Predictive ability of scores for bleeding risk in heart disease outpatients on warfarin in Brazil

INTRODUCTION: Bleeding is a common complication in patients taking warfarin. We sought to compare the performance of nine prediction models for bleeding risk in warfarin-treated Brazilian outpatients. METHODS: The dataset was derived from a clinical trial conducted to evaluate the efficacy of an anticoagulation clinic at a public hospital in Brazil. Overall, 280 heart disease outpatients taking warfarin were enrolled. The prediction models OBRI, Kuijer et al., Kearon et al., HEMORR(2)HAGES, Shireman et al., RIETE, HAS-BLED, ATRIA and ORBIT were compared to evaluate the overall model performance by Nagelkerke’s R(2) estimation, discriminative ability based on the concordance (c) statistic and calibration based on the Hosmer-Lemeshow goodness-of-fit statistic. The primary outcomes were the first episodes of major bleeding, clinically relevant non-major bleeding and non-major bleeding events within 12 months of follow-up. RESULTS: Major bleeding occurred in 14 participants (5.0%), clinically relevant non-major bleeding in 29 (10.4%), non-major bleeding in 154 (55.0%) and no bleeding at all in 115 (41.1%). Most participants with major bleeding had their risk misclassified. All the models showed low overall performance (R(2) 0.6–9.3%) and poor discriminative ability for predicting major bleeding (c <0.7), except Shireman et al. and ORBIT models (c 0.725 and 0.719, respectively). Results were not better for predicting other bleedings. All models showed good calibration for major bleeding. CONCLUSIONS: Only two models (Shireman et al. and ORBIT) showed at least acceptable performance in the prediction of major bleeding in warfarin-treated Brazilian patients. Accurate models warrant further investigation to be used in similar populations.