Clinical prediction rules

doi:10.1136/bmj.b2899

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Gavin Falk, clinical research fellow,
Tom Fahey, professor of general practice

¹Department of General Practice, Royal College of Surgeons in Ireland Medical School, Dublin 2, Republic of Ireland

Correspondence to: T Fahey tomfahey{at}rcsi.ie

In this pair of articles, Gavin Falk and Tom Fahey (doi:10.1136/bmj.b2899) set out what to consider when using a clinical prediction rule, and Dan Mayer (doi:10.1136/bmj.b2901) shows how one such rule, the Ottawa ankle rules, is applied

What are they?

Clinical prediction rules quantify the contribution of symptoms, clinical signs, and available diagnostic tests, and stratify patients according to the probability of having a target disorder.1 The outcome of interest can be diverse and be anywhere along the diagnostic, prognostic, and therapeutic spectrum. Developing and validating a clinical prediction rule is a form of observational epidemiological research that requires referring to specific methodological standards.2 3

These rules usually go through three distinct stages before they are used in a clinical setting:

Development of the rule—establishing the independent and combined effect of explanatory variables (or clinical predictors), which can be symptoms, signs, or diagnostic tests
Narrow and broad validation—the explanatory variables or clinical predictors in the derivation set are assessed in separate populations
Impact analysis—a randomised controlled trial measures the impact of applying the rule in a clinical setting in terms of patient outcome, health professionals’ behaviour, resource use, or any combination of these.

The CAGE score (box) is a clinical example of a rule developed to aid in the diagnosis of alcohol abuse.