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Cited by 254Statistical Methods in EpidemiologyMeta-analysis and systematic reviewsAdvanced Causal Inference Techniques

The DOI matches its Crossref record, with a small difference in title or year; 69 of the 70 references it cites were found in a registry or an index.

False Alarms and Pseudo-Epidemics: The Limitations of Observational Epidemiology

Grimes, David A., Schulz, Kenneth F.·2012·Obstetrics & Gynecology
DOI 10.1097/aog.0b013e31826af61a
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Abstract

Most reported associations in observational clinical research are false, and the minority of associations that are true are often exaggerated. This credibility problem has many causes, including the failure of authors, reviewers, and editors to recognize the inherent limitations of these studies. This issue is especially problematic for weak associations, variably defined as relative risks (RRs) or odds ratios (ORs) less than 4. Such associations, commonly reported in the medical literature, are more likely to be attributable to bias than to causal association. All observational research has bias (which can include selection, information, and confounding bias). Hence, detection of small associations falls below the discriminatory ability of observational studies. In general, unless RRs in cohort studies exceed 2 to 3 or ORs in case-control studies exceed 3 or 4, associations in observational research findings should not be considered credible. However, these guidelines are not foolproof: strong (yet spurious) associations can result when large amounts of bias are present. Only in a properly performed randomized controlled trial, free of bias, should small associations merit attention. Better training and more circumspection on the part of investigators, tougher editorial standards on the part of journals, and hefty skepticism on the part of referees and readers are necessary to avoid the dangers of false alarms, pseudo-epidemics, and their unfortunate consequences.

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Research works printed but not linked: 7

  1. Chalmers, 2007, Bull World Health Organ, 85, 658
  2. Russell, 1999, J Nat Cancer Inst Monographs, 167-, 70
  3. Smith, 1992, ancet, 340, 709
  4. Grimes, 2002, Obstet Gynecol, 100, 1344
  5. Bartholomew, 1998, urv, 53, 708
  6. Evans, 1976, Yale J Biol Med, 49, 175
  7. Shapiro, 1997, pidemiol, 50, 223

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Metadata

Authors
Grimes, D. A., & Schulz, K. F.
Affiliations
University of North Carolina at Chapel Hill (US)
ORCID
Venue
Obstetrics & Gynecology
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2012-10
Volume
120
Issue
4
Pages
920-927
ISSN
0029-7844 (ISSN-L)
DOI
10.1097/aog.0b013e31826af61a
OpenAlex
W2130635109
Cited by
254
References
70
Citations by year
2026: 5 · 2025: 13 · 2024: 14 · 2023: 13 · 2022: 17 · 2021: 23 · 2020: 27 · 2019: 18 · 2018: 30 · 2017: 19 · 2016: 18 · 2015: 25 · 2014: 19 · 2013: 10 · 2012: 2
FWCI
17.14
Type
journal article
Language
en
Open access
closed
Locations
  • Obstetrics and Gynecology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords
false alarms, weak associations, spurious association, bias in observational studies, confounding, selection bias, information bias, relative risk, odds ratio, editorial standards, peer review, randomized controlled trials
MeSH terms
Data Interpretation, Statistical, Risk, Reproducibility of Results, Cohort Studies, Bias, Causality, Odds Ratio, Case-Control Studies, Observation

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