David M Kent1, Issa J Dahabreh2, Robin Ruthazer3, Anthony J Furlan4, Christian Weimar5, Joaquín Serena6, Bernhard Meier7, Heinrich P Mattle8, Emanuele Di Angelantonio9, Maurizio Paciaroni10, Herwig Schuchlenz11, Shunichi Homma12, Jennifer S Lutz3, David E Thaler13. 1. Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, 800 Washington St, Box 63, Boston, MA 02111, USA Department of Neurology, Tufts Medical Center/Tufts University School of Medicine, Boston, MA, USA dkent1@tuftsmedicalcenter.org. 2. Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, 800 Washington St, Box 63, Boston, MA 02111, USA Center for Evidence-Based Medicine, School of Public Health, Brown University, Providence, RI, USA Department of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, RI, USA. 3. Predictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, 800 Washington St, Box 63, Boston, MA 02111, USA. 4. Department of Neurology, Case Western Reserve University, Cleveland, OH, USA. 5. Department of Neurology, University of Duisburg-Essen, Essen, Germany. 6. Neurology Department, Hospital Universitari Doctor Josep Trueta Institut D'Investigació Biomèdica de Girona, Girona, Spain. 7. Department of Cardiology, Swiss Cardiovascular Center, Inselspital, University of Bern, Bern, Switzerland. 8. Inselspital, University of Bern, Bern, Switzerland. 9. Department of Public Health and Primary Care, Cambridge University, Cambridge, UK. 10. Stroke Unit and Division of Cardiovascular Medicine, University of Perugia, Perugia, Italy. 11. Department of Medicine, LKH-Graz West, Graz, Austria. 12. Division of Cardiology, Columbia University, New York, NY, USA. 13. Department of Neurology, Tufts Medical Center/Tufts University School of Medicine, Boston, MA, USA.
Abstract
AIMS: The preferred antithrombotic strategy for secondary prevention in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO) is unknown. We pooled multiple observational studies and used propensity score-based methods to estimate the comparative effectiveness of oral anticoagulation (OAC) compared with antiplatelet therapy (APT). METHODS AND RESULTS: Individual participant data from 12 databases of medically treated patients with CS and PFO were analysed with Cox regression models, to estimate database-specific hazard ratios (HRs) comparing OAC with APT, for both the primary composite outcome [recurrent stroke, transient ischaemic attack (TIA), or death] and stroke alone. Propensity scores were applied via inverse probability of treatment weighting to control for confounding. We synthesized database-specific HRs using random-effects meta-analysis models. This analysis included 2385 (OAC = 804 and APT = 1581) patients with 227 composite endpoints (stroke/TIA/death). The difference between OAC and APT was not statistically significant for the primary composite outcome [adjusted HR = 0.76, 95% confidence interval (CI) 0.52-1.12] or for the secondary outcome of stroke alone (adjusted HR = 0.75, 95% CI 0.44-1.27). Results were consistent in analyses applying alternative weighting schemes, with the exception that OAC had a statistically significant beneficial effect on the composite outcome in analyses standardized to the patient population who actually received APT (adjusted HR = 0.64, 95% CI 0.42-0.99). Subgroup analyses did not detect statistically significant heterogeneity of treatment effects across clinically important patient groups. CONCLUSION: We did not find a statistically significant difference comparing OAC with APT; our results justify randomized trials comparing different antithrombotic approaches in these patients. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: The preferred antithrombotic strategy for secondary prevention in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO) is unknown. We pooled multiple observational studies and used propensity score-based methods to estimate the comparative effectiveness of oral anticoagulation (OAC) compared with antiplatelet therapy (APT). METHODS AND RESULTS: Individual participant data from 12 databases of medically treated patients with CS and PFO were analysed with Cox regression models, to estimate database-specific hazard ratios (HRs) comparing OAC with APT, for both the primary composite outcome [recurrent stroke, transient ischaemic attack (TIA), or death] and stroke alone. Propensity scores were applied via inverse probability of treatment weighting to control for confounding. We synthesized database-specific HRs using random-effects meta-analysis models. This analysis included 2385 (OAC = 804 and APT = 1581) patients with 227 composite endpoints (stroke/TIA/death). The difference between OAC and APT was not statistically significant for the primary composite outcome [adjusted HR = 0.76, 95% confidence interval (CI) 0.52-1.12] or for the secondary outcome of stroke alone (adjusted HR = 0.75, 95% CI 0.44-1.27). Results were consistent in analyses applying alternative weighting schemes, with the exception that OAC had a statistically significant beneficial effect on the composite outcome in analyses standardized to the patient population who actually received APT (adjusted HR = 0.64, 95% CI 0.42-0.99). Subgroup analyses did not detect statistically significant heterogeneity of treatment effects across clinically important patient groups. CONCLUSION: We did not find a statistically significant difference comparing OAC with APT; our results justify randomized trials comparing different antithrombotic approaches in these patients. Published on behalf of the European Society of Cardiology. All rights reserved.
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