Literature DB >> 30713399

Direct Comparison of Low-Dose Dabigatran and Rivaroxaban for Effectiveness and Safety in Patients with Non-Valvular Atrial Fibrillation.

Shih-Wei Meng1, Ting-Tse Lin1, Min-Tsun Liao1, Ho-Min Chen2, Chao-Lun Lai1,2,3,4.   

Abstract

BACKGROUND: We aimed to examine the comparative effectiveness and safety between low-dose dabigatran and rivaroxaban in atrial fibrillation (AF) patients.
METHODS: Using the National Health Insurance claims database in Taiwan, we conducted head-to-head comparisons among adult non-valvular AF patients prescribed with dabigatran 110 mg or rivaroxaban 15 mg between June 1, 2012 and May 31, 2015. A propensity score was derived using logistic regression to model the probability of receiving different non-VKA oral anticoagulants (NOACs) as a function of potential confounders, and an inverse-probability- of-treatment-weighted (IPTW) pseudo-cohort was created. A Cox proportional hazards model was used to compare clinical outcomes in the IPTW pseudo-cohort as the primary analysis. The propensity score-matched analysis was applied as the secondary analysis.
RESULTS: Overall, 13505 dabigatran 110 mg users and 6551 rivaroxaban 15 mgusers were identified. In the primary analysis, the rivaroxaban 15 mg users had a higher risk of all-cause death [hazard ratio (HR) 1.19, 95% confidence interval (CI) 1.02-1.38]. In addition, the rivaroxaban 15 mg users had an increased risk of all-cause death (HR 1.25, 95% CI 1.05-1.50) in the secondary analysis. The risks of ischemic stroke, intracranial hemorrhage and gastrointestinal hemorrhage were similar between the 2 study groups in both the primary and secondary analyses.
CONCLUSIONS: For non-valvular AF patients, rivaroxaban 15 mg seemed to be associated with an increased risk of all-cause death compared with dabigatran 110 mg. This was a retrospective data analysis and the results should not be over-interpreted to guide the choice of different NOACs.

Entities:  

Keywords:  Anticoagulant; Dabigatran; Death; Effectiveness; Rivaroxaban; Safety

Year:  2019        PMID: 30713399      PMCID: PMC6342833          DOI: 10.6515/ACS.201901_35(1).20180817A

Source DB:  PubMed          Journal:  Acta Cardiol Sin        ISSN: 1011-6842            Impact factor:   2.672


  30 in total

1.  Accuracy of cause-of-death coding in Taiwan: types of miscoding and effects on mortality statistics.

Authors:  T H Lu; M C Lee; M C Chou
Journal:  Int J Epidemiol       Date:  2000-04       Impact factor: 7.196

2.  Marginal structural models and causal inference in epidemiology.

Authors:  J M Robins; M A Hernán; B Brumback
Journal:  Epidemiology       Date:  2000-09       Impact factor: 4.822

3.  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.

Authors:  John W Eikelboom; Lars Wallentin; Stuart J Connolly; Mike Ezekowitz; Jeff S Healey; Jonas Oldgren; Sean Yang; Marco Alings; Scott Kaatz; Stefan H Hohnloser; Hans-Christoph Diener; Maria Grazia Franzosi; Kurt Huber; Paul Reilly; Jeanne Varrone; Salim Yusuf
Journal:  Circulation       Date:  2011-05-16       Impact factor: 29.690

4.  Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.

Authors:  B F Gage; A D Waterman; W Shannon; M Boechler; M W Rich; M J Radford
Journal:  JAMA       Date:  2001-06-13       Impact factor: 56.272

5.  A basic study design for expedited safety signal evaluation based on electronic healthcare data.

Authors:  Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2010-08       Impact factor: 2.890

6.  Mortality trends in patients diagnosed with first atrial fibrillation: a 21-year community-based study.

Authors:  Yoko Miyasaka; Marion E Barnes; Kent R Bailey; Stephen S Cha; Bernard J Gersh; James B Seward; Teresa S M Tsang
Journal:  J Am Coll Cardiol       Date:  2007-02-16       Impact factor: 24.094

7.  Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

Authors:  Hude Quan; Vijaya Sundararajan; Patricia Halfon; Andrew Fong; Bernard Burnand; Jean-Christophe Luthi; L Duncan Saunders; Cynthia A Beck; Thomas E Feasby; William A Ghali
Journal:  Med Care       Date:  2005-11       Impact factor: 2.983

8.  Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation.

Authors:  Robert G Hart; Lesly A Pearce; Maria I Aguilar
Journal:  Ann Intern Med       Date:  2007-06-19       Impact factor: 25.391

9.  Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation.

Authors:  Gregory Y H Lip; Robby Nieuwlaat; Ron Pisters; Deirdre A Lane; Harry J G M Crijns
Journal:  Chest       Date:  2009-09-17       Impact factor: 9.410

10.  Dabigatran versus warfarin in patients with atrial fibrillation.

Authors:  Stuart J Connolly; Michael D Ezekowitz; Salim Yusuf; John Eikelboom; Jonas Oldgren; Amit Parekh; Janice Pogue; Paul A Reilly; Ellison Themeles; Jeanne Varrone; Susan Wang; Marco Alings; Denis Xavier; Jun Zhu; Rafael Diaz; Basil S Lewis; Harald Darius; Hans-Christoph Diener; Campbell D Joyner; Lars Wallentin
Journal:  N Engl J Med       Date:  2009-08-30       Impact factor: 91.245

View more
  4 in total

1.  Health Economics of Stroke Prevention in Atrial Fibrillation.

Authors:  Kang-Ling Wang; Chern-En Chiang
Journal:  Acta Cardiol Sin       Date:  2020-01       Impact factor: 2.672

2.  Percutaneous Left Atrial Appendage Closure Confirmed by Intra-Procedural Transesophageal Echocardiography under Local Anesthesia: Safety and Clinical Efficacy.

Authors:  Binhao Wang; Zhao Wang; Bin He; Guohua Fu; Mingjun Feng; Jing Liu; Yibo Yu; Xianfeng Du; Huimin Chu
Journal:  Acta Cardiol Sin       Date:  2021-03       Impact factor: 2.672

3.  Critical appraisal and issues regarding generalisability of comparative effectiveness studies of NOACs in atrial fibrillation and their relation to clinical trial data: a systematic review.

Authors:  Eveline M Bunge; Ben van Hout; Sylvia Haas; Georgios Spentzouris; Alexander Cohen
Journal:  BMJ Open       Date:  2021-02-01       Impact factor: 2.692

4.  Cost-Effectiveness Analysis of Oral Anticoagulants in Stroke Prevention among Patients with Atrial Fibrillation in Taiwan.

Authors:  Chia-Te Liao; Mei-Chuan Lee; Zhih-Cherng Chen; Li-Jung Elizabeth Ku; Jung-Der Wang; Han Siong Toh
Journal:  Acta Cardiol Sin       Date:  2020-01       Impact factor: 2.672

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.