ArticleDrug safety2013
Variation in choice of study design: findings from the Epidemiology Design Decision Inventory and Evaluation (EDDIE) survey.
Article in Drug safety, 2013. 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
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
9 citing papers in PubMed, 14 citations in OpenAlex.
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- Unreformed nutritional epidemiology: a lamp post in the dark forest.European journal of epidemiology · 2019Article
- A Multiagent System for Integrated Detection of Pharmacovigilance Signals.Journal of medical systems · 2016Article
- The impact of standardizing the definition of visits on the consistency of multi-database observational health research.BMC medical research methodology · 2015Article
- Computational approaches for pharmacovigilance signal detection: toward integrated and semantically-enriched frameworks.Drug safety · 2015Article
- Authors' reply to Hennessy and Leonard's comment on "Desideratum for evidence-based epidemiology".Drug safety · 2015Article
- Empirical performance of a new user cohort method: lessons for developing a risk identification and analysis system.Drug safety · 2013Article
- Desideratum for evidence based epidemiology.Drug safety · 2013Review
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 at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResearchers using observational data to understand drug effects must make a number of analytic design choices that suit the characteristics of the data and the subject of the study. Review of the published literature suggests that there is a lack of consistency even when addressing the same research question in the same database.
objectiveTo characterize the degree of similarity or difference in the method and analysis choices made by observational database research experts when presented with research study scenarios. RESEARCH
designOn-line survey using research scenarios on drug-effect studies to capture method selection and analysis choices that follow a dependency branching based on response to key questions. SUBJECTS: Voluntary participants experienced in epidemiological study design solicited for participation through registration on the Observational Medical Outcomes Partnership website, membership in particular professional organizations, or links in relevant newsletters. MEASURES: Description (proportion) of respondents selecting particular methods and making specific analysis choices based on individual drug-outcome scenario pairs. The number of questions/decisions differed based on stem questions of study design, time-at-risk, outcome definition, and comparator.
resultsThere is little consistency across scenarios, by drug or by outcome of interest, in the decisions made for design and analyses in scenarios using large healthcare databases. The most consistent choice was the cohort study design but variability in the other critical decisions was common.
conclusionsThere is great variation among epidemiologists in the design and analytical choices that they make when implementing analyses in observational healthcare databases. These findings confirm that it will be important to generate empiric evidence to inform these decisions and to promote a better understanding of the impact of standardization on research implementation.
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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.