Validation, updating and impact of clinical prediction rules: A review

Objective To provide an overview of the research steps that need to follow the development of diagnostic or prognostic prediction rules. These steps include validity assessment, updating (if necessary), and impact assessment of clinical prediction rules. Study Design and Setting Narrative review covering methodological and empirical prediction studies from primary and secondary care. Results In general, three types of validation of previously developed prediction rules can be distinguished: temporal, geographical, and domain validations. In case of poor validation, the validation data can be used to update or adjust the previously developed prediction rule to the new circumstances. These update methods differ in extensiveness, with the easiest method a change in model intercept to the outcome occurrence at hand. Prediction rules—with or without updating—showing good performance in (various) validation studies may subsequently be subjected to an impact study, to demonstrate whether they change physicians' decisions, improve clinically relevant process parameters, patient outcome, or reduce costs. Finally, whether a prediction rule is implemented successfully in clinical practice depends on several potential barriers to the use of the rule. Conclusion The development of a diagnostic or prognostic prediction rule is just a first step. We reviewed important aspects of the subsequent steps in prediction research.