Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators.

ABSTRACT:

Context

Urologists regularly develop clinical risk prediction models to support clinical decisions. In contrast to traditional performance measures, decision curve analysis (DCA) can assess the utility of models for decision making. DCA plots net benefit (NB) at a range of clinically reasonable risk thresholds.

Objective

To provide recommendations on interpreting and reporting DCA when evaluating prediction models.

Evidence acquisition

We informally reviewed the urological literature to determine investigators' understanding of DCA. To illustrate, we use data from 3616 patients to develop risk models for high-grade prostate cancer (n=313, 9%) to decide who should undergo a biopsy. The baseline model includes prostate-specific antigen and digital rectal examination; th

SUBMITTER: Van Calster B 

PROVIDER: S-EPMC6261531 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature