Literature DB >> 27370013

Comparison of treatment effect estimates of non-vitamin K antagonist oral anticoagulants versus warfarin between observational studies using propensity score methods and randomized controlled trials.

Guowei Li1,2, Anne Holbrook3,4,5, Yanling Jin3, Yonghong Zhang6, Mitchell A H Levine3,4,5, Lawrence Mbuagbaw3,4, Daniel M Witt7, Mark Crowther3,4,5, Stuart Connolly5,8, Chatree Chai-Adisaksopha3, Zhongxiao Wan9, Ji Cheng3,4, Lehana Thabane10,11.   

Abstract

Emerging observational studies using propensity score (PS) methods assessed real-world comparative effectiveness of non-vitamin K antagonist oral anticoagulants (NOACs) versus warfarin in patients with non-valvular atrial fibrillation (AF). We aimed to compare treatment effect estimates of NOACs between PS studies and randomized controlled trials (RCTs). Electronic databases and conference proceedings were searched systematically. Primary outcomes included stroke or systemic embolism (SE) and major bleeding. A random-effects meta-analysis was performed to synthesize the data by pooling the PS- and RCT-derived hazard ratios (HRs) separately. The ratio of HRs (RHR) from the ratio of PS-derived HRs relative to RCT-derived HRs was used to determine whether there was a difference between estimates from PS studies and RCTs. There were 10 PS studies and 5 RCTs included for analysis. No significant difference of treatment effect estimates between the PS studies and RCTs was observed: RHR 1.11, 95 % CI 0.98-1.23 for stroke or SE; RHR 1.07, 95 % CI 0.87-1.34 for major bleeding. A significant association between NOACs and risk of stroke or SE was observed: HR 0.88, 95 % CI 0.83-0.94 for the PS studies; HR 0.79, 95 % CI 0.72-0.87 for the RCTs. However, no relationship between NOACs and risk of major bleeding was found: HR 0.91, 95 % CI 0.79-1.05 for the PS studies; HR 0.85, 95 % CI 0.73-1.00 for the RCTs. In this study, treatment effect estimates of NOACs versus warfarin in patients with non-valvular AF from PS studies are found to be in agreement with those from RCTs.

Entities:  

Keywords:  Anticoagulant; Atrial fibrillation; Propensity score method; Stroke; Warfarin

Mesh:

Substances:

Year:  2016        PMID: 27370013     DOI: 10.1007/s10654-016-0178-y

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  51 in total

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2.  Newly identified events in the RE-LY trial.

Authors:  Stuart J Connolly; Michael D Ezekowitz; Salim Yusuf; Paul A Reilly; Lars Wallentin
Journal:  N Engl J Med       Date:  2010-11-04       Impact factor: 91.245

3.  Understanding interobserver agreement: the kappa statistic.

Authors:  Anthony J Viera; Joanne M Garrett
Journal:  Fam Med       Date:  2005-05       Impact factor: 1.756

4.  Risk of Stroke and Death in Atrial Fibrillation by Type of Anticoagulation: A Propensity-Matched Analysis.

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Journal:  Pacing Clin Electrophysiol       Date:  2015-08-07       Impact factor: 1.976

Review 5.  Treatments effects from randomized trials and propensity score analyses were similar in similar populations in an example from cardiac surgery.

Authors:  O Kuss; T Legler; J Börgermann
Journal:  J Clin Epidemiol       Date:  2011-04-09       Impact factor: 6.437

6.  Observational studies using propensity score analysis underestimated the effect sizes in critical care medicine.

Authors:  Zhongheng Zhang; Hongying Ni; Xiao Xu
Journal:  J Clin Epidemiol       Date:  2014-04-26       Impact factor: 6.437

Review 7.  An overview of the objectives of and the approaches to propensity score analyses.

Authors:  Georg Heinze; Peter Jüni
Journal:  Eur Heart J       Date:  2011-02-28       Impact factor: 29.983

8.  Canadian Cardiovascular Society atrial fibrillation guidelines 2010: prevention of stroke and systemic thromboembolism in atrial fibrillation and flutter.

Authors:  John A Cairns; Stuart Connolly; Sean McMurtry; Michael Stephenson; Mario Talajic
Journal:  Can J Cardiol       Date:  2011 Jan-Feb       Impact factor: 5.223

Review 9.  Comparing the guidelines: anticoagulation therapy to optimize stroke prevention in patients with atrial fibrillation.

Authors:  Stanley G Rockson; Gregory W Albers
Journal:  J Am Coll Cardiol       Date:  2004-03-17       Impact factor: 24.094

10.  Edoxaban versus warfarin in patients with atrial fibrillation.

Authors:  Robert P Giugliano; Christian T Ruff; Eugene Braunwald; Sabina A Murphy; Stephen D Wiviott; Jonathan L Halperin; Albert L Waldo; Michael D Ezekowitz; Jeffrey I Weitz; Jindřich Špinar; Witold Ruzyllo; Mikhail Ruda; Yukihiro Koretsune; Joshua Betcher; Minggao Shi; Laura T Grip; Shirali P Patel; Indravadan Patel; James J Hanyok; Michele Mercuri; Elliott M Antman
Journal:  N Engl J Med       Date:  2013-11-19       Impact factor: 91.245

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Authors:  M Arfan Ikram; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Stricker; Henning Tiemeier; André G Uitterlinden; Meike W Vernooij; Albert Hofman
Journal:  Eur J Epidemiol       Date:  2017-10-24       Impact factor: 8.082

2.  Association of Whole-Body Computed Tomography With Mortality Risk in Children With Blunt Trauma.

Authors:  James A Meltzer; Melvin E Stone; Srinivas H Reddy; Ellen J Silver
Journal:  JAMA Pediatr       Date:  2018-06-01       Impact factor: 16.193

3.  Comparative effectiveness and safety of low-strength and high-strength direct oral anticoagulants compared with warfarin: a sequential cohort study.

Authors:  Nicole L Pratt; Emmae Ramsay; Lisa M Kalisch Ellett; Katherine Duszynski; Sepehr Shakib; Mhairi Kerr; Gillian Caughey; Elizabeth Ellen Roughead
Journal:  BMJ Open       Date:  2019-05-05       Impact factor: 2.692

Review 4.  Risk-Benefit Profile of Direct-Acting Oral Anticoagulants in Established Therapeutic Indications: An Overview of Systematic Reviews and Observational Studies.

Authors:  Emanuel Raschi; Matteo Bianchin; Walter Ageno; Roberto De Ponti; Fabrizio De Ponti
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