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Research Article
Originally Published 21 July 2015
Open Access

Comparison of the Short-Term Risk of Bleeding and Arterial Thromboembolic Events in Nonvalvular Atrial Fibrillation Patients Newly Treated With Dabigatran or Rivaroxaban Versus Vitamin K Antagonists: A French Nationwide Propensity-Matched Cohort Study

Abstract

Background—

The safety and effectiveness of non–vitamin K antagonist (VKA) oral anticoagulants, dabigatran or rivaroxaban, were compared with VKA in anticoagulant-naive patients with nonvalvular atrial fibrillation during the early phase of anticoagulant therapy.

Methods and Results—

With the use of the French medico-administrative databases (SNIIRAM and PMSI), this nationwide cohort study included patients with nonvalvular atrial fibrillation who initiated dabigatran or rivaroxaban between July and November 2012 or VKA between July and November 2011. Patients presenting a contraindication to oral anticoagulants were excluded. Dabigatran and rivaroxaban new users were matched to VKA new users by the use of 1:2 matching on the propensity score. Patients were followed for up to 90 days until outcome, death, loss to follow-up, or December 31 of the inclusion year. Hazard ratios of hospitalizations for bleeding and arterial thromboembolic events were estimated in an intent-to-treat analysis using Cox regression models. The population was composed of 19 713 VKA, 8443 dabigatran, and 4651 rivaroxaban new users. All dabigatran- and rivaroxaban-treated patients were matched to 16 014 and 9301 VKA-treated patients, respectively. Among dabigatran-, rivaroxaban-, and their VKA-matched–treated patients, 55 and 122 and 31 and 68 bleeding events and 33 and 58 and 12 and 28 arterial thromboembolic events were observed during follow-up, respectively. After matching, no statistically significant difference in bleeding (hazard ratio, 0.88; 95% confidence interval, 0.64–1.21) or thromboembolic (hazard ratio, 1.10; 95% confidence interval, 0.72–1.69) risk was observed between dabigatran and VKA new users. Bleeding (hazard ratio, 0.98; 95% confidence interval, 0.64–1.51) and ischemic (hazard ratio, 0.93; 95% confidence interval, 0.47–1.85) risks were comparable between rivaroxaban and VKA new users.

Conclusions—

In this propensity-matched cohort study, our findings suggest that physicians should exercise caution when initiating either non-VKA oral anticoagulants or VKA in patients with nonvalvular atrial fibrillation.

Introduction

Long-term prophylaxis with oral anticoagulants (OACs) is now widely recommended by international guidelines to prevent stroke in all patients with atrial fibrillation (AF) without contraindications presenting an independent risk factor for stroke.13
Clinical Perspective on p 1260
However, there are several important considerations in the management of patients taking OACs, starting with the initiation of therapy. The initial phase of anticoagulant therapy, especially in patients with newly diagnosed AF, is of concern: early bleeding and thromboembolic risks have been observed to be significantly higher during the first 90 days of therapy in AF patients initiating warfarin.46
Recently, non–vitamin K antagonist (VKA) oral anticoagulants (NOACs), such as the direct thrombin inhibitor dabigatran and the factor Xa inhibitor rivaroxaban, have been introduced as alternatives to VKAs.7,8
Unlike VKAs, NOACs have 2 fixed-dose regimens: dabigatran and rivaroxaban are usually given at 150 mg twice daily and 20 mg daily, respectively, except in patients with a high bleeding risk for whom the recommended doses are dabigatran 110 mg twice daily in Europe and rivaroxaban 15 mg daily (10 mg daily in Japan in elderly patients or patients with renal dysfunction).911 Large randomized trials have demonstrated the relative safety and efficacy of these agents versus warfarin, but in selected patients with nonvalvular AF (nv-AF)1214 and subsequent observational data have provided conflicting results.1519 Few of these studies specifically focused on the early phase of therapy,15,20 and most of them were based on Medicare and Danish data. Large postmarketing studies using other databases are needed to better understand the short-term comparative effectiveness and safety of each specific agent and the dosage of NOACs versus VKAs.
At the initiative of the French medicines agency, we therefore conducted an observational study using the French nationwide medico-administrative databases to assess the bleeding and arterial thrombotic risks of dabigatran and rivaroxaban, each compared with VKA, during the early phase of therapy.21 In this article, we focused on newly treated patients with nv-AF.

Methods

Study Design and Data Source

We performed a retrospective propensity-matched cohort study using 2 French nationwide datasets linked by a unique patient identifier:
1.
The French National Health Insurance information system (SNIIRAM), which collects all individualized and anonymous healthcare claims reimbursed by the French National Health Insurance covering the entire French population: this database also contains patient data such as age, sex, vital status, and eligibility for 100% health insurance coverage for serious and costly long-term diseases (LTDs) encoded in the International Classification of Diseases, 10th Revision (ICD-10), and healthcare professional characteristics, as well, but does not include outpatient medical indications;
2.
The French Hospital Discharge database (PMSI), which contains discharge diagnoses (ICD-10 codes) and medical procedures for all patients admitted to hospital in France.
This linkage has previously been used to conduct large-scale epidemiological or postauthorization studies.22,23

Study Population

This study was based on the French National Health Insurance general scheme, covering ≈50 million people. To be eligible for inclusion, patients had to have evidence of continuous general scheme enrolment for a 5-year preindex period.
The index date was the date of first reimbursement for an OAC. New users, defined as patients with no reimbursement for any OAC during the previous 24 months, were assigned to 1 of the 3 treatment groups according to their index OAC: dabigatran or rivaroxaban with both inclusion periods defined between July 20, 2012 (NOAC French market entry date) and November 30, 2012; or VKA with patients included during the same period of 2011. NOAC doses were classified as low (dabigatran 75 mg and 110 mg or rivaroxaban 10 mg and 15 mg) or high (dabigatran 150 mg or rivaroxaban 20 mg).
Patients <18 years of age, or who were reimbursed for both dabigatran and rivaroxaban or VKA and NOAC on the index date, or who died on the index date, were excluded. Patients presenting a contraindication to treatment (history of valvular heart disease, ongoing cancer treatment, dialysis for end-stage renal disease, hematologic disease or certain immune system disorders considered to be at higher risk of major bleeding (ie, LTD or discharge diagnoses ICD-10 codes D50–D89), hepatic cirrhosis or fibrosis or liver failure, acute bleeding peptic ulcer) were also excluded. Finally, patients undergoing lower limb orthopedic procedures during the 6-week preindex period were excluded, because they were assumed to be treated for primary prevention of venous thromboembolic events (Table I in the online-only Data Supplement).
From the resulting cohort, we identified: (1) patients with nv-AF by using LTD or discharge diagnoses with ICD-10 code I48 or specific procedures during the 4-year preindex period; (2) patients with deep vein thrombosis/pulmonary embolism by using discharge diagnoses (I26, I80 except I80.0, I81, I82) or specific procedures during the 6-week preindex period; (3) outpatients assumed to have nv-AF among the remaining patients with an algorithm by using proxies discriminating AF from deep vein thrombosis/pulmonary embolism with a 95% specificity (age, sex, use of β-blockers, antiarrhythmics, antiplatelets, antihypertensives, Holter/echocardiography procedures, specialty of the first anticoagulant prescriber, and d-dimer assessment; see online-only Data Supplement).24

Outcomes

The primary end points were (1) hospitalization for bleeding, including intracranial (hospital discharge ICD-10 codes I60, I61, I62, S06.3, S06.4, S06.5, S06.6), gastrointestinal (I85.0, K25.0, K25.2, K25.4, K25.6, K26.0, K26.2, K26.4, K26.6, K27.0, K272, K27.4, K27.6, K28.0, K282, K28.4, K28.6, K29.0, K62.5, K92.0, K92.1, K92.2) and other bleeding (D62, N02, R31, R58, H11.3, H35.6, H43.1, H45.0, H92.2, J94.2, K66.1, M25.0, N92.0, N92.1, N92.4, N93.8, N93.9, N95.0, R04.0, R04.1, R04.2, R04.8, R04.9) and (2) a composite outcome combining hospitalization for bleeding and all-cause mortality.
The secondary end points were (1) hospitalization for ischemic stroke (I63 except for I63.6) or systemic embolism (I74) and (2) a composite outcome combining hospitalization for ischemic stroke or systemic embolism and all-cause mortality. Only principal discharge diagnoses were used to define end points.

Follow-Up

Patients were followed for up to 90 days from the day after the index date until predefined outcome, loss to follow-up (>2 consecutive months with no reimbursement), death from any cause, end of the year of inclusion, or end of the 90-day follow-up, whichever came first.

Baseline Covariates

The following sociodemographic covariates were used: sex, age at initiation of treatment, and the deprivation index of the patient’s municipality of residence (divided into quintiles with a sixth group created for patients residing in overseas departments).25 Baseline covariates also included the specialty of the first OAC prescriber and comorbidities or comedications deemed to be risk factors for bleeding or arterial thromboembolic events.
Comorbidities (heart failure, diabetes mellitus, coronary heart disease, dementia, history of stroke or systemic embolism, peripheral vascular disease, chronic kidney disease, history of transient ischemic attack, history of hospitalization for bleeding) were identified by hospital discharge/LTD diagnoses and specific procedures or drug reimbursements (Table I in the online-only Data Supplement). Comedications (antihypertensives, antiarrhythmics, nonsteroidal anti-inflammatory drugs, antiplatelets, lipid-lowering and antiulcer agents, cardiac glycosides, oral corticosteroids, benzodiazepine drugs) were defined as medications dispensed at least once during the 4-month preindex period.
Because smoking status and alcohol abuse were not directly available from the databases, we used reimbursement of nicotine replacement therapy and hospital discharge diagnoses related to tobacco use (ICD-10 F17, Z71.6, and Z72.0) or alcohol abuse (F10, K70, T51 E24.4, G31.2, G62.1, G72.1, I42.6, K29.2, K86.0, Z50.2, Z71.4, and Z72.1). Clinical scores predicting the risk of stroke (CHA2DS2-VASc) or bleeding (HAS-BLED) in nv-AF patients adapted to medicoadministrative data were calculated.

Statistical Analyses

All analyses were performed separately according to type (dabigatran/rivaroxaban) and dose (low/high) of NOACs by using an intent-to-treat approach. A propensity score (PS) matching analysis was performed to create similar treatment groups with respect to observed characteristics. This PS was determined by using a logistic regression model including the covariates listed above as potential confounders, with age as a categorical variable, with the exception of smoking and alcohol abuse, because only a small proportion of tobacco and alcohol users was identified. The CHA2DS2-VASc and HAS-BLED scores were not included in the PS because most of their clinical characteristics were already taken into account. One NOAC-treated patient was matched to 2 VKA-treated patients on the logit of the estimated PS without replacement.26 We used nearest-neighbor matching within a caliper width equal to 0.2 of the standard deviation of the logit of the PS.27
Before matching, categorical and continuous baseline covariates were compared between NOAC-exposed and VKA-exposed patients using the χ2 test and the Wilcoxon test, respectively, and absolute standardized differences, as well. After matching, weighted standardized differences adapted to incomplete many-to-one matching were calculated to assess the balance between NOAC-exposed and their matched VKA-exposed patients.28 Crude incidence rates were calculated, and Cox models with robust sandwich estimates were used to account for the clustering within matched sets.29 Hazard ratios and their 95% confidence intervals were reported.
Two sensitivity analyses were performed to assess the robustness of the findings based on the primary analyses: exclusion of traumatic bleeding events (S06.3, S06.4, S06.5, S06.6), and restriction of the study population to hospitalized or LTD nv-AF patients. Two subgroup analyses according to age (<75; ≥75) and level of the HAS-BLED score (<3; ≥3) were also performed for the bleeding events in nv-AF patients.
All statistical analyses were performed by using SAS Enterprise Guide 4.3 software (SAS Institute, Inc, Cary, NC).

Results

Characteristics of the Cohort

Out of a total of 65 743 VKA new users, 15 400 (23.4%) were excluded because of contraindications and 1771 (2.7%) were excluded because of a lower limb orthopedic procedure. Among the NOAC new users, 3185 (16.8%) of the 18 974 dabigatran patients and 3050 (15.4%) of the 19 815 rivaroxaban patients were excluded because of contraindications and 4149 (21.9%) and 7548 (38.1%), respectively, were excluded because of a lower limb orthopedic procedure. The most frequent contraindication was the exclusion criterion hematologic disease or certain immune system disorders, particularly nutritional anemia. Among the 71 589 eligible patients, 32 807 (45.8%) were identified as having nv-AF (26.9% by ICD-10 I48 or specific procedures and 18.9% by using the algorithm). This population was composed of 19 713 VKA (fluindione: 83.7%, warfarin: 11.8%), 8443 dabigatran (low doses: 69.8%), and 4651 rivaroxaban (low doses: 38.5%) new users (Figure 1).
Figure 1. Study population flow chart. All figures are numbers or percentages of patients. DVT indicates deep vein thrombosis; NOAC, non–vitamin K antagonist oral anticoagulants; PE, pulmonary embolism; and VKA, vitamin K antagonist;
Baseline patient characteristics, before matching, are shown in Tables II and III in the online-only Data Supplement. Dabigatran and rivaroxaban were more frequently initiated than VKA by cardiologists in private practice. Dabigatran and rivaroxaban users had a lower mean CHA2DS2-VASc score and fewer comorbidities than VKA users. The mean HAS-BLED score was comparable between NOAC and VKA users. Patients treated with dabigatran 150 mg or rivaroxaban 20 mg were more frequently males, younger, with lower mean HAS-BLED and CHA2DS2-VASc scores, and much fewer comorbidities than VKA users. Patients initiating low-dose dabigatran or rivaroxaban were more frequently females and older than VKA users. The proportion of antiplatelet users was higher among patients initiating low-dose dabigatran or rivaroxaban.
In the overall study population, the median duration from the start of treatment (from the day after the index date) to the end of follow-up was 87 days (interquartile range, 56–90 days) for the dabigatran/matched VKA cohort and 80 days (interquartile range, 53–90 days) for the rivaroxaban/matched VKA cohort.

Evaluation of Propensity Score Matching

All 8443 dabigatran-treated patients and 4651 rivaroxaban-treated patients were matched with at least 1 VKA user, and 89.7% and 100.0% of these patients were matched with 2 VKA users, respectively. For each NOAC dose category, 100% of the patients were matched with 2 VKA users, except for the low-dose dabigatran category, in which 96.3% of patients were matched with 2 VKA users.
Before matching, across all variables included in the PS, the absolute standardized differences ranged from 0.000 to 0.861 for dabigatran and from 0.001 to 0.518 for rivaroxaban. After matching, all standardized differences were <0.030 and 0.050, respectively, indicating a good balance between treatment groups (Tables 1 and 2).
Table 1. Dabigatran- and VKA-Matched–Treated Patients: Baseline Characteristics According to Treatment Group After Propensity Score Matching
 Dabigatran All Doses n=8443VKA D-All Doses Matched n=16 014Dabigatran 75–110 mg n=5895VKA D75–110 Matched n=11 571Dabigatran 150 mg n=2548VKA D150 Matched n=5096
Characteristicsn (%)*n (%)*Stand Diffn (%)*n (%)*Stand Diffn (%)*n (%)*Stand Diff
Female3903 (46)7430 (46)0.0113048 (52)5912 (51)0.011855 (34)1711 (34)0.000
Age, mean (SD)74.0 (11.3)73.9 (11.2)0.00877.4 (10.1)76.9 (10.0)0.03566.1 (10.0)66.5 (10.3)0.040
 18–49 y271 (3)508 (3)0.00497 (2)191 (2)0.002174 (7)353 (7)0.004
 50–64 y1294 (15)2499 (16)0.000521 (9)1090 (9)0.014773 (30)1506 (30)0.017
 65–74 y2305 (27)4322 (27)0.0111214 (21)2417 (21)0.0021091 (43)2229 (44)0.019
 75–79 y1562 (19)2990 (19)0.0011174 (20)2347 (20)0.002388 (15)763 (15)0.007
 ≥80 y3011 (36)5695 (36)0.0092889 (49)5526 (48)0.008122 (5)245 (5)0.001
Deprivation index
 Quintile 11617 (19)2966 (19)0.0021197 (20)2322 (20)0.010420 (16)824 (16)0.008
 Quintile 21553 (18)2979 (19)0.0041013 (17)2064 (18)0.011540 (21)1045 (21)0.017
 Quintile 31654 (20)3120 (19)0.0011142 (19)2239 (19)0.002512 (20)1042 (20)0.009
 Quintile 41752 (21)3344 (21)0.0031240 (21)2403 (21)0.010512 (20)1049 (21)0.012
 Quintile 51767 (21)3413 (21)0.0011232 (21)2410 (21)0.007535 (21)1078 (21)0.004
 Overseas dpts100 (1)192 (1)0.00471 (1)133 (1)0.00729 (1)58 (1)0.000
First prescriber’s specialty
 Hospital practitioner2806 (33)5619 (35)0.0021919 (33)3884 (34)0.008887 (35)1771 (35)0.001
 General practitioner1865 (22)3786 (24)0.0081410 (24)2743 (24)0.014455 (18)942 (18)0.016
 Private cardiologist3613 (43)6296 (39)0.0092459 (42)4718 (41)0.0021154 (45)2294 (45)0.006
 Other specialties159 (2)313 (2)0.000107 (2)226 (2)0.00852 (2)89 (2)0.022
HAS-BLED, mean (SD)2.3 (1.0)2.3 (1.0)0.0092.4 (0.9)2.4 (0.9)0.0152.0 (1.0)2.0 (1.0)0.000
CHA2DS2-VASc, mean (SD)3.2 (1.6)3.2 (1.6)0.0113.6 (1.5)3.6 (1.5)0.0152.4 (1.5)2.4 (1.5)0.016
Comorbidities
 Heart failure1901 (23)3681 (23)0.0021407 (24)2739 (24)0.008494 (19)941 (18)0.024
 Diabetes mellitus1626 (19)3172 (20)0.0011158 (20)2294 (20)0.001468 (18)931 (18)0.003
 CKD198 (2)366 (2)0.012170 (3)310 (3)0.01528 (1)51 (1)0.010
 Dementia326 (4)592 (4)0.013303 (5)584 (5)0.00123 (1)54 (1)0.016
 History of stroke603 (7)1190 (7)0.002453 (8)870 (8)0.012150 (6)295 (6)0.004
 History of TIA210 (2)417 (3)0.000151 (3)305 (3)0.00359 (2)100 (2)0.024
 CHD1766 (21)3442 (21)0.0011391 (24)2786 (24)0.011375 (15)771 (15)0.012
 PVD521 (6)1034 (6)0.001408 (7)813 (7)0.001113 (4)227 (4)0.001
 History of bleeding224 (3)408 (3)0.003172 (3)346 (3)0.01152 (2)89 (2)0.022
 Alcohol abuse136 (2)300 (2)0.01585 (1)168 (1)0.00151 (2)140 (3)0.049
 Smoking301 (4)570 (4)0.006173 (3)312 (3)0.016128 (5)268 (5)0.011
Comedications
 Antihypertensives6758 (80)12 905 (81)0.0014883 (83)9590 (83)0.0011875 (74)3809 (75)0.026
 Cardiac glycosides994 (12)2000 (12)0.004739 (13)1429 (12)0.012255 (10)488 (10)0.015
 Antiarrhythmics5905 (70)11 141 (70)0.0074025 (68)7915 (68)0.0051880 (74)3786 (74)0.012
 Lipid-lowering agents3959 (47)7570 (47)0.0012850 (48)5524 (48)0.0131109 (44)2223 (44)0.002
 Oral corticosteroids1108 (13)1995 (12)0.004768 (13)1469 (13)0.005340 (13)687 (13)0.004
 Antiulcer agents3458 (41)6513 (41)0.0052557 (43)5012 (43)0.003901 (35)1743 (34)0.024
 Benzodiazepines2471 (29)4752 (30)0.0031883 (32)3640 (31)0.012588 (23)1161 (23)0.007
 Antiplatelets4499 (53)8423 (53)0.0003350 (57)6497 (56)0.0041149 (45)2286 (45)0.005
 NSAIDs1636 (19)2976 (19)0.0011072 (18)2053 (18)0.005564 (22)1119 (22)0.004
CHD indicates coronary heart disease; CKD, chronic kidney disease; D, dabigatran; Dpts, departments; NOAC, non–vitamin K antagonist oral anticoagulants; NSAIDs, nonsteroidal anti-inflammatory drugs; PVD, peripheral vascular disease; R, rivaroxaban; SD, standard deviation; Stand Diff, absolute weighted standardized differences; TIA, transient ischemic attack; and VKA, vitamin K antagonist.
*
Dichotomous variables are expressed as n (%); continuous variables are expressed as mean (standard deviation).
Absolute weighted standardized differences comparing baseline characteristics between NOAC- (all NOAC patients were matched) and VKA-matched–treated patients.
Smoking or alcoholism data: reimbursements for nicotine replacement therapy and hospital discharge diagnoses related to tobacco use or alcohol abuse.
Table 2. Rivaroxaban- and VKA-Matched-Treated Patients: Baseline Characteristics According to Treatment Group After Propensity Score Matching
 Rivaroxaban All Doses n=4651VKA R-All Doses Matched n=9301Rivaroxaban 10–15 mg n=1790VKA R10–15 Matched n=3580Rivaroxaban 20 mg n=2861VKA R20 Matched n=5722
Characteristicsn (%)*n (%)*Stand Diffn (%)*n (%)*Stand Diffn (%)*n (%)*Stand Diff
Female2108 (45)4204 (45)0.003978 (55)1950 (54)0.0031130 (39)2265 (40)0.002
Age, mean (SD)73.6 (11.4)73.4 (11.2)0.02479.1 (10.1)78.5 (9.8)0.06070.2 (10.8)70.5 (10.9)0.030
 18–49 y160 (3)334 (4)0.00832 (2)71 (2)0.014128 (4)262 (5)0.005
 50–64 y747 (16)1511 (16)0.005125 (7)233 (7)0.019622 (22)1209 (21)0.015
 65–74 y1275 (27)2605 (28)0.013260 (15)536 (15)0.0131015 (35)2037 (36)0.003
 75–79 y891 (19)1733 (19)0.013355 (20)707 (20)0.002536 (19)1088 (19)0.007
 ≥80 y1578 (34)3118 (34)0.0091018 (57)2033 (57)0.002560 (20)1126 (20)0.003
Deprivation index
 Quintile 1934 (20)1835 (20)0.009378 (21)773 (22)0.012556 (19)1130 (20)0.008
 Quintile 2965 (21)1935 (21)0.002350 (20)697 (19)0.002615 (21)1222 (21)0.003
 Quintile 3956 (21)1905 (20)0.002364 (20)712 (20)0.011592 (21)1174 (21)0.004
 Quintile 4847 (18)1700 (18)0.002324 (18)654 (18)0.004523 (18)1037 (18)0.004
 Quintile 5908 (20)1851 (20)0.009358 (20)708 (20)0.006550 (19)1111 (19)0.005
 Overseas dpts41 (1)75 (1)0.00816 (1)36 (1)0.01225 (1)48 (1)0.004
First prescriber’s specialty
 Hospital practitioner1004 (22)1995 (21)0.003389 (22)796 (22)0.012615 (21)1258 (22)0.012
 General practitioner992 (21)2020 (22)0.009463 (26)912 (25)0.009529 (18)1048 (18)0.005
 Private cardiologist2576 (55)5128 (55)0.005905 (51)1818 (51)0.0041671 (58)3347 (58)0.002
 Other specialties79 (2)158 (2)0.00033 (2)54 (2)0.02646 (2)69 (1)0.034
HAS-BLED, mean (SD)2.3 (1.0)2.2 (1.0)0.0522.5 (0.9)2.5 (0.9)0.0152.2 (1.0)2.1 (1.0)0.033
CHA2DS2-VASc, mean (SD)3.1 (1.5)3.1 (1.5)0.0453.7 (1.4)3.6 (1.4)0.0382.8 (1.5)2.7 (1.5)0.014
Comorbidities
 Heart failure982 (21)1859 (20)0.028469 (26)917 (26)0.013513 (18)1013 (18)0.006
 Diabetes mellitus875 (19)1665 (18)0.024319 (18)593 (17)0.033556 (19)1055 (18)0.025
 CKD117 (3)237 (3)0.00275 (4)163 (5)0.01842 (1)72 (1)0.018
 Dementia138 (3)257 (3)0.01293 (5)172 (5)0.01845 (2)72 (1)0.027
 History of stroke219 (5)408 (4)0.01597 (5)182 (5)0.015122 (4)234 (4)0.009
 History of TIA100 (2)189 (2)0.00849 (3)73 (2)0.04651 (2)90 (2)0.016
 CHD963 (21)1908 (21)0.005430 (24)840 (23)0.013533 (19)1011 (18)0.025
 PVD282 (6)522 (6)0.019137 (8)254 (7)0.021145 (5)272 (5)0.015
 History of bleeding110 (2)207 (2)0.00955 (3)99 (3)0.01855 (2)101 (2)0.012
 Alcohol abuse50 (1)132 (1)0.03119 (1)33 (1)0.01431 (1)101 (2)0.058
 Smoking125 (3)278 (3)0.01842 (2)72 (2)0.02383 (3)193 (3)0.027
Comedications
 Antihypertensives3624 (78)7222 (78)0.0071486 (83)2987 (83)0.0112138 (75)4340 (76)0.026
 Cardiac glycosides604 (13)1189 (13)0.006251 (14)447 (12)0.045353 (12)682 (12)0.013
 Antiarrhythmics3393 (73)6876 (74)0.0221235 (69)2511 (70)0.0252158 (75)4413 (77)0.040
 Lipid-lowering agents2204 (47)4358 (47)0.011811 (45)1657 (46)0.0201393 (49)2720 (48)0.023
 Oral corticosteroids534 (11)1015 (11)0.018211 (12)418 (12)0.003323 (11)615 (11)0.017
 Antiulcer agents1756 (38)3501 (38)0.002730 (41)1409 (39)0.0291026 (36)2052 (36)0.000
 Benzodiazepines1343 (29)2574 (28)0.027597 (33)1199 (33)0.003746 (26)1485 (26)0.003
 Antiplatelets2604 (56)5098 (55)0.0241086 (61)2154 (60)0.0101518 (53)2969 (52)0.023
 NSAID867 (19)1636 (18)0.027297 (17)583 (16)0.008570 (20)1107 (19)0.015
CHD indicates coronary heart disease; CKD, chronic kidney disease; D, dabigatran; Dpts, departments; NOAC, non–vitamin K antagonist oral anticoagulants; NSAIDs, nonsteroidal anti-inflammatory drugs; PVD, peripheral vascular disease; R, rivaroxaban; SD, standard deviation; Stand Diff, absolute weighted standardized differences; TIA, transient ischemic attack; and VKA, vitamin K antagonist.
*
Dichotomous variables are expressed as n (%); continuous variables are expressed as mean (standard deviation).
Absolute weighted standardized differences comparing baseline characteristics between NOAC- (all NOAC patients were matched) and VKA-matched–treated patients.
Smoking or alcoholism data: reimbursements for nicotine replacement therapy and hospital discharge diagnoses related to tobacco use or alcohol abuse.

Association With Primary End Points

Table 3 presents the number of bleeding and arterial thromboembolic events, person-years at risk, and crude event rates for each of the combinations of NOAC dose group and their matched VKA-treated patients.
Table 3. Events, Person-Years at Risk, and Crude Event Rates Among NOAC New Users and Matched VKA New Users
 Dabigatran All DosesVKA D-All Doses MatchedDabigatran 75–110VKA D75–110 MatchedDabigatran 150VKA D75–110 MatchedRivaroxaban All DosesVKA R-All Doses MatchedRivaroxaban 10–15VKA R10–15 MatchedRivaroxaban 20VKA R20 Matched
Bleeding events55/1684/3.3122/3292/3.743/1195/3.6101/2368/4.312/489/2.530/1054/2.831/848/3.768/1913/3.616/328/4.936/734/4.915/520/2.940/1178/3.4
Bleeding events or death158/1684/9.4341/3292/10.4137/1195/11.5295/2368/12.521/489/4.356/1054/5.375/848/8.8161/1913/8.443/328/13.189/734/12.132/520/6.280/1178/6.8
Ischemic stroke or SE33/1687/258/3300/1.828/1198/2.337/2376/1.65/490/114/1056/1.312/851/1.428/1918/1.56/329/1.813/736/1.86/521/1.215/1182/1.3
Ischemic stroke or SE or death136/1687/8.1280/3300/8.5121/1198/10.1243/2376/10.215/490/3.143/1056/4.160/851/7.1125/1918/6.537/329/11.266/736/923/521/4.456/1182/4.7
Values are events/person-years at risk/crude event rate/100 person-years. D, dabigatran; NOAC, non–vitamin K antagonist oral anticoagulants; R, rivaroxaban; SE, systemic embolism; and VKA, vitamin K antagonist.
No significant difference in bleeding risk was observed between VKA- and dabigatran- or rivaroxaban-treated patients (HR, 0.88; 95% confidence interval, 0.64–1.21 and HR, 0.98; 95% confidence interval, 0.64–1.51, respectively). The bleeding risk was not significantly different in patients exposed to either low or high doses of each NOAC in comparison with patients exposed to VKA (Figure 2).
Figure 2. Hazard ratios for hospitalized bleeding events according to type and dose of NOAC. All figures are hazard ratios and their 95% confidence interval. NOAC indicates non–vitamin K antagonist oral anticoagulants; and nv-AF, nonvalvular atrial fibrillation.
The incidence of the composite outcome comprising hospitalization for bleeding and death was comparable between VKA and NOAC new users for all NOAC types and doses (Figure 2).
The results of sensitivity analyses confirmed those obtained with the primary analyses for both dabigatran and rivaroxaban. No significant difference between NOAC and VKA was observed in the subgroup analyses (Figure 2).

Association With Secondary End Points

No significant difference was observed between VKA- and dabigatran- or rivaroxaban-treated patients (HR, 1.10; 95% confidence interval, 0.72–1.69 and HR, 0.93; 95% confidence interval, 0.47–1.85, respectively) in terms of arterial thromboembolic events. Analyses according to NOAC doses did not show any increased risk of stroke or systemic embolism. No significant difference in the incidence of the composite outcome comprising stroke, systemic embolism and death was observed according to the various NOAC types and doses (Table 3; Figure 3).
Figure 3. Hazard ratios for stroke or systemic embolism according to type and dose of NOAC. All figures are hazard ratios and their 95% confidence interval. NOAC indicates non–vitamin K antagonist oral anticoagulants.

Discussion

In this large-scale, nationwide cohort study, no significant differences were observed between NOAC (dabigatran or rivaroxaban) and VKA in terms of hospitalizations for bleeding or for arterial thromboembolic events during the early phase of anticoagulant therapy among new users with nv-AF. To our knowledge, this is the first study to assess the short-term benefit/risk balance of both dabigatran and rivaroxaban versus VKA using French medico-administrative databases, because previous studies were conducted on Danish and US Medicare data.1520 This study also provides insight into French prescribing patterns of dabigatran and rivaroxaban immediately following their approval for stroke prevention in nv-AF. Significant channeling of the new drugs, ie, NOAC over VKA toward a younger and healthier population, was observed, and the channeling of low doses of each NOAC (dabigatran 75/110 mg or rivaroxaban 10/15 mg) over high doses toward older patients with higher bleeding and stroke risks, as well.
The results of this study are consistent with the overall findings of the randomized clinical trials and most of the subsequent observational studies that did not find any evidence for increased stroke or bleeding risks with NOAC in comparison with warfarin in the short to medium term.7,8,1517,20 Few observational studies on NOAC have been published to date, and this study is one of the first large incident cohorts to assess rivaroxaban effectiveness and bleeding risks relative to VKA.17 The observed prescribing trends are in line with those described in the available observational studies.1517 French prescribing practices appear to be strongly guided by bleeding risk, as suggested by the high proportion of patients who were prescribed low doses, especially dabigatran 75 mg and rivaroxaban 10 mg. These doses have not been approved in the European Union on the basis of clinical judgment, which raises the question of their effectiveness in patients at high risk of stroke.9,10 It should be noted that more than one-third of dabigatran- or rivaroxaban-treated patients were aged 80 and over, a population that was underrepresented in pivotal clinical trials.7,8
Nevertheless, as in the study by Sørensen et al,15 our design focused on the early phase of OAC therapy, bearing in mind that early events can have a major impact on the overall success of treatment, starting with treatment persistence. Although our overall results are reassuring in relation to the initiation of NOACs in nv-AF patients in France with no marked excess thromboembolic or bleeding risk, they also suggest that particular caution is required when initiating NOACs. Indeed, the initiation of VKAs has been shown to be hazardous owing to the increased risks of bleeding and stroke, which may partly explain the reported underuse of anticoagulant therapy in nv-AF.46,20 But, on the basis of this study comparing NOAC with VKA, NOACs cannot be considered to be safer than VKA during the early phase of treatment. On the contrary, the clinical implications of our results are that physicians must be just as cautious when initiating NOACs as when initiating VKAs, particularly in view of the absence of an antidote and objective monitoring of the extent of anticoagulation. However, one should keep in mind when initiating OAC therapy that good anticoagulation control is difficult to achieve and maintain with VKA: the quality of anticoagulation in warfarin-treated patients with AF has been reported to be suboptimal by many authors in the real-word setting,3032 with the corresponding significantly increased risk of adverse clinical outcomes.33,34
Because of the observational design and the 2 existing dosage regimens of NOAC, residual confounding by indication is a particular concern in this study.35 Various techniques were used to mitigate this bias. First, we excluded patients with no nv-AF or with contraindications to avoid artificially biasing the treatment effect by ineligible populations or inappropriate treatment indications. Exclusion of these patients could partly explain the apparent discrepancy between our results and those of a recent study based on Medicare data, in which no exclusions were reported.18 Second, VKA-treated patients were selected in 2011, a period during which NOACs could not be prescribed in France for stroke prevention in nv-AF. Third, analyses were restricted to low and high doses with consistent results.36 Finally, the use of PS matching provides one of the best conditions for nondifferential comparison between NOAC and VKA.2629 Moreover, variables of the PS would be expected to be strong confounders. However, PS matching did not control for unobserved factors. Because this study was based on administrative data, confounders such as lifestyle or alcohol consumption and differences between severity levels of certain diseases such as renal impairment were not taken into account. Residual confounding therefore cannot be excluded.
Identifying AF on the basis of administrative data is challenging and a source of selection bias. We therefore used a highly specific algorithm to more accurately identify treated AF outpatients.24 The results are consistent with those obtained on patients identified only by I48 ICD-10 code or specific procedures.
Outcome misclassification, although nondifferential, also constitutes a limitation, because the external validity of the ischemic stroke and bleeding diagnosis codes have not been previously assessed in the French PMSI database. However, only primary hospital discharge diagnoses were used to define outcomes. Furthermore, this database is used to calculate payments for acute inpatient care with internal and external quality control processes.
Intention-to-treat analysis was performed because of the short-term follow-up and the use of medico-administrative databases. The accuracy of this approach to estimate the treatment assignment effect could be open to criticism, because exposure to treatment was based on pharmacy claims, which do not indicate how the patient actually takes the medications.
With a maximum 3-month follow-up period, our study only captured early events. The outcomes studied are rare events, and the small number of events in this study may not have allowed identification of small-to-moderate differences between groups. Because the study was conducted at the time of the introduction of NOACs for nv-AF patients in France, time-varying characteristics of both patients and prescribers cannot be ruled out. Finally, a much longer follow-up would be necessary to assess the long-term benefit-risk balance of NOACs versus VKAs, especially for arterial thromboembolic events.
In conclusion, in this study based on medico-administrative data, no statistically significant difference was observed between NOACs, dabigatran or rivaroxaban, and VKAs in terms of the risk of bleeding or arterial thromboembolic events during the early phase of anticoagulant therapy in nv-AF patients. The same level of clinical caution is therefore required when initiating either NOACs or VKAs. Similar analyses should be extended to other NOACs such as apixaban, and observational studies should now focus on NOAC head-to-head comparison in a noninferiority design.

Acknowledgments

We thank the ANSM Epidemiology of Health Products Working group for providing us with their comments and suggestions concerning this study.

CLINICAL PERSPECTIVES

The non–vitamin K antagonists (VKA) oral anticoagulants (NOACs), such as the direct thrombin inhibitor dabigatran and the factor Xa inhibitor rivaroxaban, have provided patients who have atrial fibrillation with a convenient, fixed-dose alternative to VKAs. Although NOACs might have some advantages over VKAs, some concerns have emerged about their safety. Few real-world data has been reported so far, and few studies have specifically focused on the early phase of therapy. However, early bleeding and thromboembolic risks have been observed to be significantly higher during the first 90 days of therapy in patients who have atrial fibrillation initiating warfarin. We therefore conducted a large postmarketing study using the French medicoadministrative databases to better investigate the short-term comparative effectiveness and safety of each specific agent of NOAC versus VKA. In this nationwide propensity-matched cohort study (8443 dabigatran- and 4651 rivaroxaban-treated patients matched with at least 1 VKA user), no significant difference between NOAC (dabigatran or rivaroxaban) and VKA was found in terms of hospitalizations for bleeding or for arterial thromboembolic events during the early phase of therapy among new users with nonvalvular atrial fibrillation. Physicians must therefore be as cautious when initiating NOACs as when initiating VKAs, particularly in view of the absence of a NOAC antidote and objective monitoring of the extent of anticoagulation. These results are consistent with those from the few observational studies published to date and offer clinicians a more comprehensive picture of the NOAC benefit-risk balance during the early phase of treatment.

Supplemental Material

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References

1.
Steinberg BA, Piccini JP. Anticoagulation in atrial fibrillation. BMJ. 2014;348:g2116.
2.
Guyatt GH, Akl EA, Crowther M, Gutterman DD, Schuünemann HJ; American College of Chest Physicians Antithrombotic Therapy and Prevention of Thrombosis Panel. Executive summary: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012;141(2 suppl):7S–47S. doi: 10.1378/chest.1412S3.
3.
Camm AJ, Lip GY, De Caterina R, Savelieva I, Atar D, Hohnloser SH, Hindricks G, Kirchhof P; ESC Committee for Practice Guidelines (CPG). 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC Guidelines for the management of atrial fibrillation. Developed with the special contribution of the European Heart Rhythm Association. Eur Heart J. 2012;33:2719–2747. doi: 10.1093/eurheartj/ehs253.
4.
Hylek EM, Evans-Molina C, Shea C, Henault LE, Regan S. Major hemorrhage and tolerability of warfarin in the first year of therapy among elderly patients with atrial fibrillation. Circulation. 2007;115:2689–2696. doi: 10.1161/CIRCULATIONAHA.106.653048.
5.
Garcia DA, Lopes RD, Hylek EM. New-onset atrial fibrillation and warfarin initiation: high risk periods and implications for new antithrombotic drugs. Thromb Haemost. 2010;104:1099–1105. doi: 10.1160/TH10-07-0491.
6.
ACTIVE Writing Group of the ACTIVE InvestigatorsConnolly S, Pogue J, Hart R, Pfeffer M, Hohnloser S, Chrolavicius S, Pfeffer M, Hohnloser S, Yusuf S. Clopidogrel plus aspirin versus oral anticoagulation for atrial fibrillation in the Atrial fibrillation Clopidogrel Trial with Irbesartan for prevention of Vascular Events (ACTIVE W): a randomised controlled trial. Lancet. 2006;367:1903–1912.
7.
Connolly SJ, Ezekowitz MD, Yusuf S, Eikelboom J, Oldgren J, Parekh A, Pogue J, Reilly PA, Themeles E, Varrone J, Wang S, Alings M, Xavier D, Zhu J, Diaz R, Lewis BS, Darius H, Diener HC, Joyner CD, Wallentin L; RE-LY Steering Committee and Investigators. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med. 2009;361:1139–1151. doi: 10.1056/NEJMoa0905561.
8.
Patel MR, Mahaffey KW, Garg J, Pan G, Singer DE, Hacke W, Breithardt G, Halperin JL, Hankey GJ, Piccini JP, Becker RC, Nessel CC, Paolini JF, Berkowitz SD, Fox KA, Califf RM; ROCKET AF Investigators. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med. 2011;365:883–891. doi: 10.1056/NEJMoa1009638.
9.
PRADAXA-Product information as approved by the CHMP on 24 October 2014, pending endorsement by the European Commission [Internet]. http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000829/WC500041059.pdf. Accessed November 4, 2014.
10.
XARELTO-Product information as approved by the CHMP on 24 October 2014, pending endorsement by the European Commission [Internet]. http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000944/WC500057108.pdf. Accessed November 4, 2014.
11.
Hori M, Matsumoto M, Tanahashi N, Momomura S, Uchiyama S, Goto S, Izumi T, Koretsune Y, Kajikawa M, Kato M, Ueda H, Iwamoto K, Tajiri M; J-ROCKET AF study investigators. Rivaroxaban vs. warfarin in Japanese patients with atrial fibrillation – the J-ROCKET AF study –. Circ J. 2012;76:2104–2111.
12.
Ruff CT, Giugliano RP, Braunwald E, Hoffman EB, Deenadayalu N, Ezekowitz MD, Camm AJ, Weitz JI, Lewis BS, Parkhomenko A, Yamashita T, Antman EM. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet. 2014;383:955–962. doi: 10.1016/S0140-6736(13)62343-0.
13.
Bruins Slot KM, Berge E. Factor Xa inhibitors versus vitamin K antagonists for preventing cerebral or systemic embolism in patients with atrial fibrillation. Cochrane Database Syst Rev. 2013;8:CD008980. doi: 10.1002/14651858.CD008980.pub2.
14.
Miller CS, Grandi SM, Shimony A, Filion KB, Eisenberg MJ. Meta-analysis of efficacy and safety of new oral anticoagulants (dabigatran, rivaroxaban, apixaban) versus warfarin in patients with atrial fibrillation. Am J Cardiol. 2012;110:453–460. doi: 10.1016/j.amjcard.2012.03.049.
15.
Sørensen R, Gislason G, Torp-Pedersen C, Olesen JB, Fosbøl EL, Hvidtfeldt MW, Karasoy D, Lamberts M, Charlot M, Køber L, Weeke P, Lip GY, Hansen ML. Dabigatran use in Danish atrial fibrillation patients in 2011: a nationwide study. BMJ Open. 2013;3:. doi: 10.1136/bmjopen-2013-002758.
16.
Larsen TB, Rasmussen LH, Skjøth F, Due KM, Callréus T, Rosenzweig M, Lip GY. Efficacy and safety of dabigatran etexilate and warfarin in “real-world” patients with atrial fibrillation: a prospective nationwide cohort study. J Am Coll Cardiol. 2013;61:2264–2273. doi: 10.1016/j.jacc.2013.03.020.
17.
Laliberté F, Cloutier M, Nelson WW, Coleman CI, Pilon D, Olson WH, Damaraju CV, Schein JR, Lefebvre P. Real-world comparative effectiveness and safety of rivaroxaban and warfarin in nonvalvular atrial fibrillation patients. Curr Med Res Opin. 2014;30:1317–1325. doi: 10.1185/03007995.2014.907140.
18.
Hernandez I, Baik SH, Piñera A, Zhang Y. Risk of bleeding with dabigatran in atrial fibrillation. JAMA Intern Med. 2015;175:18–24. doi: 10.1001/jamainternmed.2014.5398.
19.
Larsen TB, Rasmussen LH, Gorst-Rasmussen A, Skjøth F, Lane DA, Lip GY. Dabigatran and warfarin for secondary prevention of stroke in atrial fibrillation patients: a nationwide cohort study. Am J Med. 2014;127:1172–8.e5. doi: 10.1016/j.amjmed.2014.07.023.
20.
Larsen TB, Gorst-Rasmussen A, Rasmussen LH, Skjøth F, Rosenzweig M, Lip GY. Bleeding events among new starters and switchers to dabigatran compared with warfarin in atrial fibrillation. Am J Med. 2014;127:650–656.e5. doi: 10.1016/j.amjmed.2014.01.031.
21.
Agence nationale de sécurité du médicament et des produits de santé. Étude ‘en vie réelle’ du bénéfice/risque à court terme des nouveaux anticoagulants oraux (dabigatran, rivaroxaban) chez les patients débutant un traitement et non précédemment traités par des antivitamines K (02/07/2014) [Internet]. http://ansm.sante.fr/Dossiers/Les-anticoagulants/Les-anticoagulants-en-France-Etudes-et-surveillance/%28offset%29/0#paragraph_58691. Accessed November 4, 2014.
22.
Weill A, Païta M, Tuppin P, Fagot JP, Neumann A, Simon D, Ricordeau P, Montastruc JL, Allemand H. Benfluorex and valvular heart disease: a cohort study of a million people with diabetes mellitus. Pharmacoepidemiol Drug Saf. 2010;19:1256–1262. doi: 10.1002/pds.2044.
23.
Fagot JP, Blotière PO, Ricordeau P, Weill A, Alla F, Allemand H. Does insulin glargine increase the risk of cancer compared with other basal insulins?: A French nationwide cohort study based on national administrative databases. Diabetes Care. 2013;36:294–301. doi: 10.2337/dc12-0506.
24.
Billionnet C, Maura G, Weill A, Ricordeau P, Alla F.Identifying atrial fibrillation in patients initiating new oral anticoagulants using the French national health insurance database (abstract). EuroDURG 2014 Scientific Annual Meeting; August 27–29, 2014.
25.
Rey G, Jougla E, Fouillet A, Hémon D. Ecological association between a deprivation index and mortality in France over the period 1997–2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death. BMC Public Health. 2009;9:33. doi: 10.1186/1471-2458-9-33.
26.
Austin PC. Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score. Am J Epidemiol. 2010;172:1092–1097. doi: 10.1093/aje/kwq224.
27.
Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat. 2011;10:150–161. doi: 10.1002/pst.433.
28.
Austin PC. Assessing balance in measured baseline covariates when using many-to-one matching on the propensity-score. Pharmacoepidemiol Drug Saf. 2008;17:1218–1225. doi: 10.1002/pds.1674.
29.
Gayat E, Resche-Rigon M, Mary JY, Porcher R. Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study. Pharm Stat. 2012;11:222–229. doi: 10.1002/pst.537.
30.
Rose AJ, Ozonoff A, Henault LE, Hylek EM. Warfarin for atrial fibrillation in community-based practise. J Thromb Haemost. 2008;6:1647–1654.
31.
Melamed OC, Horowitz G, Elhayany A, Vinker S. Quality of anticoagulation control among patients with atrial fibrillation. Am J Manag Care. 2011;17:232–237.
32.
Nakatani Y, Mizumaki K, Nishida K, Hirai T, Sakabe M, Oda Y, Joho S, Fujiki A, Nozawa T, Inoue H. Anticoagulation control quality affects the D-dimer levels of atrial fibrillation patients. Circ J. 2012;76:317–321.
33.
Jones M, McEwan P, Morgan CL, Peters JR, Goodfellow J, Currie CJ. Evaluation of the pattern of treatment, level of anticoagulation control, and outcome of treatment with warfarin in patients with non-valvar atrial fibrillation: a record linkage study in a large British population. Heart. 2005;91:472–477. doi: 10.1136/hrt.2004.042465.
34.
Nelson WW, Wang L, Baser O, Damaraju CV, Schein JR. Out-of-range INR values and outcomes among new warfarin patients with non-valvular atrial fibrillation. Int J Clin Pharm. 2015;37:53–59. doi: 10.1007/s11096-014-0038-3.
35.
Eikelboom JW, Wallentin L, Connolly SJ, Ezekowitz M, Healey JS, Oldgren J, Yang S, Alings M, Kaatz S, Hohnloser SH, Diener HC, Franzosi MG, Huber K, Reilly P, Varrone J, Yusuf S. Risk of bleeding with 2 doses of dabigatran compared with warfarin in older and younger patients with atrial fibrillation: an analysis of the randomized evaluation of long-term anticoagulant therapy (RE-LY) trial. Circulation. 2011;123:2363–2372. doi: 10.1161/CIRCULATIONAHA.110.004747.
36.
Psaty BM, Siscovick DS. Minimizing bias due to confounding by indication in comparative effectiveness research: the importance of restriction. JAMA. 2010;304:897–898. doi: 10.1001/jama.2010.1205.

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Circulation
Pages: 1252 - 1260
PubMed: 26199338

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History

Received: 3 February 2015
Accepted: 13 July 2015
Published online: 21 July 2015
Published in print: 29 September 2015

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Keywords

  1. atrial fibrillation
  2. anticoagulants
  3. comparative effectiveness research
  4. databases, factual
  5. France
  6. hemorrhage
  7. pharmacoepidemiology
  8. stroke

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Authors

Affiliations

Géric Maura, PharmD*
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).
Pierre-Olivier Blotière, MSc*
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).
Kim Bouillon, MD, PhD
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).
Cécile Billionnet, MSc, PhD
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).
Philippe Ricordeau, MD
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).
François Alla, MD, PhD
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).
Mahmoud Zureik, MD, PhD
From Strategy and Research Department, National Health Insurance (CNAMTS), Paris, France (G.M., P.-O.B., C.B., P.R., F.A.); and Department of Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM), Saint-Denis, France (K.B., M.Z.).

Notes

*
Drs Maura and Blotière are joint first authors.
The online-only Data Supplement is available with this article at http://circ.ahajournals.org/lookup/suppl/doi:10.1161/CIRCULATIONAHA.115.015710/-/DC1.
Correspondence to Géric Maura, PharmD, Strategy and Research Department, National Health Insurance (CNAMTS), 50 avenue du Pr André Lemierre, 75986 Paris cedex 20, France. E-mail [email protected]

Disclosures

None.

Sources of Funding

The authors are employees of the French National Health Insurance (CNAMTS) or of the French National Agency for Medicines and Health Products Safety (ANSM) and received no funding.

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  9. Bleeding risk with concurrent use of anticoagulants and ibrutinib: A population‐based nested case‐control study, British Journal of Haematology, 203, 2, (311-318), (2023).https://doi.org/10.1111/bjh.18995
    Crossref
  10. Do Proton Pump Inhibitors Reduce Upper Gastrointestinal Bleeding in Older Patients with Atrial Fibrillation Treated with Oral Anticoagulants? A Nationwide Cohort Study in France, Drugs & Aging, 41, 1, (65-76), (2023).https://doi.org/10.1007/s40266-023-01085-7
    Crossref
  11. See more
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Comparison of the Short-Term Risk of Bleeding and Arterial Thromboembolic Events in Nonvalvular Atrial Fibrillation Patients Newly Treated With Dabigatran or Rivaroxaban Versus Vitamin K Antagonists
Circulation
  • Vol. 132
  • No. 13

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Circulation
  • Vol. 132
  • No. 13
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