Association of Race/Ethnicity With Oral Anticoagulant Use in Patients With Atrial Fibrillation: Findings From the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II

Utibe R Essien; DaJuanicia N Holmes; Larry R Jackson, II; Gregg C Fonarow; Kenneth W Mahaffey; James A Reiffel; Benjamin A Steinberg; Larry A Allen; Paul S Chan; James V Freeman; Rosalia G Blanco; Karen S Pieper; Jonathan P Piccini; Eric D Peterson; Daniel E Singer

doi:10.1001/jamacardio.2018.3945

. 2018 Nov 28;3(12):1174–1182. doi: 10.1001/jamacardio.2018.3945

Association of Race/Ethnicity With Oral Anticoagulant Use in Patients With Atrial Fibrillation

Findings From the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II

Utibe R Essien ^1,², DaJuanicia N Holmes ³, Larry R Jackson II ³, Gregg C Fonarow ⁴, Kenneth W Mahaffey ⁵, James A Reiffel ⁶, Benjamin A Steinberg ⁷, Larry A Allen ⁸, Paul S Chan ⁹, James V Freeman ¹⁰, Rosalia G Blanco ³, Karen S Pieper ³, Jonathan P Piccini ³, Eric D Peterson ³, Daniel E Singer ^1,^2,^✉

¹Division of General Internal Medicine, Massachusetts General Hospital, Boston

²Harvard Medical School, Boston, Massachusetts

³Duke Clinical Research Institute, Durham, North Carolina

⁴Division of Cardiology, University of California, Los Angeles

⁵Stanford Center for Clinical Research, Stanford University School of Medicine, Stanford, California

⁶College of Physicians and Surgeons, Columbia University, New York, New York

⁷Division of Cardiovascular Medicine, University of Utah Health Sciences Center, Salt Lake City

⁸Division of Cardiology, University of Colorado School of Medicine, Aurora

⁹Saint Luke’s Mid America Heart Institute and the University of Missouri, Kansas City

¹⁰Yale School of Medicine, New Haven, Connecticut

^✉

Corresponding Author: Daniel E. Singer, MD, Division of General Internal Medicine, Massachusetts General Hospital, 100 Cambridge St, Room 1652, Boston, MA 02114 (desinger@mgh.harvard.edu).

Accepted for Publication: October 9, 2018.

Published Online: November 28, 2018. doi:10.1001/jamacardio.2018.3945

Author Contributions: Dr Singer and Ms Holmes had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Essien, Fonarow, Mahaffey, Reiffel, Allen, Piccini, Peterson, Singer.

Acquisition, analysis, or interpretation of data: Essien, Holmes, Jackson, Fonarow, Mahaffey, Steinberg, Chan, Freeman, Blanco, Pieper, Peterson, Singer.

Drafting of the manuscript: Essien, Blanco, Singer, Holmes.

Critical revision of the manuscript for important intellectual content: Essien, Holmes, Jackson, Fonarow, Mahaffey, Reiffel, Steinberg, Allen, Chan, Freeman, Pieper, Piccini, Peterson.

Statistical analysis: Holmes, Singer.

Obtained funding: Piccini, Peterson.

Administrative, technical, or material support: Steinberg, Blanco, Piccini, Singer.

Supervision: Essien, Mahaffey, Steinberg, Allen, Pieper.

Conflict of Interest Disclosures: Dr Fonarow reports serving as a consultant to Janssen. Dr Mahaffey reports receiving research grants from Afferent, Amgen, Apple Inc, AstraZeneca, Cardiva Medical Inc, Daiichi Sankyo, Ferring, Google (Verily), Johnson and Johnson, Luitpold, Medtronic, Merck, Novartis, Sanofi, St Jude, and Tenax; receiving consulting fees from Ablynx, AstraZeneca, Baim Institute, Boehringer Ingelheim, BristolMyers Squibb, Cardiometabolic Health Congress, Elsevier, GlaxoSmith Kline, Johnson and Johnson, Medergy, Medscape, Merck, Mitsubishi, Myokardia, Novartis, Oculeve, Portola, Springer Publishing, Theravance, University of California–San Francisco, and WebMD; and holding equity in Bioprint Fitness. Dr Reiffel reports receiving research funding from Janssen and Medtronic; serving as a consultant for Janssen, Acesion, InCardia Therapeutics, Portola, and Medtronic; and receiving speaker’s fee from Janssen. Dr Steinberg reports receiving research support from Janssen and Boston Scientific and consulting fees from Janssen and Bayer. Dr Allen reports receiving research funding from Patient-Centered Outcomes Research Institute, American Heart Association, and the National Institutes of Health and consulting fees from Janssen, Boston Scientific, and Cytokinetics. Dr Chan reports receiving research funding from the American Heart Association and consulting fees from Optum Rx. Dr Freeman reports receiving research funding from the Nationl Heart, Blood, and Lung Institute and consulting fees from Janssen, Boston Scientific, and Biosense Webster. Dr Piccini reports receiving grants from Abbott Laboratories, ARCA Biopharma, Boston Scientific, German AFNET, Gilead, Janssen, and Verily and consulting fees from Bayer AG, GlaxoSmith Kline, Johnson and Johnson, Medtronic, Sanofi-Aventis, Philips, and Allergan. Dr Peterson reports receiving research grants from Abiomed, AstraZeneca, Bayer AG, Janssen, Merck, Novartis, Regeneron, Sanofi-Aventis, and Society of Thoracic Surgeons and consulting fees from Bayer, Janssen, Sanofi-Aventis, and Livongo. Dr Singer reports serving as a consultant/advisory board member for Boehringer Ingelheim, Bristol-Myers Squibb, CVS Health, Merck, Johnson and Johnson, Medtronic, and Pfizer and receiving research grants from Boehringer Ingelheim and Bristol-Myers Squibb.

Funding/Support: The ORBIT-AF II registry is sponsored by Janssen Scientific Affairs, LLC. This study was suppported by the Eliot B. and Edith C. Shoolman Fund of Massachusetts General Hospital (Dr Singer) and the National Research Service Award (grant T32 HP10251; Dr Essien).

Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: Gregg C. Fonarow is Section Editor of JAMA Cardiology, but he was not involved in any of the decisions regarding review of the manuscript or its acceptance.

Additional Contributions: The authors thank the staff and participants of the ORBIT-AF Registry for their important contributions to this work.

^✉

Corresponding author.

PMCID: PMC6583087 PMID: 30484833

Key Points

Question

Are there racial/ethnic differences in the use of oral anticoagulants, particularly direct-acting oral anticoagulants, in patients with atrial fibrillation?

Findings

In this multicenter US-based registry study of a cohort of 12 147 outpatients with atrial fibrillation, black patients were significantly less likely to receive direct-acting oral anticoagulants than white patients, even after controlling for clinical and sociodemographic features; no difference between white patients and Hispanic patients was observed.

Meaning

Reducing disparities in stroke prevention for patients with atrial fibrillation may improve overall quality of care and result in reduced complication rates.

This cohort study uses data from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II to assess racial/ethnic differences in the use of oral anticoagulants by patients with atrial fibrillation.

Abstract

Importance

Black and Hispanic patients are less likely than white patients to use oral anticoagulants for atrial fibrillation. Little is known about racial/ethnic differences in use of direct-acting oral anticoagulants (DOACs) for atrial fibrillation.

Objective

To assess racial/ethnic differences in the use of oral anticoagulants, particularly DOACs, in patients with atrial fibrillation.

Design, Setting, and Participants

This cohort study used data from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II, a prospective, US-based registry of outpatients with nontransient atrial fibrillation 21 years and older who were followed up from February 2013 to July 2016. Data were analyzed from February 2017 to February 2018.

Exposures

Self-reported race/ethnicity as white, black, or Hispanic.

Main Outcomes and Measures

The primary outcome was use of any oral anticoagulant, particularly DOACs. Secondary outcomes included the quality of anticoagulation received and oral anticoagulant discontinuation at 1 year.

Results

Of 12 417 patients, 11 100 were white individuals (88.6%), 646 were black individuals (5.2%), and 671 were Hispanic individuals (5.4%) with atrial fibrillation. After adjusting for clinical features, black individuals were less likely to receive any oral anticoagulant than white individuals (adjusted odds ratio [aOR], 0.75 [95% CI, 0.56, 0.99]) and less likely to receive DOACs if an anticoagulant was prescribed (aOR, 0.63 [95% CI, 0.49-0.83]). After further controlling for socioeconomic factors, oral anticoagulant use was no longer significantly different in black individuals (aOR, 0.78 [95% CI, 0.59-1.04]); among patients using oral anticoagulants, DOAC use remained significantly lower in black individuals (aOR, 0.73 [95% CI, 0.55-0.95]). There was no significant difference between white and Hispanic groups in use of oral anticoagulants. Among patients receiving warfarin, the median time in therapeutic range was lower in black individuals (57.1% [IQR, 39.9%-72.5%]) and Hispanic individuals (51.7% [interquartile range {IQR}, 39.1%-66.7%]) than white individuals (67.1% [IQR, 51.8%-80.6%]; P < .001). Black and Hispanic individuals treated with DOACs were more likely to receive inappropriate dosing than white individuals (black patients, 61 of 394 [15.5%]; Hispanic patients, 74 of 409 [18.1%]; white patients, 1003 of 7988 [12.6%]; P = .01). One-year persistence on oral anticoagulants was the same across groups.

Conclusions and Relevance

After controlling for clinical and socioeconomic factors, black individuals were less likely than white individuals to receive DOACs for atrial fibrillation, with no difference between white and Hispanic groups. When atrial fibrillation was treated, the quality of anticoagulant use was lower in black and Hispanic individuals. Identifying modifiable causes of these disparities could improve the quality of care in atrial fibrillation.

Introduction

Atrial fibrillation (AF) is the most common heart rhythm disorder in the United States and a significant risk factor for ischemic stroke.^1,2,3,4 Long-term oral anticoagulant therapy (OAC) can reduce the stroke risk attributable to AF.^5,6 While the prevalence of AF is lower in black individuals, they face a higher risk of stroke.^7,8,9 Similarly, the prevalence of AF is lower in Hispanic patients but with poorer outcomes observed compared with white patients with AF.^10,11,12

Prior studies have shown that anticoagulation use in underrepresented ethnic groups with AF is lower than in white individuals, with some of this disparity explained by socioeconomic status.^13,14 Time in the therapeutic range (TTR) of international normalized ratio (INR) of 2.0 to 3.0 on warfarin, a measure of anticoagulation quality, has also been shown to be lower in black patients compared with white patients, as well as in patients with limited English proficiency, increasing the stroke risk in these populations.^15,16 However, these studies did not examine whether these differences in AF care extended to the use of direct-acting oral anticoagulants (DOACs).^17,18,19,20

We assessed contemporary racial/ethnic disparities in the use of warfarin and DOACs for patients with AF in the US-based Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II (ORBIT-AF II). The objectives of our analysis were to determine the rates of warfarin and DOAC use in patients with AF by race/ethnicity, assess the appropriateness of anticoagulant use by race/ethnicity per standard guidelines based on patients’ CHA₂DS₂-VASc scores,²¹ and examine anticoagulant quality and persistence by race/ethnicity.

Methods

Study Design

The rationale, design, and methods of the ORBIT-AF II registry have been published previously.²² Briefly, ORBIT-AF II is a prospective, multicenter, US-based registry of outpatients with AF. Patients were enrolled at 244 sites by various health care professionals, including primary care physicians, general cardiologists, and electrophysiologists. The ORBIT-AF II study only enrolled patients who either had a new diagnosis of AF within the prior 6 months or started receiving a DOAC for AF within the prior 3 months. The ORBIT-AF I cohort was not used in the current analysis since it preceded widespread use of DOAC medications.²³ Eligible patients were those 21 years or older with electrocardiographically documented AF. Patients with transient AF owing to a reversible cause (eg, postoperative status), solitary atrial flutter without AF, or an estimated life expectancy of less than 6 months were excluded. A web-based case report form was used to collect patient demographics, medical history, medications, vital signs, laboratory data (including INR tests), imaging, and electrocardiographic parameters. Changes in pharmacotherapy, cardiac rhythm, and subsequent cardiovascular events and procedures were documented in follow-up.

Participants in the ORBIT-AF II study provided written informed consent, and sites received regulatory board approval for this study pursuant to local regulations. The study was coordinated by the Duke Clinical Research Institute and approved by the Duke University Institutional Review Board.

Study Population

Between February 2013 and July 2016, the registry enrolled 13 404 patients. Follow-up occurred at 6-month intervals and lasted 12 to 24 months, depending on enrollment date. At baseline, patients were asked to identify their race and ethnicity. Racial/ethnic groups were treated as mutually exclusive. For the present analysis, patients who selected identifiers other than “White,” “Black/African American,” or “Hispanic/Latino” at intake were excluded. We also excluded patients without any available follow-up information.

Statistical Analysis

Use of anticoagulants at the index ORBIT-II enrollment visit and other baseline characteristics were compared across race/ethnicity. Categorical variables are presented as frequencies and percentages, with differences between groups assessed by the χ² test. Continuous variables are presented as median (interquartile range [IQR]) with differences between groups assessed by the Kruskal-Wallis test.

Racial/ethnic comparisons of percentages of any anticoagulant use, warfarin use, and DOAC use overall and in groups stratified by CHA₂DS₂-VASc scores (an index composed of points for congestive heart failure; hypertension; age ≥75 years; diabetes mellitus; prior stroke, transient ischemic attack, or thromboembolism; vascular disease; age 65-74 years; and sex category [female]) less than 2 or 2 or greater were assessed by the χ² test. A multivariable logistic regression model with site as a random effect was used to evaluate the association between race/ethnicity and overall OAC use at baseline. The same model strategy was repeated for the association between race/ethnicity and DOAC use at baseline among patients on any OAC. The white racial group served as the reference group. Continuous variables, nonlinear with respect to the outcome, were fit with linear splines. The model was adjusted for patient characteristics that might explain the association between race/ethnicity and outcomes, including clinical characteristics (eg, medical history, laboratory data, medications, and AF type), clinician type, and sociodemographic characteristics (eg, education, insurance type, and median household income). Median household income was obtained from the American Community Survey (5-year estimate for the 2010-2014 data set) and linked using patient zip code.

Missing data (nonresponses) on the covariates used in the modeling was handled with multiple imputation, and imputed values were obtained by Markov chain Monte Carlo or regression methods. All variables included for adjustment had less than 5% missing, except for left ventricular ejection fraction (1339 of 12417 [10.8%]), estimated glomerular filtration rate (885 of 12417 [7.1%]), hematocrit (1435 of 12417 [11.6%]), and hemoglobin levels (1368 of 12417 [11.0%]). Associations are presented with odds ratios (ORs), 95% CIs, and P values.

The discontinuation of OAC medications was defined as a report of discontinuation of OAC with a discontinuation date and a patient’s receiving no OAC at the following visit. This definition minimizes discontinuations that are temporary. Time to discontinuation is displayed via a Kaplan-Meier plot. A Cox frailty model, with a random effect for site, was used to evaluate the association between race/ethnicity and OAC discontinuation before and after adjustment for potential confounders. Associations are presented as hazard ratios, 95% CIs, and P values.

We assessed quality of warfarin anticoagulation by TTR as calculated from the first INR to the last INR available, using the Rosendaal method.²⁴ Any inter-INR test gaps greater than 8 weeks (ie, 56 days) were excluded. The median TTR length during follow-up was compared across groups with the Kruskal-Wallis test. For patients receiving DOACs at baseline, quality was assessed by whether the dose prescribed matched the US Food and Drug Administration label for each patient, given the patient’s age, weight, renal function, and concomitant medications, as previously described.²² The percentage of patients classified as appropriately dosed was compared across race/ethnicity by the χ² test.

Statistical analyses were performed using SAS version 9.4 (SAS Institute), and 2-tailed P values <.05 were considered significant for all statistical tests. Data analysis occurred from February 2017 to February 2018.

Results

The baseline ORBIT-AF II population included 13 404 patients enrolled at 244 sites from February 2013 to July 2016. For this analysis, we excluded 546 patients who identified as races/ethnicities other than white, black, or Hispanic. We also excluded 1 patient who was taking more than 1 anticoagulant and 440 patients without any follow-up information. This yielded a study cohort of 12 417 patients, including 9166 patients with newly diagnosed AF (within 6 months of study entry). A total of 8572 of 12 417 patients (69.0%) were enrolled by general cardiologists, 2806 of 12 417 (22.6%) by electrophysiologists, and 942 of 12 417 (7.6%) by internists or primary care clinicians. Within this cohort, 11 100 patients (89.4%) were white, 646 (5.2%) were black, and 671 (5.4%) were Hispanic (Table 1).

Table 1. Patient Characteristics at Baseline by Race and Ethnicity.

Demographic	Patients, No. (%)			P Value
Demographic	White (n = 11 100)	Black (n = 646)	Hispanic (n = 671)	P Value
Age, median (IQR)	71.0 (64.0-78.0)	67.0 (60.0-76.0)	72.0 (64.0-80.0)	<.001
Female	4544 (40.9)	300 (46.4)	315 (46.9)	<.001
Insurance
Private	5947 (53.6)	242 (37.5)	297 (44.3)	<.001
Medicaid	318 (2.9)	75 (11.6)	104 (15.5)
Medicare	4326 (39.0)	252 (39.0)	198 (29.5)
Other	372 (3.4)	63 (9.8)	58 (8.6)
None	137 (1.2)	14 (2.2)	14 (2.1)
Education level
Some school	853 (7.7)	123 (19.0)	228 (34.0)	<.001
High school graduate	5392 (48.6)	361 (55.9)	281 (41.9)
College graduate	3291 (29.6)	111 (17.2)	124 (18.5)
Postgraduate	1078 (9.7)	22 (3.4)	25 (3.7)
Household income, median (IQR), $	56 354 (45 056-75 180)	42 580 (33 557-52 572)	51 010 (40 180-64 089)	<.001
CHA₂DS₂-VASc score^a
Low (0)	447 (4.0)	23 (3.6)	23 (3.4)	.06
Medium (1)	1228 (11.1)	60 (9.3)	60 (8.9)
High (≥2)	9425 (84.9)	563 (87.2)	588 (87.6)
ORBIT bleeding score^b
Low (0-2 points)	7336 (66.1)	366 (56.7)	363 (54.1)	<.001
Medium (3 points)	1496 (13.5)	117 (18.1)	88 (13.1)
High (≥4 points)	1536 (13.8)	117 (18.1)	113 (16.8)
Smoking history
Never	5639 (50.8)	334 (51.7)	463 (69.0)	<.001
Current	792 (7.1)	62 (9.6)	28 (4.2)
Former	4669 (42.0)	250 (38.7)	180 (26.8)
Hypertension	8770 (79.0)	572 (88.5)	567 (84.5)	<.001
Hyperlipidemia	7214 (65.0)	397 (61.5)	410 (61.1)	.03
Diabetes	2759 (24.9)	238 (36.8)	264 (39.3)	<.001
Congestive heart failure	2333 (21.0)	214 (33.1)	141 (21.0)	<.001
History of coronary artery disease	2986 (26.9)	162 (25.1)	150 (22.4)	.02
Prior cerebrovascular accident	1212 (10.9)	90 (13.9)	80 (11.9)	.049
BMI, median (IQR)^c	29.8 (26.0-34.9)	31.2 (26.9-37.9)	29.9 (26.2-34.4)	<.001
Systolic blood pressure, median (IQR), mm Hg^c	126.0 (116.0-138.0)	130.0 (120.0-142.0)	128.0 (118.0-140.0)	<.001
Clinician specialty
Primary care	736 (6.6)	64 (9.9)	142 (21.2)	<.001
Cardiology	7682 (69.2)	419 (64.9)	471 (70.2)
Electrophysiology	2585 (23.3)	163 (25.2)	58 (8.6)
Neurology	96 (0.9)	0 (0.0)	0 (0.0)
Site region
West	1979 (17.8)	80 (12.4)	321 (47.8)	<.001
Northeast	2186 (19.7)	70 (10.8)	68 (10.1)
Midwest	2527 (22.8)	83 (12.8)	26 (3.9)
South	4408 (39.7)	413 (63.9)	256 (38.2)
Contraindication to anticoagulation^d	675 (6.1)	37 (5.7)	32 (4.8)	.36

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Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); IQR, interquartile range.

^{^a}

CHA₂DS₂-VASc stands for congestive heart failure; hypertension; age 75 years or older; diabetes mellitus; prior stroke, transient ischemic attack, or thromboembolism; vascular disease; age 65 to 74 years; and sex category (female).

^{^b}

ORBIT stands for older age (≥75 years); reduced hemoglobin, hematocrit, or history of anemia; bleeding history; insufficient kidney function; and treatment with an antiplatelet agent.

^{^c}

Values are median (IQR).

^{^d}

Included in contraindication to anticoagulation are a need for dual antiplatelet therapy, high bleeding risk, change in renal function, prior intracranial hemorrhage, and frequent falls or frailty.

Relative to white patients and Hispanic patients, black patients were significantly younger (median [IQR] age, white patients, 71.0 [64.0-78.0] years; black patients, 67.0 [60.0-76.0] years; Hispanic patients, 72.0 [64.0-80.0] years; P < .001; Table 1). Relative to white patients, black patients and Hispanic patients were more likely to be women (white patients, 4544 of 11100 [40.9%]; black patients, 300 of 646 [46.4%]; Hispanic patients, 315 of 671 [46.9%]; P < .001), more likely to have Medicaid health insurance (white patients, 318 [2.9%]; black patients, 75 [11.6%]; Hispanic patients, 104 [15.5%]; P < .001), and less likely to be college graduates (white patients, 3291 [29.6%]; black patients, 111 [17.2%]; Hispanic patients, 124 [18.5%]; P < .001) than white patients.

Black patients and Hispanic patients were more likely to have a high ORBIT bleeding risk score (white patients, 1536 [13.8%]; black patients, 117 [18.1%]; Hispanic patients, 113 [16.8%]; P < .001). (The ORBIT score assigns points for older age [≥75 years]; reduced hemoglobin, hematocrit, or history of anemia; bleeding history; insufficient kidney function; and treatment with an antiplatelet agent. In this study, a score of 4 or more points on a scale of 0 to 7 points was considered high.)

Black patients and Hispanic patients were also more likely to have a diagnosis of hypertension (white patients, 8770 [79.0%]; black patients, 572 [88.5%]; Hispanic patients, 567 [84.5%]; P < .001) and diabetes (white patients, 2759 [24.9%]; black patients; 238 [36.8%]; Hispanic patients, 264 [39.3%]; P < .001), and a history of stroke (white patients, 1212 [10.9%]; black patients, 90 [13.9%]; Hispanic patients, 80 [11.9%]; P = .049). In addition, they had higher median (IQR) systolic blood pressure levels (white patients, 126.0 [116.0-138.0] mm Hg; black patients, 130.0 [120.0-142.0] mm Hg; Hispanic patients: 128.0 [118.0-140.0] mm Hg; P < .001). Black patients had higher median body mass index values (calculated as weight in kilograms divided by height in meters squared) than the other groups did (white patients, 29.8 [26.0-34.9]; black patients, 31.2 [26.9-37.9]; Hispanic patients, 29.9 [26.2-34.4]; P < .001). Hispanic patients and black patients were more likely than white patients to be enrolled in the study by a primary care clinician (white patients, 736 [6.6%]; black patients, 64 [9.9%]; Hispanic patients, 142 [21.2%]; P < .001). Most black patients were from the South (n = 413 [63.9%]), nearly half of Hispanic patients were from the West (n = 321 [47.8%]), and white patients were more evenly distributed over US geographic regions, although the largest proportion came from the South (n = 4408 [39.7%]).

Physicians reported contraindications to oral anticoagulant therapy (including high bleeding risk, frequent falls, and frailty). The proportion with contraindications did not differ by race/ethnicity (Table 1).

Overall OAC use, either with warfarin or DOACs, was high, with 9865 of 11 100 white patients (88.9%), 544 of 646 black patients (84.2%), and 586 of 671 Hispanic patients (87.3%) reporting taking any OAC (Table 2). The unadjusted OR for any anticoagulant use among black patients compared with white patients was 0.71 (95% CI, 0.56-0.90). After adjusting for baseline clinical features, the OR increased modestly to 0.75 (95% CI, 0.56-0.99) (Table 2). There was no significant difference observed in OAC use between Hispanic patients and white patients (adjusted OR [aOR], 0.90 [95% CI, 0.66-1.23]).

Table 2. Association Between Race/Ethnicity and Use of Any Oral Anticoagulant.

Racial/Ethnic Group	Patients Using OACs, No. (%)	Unadjusted		Adjusted for Baseline Clinical Features^a		Adjusted for Additional Baseline Socioeconomic Markers^b
Racial/Ethnic Group	Patients Using OACs, No. (%)	Odds Ratio (95%CI)	P Value	Odds Ratio (95%CI)	P Value	Odds Ratio (95%CI)	P Value
White (n = 11 000)	9865 (88.9)	1 [Reference]	NA	1 [Reference]	NA	1 [Reference]	NA
Black (n = 646)	544 (84.2)	0.71 (0.56-0.90)	.005	0.75 (0.56-0.99)	0.04	0.78 (0.59-1.04)	.09
Hispanic (n = 671)	586 (87.3)	0.85 (0.65-1.12)	.25	0.90 (0.66-1.23)	0.50	0.98 (0.71-1.36)	.92

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Abbreviations: NA, not applicable; OAC, oral anticoagulant.

^{^a}

Baseline clinical features include demographics, medical history, medications, laboratory data, atrial fibrillation status, and enrolling physician specialty.

^{^b}

Baseline socioeconomic markers include median household income by zip code, level education, and insurance type. US geographic region is also included in this regression model.

Among patients receiving any OAC, DOACs were used more frequently than warfarin and differences between black patients and white patients were more clearly evident; the unadjusted OR was 0.60 (95% CI, 0.46-0.77). After adjustment for clinical features, the aOR was 0.63 (95% CI, 0.49-0.83) (Table 3). There was no significant difference observed in DOAC use between Hispanic individuals and white individuals (aOR, 0.92 [95% CI, 0.69-1.22]).

Table 3. Association Between Race/Ethnicity and Direct-Acting Oral Anticoagulant Use Among Patients Taking Oral Anticoagulants.

Racial/Ethnic Group	Patients Using DOACs, No. (%)	Unadjusted		Adjusted for Baseline Clinical Features^a		Adjusted for Additional Baseline Socioeconomic Markers^b
Racial/Ethnic Group	Patients Using DOACs, No. (%)	Odds Ratio (95%CI)	P Value	Odds Ratio (95%CI)	P Value	Odds Ratio (95%CI)	P Value
White (n = 9865)	8403 (85.2)	1 [Reference]	NA	1 [Reference]	NA	1 [Reference]	NA
Black (n = 544)	423 (77.8)	0.60 (0.46-0.77)	<.001	0.63 (0.49-0.83)	<.001	0.73 (0.55-0.95)	.02
Hispanic (n = 586)	465 (79.4)	0.83 (0.64-1.09)	.19	0.92 (0.69-1.22)	.56	1.10 (0.81-1.49)	.54

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Abbreviations: DOAC, direct-acting oral anticoagulant, NA, not applicable.

^{^a}

Baseline clinical features include demographics, medical history, medications, laboratory data, atrial fibrillation status, and enrolling physician specialty.

^{^b}

Baseline socioeconomic markers include median household income, level education, and insurance type. Geographic region is also included in this regression model.

Across race/ethnicity, overall anticoagulant use was greater for those with CHA₂DS₂-VASc scores of 2 or more (9614 of 10 576 [90.9%]) than with those with CHA₂DS₂-VASc scores less than 2 (1381 of 1841 [75.0%]; P < .001) (Figure). Both black patients and Hispanic patients with CHA₂DS₂-VASc scores of 2 or more were less likely to receive DOACs than white patients (black patients, 67.5% [95% CI, 63.6%-71.4%]; Hispanic patients, 69.9% [95% CI, 66.2%-73.6%]; white patients, 77.0% [95% CI, 76.1%-77.8%]). Notably, differences between black and white patients persisted among patients with a CHA₂DS₂-VASc score less than 2 (black patients, 51.8% [95% CI, 41.1%-62.6%] vs white patients, 68.6% [95% CI, 66.4%-70.8%]), with no significant difference observed between white patients and Hispanic patients (65.1% [95% CI, 54.8%-75.3%]).

Figure. — CHA₂DS₂-VASc indicates a score composed of points for congestive heart failure; hypertension; age ≥75 years; diabetes mellitus; prior stroke, transient ischemic attack, or thromboembolism; vascular disease; age 65-74 years; and sex category (female).

Adjusting for Socioeconomic Status

Additional adjusting for level of education, median household income by zip code, and insurance type, the markers of socioeconomic status, as well as region, produced a small change in the OR of use of any anticoagulant by black patients or white patients, but the value was no longer significant (aOR, 0.78 [95% CI, 0.59-1.04]; Table 2). (Complete results of the full model are provided in eTable 1 in the Supplement.) Addition of socioeconomic status markers reduced the difference between black patients and white patients with respect to DOAC use, but the independent effect of race remained significant (aOR, 0.73 [95% CI, 0.55-0.95]) (Table 3; eTable 2 in the Supplement). After adjustment for socioeconomic status, there remained no significant difference between Hispanic patients and white patients in any anticoagulant use (aOR, 0.98 [95% CI, 0.71-1.36]) or in DOAC use (aOR, 1.10 [95% CI, 0.81-1.49]). When the analyses were restricted to the 9166 patients with newly diagnosed AF, the results were highly similar (eTables 3 and 4 in the Supplement).

Anticoagulation Quality and Persistence

The study cohort included 1704 patients with AF who were treated with warfarin. The median number of INR tests during the follow-up period for patients taking warfarin for whom a TTR could be calculated (ie, those having at least 2 INR tests) was 18 (IQR, 8-26). The median number of INR tests by race/ethnicity was 17 (IQR, 8-26) for white patients, 18 (IQR, 8-26) for black patients, and 23 (IQR, 9-31) for Hispanic patients. Of patients taking warfarin, 799 of 1704 (46.9%) had their INRs managed by an anticoagulation clinic, with 72 of 121 Hispanic patients (59.5%) compared with 60 of 121 black patients (49.6%) and 667 of 1462 white patients (45.6%) followed up at such clinics. Relative to white patients, the median TTR was markedly lower in black patients and Hispanic patients (white patients, 67.1% [IQR, 51.8%-80.6%]; black patients, 57.1% [IQR, 39.9%-72.5%]; Hispanic patients, 51.7% [IQR, 39.1%-66.7%]; Table 4). Specifically, black patients (20.0% [IQR, 8.7%-41.2%]) and Hispanic patients (27.4% [IQR, 15.5%-41.0%]) had a significantly higher percentage of time spent with INR less than 2 than white patients did (16.0% [5.0%-29.4%]), with no significant difference observed in percent time with INR greater than 3.

Table 4. Quality of Anticoagulant Use by Race/Ethnicity.

Characteristic	Patients Overall	White Patients	Black Patients	Hispanic Patients	P Value
Warfarin
No.	1704	1462	121	121
Time in therapeutic range during follow-up, median (IQR), %^a	66.0 (50.0-79.3)	67.1 (51.8-80.6)	57.1 (39.9-72.5)	51.7 (39.1-66.7)	<.001
Time spent with international normalized ratio, %, median (IQR)
<2	17.0 (5.7-31.6)	16.0 (5.0-29.4)	20.0 (8.7-41.2)	27.4 (15.5-41.0)	<.001
>3	10.8 (1.4-21.2)	10.4 (0.8-20.4)	11.5 (2.5-22.4)	13.5 (2.2-23.6)	.23
Dose of direct-acting oral anticoagulant, No. (%)
No.	8791	7988	394	409
Underdose	824 (9.4)	726 (9.1)	44 (11.2)	54 (13.2)	.01
Appropriate	7653 (87.1)	6985 (87.4)	333 (84.5)	335 (81.9)
Excessive	314 (3.6)	277 (3.5)	17 (4.3)	20 (4.9)

Open in a new tab

Abbrevation: IQR, interquartile range.

^{^a}

Missing 26.1% of data in the time in therapeutic range in follow-up overall, including 26.1% of white patients, 28.1% of black patients, and 24.8% of Hispanic patients.

Overall, DOAC dosing differed from that specified on the Food and Drug Administration label in 13.0% of cases. Such inappropriate DOAC dosing was seen in 15.5% of black patients (underdosing, 44 of 394 patients [11.2%]; excessive dosing, 17 patients [4.3%]) and 18.1% of Hispanic patients (underdosing, 54 of 409 patients [13.2%]; excessive dosing, 20 patients [4.9%]) compared with 12.6% of white patients (underdosing, 726 of 7988 patients [9.1%]; excessive dosing, 277 patients [3.5%]; P = .01 for differences across the 3 groups) (Table 4). Most inappropriate dosing of DOACs was underdosing.

The time to discontinuation of anticoagulation was similar across racial/ethnic groups (eFigure in the Supplement). After adjusting for patient sociodemographic and clinical factors, the adjusted hazard ratio for discontinuing anticoagulant therapy was 0.88 (95% CI, 0.70-1.12) for black patients and 0.99 (95% CI, 0.79-1.25) for Hispanic patients compared with white patients.

Discussion

Anticoagulation is standard therapy for patients with AF who are at increased stroke risk. Racial and ethnic disparities in anticoagulant use have been described previously.^25,26 However, few studies have explored racial/ethnic disparities in the use of DOACs by patients with AF. We examined the association between race/ethnicity and the use of any OAC, and specifically DOACs, in patients with AF in the ORBIT-AF II registry. There are several notable findings from this analysis. First, although OAC use was high in the ORBIT-AF II registry, black patients were less likely to use any OAC than white patients and were particularly less likely to use DOACs. Hispanic patients, however, had similar treatment rates with any OAC and DOACs as white patients. Second, while we expected to see the difference in race mediated by socioeconomic status, differences between black and white patients largely persisted despite inclusion of socioeconomic markers in our statistical models. Third, anticoagulation quality was poorer in black patients and Hispanic patients, with lower overall TTR and lower rates of appropriate DOAC dosing. Lastly, rates of discontinuation of OAC were similar across races/ethnicities.

Prior studies have addressed racial/ethnic disparities in the use of anticoagulants in AF. Using the American College of Cardiology National Cardiovascular Data Registry’s outpatient registry, Katz et al²⁷ found that black patients with AF had a lower odds of receiving any OAC (OR, 0.85 [95% CI, 0.81-0.90]) and specifically DOAC prescriptions (OR, 0.66 [95% CI, 0.60-0.73]) compared with white patients. A limitation of this study was its high rate of missing data (29.7%-33.0%) for race/ethnicity. Using Get with the Guidelines–Stroke data, Patel et al²⁸ found the aOR of receiving DOAC therapy was 1.2 times greater for white patients than for nonwhite patients with AF (95% CI, 1.09-1.32), but this study only included patients who were hospitalized with stroke.

Using a random sample of Medicare beneficiaries newly diagnosed with AF, researchers found that black race was significantly associated with a lower odds of receiving DOACs (ie, dabigatran and rivaroxaban) compared with receiving warfarin.²⁹ The study period for this report from Medicare concluded on December 31, 2012, and was thus unlikely to represent current DOAC usage patterns. The earlier ORBIT-AF I registry also observed differences in anticoagulant use and treatment quality by race/ethnicity.³⁰ However, the ORBIT-AF I study was unable to assess contemporary use of DOAC medications. Additionally, none of these studies included detailed data on INR measures and DOAC dosing, as the present analysis does.

There have been several possible reasons proposed to explain racial/ethnic disparities in AF management. First, limited access to specialists in minority populations has been described and remains an important target of interventions to reduce disparities.³¹ In our study, a higher percentage of black patients and Hispanic patients than white patients were enrolled by primary care physicians. While we observed that internal medicine and primary care clinicians were less likely to prescribe DOACs than cardiologists and electrophysiologists, our results were adjusted for clinician type (eTables 1 and 2 in the Supplement). Second, out-of-pocket costs for DOACs may be a greater barrier to their use among patients in lower socioeconomic brackets. Adjustment for socioeconomic status did not substantially reduce the racial differences in our results, but our control for economic determinants is incomplete. Others have also highlighted the roles of health literacy, patient perceptions, patient adherence, implicit bias, and trust in medical care as additional explanations of racial/ethnic disparities in care.^{16,32,33,34,35} This study cannot address these latter features. Detailed assessment of the respective roles and preferences of patients and physicians in the anticoagulation decision is merited.

Notably, we found that increased rates of OAC use among white patients extended to patients with CHA₂DS₂-VASc scores less than 2, a group at low risk of stroke in which there may be little net benefit of OACs. Such possible overuse is consistent with other observations of potentially harmful medical overuse among individuals of higher socioeconomic status in the United States.³⁶ While racial/ethnic disparities are usually marked by underuse, overuse in racial/ethnic majority populations is another reasonable target for quality improvement initiatives.

As we and others have shown, the quality of warfarin treatment is lower in racial/ethnic minority patients than white patients, and poor TTR is associated with increased stroke risk.^37,38 Further, black patients with AF were less likely to receive DOACs, which are easier to use than warfarin and likely safer.^39,40 Recent evidence has shown that medication adherence is higher for DOACs than for warfarin.⁴¹ This increase in adherence to DOACs over warfarin may serve as a way to improve anticoagulant treatment in racial/ethnic minority patients with AF. Our findings are particularly notable given this population’s access to health care (ie, all included patients were recruited from medical clinics).

This analysis has several strengths. It is, to our knowledge one of the first studies to compare baseline use of DOACs by race/ethnicity as well as the quality of DOAC use. The data were obtained from a prospectively assembled registry with detailed clinical information and close follow-up, thereby avoiding pitfalls of alternative designs, such as administrative database analyses.⁴²

Limitations

There are also potential limitations to our analyses. First, because this was an observational study, we cannot exclude the possibility of residual or unmeasured confounding. Second, there can be concerns about the representativeness of patients enrolled in registries. The ORBIT-AF II registry sought recruitment sites throughout the United States, but investigator participation was voluntary, and patients had to agree to enter the study through the informed consent process.⁴³ These aspects of study design may raise concerns whether these findings apply to the broad population of patients with AF.⁴⁴ The proportion of patients in the ORBIT-AF II registry overall who were taking anticoagulants was 89%, higher than that reported from cohorts that were less selective. For example, a recent claims-based study from the Veterans’ Administration reported 63% of patients with AF were taking anticoagulants.²⁵

Similarly, the overall average TTR of patients taking warfarin in the ORBIT-AF II registry, 67%, is higher than the average TTR of 56% reported by the Veteran’s Administration.²⁵ However, despite these higher overall indices of anticoagulation quality, we still observed clear racial disparities in use of anticoagulants in the ORBIT-AF II registry. Notably, the difference between black patients and white patients in TTR in this study (−10%) was very similar to the difference observed in the VA study (−8%).²⁵ As a result, the racial disparities we report appear to be more broadly generalizable.

A third limitation of our analyses is the reduced statistical power of some racial/ethnic comparisons. This issue is common in studies of AF, owing to the overall lower prevalence of AF in racial/ethnic minority populations along with limited representation of such minorities in clinical trials and registries.⁴⁵ Fourth, patients in the ORBIT-AF II registry were preferentially selected if they were starting a DOAC. This sampling feature increased the proportion using DOACs but still allowed evaluation of racial and ethnic differences in the use of these anticoagulants. Lastly, our measures of socioeconomic status were limited and measures such as zip-code level income may not have fully characterized an individual’s socioeconomic status.

Conclusions

In the ORBIT-AF II registry of patients with AF, we found reduced use of OAC therapy in black patients compared with white patients and Hispanic patients. These differences persisted after controlling for socioeconomic markers and region. The effect was particularly pronounced for DOAC use. We also found that anticoagulation quality in black patients and Hispanic patients was inferior to that that in white patients, with lower TTR values in those taking warfarin and modestly greater underdosing in patients taking DOACs. These results contribute toward understanding racial/ethnic differences in stroke-preventive treatment in patients with AF. Novel approaches are needed to address modifiable causes of racial/ethnic disparities in anticoagulant use, a central issue in improving the overall quality of care for patients with AF.

Supplement.

eTable 1. Association between Race, Ethnicity and any OAC use at baseline, including demographic and clinical features, enrolling physician specialty, and socioeconomic markers

eTable 2. Association between Race, Ethnicity and DOAC use at baseline among patients on an OAC, including demographic and clinical features, enrolling physician specialty, and socioeconomic markers

eTable 3. Association between Race/Ethnicity and any OAC use, restricted to patients newly diagnosed with atrial fibrillation

eTable 4. Association between Race/Ethnicity and DOAC use among patients on an OAC, restricted to patients newly diagnosed with atrial fibrillation

eFigure. Kaplan-Meier plot representing the time to discontinuation of any oral anticoagulant by race/ethnicity over one year

Click here for additional data file.^{(233.3KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable 1. Association between Race, Ethnicity and any OAC use at baseline, including demographic and clinical features, enrolling physician specialty, and socioeconomic markers

eTable 3. Association between Race/Ethnicity and any OAC use, restricted to patients newly diagnosed with atrial fibrillation

eTable 4. Association between Race/Ethnicity and DOAC use among patients on an OAC, restricted to patients newly diagnosed with atrial fibrillation

eFigure. Kaplan-Meier plot representing the time to discontinuation of any oral anticoagulant by race/ethnicity over one year

Click here for additional data file.^{(233.3KB, pdf)}

[hoi180059r1] 1.Magnani JW, Rienstra M, Lin H, et al. . Atrial fibrillation: current knowledge and future directions in epidemiology and genomics. Circulation. 2011;124(18):1982-1993. doi: 10.1161/CIRCULATIONAHA.111.039677 [DOI] [PMC free article] [PubMed] [Google Scholar]

[hoi180059r2] 2.Go AS, Hylek EM, Phillips KA, et al. . Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the Anticoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. JAMA. 2001;285(18):2370-2375. doi: 10.1001/jama.285.18.2370 [DOI] [PubMed] [Google Scholar]

[hoi180059r3] 3.Wolf PA, D’Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: a risk profile from the Framingham Study. Stroke. 1991;22(3):312-318. doi: 10.1161/01.STR.22.3.312 [DOI] [PubMed] [Google Scholar]

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PERMALINK

Association of Race/Ethnicity With Oral Anticoagulant Use in Patients With Atrial Fibrillation

Utibe R Essien, MD, MPH

DaJuanicia N Holmes, MS

Larry R Jackson II, MD

Gregg C Fonarow, MD

Kenneth W Mahaffey, MD

James A Reiffel, MD

Benjamin A Steinberg, MD, MHS

Larry A Allen, MD, MHS

Paul S Chan, MD, MSc

James V Freeman, MD, MPH, MS

Rosalia G Blanco, MBA

Karen S Pieper, MS

Jonathan P Piccini, MD, MHS

Eric D Peterson, MD, MPH

Daniel E Singer, MD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Design

Study Population

Statistical Analysis

Results

Table 1. Patient Characteristics at Baseline by Race and Ethnicity.

Table 2. Association Between Race/Ethnicity and Use of Any Oral Anticoagulant.

Table 3. Association Between Race/Ethnicity and Direct-Acting Oral Anticoagulant Use Among Patients Taking Oral Anticoagulants.

Figure. Association Between Race/Ethnicity and Use of Anticoagulants by Patients With Atrial Fibrillation by CHA2DS2-VASc Stroke Scores of Less Than 2 or 2 or Greater.

Adjusting for Socioeconomic Status

Anticoagulation Quality and Persistence

Table 4. Quality of Anticoagulant Use by Race/Ethnicity.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Figure. Association Between Race/Ethnicity and Use of Anticoagulants by Patients With Atrial Fibrillation by CHA₂DS₂-VASc Stroke Scores of Less Than 2 or 2 or Greater.