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Selection in Reported Epidemiological Risks: An Empirical Assessment

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  • Fotini K Kavvoura
  • George Liberopoulos
  • John P A Ioannidis

Abstract

Background: Epidemiological studies may be subject to selective reporting, but empirical evidence thereof is limited. We empirically evaluated the extent of selection of significant results and large effect sizes in a large sample of recent articles. Methods and Findings: We evaluated 389 articles of epidemiological studies that reported, in their respective abstracts, at least one relative risk for a continuous risk factor in contrasts based on median, tertile, quartile, or quintile categorizations. We examined the proportion and correlates of reporting statistically significant and nonsignificant results in the abstract and whether the magnitude of the relative risks presented (coined to be consistently ≥1.00) differs depending on the type of contrast used for the risk factor. In 342 articles (87.9%), ≥1 statistically significant relative risk was reported in the abstract, while only 169 articles (43.4%) reported ≥1 statistically nonsignificant relative risk in the abstract. Reporting of statistically significant results was more common with structured abstracts, and was less common in US-based studies and in cancer outcomes. Among 50 randomly selected articles in which the full text was examined, a median of nine (interquartile range 5–16) statistically significant and six (interquartile range 3–16) statistically nonsignificant relative risks were presented (p = 0.25). Paradoxically, the smallest presented relative risks were based on the contrasts of extreme quintiles; on average, the relative risk magnitude was 1.41-, 1.42-, and 1.36-fold larger in contrasts of extreme quartiles, extreme tertiles, and above-versus-below median values, respectively (p

Suggested Citation

  • Fotini K Kavvoura & George Liberopoulos & John P A Ioannidis, 2007. "Selection in Reported Epidemiological Risks: An Empirical Assessment," PLOS Medicine, Public Library of Science, vol. 4(3), pages 1-10, March.
    • Handle: RePEc:plo:pmed00:0040079
    DOI: 10.1371/journal.pmed.0040079
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    References listed on IDEAS

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    1. Zhenglun Pan & Thomas A Trikalinos & Fotini K Kavvoura & Joseph Lau & John PA Ioannidis, 2005. "Local Literature Bias in Genetic Epidemiology: An Empirical Evaluation of the Chinese Literature," PLOS Medicine, Public Library of Science, vol. 2(12), pages 1-1, November.
    2. Jan P Vandenbroucke & Erik von Elm & Douglas G Altman & Peter C Gøtzsche & Cynthia D Mulrow & Stuart J Pocock & Charles Poole & James J Schlesselman & Matthias Egger & for the STROBE Initiative, 2007. "Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration," PLOS Medicine, Public Library of Science, vol. 4(10), pages 1-27, October.
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