Claims-based score for the prediction of bleeding in a contemporary cohort of patients receiving oral anticoagulation for venous thromboembolism

BACKGROUND: Current scores for bleeding risk assessment in patients with venous thromboembolism (VTE) undergoing oral anticoagulation have limited predictive capacity. We developed and internally validated a bleeding prediction model using healthcare claims data. METHODS AND RESULTS: We selected patients with incident VTE initiating oral anticoagulation in the 2011 to 2017 MarketScan databases. Hospitalized bleeding events were identified using validated algorithms in the 180 days after VTE diagnosis. We evaluated demographic factors, comorbidities, and medication use before oral anticoagulation initiation as potential predictors of bleeding using stepwise selection of variables in Cox models run on 1000 bootstrap samples of the patient population. Variables included in >60% of all models were selected for the final analysis. We internally validated the model using boot-strapping and correcting for optimism. We included 165 434 patients with VTE and initiating oral anticoagulation, of whom 2294 had a bleeding event. After undergoing the variable selection process, the final model included 20 terms (15 main effects and 5 interactions). The c-statistic for the final model was 0.68 (95% CI, 0.67–0.69). The internally validated c-statistic corrected for optimism was 0.68 (95% CI, 0.67–0.69). For comparison, the c-statistic of the Hypertension, Abnormal Renal/Liver Function, Stroke, Bleeding History or Predisposition, Labile International Normalized Ratio, Elderly (>65 Years), Drugs/Alcohol Concomitantly (HAS-BLED) score in this population was 0.62 (95% CI, 0.61–0.63). CONCLUSIONS: We have developed a novel model for bleeding prediction in VTE using large healthcare claims databases. Performance of the model was moderately good, highlighting the urgent need to identify better predictors of bleeding to inform treatment decisions.