Figure 4.

Decision curve analysis. Net benefit of using a model to predict 1-year event of death as compared with strategies of ‘assume high risk to all’ or ‘assume low risk to all’ for different thresholds. A multivariable model based on all clinical information was used for comparison. The analysis is based on 24 348 patients from the ARISTOTLE and RE-LY trials. ABC-death—Age, Biomarkers (cardiac troponin, NT-proBNP, and GDF-15), Clinical history of heart failure). All clinical information—a model solely consisting of clinical variables (age, gender, smoking, alcohol, prior stroke/TIA, diabetes, hypertension, heart failure, prior myocardial infarction, peripheral arterial disease, vascular disease, AF-type, and prior bleeding). As an example, in a population with approximately 37 deaths per 1000 person-years, for a decision threshold of 5% 1-year risk of death, compared with not using any model the ABC-death model would identify 10 additional true deaths within 1 year per 1000 subjects, without increasing the number of false positive predictions. Not using a model would assume that all subjects have the same risk and is illustrated by the two alternatives of either assuming all are at low risk or that all are at high risk. The corresponding net benefit of using a model with all clinical information is five additional true deaths.