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. 2020 May;31(3):359-364.
doi: 10.1097/EDE.0000000000001173.

Aim for Clinical Utility, Not Just Predictive Accuracy

Michael C Sachs  1 , Arvid Sjölander  2 , Erin E Gabriel  2
Affiliations

Aim for Clinical Utility, Not Just Predictive Accuracy

Michael C Sachs et al. Epidemiology. 2020 May.

Abstract

The predictions from an accurate prognostic model can be of great interest to patients and clinicians. When predictions are reported to individuals, they may decide to take action to improve their health or they may simply be comforted by the knowledge. However, if there is a clearly defined space of actions in the clinical context, a formal decision rule based on the prediction has the potential to have a much broader impact. The use of a prediction-based decision rule should be formalized and preferably compared with the standard of care in a randomized trial to assess its clinical utility; however, evidence is needed to motivate such a trial. We outline how observational data can be used to propose a decision rule based on a prognostic prediction model. We then propose a framework for emulating a prediction driven trial to evaluate the clinical utility of a prediction-based decision rule in observational data. A split-sample structure is often feasible and useful to develop the prognostic model, define the decision rule, and evaluate its clinical utility. See video abstract at, http://links.lww.com/EDE/B656.

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Conflict of interest statement

The authors report no conflicts of interest.

Figures

FIGURE 1.
FIGURE 1.
Overview of the target prediction-model based trial in which patients are randomized to a prediction-based treatment decision rule versus standard of care.
FIGURE 2.
FIGURE 2.
Overview of strategies for split sample prediction model training and clinical utility assessment in observational settings.
See this image and copyright information in PMC

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