RESUMEN
BACKGROUND: In the last 4 years, four novel oral anticoagulants have been developed as alternatives to warfarin and antiplatelet agents for stroke prevention in atrial fibrillation (AF) patients. The objective of this review was to estimate the comparative effectiveness of all antithrombotic treatments for AF patients. MATERIALS AND METHODS: Data sources were Medline Ovid (1946 to October 2015), Embase Ovid (1980 to October 2015), and the Cochrane Central Register of Controlled Trials (CENTRAL, Issue 9, 2015). Randomized controlled trials of AF patients were selected if they compared at least two of the following: placebo, aspirin, aspirin and clopidogrel combination therapy, adjusted-dose warfarin (target international normalized ratio 2.0-3.0), dabigatran, rivaroxaban, apixaban, and edoxaban. Bayesian network meta-analyses were conducted for outcomes of interest (all stroke, ischemic stroke, myocardial infarction, overall mortality, major bleeding, and intracranial hemorrhage). RESULTS: Based on 16 randomized controlled trials of 96,826 patients, all oral anticoagulants were more effective than antiplatelet agents at reducing the risk of ischemic stroke and all strokes. Compared to warfarin, dabigatran 150 mg (rate ratio 0.65, 95% credible interval 0.52-0.82) and apixaban (rate ratio 0.82, 95% credible interval 0.69-0.97) reduced the risk of all strokes. Dabigatran 150 mg was also more effective than warfarin at reducing ischemic stroke risk (rate ratio 0.76, 95% credible interval 0.59-0.99). Aspirin, apixaban, dabigatran 110 mg, and edoxaban were associated with less major bleeding than warfarin. CONCLUSION: All oral anticoagulants reduce the risk of stroke in AF patients. Some novel oral anticoagulants are associated with a lower stroke and/or major bleeding risk than warfarin. In addition to the safety and effectiveness of drug therapy, as reported in this study, individual treatment recommendations should also consider the patient's underlying stroke and bleeding risk profile.
RESUMEN
BACKGROUND: Atrial fibrillation (AF) poses a significant economic burden. An increasing number of interventions for AF require cost-effectiveness analysis with decision-analytic modeling to demonstrate value. However, high-quality cost estimates of AF that can be used to inform decision-analytic models are lacking. OBJECTIVES: The objectives of this study were to determine whether phase-based costing methods are feasible and practical for informing decision-analytic models outside of oncology. METHODS: Patients diagnosed with AF between 1 January 2003 and 30 June 2011 in Ontario, Canada were identified based on a hospital admission for AF using administrative data housed at the Institute for Clinical Evaluative Sciences. Patient observations were then divided into phases based on clinical events typically used for decision-analytic modeling (i.e., minor stroke/transient ischemic attack [TIA], moderate to severe ischemic stroke, myocardial infarction, extracranial hemorrhage [ECH], intracranial hemorrhage [ICH], multiple events, death from an event, or death from other causes). First 30-day and greater than 30-day costs of healthcare resources in each health state were estimated based on a validated methodology. All costs are reported in 2013 Canadian dollars (Can$) and from a healthcare payer perspective. RESULTS: Patients (n = 109,002) with AF who did not experience a clinical event incurred costs of Can$1566 per 30 days, on average. The average 30-day cost of experiencing a fatal clinical event was Can$42,871, but the cost of dying from all other causes was much smaller (Can$12,800). The clinical events associated with the highest short-term costs were ICH (Can$22,347) and moderate to severe ischemic stroke (Can$19,937). The lowest short-term costs were due to minor ischemic stroke/TIA (Can$12,515) and ECH (Can$12,261). Patients who had experienced a moderate to severe ischemic stroke incurred the highest long-term costs. CONCLUSIONS: Real-world Canadian data and a phase-based costing approach were used to estimate short- and long-term costs associated with AF-related major clinical events. The results of this study can also inform decision-analytic models for AF.