Evidence map›Paper›PMID 25083251›Full record

ArticleTherapeutic advances in drug safety2013

Does design matter? Systematic evaluation of the impact of analytical choices on effect estimates in observational studies.

David Madigan, Patrick B Ryan, Martijn Schuemie

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. 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 · 2022
    Trial
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  9. Computational drug repositioning of atorvastatin for ulcerative colitis.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

David MadiganProfessor and Chair, Department of Statistics, Columbia University, 1255 Amsterdam Ave., New York, NY 10027, USA.
Patrick B RyanObservational Medical Outcomes Partnership, Foundation for the National Institutes of Health, Bethesda, MD and Janssen Research and Development LLC, Titusville, NJ, USA.
Martijn SchuemieObservational Medical Outcomes Partnership, Foundation for the National Institutes of Health, Bethesda, MD and Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

analysishealthcare databasehealth outcomesstudy design

Identifiers

PMID25083251
PMCPMC4110833

What OpenQuestion holds

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Registered trials

None linked

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.