Clinical prediction rules. A review and suggested modifications of methodological standards

JAMA. 1997 Feb 12;277(6):488-94.


Background: Clinical prediction rules are decision-making tools for clinicians, containing variables from the history, physical examination, or simple diagnostic tests.

Objective: To review the quality of recently published clinical prediction rules and to suggest methodological standards for their development and evaluation.

Data sources: Four general medical journals were manually searched for clinical prediction rules published from 1991 through 1994.

Study selection: Four hundred sixty potentially eligible reports were identified, of which 30 were clinical prediction rules eligible for study. Most methodological standards could only be evaluated in 29 studies.

Data abstraction: Two investigators independently evaluated the quality of each report using a standard data sheet. Disagreements were resolved by consensus.

Data synthesis: The mathematical technique was used to develop the rule, and the results of the rule were described in 100% (29/29) of the reports. All the rules but 1 (97% [28/29]) were felt to be clinically sensible. The outcomes and predictive variables were clearly defined in 83% (24/29) and 59% (17/29) of the reports, respectively. Blind assessment of outcomes and predictive variables occurred in 41% (12/29) and 79% (23/29) of the reports, respectively, and the rules were prospectively validated in 79% (11/14). Reproducibility of predictive variables was assessed in only 3% (1/29) of the reports, and the effect of the rule on clinical use was prospectively measured in only 3% (1/30). Forty-one percent (12/29) of the rules were felt to be easy to use.

Conclusions: Although clinical prediction rules comply with some methodological criteria, for other criteria, better compliance is needed.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Decision Support Techniques*
  • Models, Statistical
  • Outcome and Process Assessment, Health Care
  • Predictive Value of Tests
  • Reproducibility of Results