{"doi":"10.17615/a0tg-2y46","title":"Factors Driving Anticoagulant Selection in Patients With Atrial Fibrillation in the United States","abstract":"With the introduction of novel oral anticoagulants (NOACs), the factors driving anticoagulant selection in atrial fibrillation (AF) in real-world practice are unclear. The goal was to examine whether and to what extent utilization has been driven by predictions of stroke risk (treatment benefit), bleeding risk (treatment harm), or prescription benefits’ coverage. We extracted a cohort of non-valvular AF patients initiating anticoagulation from Oct 2010-Dec 2012 from a large US database of commercial and Medicare supplement claims. Multivariable regression examined associations between ischemic stroke (CHA2DS2-VASc) and bleeding (ATRIA) risk scores and benefits’ generosity (proportion of costs covered by patients relative to total) with warfarin and NOAC selection and also between dabigatran and rivaroxaban. C-statistics and partial chi-square statistics were used to assess the variation explained. Of 70,498 patients initiating anticoagulation, 29.9% and 7.9% used dabigatran and rivaroxaban, respectively. Compared with warfarin, patients were less likely to receive a NOAC with high ischemic stroke risk (CHA2DS2-VASc ≥2) (Adjusted Relative Risk [aRR]: 0.75, 95% CI: 0.72-0.77) and high bleeding risk (ATRIA≥5) (aRR: 0.66, 95% CI: 0.64-0.69) but more likely with good benefits’ generosity (≤20% of costs borne by patient) (aRR: 2.03, 95% CI: 1.92-2.16). Prescription generosity explained almost twice the model variation as either risk score. Compared with dabigatran, patients were more likely to fill rivaroxaban with high bleeding risk (aRR: 1.16, 95% CI: 1.09-1.24). In conclusion, patients with higher bleeding and ischemic stroke risk were more likely to initiate warfarin, but generous benefits more strongly predicted NOAC usage and drove more selection.","journal":"UNC Libraries","year":2021,"id":230244,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7359,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":323291,"name":"Anil K. Gehi","orcid":"0000-0002-6724-5294","position":1,"is_corresponding":false},{"id":395612,"name":"Julie C. Lauffenburger","orcid":"0000-0002-4940-4140","position":2,"is_corresponding":false},{"id":387632,"name":"Joel F. Farley","orcid":"0000-0002-5196-5238","position":3,"is_corresponding":false},{"id":836050,"name":"Gang Fang","orcid":"0000-0003-3561-5876","position":4,"is_corresponding":false},{"id":540857,"name":"M. Alan Brookhart","orcid":"0000-0003-1572-0564","position":5,"is_corresponding":false},{"id":836049,"name":"Denise H. Rhoney","orcid":"0000-0003-0646-6111","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:55:05.844766Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}