Clinical prediction rules

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.