Novel bleeding prediction model in atrial fibrillation patients on new oral anticoagulants

OBJECTIVE: Clinical models such as the HAS-BLED (standing for Hypertension, Abnormal liver/renal function, Stroke history, Bleeding history or predisposition, Labile INR, Elderly, Drug/alcohol usage) were developed to predict risk of major bleeding on vitamin K antagonists/antiplatelet therapy. We aimed to develop a model that will improve the ability to predict major bleeding events in patients with non-valvular atrial fibrillation (AF) treated with new oral anticoagulants (NOACs). METHODS: Clalit Health Services is the largest of four integrated healthcare organisations in Israel, which insures 4.7 million patients (53% of the population). We identified in Clalit Health Services all patients with AF, new users of an NOAC (2013-2017), and followed them until first occurrence of a major bleeding event, death, switch to another oral anticoagulant, 30 days after discontinuation of NOAC or end of follow-up (31 December 2019). Importance of the candidate model variables was estimated by inclusion frequencies across forward selection algorithm applied to 50 bootstrap samples. Then, backward selection algorithm using the modified Bayesian Information Criterion for competing risks was applied to select predictors for the final model. RESULTS: /µL), concurrent antiplatelet therapy, hypertension, prior major bleeding, risk factors for a fall, low cholesterol level and low estimated glomerular filtration rate, with apparent area-under-curve (AUC) of 0.6546. Applicability of the model was then shown for 14 118 and 5450 patients with AF, initiators of dabigatran and rivaroxaban, where the score achieved c indices of 0.62 and 0.61, respectively. CONCLUSIONS: We present a novel and simple risk score for prediction of major bleeding in patients with non-valvular AF treated with NOACs. Validation in additional cohorts is warranted.