Ratio measures in leading medical journals: structured review of accessibility of underlying absolute risks

BMJ. 2006 Dec 16;333(7581):1248. doi: 10.1136/bmj.38985.564317.7C. Epub 2006 Oct 23.

Abstract

Objective: To examine the accessibility of absolute risk in articles reporting ratio measures in leading medical journals.

Design: Structured review of abstracts presenting ratio measures.

Setting: Articles published between 1 June 2003 and 1 May 2004 in Annals of Internal Medicine, BMJ, Journal of the American Medical Association, Journal of the National Cancer Institute, Lancet, and New England Journal of Medicine.

Participants: 222 articles based on study designs in which absolute risks were directly calculable (61 randomised trials, 161 cohort studies).

Main outcome measure: Accessibility of the absolute risks underlying the first ratio measure in the abstract.

Results: 68% of articles (150/222) failed to report the underlying absolute risks for the first ratio measure in the abstract (range 55-81% across the journals). Among these articles, about half did report the underlying absolute risks elsewhere in the article (text, table, or figure) but half did not report them anywhere. Absolute risks were more likely to be reported in the abstract for randomised trials compared with cohort studies (62% v 21%; relative risk 3.0, 95% confidence interval 2.1 to 4.2) and for studies reporting crude compared with adjusted ratio measures (62% v 21%; relative risk 3.0, 2.1 to 4.3).

Conclusion: Absolute risks are often not easily accessible in articles reporting ratio measures and sometimes are missing altogether-this lack of accessibility can easily exaggerate readers' perceptions of benefit or harm.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Chi-Square Distribution
  • Cohort Studies
  • Periodicals as Topic / statistics & numerical data*
  • Randomized Controlled Trials as Topic / statistics & numerical data
  • Risk Assessment