invariably report the study design but do not discuss the rationale for the specific choice. Studies of the same clinical question with different designs, however, can generate different results, sometimes with strikingly different implications. Even within a specific study design, authors make many different analytic choices and these too can profoundly impact results. In this paper, we systematically study heterogeneity due to the type of study design and due to analytic choices within study design. METHODS AND
findingsWe conducted our analysis in 10 observational healthcare databases but mostly present our results in the context of the GE Centricity EMR database, an electronic health record database containing data for 11.2 million lives. We considered the impact of three different study design choices on estimates of associations between bisphosphonates and four particular health outcomes for which there is no evidence of an association. We show that applying alternative study designs can yield discrepant results, in terms of direction and significance of association. We also highlight that while traditional univariate sensitivity analysis may not show substantial variation, systematic assessment of all analytical choices within a study design can yield inconsistent results ranging from statistically significant decreased risk to statistically significant increased risk. Our findings show that clinical studies using observational databases can be sensitive both to study design choices and to specific analytic choices within study design.
conclusionMore attention is needed to consider how design choices may be impacting results and, when possible, investigators should examine a wide array of possible choices to confirm that significant findings are consistently identified.
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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.