A new model to predict ischemic stroke in patients with atrial fibrillation using warfarin or direct oral anticoagulants

Background: Stroke risk stratification scores (eg, CHA₂DS₂-VASc) are used to tailor therapeutic recommendations for patients with atrial fibrillation (AF) in different risk groups. Objective: The purpose of this study was to develop a tool to estimate stroke risk in patients receiving oral anticoagulants (OACs) and to identify patients who remain at high risk for stroke despite anticoagulation therapy. Methods: Patients with nonvalvular AF initiating OACs were identified in the MarketScan data from 2007 to 2015. Using bootstrapping methods and backward selection of 44 candidate variables, we developed a model that selected variables predicting stroke. The final model was validated in patients with nonvalvular AF in the Optum database in the period 2009–2015. In both databases, the discrimination of existing stroke scores were individually evaluated and compared with our new model termed the AntiCoagulaTion-specific Stroke (ACTS) score. Results: Among 135,523 patients with AF initiating OACs in the MarketScan dataset, 2028 experienced an ischemic stroke after anticoagulant initiation. The stepwise model identified 11 variables (including type of OAC) associated with ischemic stroke. The discrimination (C statistic) of the model was adequate (0.68; 95% confidence interval [CI] 0.66–0.70), showing excellent calibration (χ² = 6.1; P = .73). ACTS was then applied to 84,549 AF patients in the Optum dataset (1408 stroke events) and showed similar discrimination (C statistic 0.67; 95% CI 65-0.69). However, previously developed predictive models had similar discriminative ability (CHA₂DS₂-VASc 0.67; 95% CI 0.65–0.68). Conclusion: A novel model to identify AF patients at higher risk of ischemic stroke, using extensive administrative health care data including type of anticoagulant, did not perform better than established simpler models.