Faculty of Pharmacy, University of Montreal, Montreal, Quebec, Canada.
School of Public Health, University of Montreal, Montreal, Quebec, Canada.
PLoS One. 2021 Mar 3;16(3):e0246691. doi: 10.1371/journal.pone.0246691. eCollection 2021.
Real-world predictors of major bleeding (MB) have been well-studied among warfarin users, but not among all direct oral anticoagulant (DOAC) users diagnosed with atrial fibrillation (AF). Thus, our goal was to build a predictive model of MB for new users of all oral anticoagulants (OAC) with AF.
We identified patients hospitalized for any cause and discharged alive in the community from 2011 to 2017 with a primary or secondary diagnosis of AF in Quebec's RAMQ and Med-Echo administrative databases. Cohort entry occurred at the first OAC claim. Patients were categorized according to OAC type. Outcomes were incident MB, gastrointestinal bleeding (GIB), non-GI extracranial bleeding (NGIB) and intracranial bleeding within 1 year of follow-up. Covariates included age, sex, co-morbidities (within 3 years before cohort entry) and medication use (within 2 weeks before cohort entry). We used logistic-LASSO and adaptive logistic-LASSO regressions to identify MB predictors among OAC users. Discrimination and calibration were assessed for each model and a global model was selected. Subgroup analyses were performed for MB subtypes and OAC types.
Our cohort consisted of 14,741 warfarin, 3,722 dabigatran, 6,722 rivaroxaban and 11,196 apixaban users aged 70-86 years old. The important MB predictors were age, prior MB and liver disease with ORs ranging from 1.37-1.64. The final model had a c-statistic of 0.63 (95% CI 0.60-0.65) with adequate calibration. The GIB and NGIB models had similar c-statistics of 0.65 (95% CI 0.63-0.66) and 0.67 (95% CI 0.64-0.70), respectively.
MB and MB subtype predictors were similar among DOAC and warfarin users. The predictors selected by our models and their discriminative potential are concordant with published data. Thus, these models can be useful tools for future pharmacoepidemiologic studies involving older oral anticoagulant users with AF.
华法林使用者的大出血（MB）的真实世界预测因素已经得到了很好的研究，但在所有诊断为房颤（AF）的直接口服抗凝剂（DOAC）使用者中却没有。因此，我们的目标是为所有新使用口服抗凝剂（OAC）的 AF 患者建立一个 MB 预测模型。
我们从魁北克省 RAMQ 和 Med-Echo 行政数据库中确定了 2011 年至 2017 年间因任何原因住院并在社区中存活出院的患者，其原发性或继发性诊断为 AF。队列纳入标准为首次使用 OAC。患者根据 OAC 类型进行分类。结果为 1 年内发生的 MB、胃肠道出血（GIB）、非胃肠道外出血（NGIB）和颅内出血。协变量包括年龄、性别、合并症（队列纳入前 3 年内）和药物使用（队列纳入前 2 周内）。我们使用逻辑 LASSO 和自适应逻辑 LASSO 回归来确定 OAC 使用者的 MB 预测因素。对每个模型的区分度和校准度进行了评估，并选择了一个总体模型。对 MB 亚型和 OAC 类型进行了亚组分析。
我们的队列包括 14741 例华法林、3722 例达比加群、6722 例利伐沙班和 11196 例阿哌沙班使用者，年龄在 70-86 岁之间。重要的 MB 预测因素是年龄、既往 MB 和肝病，其比值比（OR）范围为 1.37-1.64。最终模型的 C 统计量为 0.63（95%CI 0.60-0.65），校准度良好。GIB 和 NGIB 模型的 C 统计量分别为 0.65（95%CI 0.63-0.66）和 0.67（95%CI 0.64-0.70）。
DOAC 和华法林使用者的 MB 和 MB 亚型预测因素相似。我们的模型选择的预测因素及其区分能力与已发表的数据一致。因此，这些模型可用于未来涉及 AF 的老年口服抗凝剂使用者的药物流行病学研究。
