European Heart Journal – Cardiovascular Pharmacotherapy (2015) 1, 15–28 doi:10.1093/ehjcvp/pvu007 ORIGINAL ARTICLE Thrombosis and anti-thrombotic therapy A novel approach indirectly comparing benefit–risk balance across anti-thrombotic therapies in patients with atrial fibrillation Ariel Dogliotti 1,2 and Robert P. Giugliano 3* 1 Unidad de Epidemiologı´a Clı´nica y Estadı´stica, Grupo Oron˜o, Rosario, Argentina; 2Instituto Cardiovascular de Rosario, Rosario, Argentina; and 3Brigham and Women’s Hospital, Harvard Medical School, TIMI Study Group, 350 Longwood Avenue, 1st Floor Offices, Boston 02115, MA, USA Received 7 August 2014; revised 14 September 2014; accepted 7 October 2014 Background Anti-thrombotic reduces thromboembolic events but increases bleeding in patients with atrial fibrillation (AF). We evaluated the benefit –risk of anti-platelet and anti-coagulant therapies, weighing these conflicting effects of treatment. ..................................................................................................................................................................................... Methods Randomized controlled trials in patients with AF were identified from MEDLINE, Embase, and Cochrane Central Register of Controlled Trials through April 2014. We performed a stochastic multi-criteria acceptability analysis, which allowed us to compute a comprehensive benefit –risk profile. In the primary analysis, we used prior established rankings of mortality, intracranial haemorrhage, ischaemic stroke, myocardial infarction, major extracranial haemorrhage, and systemic embolism based on utility functions. In sensitivity analyses, we explored: (i) rankings based on costs, (ii) bleeding ranked higher than thromboembolism, and (iii) thromboembolism ranked higher than bleeding events. ..................................................................................................................................................................................... Results 100 913 patients (21 studies) were allocated to placebo/control, aspirin and/or clopidogrel, vitamin K antagonists (VKAs), or new oral anti-coagulants (NOACs). Based on utility, NOACs were better than VKA or anti-platelet therapy; dabigatran 150 mg was ranked highest (21% chance of being best). Ranked by cost, the 3 factor Xa inhibitors were very similar (16 –18% chance of being best). When haemorrhagic events were weighted more than ischaemic events, edoxaban 30 mg was ranked higher (22%), while rivaroxaban (23%) was most preferred when ischaemic events were rated worse than haemorrhagic events. ..................................................................................................................................................................................... Conclusion New oral anti-coagulants had a more favourable benefit–risk profile across a wide range of assumptions regarding the relative importance of clinical events. Differences between NOACs were modest and depended upon the order of ranking of clinical events. ----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords Anti-coagulant † Anti-platelet † Atrial fibrillation † Bleeding, † Haemorrhage † Novel oral anti-coagulant † Stroke † Vitamin K antagonist Introduction In patients with atrial fibrillation (AF), Vitamin K antagonists (VKA), such as warfarin, reduce the risk of stroke by 64% compared with placebo, but increase the risk of haemorrhage.1 Anti-platelet agents also significantly reduce the incidence of stroke,1,2 but are less effective than oral anti-coagulation. A meta-analysis of trials comparing warfarin vs. aspirin (ASA) showed better stroke reduction with warfarin, but a higher rate of intracranial bleeding, with no difference in total mortality.1 In a more recent randomized trial,3 anti-coagulant therapy was superior to the combination of clopidogrel plus ASA in reducing stroke, with no difference in bleeding. Several novel oral anti-coagulants (NOACs) have been developed in an attempt to overcome the many challenges faced by clinicians and patients with the use of warfarin.4 – 6 Dabigatran,7 rivaroxaban,8 apixaban,9 and edoxaban10 were each ‘at least as effective as’ warfarin in reducing the risk of stroke or embolism. Not only did these new agents meet criteria for non-inferiority but in addition dabigatran 150 mg twice daily and apixaban 5 mg twice daily were superior to warfarin in reducing the composite of stroke or systemic embolism. Each of the NOACs markedly reduced intracranial and fatal bleeding when compared with warfarin titrated to a target INR of 2.0 –3.0. Finally, in a trial comparing apixaban with ASA in patients not eligible or willing to take a VKA, apixaban reduced the risk of stroke or * Corresponding author. Tel: +1 617 278 0145, Fax: +1 617 734 7320, Email: rgiugliano@partners.org Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2015. For permissions please email: journals.permissions@oup.com 16 systemic embolism compared with ASA monotherapy without significantly increasing the risk of major bleeding or intracranial haemorrhage.11 In a recent meta-analysis of large phase III trials of NOAC compared with warfarin in patients with AF,12 statistically significant reductions with NOAC were observed in the primary outcome of stroke or systemic embolism (19% relative reduction), as well as allcause mortality (10%) and haemorrhagic stroke (51%). However, standard meta-analyses are unable to integrate all available randomized evidence in one analysis that also includes indirect comparisons between therapies. In contrast, network meta-analysis allows a unified, coherent analysis of all randomized controlled trials that compare anti-thrombotic drugs head to head or with placebo/ control while fully respecting randomization.13 Recently, a network meta-analysis14 that included three of the NOACs showed that dabigatran 150 mg was ranked highest in prevention of stroke (70% chance of being the best), the composite of ischaemic stroke or systemic embolism (60%), and mortality (31%). Rivaroxaban (30%) and ASA plus clopidogrel had the highest likelihood of major bleeding (29%). Several large clinical trials tested the efficacy and safety of different anti-platelet and anti-coagulant strategies. In four of these studies: ACTIVE (W),3 RE-LY,7 ARISTOTLE,9 and ENGAGE AF-TIMI 48,10 the benefit –risk was assessed by comparing the NOACs vs. warfarin on net clinical outcomes that combined a variety of thromboembolic events and bleeding with mortality. However, use of net clinical outcomes can be an imprecise approach, as it does not consider the weight or clinical importance of each Figure 1 Flow diagram of literature search. A. Dogliotti and R.P. Giugliano outcome. Although such a measure is easy to interpret and implement in clinical practice, drug benefit–risk analysis typically includes multiple benefit and risk criteria and consequently must include value judgements. Moreover, when multiple alternatives (treatments) and different criteria (efficacy and safety outcomes) are involved, a more complex model is required. Choosing anti-thrombotic therapy is difficult because each therapy may have different strengths and weaknesses. We performed a network meta-analysis and a stochastic multicriteria acceptability analysis (SMAA), which allows to compute the typical value judgement that support a decision, to quantify decision uncertainly, and to compute a comprehensive benefit –risk profile to answer the following question: What anti-thrombotic treatment in patients with AF has the best balance of benefit and risk? Material and methods Search strategy We searched Medline, Embase, and the Cochrane database of systematic reviews through April 2014 with no language restriction using the following Medical Subject Heading and keywords: anti-coagulant, anti-platelet, ASA, clopidogrel, warfarin, VKAs, dabigatran, apixaban, rivaroxaban, edoxaban, AF, atrial arrhythmias, coupled with outcome searched using the terms stroke, cerebrovascular accident, and transient ischaemic attack. We also reviewed the reference lists of published meta-analyses of anti-coagulant and anti-platelet therapies to prevent stroke and embolic events in patients with AF. Overall, 21 manuscripts were included in our analyses (Figure 1). We registered our review online with METCARDIO (registration #1– 2014). Benefit– risk balance of anti-thrombotics in atrial fibrillation Eligibility of studies Inclusion criteria for eligible studies were: (i) randomized controlled trials of adjusted-dose VKA, ASA, clopidogrel, or NOACs in patients with nonvalvular AF; (ii) intention-to-treat analysis; (iii) minimum 1 year follow-up. Data abstraction and quality assessment Two independent reviewers performed data extraction. We used consensus to resolve discrepancies. The endpoints of interest were: mortality from any cause, ischaemic stroke, myocardial infarction, and systemic embolism (efficacy outcomes); intracranial haemorrhage and major extracranial haemorrhage (safety outcomes). We used data from the intention-to-treat analyses. Statistical analysis Network meta-analysis was carried out in the Bayesian framework using Markov Chain Monte Carlo simulation15 in the GeMTC R package.16 The analysis pooled relative effects on the odds ratio scale using the binomial likelihood and logit link function. GeMTC automatically specified vague prior distributions for the trial baseline effects, the relative effects, and the random-effects standard deviation. First, a random-effects model network meta-analysis was performed. The statistical analysis is based on binomial likelihoods with a logit link function. GeMTC automatically specified vague prior distributions for the trial baseline effects, the relative effects (normal with mean 0 and standard deviation 37.5), and the random-effects standard deviation (uniform in the interval 0–2.5). We used a technique known as ‘nodesplitting’17 to evaluate for inconsistency in the findings of the network 17 meta-analysis coming from direct vs. indirect evidence. Node-splitting assesses whether direct and indirect evidence on a specific node (the split node) are in agreement. Second, we used a SMAA-218 – 23 as a new and more elaborate approach to drug benefit – risk analysis to overcome the limitations of the net clinical benefit approach. Stochastic multi-criteria acceptability analysis was carried out based on the estimated incidence distributions of each of the events of interest (criteria). The incidence distributions were derived from relative effect estimates obtained from the network meta-analyses, combined with baseline incidence estimates for Warfarin treatment. We performed two main analyses in a pre-specified order based on the authors’ judgement. The first used preference information based on utility functions.24 – 34 A utility function is a generic multi-attribute preference-based measure of health status and health-related quality of life that is widely used as an outcome measure in clinical studies, in population health surveys, in the estimation of quality-adjusted life years, and in economic evaluations. Using utility functions, the events in order from lowest (worst) to highest (best) were death from any cause, intracranial haemorrhage, ischaemic stroke, myocardial infarction, major extracranial haemorrhage, and systemic embolism. The second main analysis ordered events based on medical costs.35 – 37 Here death had the highest cost and was followed by major extracranial haemorrhage, ischaemic stroke, myocardial infarction, intracranial haemorrhage, and systemic embolism. We also performed two sensitivity analyses that maintained death as the lowest state and then ranked the non-fatal events as follows: (i) assigning the bleeding events lower health states than thromboembolic events Figure 2 Network of eligible comparisons for the multiple-treatment meta-analysis for efficacy. The numbers represent the number of trials or arms comparing each pair of treatment. 18 and (ii) assigning the thromboembolic events lower health states than bleeding events. These were chosen as sensitivity analyses since the two scenarios represent the extremes in ordering of the risks (bleeding) and benefits (thromboembolic events) of anti-thrombotic therapy. Within each group of bleeding and thromboembolic events, individual endpoints were ordered according to their utility function. We also ranked the various anti-thrombotic treatments in terms of their likelihood of leading to the best results for each outcome (also known as the ‘rank acceptability index’). In this approach, the share of all possible values of the weight vector W and the joint random vector X for which alternative i is ranked at place r is calculated. The result can be interpreted as the probability that alternative i is ranked at place r, where 0 indicates that the alternative will never obtain rank r and 1 indicates that alternative i will always obtain rank r. The rank acceptability index is computed numerically as a multi-dimensional integral over the criteria distributions and the favourable rank weights. The preferred (best) alternatives are those with the highest probabilities for the best rank. The confidence factor (CF) is the probability for an alternative to obtain the first rank when the central weight vector is chosen. The CF is computed as a multi-dimensional integral over the criteria distributions. Results There were 100 913 patients with non-valvular AF, treated with one of 10 different therapies: ASA, ASA plus clopidogrel, dabigatran 150 mg twice daily, dabigatran 110 mg twice daily, adjusted dose of VKA, rivaroxaban, apixaban, edoxaban 30 mg once daily, edoxaban 60 mg once daily, and control/placebo (Figure 2). The main study and baseline characteristics are listed in Table 1. The 10 therapies resulted in 45 theoretical two-way comparisons for each of six outcomes (yielding a total of 6 × 45 ¼ 270 evaluations). The following 14 comparisons were direct (Figure 2): VKA vs. control/placebo, ASA vs. control/placebo, VKA vs. ASA, ASA vs. ASA plus clopidogrel, ASA plus clopidogrel vs. VKA, VKA vs. apixaban, ASA vs. apixaban, VKA vs. dabigatran 150 mg, VKA vs. dabigatran 110 mg, dabigatran 150 mg vs. dabigatran 110 mg, rivaroxaban vs. VKA, edoxaban 30 mg vs. VKA, edoxaban 60 mg vs. VKA, and edoxaban 30 mg vs. edoxaban 60 mg. Findings Network meta-analyses We built a network meta-analysis in order to synthesize the outcomes for each treatment and endpoint. The summary results are shown in Table 2, and details of the network meta-analysis are provided in Table A1. Analyses with preference information When utility values were used to order outcomes (Figure 3, Table A2), dabigatran 150 mg obtained 20% of chance to rank first, followed closely by the other five NOAC regimens. Meanwhile VKA, antiplatelet regimens, and placebo/control had a 0–1% probability of the first rank. Placebo/control had a 74% chance to be ranked worst (rank 10), while ASA alone and ASA plus clopidogrel had the highest probabilities to be ranked 9th (49 and 23%, respectively), while VKA occupied the central ranks (82% probability of being ranked 4th to 7th). When the order of events was based on medical costs (Figure 4, Table A2), the chance of been ranked first changed little: rivaroxaban, A. Dogliotti and R.P. Giugliano dabigatran 150 mg, and edoxaban 30 mg each achieved 18% of being ranked first. Again, placebo/control and anti-platelet therapy ranked worst. Vitamin K antagonist had an identical performance whether using medical costs or patient utilities. Figure 4A and B and Table A3 show the CFs. Again in both scenarios, the NOACs were the best options. Based on utility, all NOACs were similar, although dabigatran 150 mg obtained modestly the first probability to be the best alternative (21% chance of been the best). Aspirin was the worst alternative (0%). Based on medical costs, NOACs were closely similar: edoxaban 30 mg 19%, rivaroxaban and dabigatran 150 mg 18%, VKA (1%), ASA (0%) or ASA plus clopidogrel (1%) were similar to placebo/control (1%). An analysis based on the central weights and CFs showed that the first-rank acceptabilities are unlikely to change if more precise preference information (e.g. an exact weighting) were given. In a sensitivity analysis, ranking all the bleeding events higher than thromboembolic events resulted in edoxaban 30 mg scoring the highest CF (22%), while dabigatran 150 mg, rivaroxaban, apixaban and edoxaban 60 mg each scored 15%. In the second sensitivity analysis that ranked ischaemic events highest, rivaroxaban (23%) and dabigatran 150 mg (22%) were ranked highest, while dabigatran 110 mg and edoxaban 30 mg (both 10%) were ranked lowest among the six NOAC regimens. In both sensitivity analyses, antiplatelet regimens and VKA rated equal or slightly worse than placebo/control. Consistency of network model No major inconsistencies or qualitative differences (e.g. change in directionality of the estimate) were observed when we compared the effect estimates based on direct vs. indirect evidence from the comparisons, supporting the robustness of the model. Discussion In this analysis of data from randomized clinical trials of antithrombotic agents in patients with non-valvular AF, we observed that the benefit– risk including both efficacy and safety endpoints favoured NOACs over either VKA or anti-platelet regimens. The benefit of NOACs over other therapies was consistent whether clinical events were ordered based on utility, costs, with greatest weight for thrombotic events, or with greatest weight for haemorrhagic events. Since individual trials used a composite of all stroke and systemic embolism as the primary efficacy outcome, and major bleeding as the principal safety outcome, performing a benefit–risk analysis can be tricky. For example, the endpoint of ‘all stroke’ consists of ischaemic stroke (an event prevented by anti-thrombotic therapy) and haemorrhagic stroke (an event that may be a consequence of anti-thrombotic therapy). Moreover, major bleeding consists of serious bleeding events that may be intra- or extracranial in location, with all haemorrhagic stroke qualifying as a major bleed by definition. This leads to the possibility of ‘double counting’ the importance of haemorrhagic stroke if the traditional primary efficacy and safety endpoints are not carefully analysed. In our analysis, we have differentiated each of the major clinical events and also explored different orders of clinical impact in order to provide a more accurate and Main study and baseline characteristics Clinical trial, year Size (n) Age (mean) Male (%) HTN (%) DM (%) Prior MI (%) HF (%) Prior TIA or stroke (%) Target INR Median follow-up (months) Lost to follow-up (%) 24 24 NR 0 ............................................................................................................................................................................................................................................. AFASAK-I38, 1989 BAATAF39, 1990 1007 420 CAFA40, 1991 378 SPAF-I41, 1991 SPINAF42, 1992 421 525 EAFT43, 1993 439 SPAF-II44, 1994 AFASAK-II45, 1998 PATAF46, 1999 LASAF47, 1999 ACTIVE (W)3, 2006 JAST48, 2006 ACTIVE (A) 2, 2006 ATAFS49, 2006 BAFTA50, 2007 WASPO51, 2007 RE-LY7, 2009a 73.7 68 8.5 14.9 12.9 13.4 38.6 11.9 52 58.5 15.5 18.4 71.5 56 42.03 12.9 8.4 715 339 64 73.6 76 62 53 42 17 12 9 272 70.4 46 36.3 17 8.6 285 6706 66 70.2 52 66 51 82 8 21 38 14 65,5 67 74.79 31.5 51 72 100 871 67.7 53.5 72.52 65 70 7554 704 71 63.3 58 59.7 973 81.5 54 53.1 13.9 83 71 50 63 48 78.9 4 23.3 75 18 113 50.5 25.9 5 16.51 8 3.71 18.9 70 17 69.5 18 5 31 14 33 9 9.6 16.1 19.7 31.8 2.8–4.2 1.5–2.7 2–3 14.4 1.3 2–4.5 1.4–2.8 15.6 21 0 6 27.6 1.9 2–4.5 2–3 37.2 42 0.4 0 2.5–3.5 32.4 0 2–3 24 15.4 NR 0.33 25.2 NR 2–3 44.4 18.12 0.8 NR 13.1 2–3 32.4 0.82 20 2–3 2–3 13.2 24 NR 0.16 6 15 2.5–4 2.5 13 ROCKET-AF8, 2011 14 171 73 60.3 90.5 40 18 62 55 2–3 23.3 0.22 ARISTOTLE9, 2011 18 201 70 60.5 87.4 25 13.9 35 19.4 2–3 21.6 0.4 AVERROES11, 2011b ENGAGE AF-TIMI 4810, 2013 5599 21 105 70 72 59 62 86.5 93.6 19 36.1 12 39 57.5 14 28.3 2–3 21 33.6 NR 0.05 Benefit– risk balance of anti-thrombotics in atrial fibrillation Table 1 DM, diabetes mellitus; HF, heart failure; HTN, hypertension; NR, not reported; TIA, transient ischaemic attack. a RE-LY, corrected data.61 Patients were eligible for this study if their physicians considered VKA therapy to be unsuitable for them. The difficulty or anticipated difficulty of maintaining the INR in the therapeutic range was a major reason for the unsuitability of vitamin K antagonist therapy in this study. b 19 20 Table 2 Results of network meta-analyses Drug, better than Mortality OR (95% CI) Ischaemic stroke OR (95% CI) Systemic embolism OR (95% CI) Intracranial haemorrhage OR (95% CI) Apixaban vs. Control 0.58 (0.34, 0.87) ASA ASA+ Clop Control 0.39 (0.25, 0.64) 0.53 (0.26, 0.92) 0.28 (0.16, 0.47) ASA ASA+ Clop Control 0.27 (0.10, 0.74) 0.25 (0.06, 0.73) 0.23 (0.07, 0.65) VKA 0.42 (0.16, 0.92) Control Control 0.71 (0.47, 0.98) 0.53 (0.32, 0.95) ASA+ Clop 0.41 (0.15, 0.88) ASA+ Clop VKA 0.12 (0.01, 0.57) 0.16 (0.01, 0.65) VKA 0.31 (0.10, 0.88) ASA+ Clop VKA 0.23 (0.06, 0.97) 0.30 (0.10, 0.88) ............................................................................................................................................................................................................................................. ASA vs. ASA+ Clop vs. Control Dabigatran 110 vs. Control 0.56 (0.29, 0.96) Control 0.35 (0.18, 0.73) Dabigatran 150 vs. Control 0.55 (0.27, 0.93) Edoxaban 30 vs. Control 0.54 (0.28, 0.90) ASA ASA+ Clop Control Control 0.34 (0.19, 0.71) 0.45 (0.21, 0.94) 0.24 (0.12, 0.50) 0.46 (0.23, 0.91) Edoxaban 60 vs. Control 0.57 (0.28, 0.95) ASA Control 0.44 (0.25, 0.92) Rivaroxaban vs. VKA vs. Control Control ASA 0.57 (0.29, 0.96) 0.61 (0.43, 0.81) 0.79 (0.59, 0.94) ASA ASA ASA+ Clop Control 0.31 (0.16, 0.64) ASA ASA+ Clop Control 0.25 (0.07, 0.97) 0.24 (0.05, 0.89) 0.22 (0.06, 0.79) 0.41 (0.22, 0.85) 0.45 (0.35, 0.63) 0.59 (0.37, 0.93) 0.32 (0.22, 0.46) ASA ASA+ Clop Control 0.41 (0.20, 0.82) 0.37 (0.13, 0.83) 0.34 (0.16, 0.71) Drugs of the first column are better than the therapies listed in the other columns to the right. There were no statistically significant differences between therapies for the endpoints of myocardial infarction and major extracranial haemorrhage (as detailed results in Appendix). ASA, aspirin; Clop, clopidogrel; OR (95% CI), odds ratio (credibility interval); VKA, vitamin K antagonist. A. Dogliotti and R.P. Giugliano Benefit– risk balance of anti-thrombotics in atrial fibrillation 21 Figure 3 Preference information. (A) Based on utility functions:24 – 34 (means ‘worse than’) mortality intracranial haemorrhage ischaemic stroke myocardial infarction major extracranial haemorrhage systemic embolism. (B) Based on medical costs:35 – 37 mortality major extracranial haemorrhage ischaemic stroke myocardial infarction intracranial haemorrhage systemic embolism. The rank acceptabilities represent, given the preference information, the probability (in per cent) that each treatment is best (rank 1), the second highest (rank 2), etc. Rank probabilities sum to 100%, both within a rank over treatments and within a treatment over ranks. Figure shows the cumulative probability (plotted on the y-axis) of having a rank that is equal to or less than the ranking on the x-axis. fair assessment of the various anti-thrombotic regimens in patients with AF. We used a SMAA that ranks the individual therapeutic interventions from most likely to least likely of being the best. We found that the NOACs were most likely to be the best active therapy with respect to each of the six major efficacy-safety outcomes of mortality from any cause, intracranial haemorrhage, ischaemic stroke, myocardial infarction, major extracranial haemorrhage, and systemic embolism. Several other network meta-analyses of NOACs in patients with AF have been published,14,52 – 60 but none shared our approach of ordering clinical endpoints to permit comparison of net outcomes with the various anti-thrombotic strategies that have been tested in clinical trials. Furthermore, we included data from the largest and most recent trial in AF (ENGAGE AF-TIMI 48).10 In contrast with standard pairwise meta-analyses,12 our approach evaluated weighted ordering of events (with three sensitivity analyses exploring differing approaches to order the events), integrated indirect comparisons, and included trials with various comparator arms. There have been no large randomized clinical trials directly comparing new oral anti-coagulants in patients with AF to date. Furthermore, it is impractical to perform head-to-head comparisons of the 10 anti-thrombotic strategies that have been tested thus far in clinical trials. Thus, indirect analyses represent an important tool to evaluate the 45 different pairwise comparisons of these 10 options. While NOACs appeared the most favourable strategy in our analyses, we recognize these drugs have limitations. Currently, there is no widely available assay to measure their anti-coagulant effect. In cases of life-threatening bleeding or need for urgent surgery, currently there are no antidotes or specific reversible agents available for clinical use. Finally, the greater drug costs of NOACs limits their availability in countries where the majority of the drug costs is borne by the patient. When interpreting the results of these analyses and considering how an individual patient should be treated, it is important for the clinician to consider and weigh the relative balance of thromboembolic events and risk of bleeding for the individual patient. 22 A. Dogliotti and R.P. Giugliano Figure 4 Confidence factor. The confidence is the probability that an alternative ranks first if the decision-maker’s preferences agree with the alternative’s central weight vector. (A) Based on utility functions. (B) Based on medical costs. Limitations We recognize that our approach to analysing benefit– risk has several limitations. The findings based on clinical trial populations may not be generalizable to clinical practice where patients tend to be older and have more comorbidities (e.g. cancer, severe renal failure) that exclude them from clinical trials. The studies in our analysis were heterogeneous with respect to the characteristics of the patients, the definitions and assessment of some of the outcomes, the concomitant interventions allowed by the protocols, the length of, and differential loss in follow-up (Table 1). In addition, our analyses do not account for other changes in clinical practice that have evolved over the past 25 years. There were a limited numbers of some events (e.g. systemic embolism) and certain therapies across the 21 studies were under-represented, which reduces the power to find differences and may affect the precision of our results. Specifically, given the small number of trials5 performed to date with the four NOACs, our analyses are underpowered to determine whether important differences exist between individual NOACs. We did not adjust for multiple comparisons, and thus difference of marginal statistical significance should be interpreted cautiously. We recognize that events are not completely independent of one another, and we did allow multiple events per patient. Nevertheless, we believe that our approach offers clinicians a more comprehensive, quantitative, and objective framework, as opposed to an intuitive approach, to evaluate the benefit–risk of 10 anti-thrombotic strategies in patients with AF. Conclusions In this benefit –risk analysis of anti-thrombotic therapies in patients with AF using a multiple-treatment meta-analysis and stochastic Benefit– risk balance of anti-thrombotics in atrial fibrillation multi-objective acceptability procedures, we found that novel anticoagulants were the most preferred. None of the individual novel agents should be considered superior to another based on these data. Vitamin K antagonist and anti-platelet regimens appeared to offer little advantage in efficacy or safety compared with NOACs. Conflict of interest: R.G. is a member of the TIMI Study Group, who has received research grant support from Johnson & Johnson and from Daiichi-Sankyo related to clinical trials of anti-coagulants. He has received honoraria for consultation and/or lectures from Bristol-Myers Squibb, Daiichi-Sankyo, Johnson & Johnson, Pfizer and Portola. References 1. Hart RG, Pearce LA, Aguilar MI. 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Table A1 Odds ratio and credibility interval of drug named in column vs. row Mortality from any cause Apixaban 1.36 (0.96, 2.13) 1.23 (0.72, 2.08) 1.73 (1.14, 2.90) 0.96 (0.49, 1.82) 0.97 (0.47, 1.79) 0.94 (0.47, 1.74) 0.97 (0.51, 1.84) 0.97 (0.51, 1.82) 1.07 (0.71, 1.56) 0.73 (0.47, 1.04) 0.82 (0.48, 1.38) ASA 1.10 (0.78, 1.73) 0.91 (0.58, 1.28) ASA+ clopidogrel 1.26 (0.96, 1.72) 1.41 (0.94, 2.35) 0.72 (0.38, 1.18) 0.78 (0.40, 1.52) 0.70 (0.36, 1.16) 0.78 (0.39, 1.49) 0.69 (0.36, 1.14) 0.76 (0.39, 1.42) 0.72 (0.38, 1.19) 0.80 (0.40, 1.52) 0.73 (0.39, 1.17) 0.80 (0.42, 1.52) 0.79 (0.59, 0.94) 0.88 (0.58, 1.27) 0.58 (0.34, 0.87) 0.80 (0.58, 1.04) 0.71 (0.43, 1.07) Control 0.56 (0.29, 0.96) 0.55 (0.27, 0.93) 0.54 (0.28, 0.90) 0.57 (0.28, 0.95) 0.57 (0.29, 0.96) 0.61 (0.43, 0.81) 1.04 (0.55, 2.04) 1.04 (0.56, 2.12) 1.38 (0.85, 2.67) 1.42 (0.86, 2.78) 1.28 (0.66, 2.48) 1.28 (0.67, 2.59) 1.77 (1.04, 3.49) 1.81 (1.07, 3.68) Dabigatran 110 1.01 (0.61, 1.78) 0.99 (0.56, 1.64) Dabigatran 150 0.97 (0.46, 2.01) 0.97 (0.47, 2.09) 1.02 (0.48, 2.07) 1.02 (0.49, 2.19) 1.02 (0.49, 2.14) 1.02 (0.48, 2.21) 1.11 (0.65, 1.88) 1.12 (0.66, 1.95) 1.07 (0.58, 2.11) 1.46 (0.88, 2.75) 1.31 (0.70, 2.58) 1.86 (1.11, 3.63) 1.03 (0.50, 2.16) 1.04 (0.48, 2.14) Edoxaban 30 1.04 (0.62, 1.75) 1.04 (0.52, 2.21) 1.14 (0.69, 1.93) 1.03 (0.54, 1.98) 1.03 (0.55, 1.94) 1.38 (0.84, 2.65) 1.37 (0.85, 2.57) 1.25 (0.66, 2.48) 1.25 (0.66, 2.41) 1.75 (1.06, 3.52) 1.75 (1.04, 3.47) 0.98 (0.48, 2.09) 0.98 (0.47, 2.05) 0.98 (0.46, 2.04) 0.98 (0.45, 2.07) 0.96 (0.57, 1.60) 0.96 (0.45, 1.94) Edoxaban 60 1.00 (0.48, 2.07) 1.00 (0.48, 2.08) Rivaroxaban 1.10 (0.65, 1.86) 1.09 (0.65, 1.84) 0.94 (0.64, 1.41) 1.27 (1.06, 1.70) 1.14 (0.78, 1.73) 1.64 (1.24, 2.33) 0.90 (0.53, 1.54) 0.89 (0.51, 1.51) 0.87 (0.52, 1.46) 0.91 (0.54, 1.54) 0.91 (0.54, 1.53) VKA 1.14 (0.75, 1.88) Ischaemic stroke Apixaban 2.56 (1.56, 3.97) 1.90 (1.09, 3.79) 3.60 (2.11, 6.43) 1.27 (0.62, 2.80) 0.85 (0.43, 1.96) 1.64 (0.80, 3.56) 1.14 (0.57, 2.47) 1.05 (0.51, 2.33) 0.39 (0.25, 0.64) ASA 0.75 (0.52, 1.27) 1.42 (1.02, 2.12) 0.50 (0.27, 1.04) 0.34 (0.19, 0.71) 0.64 (0.36, 1.30) 0.44 (0.25, 0.92) 0.41 (0.22, 0.85) 0.45 (0.35, 0.63) 0.53 (0.26, 0.92) 0.28 (0.16, 0.47) 1.34 (0.79, 1.94) 0.71 (0.47, 0.98) ASA+clopidogrel 0.53 (0.32, 0.95) 1.90 (1.05, 3.13) Control 0.67 (0.31, 1.43) 0.35 (0.18, 0.73) 0.45 (0.21, 0.94) 0.24 (0.12, 0.50) 0.87 (0.40, 1.75) 0.46 (0.23, 0.91) 0.60 (0.28, 1.24) 0.31 (0.16, 0.64) 0.55 (0.25, 1.12) 0.29 (0.15, 0.59) 0.59 (0.37, 0.93) 0.32 (0.22, 0.46) 0.78 (0.36, 1.62) 2.00 (0.96, 3.69) 1.49 (0.70, 3.28) 2.83 (1.36, 5.63) Dabigatran 110 0.68 (0.37, 1.28) 1.28 (0.56, 2.97) 0.89 (0.38, 2.08) 0.83 (0.36, 1.91) 0.89 (0.49, 1.64) 1.18 (0.51, 2.35) 0.61 (0.28, 1.25) 2.96 (1.41, 5.39) 1.55 (0.77, 2.81) 2.20 (1.06, 4.84) 1.15 (0.57, 2.49) 4.25 (1.99, 8.26) 2.19 (1.10, 4.30) 1.48 (0.78, 2.73) 0.78 (0.34, 1.78) Dabigatran 150 0.52 (0.23, 1.22) 1.93 (0.82, 4.37) Edoxaban 30 1.33 (0.58, 3.03) 0.69 (0.39, 1.23) 1.22 (0.52, 2.83) 0.64 (0.28, 1.43) 1.32 (0.71, 2.38) 0.69 (0.39, 1.25) 0.88 (0.41, 1.77) 2.26 (1.08, 4.04) 1.67 (0.80, 3.57) 3.18 (1.56, 6.20) 1.12 (0.48, 2.60) 0.75 (0.33, 1.73) 1.45 (0.81, 2.56) Edoxaban 60 0.93 (0.40, 2.04) 1.00 (0.55, 1.78) 0.95 (0.43, 1.96) 0.88 (0.53, 1.34) 2.42 (1.18, 4.46) 2.23 (1.59, 2.85) 1.81 (0.89, 3.95) 1.68 (1.08, 2.72) 3.42 (1.71, 6.85) 3.16 (2.17, 4.58) 1.21 (0.52, 2.81) 1.12 (0.61, 2.05) 0.82 (0.35, 1.93) 0.76 (0.42, 1.40) 1.57 (0.70, 3.51) 1.45 (0.80, 2.57) 1.08 (0.49, 2.52) 1.00 (0.56, 1.83) Rivaroxaban 0.93 (0.51, 1.66) 1.08 (0.60, 1.98) VKA 1.42 (0.82, 2.36) ASA 1.26 (0.66, 2.50) 0.90 (0.56, 1.54) 1.95 (0.88, 4.72) 1.40 (0.71, 2.93) 1.37 (0.61, 2.89) 0.95 (0.47, 1.99) 1.33 (0.58, 2.87) 0.93 (0.46, 1.94) 1.29 (0.57, 2.65) 0.92 (0.44, 1.81) 1.02 (0.44, 2.06) 0.72 (0.35, 1.42) 0.84 (0.38, 1.74) 0.60 (0.29, 1.18) 1.05 (0.62, 1.67) 0.74 (0.51, 1.07) Benefit– risk balance of anti-thrombotics in atrial fibrillation Appendix Myocardial infarction Apixaban 0.70 (0.42, 1.22) 0.79 (0.40, 1.52) 1.11 (0.65, 1.78) ASA+ clopidogrel 1.57 (0.69, 3.67) 1.08 (0.47, 2.37) 1.05 (0.45, 2.29) 1.03 (0.43, 2.13) 0.81 (0.34, 1.68) 0.67 (0.29, 1.45) 0.83 (0.48, 1.33) 0.51 (0.21, 1.14) 0.73 (0.35, 1.63) 0.72 (0.34, 1.40) 1.05 (0.50, 2.13) 0.64 (0.27, 1.46) 0.93 (0.42, 2.14) Control 1.46 (0.57, 3.99) 0.68 (0.25, 1.77) Dabigatran 110 0.67 (0.25, 1.74) 0.98 (0.52, 1.82) 0.66 (0.24, 1.59) 0.95 (0.39, 2.09) 0.53 (0.19, 1.25) 0.74 (0.31, 1.68) 0.43 (0.16, 1.04) 0.62 (0.26, 1.43) 0.53 (0.24, 1.08) 0.77 (0.42, 1.40) 0.75 (0.35, 1.71) 1.07 (0.52, 2.19) 0.95 (0.44, 2.22) 1.49 (0.58, 3.99) 1.02 (0.55, 1.92) Dabigatran 150 0.97 (0.41, 2.17) 0.76 (0.31, 1.73) 0.63 (0.27, 1.49) 0.79 (0.43, 1.45) 0.77 (0.38, 1.75) 0.98 (0.49, 2.25) 1.08 (0.55, 2.30) 1.39 (0.71, 2.83) 0.97 (0.47, 2.32) 1.24 (0.59, 2.90) 1.52 (0.63, 4.25) 1.90 (0.80, 5.38) 1.05 (0.48, 2.54) 1.36 (0.60, 3.18) 1.03 (0.46, 2.45) 1.32 (0.58, 3.20) Edoxaban 30 1.27 (0.70, 2.27) 0.78 (0.44, 1.43) Edoxaban 60 0.66 (0.29, 1.55) 0.84 (0.37, 2.00) 0.81 (0.45, 1.49) 1.04 (0.58, 1.89) 1.19 (0.57, 2.61) 1.68 (0.85, 3.45) 1.50 (0.69, 3.42) 2.32 (0.96, 6.32) 1.62 (0.70, 3.84) 1.58 (0.67, 3.77) 1.51 (0.65, 3.49) 1.19 (0.50, 2.74) Rivaroxaban 1.24 (0.67, 2.27) 0.96 (0.60, 1.62) 1.35 (0.93, 1.98) 1.20 (0.75, 2.10) 1.88 (0.93, 4.12) 1.29 (0.71, 2.41) 1.26 (0.69, 2.35) 1.24 (0.67, 2.20) 0.96 (0.53, 1.72) 0.80 (0.44, 1.49) VKA 25 Continued 26 Table A1 Continued Systemic embolism Apixaban 3.69 (1.35, 10.14) 4.03 (1.36, 16.20) 4.31 (1.53, 14.39) 1.07 (0.25, 5.49) 1.16 (0.29, 5.68) 1.77 (0.51, 7.87) 0.95 (0.25, 4.23) 1.22 (0.30, 6.05) 1.45 (0.64, 4.01) 0.27 (0.10, 0.74) ASA 1.11 (0.55, 2.86) 1.19 (0.59, 2.57) 0.30 (0.08, 1.23) 0.32 (0.09, 1.34) 0.50 (0.15, 1.75) 0.25 (0.07, 0.97) 0.33 (0.09, 1.33) 0.41 (0.20, 0.82) 0.25 (0.06, 0.73) 0.23 (0.07, 0.65) 0.90 (0.35, 1.81) 0.84 (0.39, 1.68) ASA+ clopidogrel 0.92 (0.36, 2.82) 1.08 (0.35, 2.76) Control 0.26 (0.06, 1.15) 0.25 (0.06, 1.06) 0.28 (0.07, 1.20) 0.26 (0.07, 1.13) 0.43 (0.10, 1.64) 0.42 (0.12, 1.45) 0.24 (0.05, 0.89) 0.22 (0.06, 0.79) 0.30 (0.07, 1.27) 0.28 (0.07, 1.13) 0.37 (0.13, 0.83) 0.34 (0.16, 0.71) 0.93 (0.18, 4.05) 3.32 (0.82, 12.14) 3.91 (0.87, 17.59) 4.03 (0.94, 15.67) Dabigatran 110 1.11 (0.33, 3.59) 1.65 (0.32, 7.88) 0.89 (0.16, 4.18) 1.16 (0.21, 5.56) 1.37 (0.39, 4.23) 0.86 (0.18, 3.45) 3.13 (0.74, 10.96) 3.61 (0.83, 15.01) 3.78 (0.88, 13.80) 0.90 (0.28, 3.05) Dabigatran 150 1.54 (0.31, 7.33) 0.84 (0.15, 3.95) 1.08 (0.21, 5.35) 1.28 (0.37, 3.78) 0.56 (0.13, 1.97) 1.05 (0.24, 3.97) 2.01 (0.57, 6.58) 3.92 (1.03, 13.66) 2.30 (0.61, 9.63) 4.21 (1.12, 19.79) 2.38 (0.69, 8.37) 4.47 (1.26, 17.07) 0.61 (0.13, 3.12) 1.13 (0.24, 6.29) 0.65 (0.14, 3.20) 1.19 (0.25, 6.78) Edoxaban 30 1.89 (0.66, 5.86) 0.53 (0.17, 1.52) Edoxaban 60 0.69 (0.15, 3.32) 1.27 (0.28, 6.50) 0.81 (0.29, 2.23) 1.53 (0.53, 4.71) 0.82 (0.17, 3.36) 3.01 (0.75, 10.78) 3.32 (0.79, 14.89) 3.63 (0.89, 13.35) 0.87 (0.18, 4.72) 0.92 (0.19, 4.79) 1.44 (0.30, 6.88) 0.79 (0.15, 3.59) Rivaroxaban 1.22 (0.36, 3.71) 2.72 (1.20, 7.53) 2.97 (1.42, 6.30) 0.73 (0.24, 2.58) 0.78 (0.26, 2.69) 1.24 (0.45, 3.48) 0.65 (0.21, 1.88) 0.82 (0.27, 2.76) VKA 0.69 (0.25, 1.56) 2.44 (1.22, 4.96) Intracranial haemorrhage Apixaban 1.26 (0.46, 2.98) 3.05 (1.02, 10.34) 0.39 (0.03, 1.82) 0.72 (0.18, 3.13) 0.94 (0.25, 3.95) 0.71 (0.19, 3.08) 1.07 (0.29, 4.87) 1.50 (0.42, 6.70) 2.37 (1.08, 6.17) 0.79 (0.34, 2.16) 0.33 (0.10, 0.98) ASA 0.41 (0.15, 0.88) 2.47 (1.13, 6.72) ASA+ clopidogrel 0.31 (0.02, 1.31) 0.12 (0.01, 0.57) 0.57 (0.17, 2.56) 0.24 (0.06, 1.03) 0.74 (0.23, 3.22) 0.30 (0.08, 1.37) 0.56 (0.17, 2.48) 0.23 (0.06, 0.97) 0.85 (0.26, 3.86) 0.35 (0.09, 1.47) 1.19 (0.38, 5.30) 0.49 (0.12, 2.13) 1.88 (0.97, 4.67) 0.75 (0.32, 2.03) 2.58 (0.55, 37.87) 3.24 (0.76, 41.87) 8.12 (1.77, 119.74) Control 1.91 (0.32, 32.94) 2.50 (0.44, 44.91) 1.89 (0.36, 31.39) 2.82 (0.53, 47.71) 3.97 (0.71, 68.05) 6.25 (1.53, 89.72) 1.39 (0.32, 5.50) 1.06 (0.25, 4.03) 1.76 (0.39, 5.84) 1.36 (0.31, 4.44) 4.19 (0.97, 18.11) 3.37 (0.73, 13.25) 0.52 (0.03, 3.10) 0.40 (0.02, 2.27) Dabigatran 110 0.78 (0.24, 2.32) 1.28 (0.43, 4.15) Dabigatran 150 0.97 (0.22, 4.76) 0.77 (0.16, 3.58) 1.45 (0.34, 7.57) 1.16 (0.23, 5.32) 2.10 (0.49, 10.20) 1.67 (0.34, 7.64) 3.23 (1.13, 10.11) 2.53 (0.83, 7.45) 1.40 (0.32, 5.29) 1.78 (0.40, 5.84) 4.35 (1.03, 17.11) 0.53 (0.03, 2.81) 1.04 (0.21, 4.63) 1.29 (0.28, 6.25) Edoxaban 30 1.50 (0.51, 4.59) 2.11 (0.47, 9.66) 3.33 (1.14, 9.59) 0.93 (0.21, 3.46) 0.67 (0.15, 2.41) 1.17 (0.26, 3.78) 0.84 (0.19, 2.60) 2.88 (0.68, 11.03) 2.06 (0.47, 8.14) 0.35 (0.02, 1.88) 0.25 (0.01, 1.42) 0.69 (0.13, 2.98) 0.48 (0.10, 2.06) 0.86 (0.19, 4.27) 0.60 (0.13, 2.91) 0.67 (0.22, 1.95) 0.47 (0.10, 2.13) Edoxaban 60 0.71 (0.16, 3.31) 1.41 (0.30, 6.27) Rivaroxaban 2.22 (0.75, 6.24) 1.58 (0.52, 4.54) 0.42 (0.16, 0.92) 0.53 (0.21, 1.03) 1.34 (0.49, 3.14) 0.16 (0.01, 0.65) 0.31 (0.10, 0.88) 0.40 (0.13, 1.20) 0.30 (0.10, 0.88) 0.45 (0.16, 1.33) 0.63 (0.22, 1.92) VKA 1.14 (0.32, 2.79) 1.54 (0.27, 9.35) 0.48 (0.07, 1.80) 1.10 (0.14, 5.05) 1.25 (0.16, 5.78) 0.59 (0.08, 2.94) 1.03 (0.14, 4.98) 1.29 (0.18, 6.32) 1.00 (0.32, 2.85) ASA 1.53 (0.36, 6.50) 0.47 (0.09, 1.53) 1.10 (0.15, 4.36) 1.24 (0.18, 4.88) 0.59 (0.09, 2.39) 1.02 (0.16, 4.18) 1.26 (0.21, 5.37) 1.11 (0.40, 2.19) 0.65 (0.11, 3.72) 2.08 (0.56, 13.97) 0.65 (0.15, 2.79) 2.11 (0.65, 11.67) ASA+ clopidogrel 3.18 (0.66, 32.41) 0.31 (0.03, 1.52) Control 0.72 (0.06, 4.93) 2.13 (0.40, 16.01) 0.81 (0.07, 5.60) 2.44 (0.48, 19.06) 0.38 (0.04, 2.72) 1.20 (0.24, 8.99) 0.66 (0.06, 4.61) 2.05 (0.44, 15.44) 0.83 (0.08, 6.12) 2.54 (0.51, 20.35) 0.73 (0.11, 3.11) 2.31 (0.80, 8.93) 0.91 (0.20, 7.23) 0.91 (0.23, 6.67) 1.40 (0.20, 17.50) 0.47 (0.06, 2.48) Dabigatran 110 1.14 (0.26, 5.12) 0.55 (0.07, 4.36) 0.95 (0.13, 7.24) 1.17 (0.16, 9.86) 1.05 (0.27, 4.79) 0.80 (0.17, 6.10) 1.68 (0.34, 12.45) 0.80 (0.21, 5.66) 1.70 (0.42, 10.76) 1.23 (0.18, 13.98) 2.60 (0.37, 27.91) 0.41 (0.05, 2.08) 0.83 (0.11, 4.13) 0.88 (0.20, 3.91) 1.82 (0.23, 13.69) Dabigatran 150 2.09 (0.26, 16.29) 0.48 (0.06, 3.81) Edoxaban 30 0.83 (0.12, 6.45) 1.73 (0.42, 7.64) 1.03 (0.15, 7.92) 2.13 (0.29, 17.17) 0.91 (0.23, 4.04) 1.91 (0.45, 7.99) 0.97 (0.20, 7.17) 0.98 (0.24, 6.17) 1.51 (0.22, 15.74) 0.49 (0.06, 2.29) 1.06 (0.14, 7.93) 1.21 (0.16, 8.53) 0.58 (0.13, 2.36) Edoxaban 60 1.24 (0.18, 9.45) 1.12 (0.28, 4.51) 0.78 (0.16, 5.49) 0.88 (0.36, 3.11) 0.79 (0.19, 4.71) 0.90 (0.46, 2.52) 1.21 (0.16, 12.09) 1.37 (0.32, 8.87) 0.39 (0.05, 1.95) 0.43 (0.11, 1.25) 0.85 (0.10, 6.12) 0.96 (0.21, 3.68) 0.97 (0.13, 6.83) 1.09 (0.25, 4.38) 0.47 (0.06, 3.43) 0.52 (0.13, 2.21) 0.80 (0.11, 5.46) 0.89 (0.22, 3.58) Rivaroxaban 1.12 (0.27, 4.77) 0.90 (0.21, 3.68) VKA Interventions are reported in alphabetical order. Results are the ORs in the column-defining treatment compared with the ORs in the row-defining treatment. For efficacy, ORs lower than one favour the column-defining treatment (i.e. the first in alphabetical order). To obtain ORs for comparisons in the opposite direction, reciprocals should be taken. Significant results are in bold. VKA, vitamin K antagonist. A. Dogliotti and R.P. Giugliano Major extracranial haemorrhage Apixaban 1.00 (0.35, 3.16) 27 Benefit– risk balance of anti-thrombotics in atrial fibrillation Table A2 Rank acceptabilities Rank 1 (%) Based on utility functions Apixaban 17 Rank 2 (%) Rank 3 (%) Rank 4 (%) Rank 5 (%) Rank 6 (%) Rank 7 (%) Rank 8 (%) Rank 9 (%) Rank 10 (%) 18 17 15 12 10 7 2 1 0 ASA 0 0 0 0 1 4 9 33 49 3 ASA+ clopidogrel 0 1 1 2 3 6 13 35 23 17 Control Dabigatran 110 1 13 0 16 1 14 1 14 1 12 2 12 2 11 5 5 13 3 74 1 Dabigatran 150 20 18 16 12 10 10 8 4 2 1 Edoxaban 30 Edoxaban 60 15 16 16 16 14 15 14 14 12 12 11 11 12 9 4 4 2 2 1 1 Rivaroxaban 18 13 13 12 11 11 11 5 3 2 Vitamin K antagonist 0 2 8 17 24 24 17 4 3 1 Apixaban ASA 16 0 17 0 17 0 14 1 12 2 10 5 9 11 4 31 1 47 1 3 ASA+ clopidogrel 0 1 2 3 4 8 13 32 21 16 Control 1 1 2 2 2 2 3 7 12 68 Dabigatran 110 Dabigatran 150 11 18 14 16 14 14 13 12 12 10 13 9 12 9 6 5 4 4 3 3 Edoxaban 30 18 17 15 12 11 10 11 4 2 1 Edoxaban 60 Rivaroxaban 16 18 17 14 14 12 12 11 11 10 11 10 9 11 5 6 3 4 2 4 Vitamin K antagonist 1 4 11 22 26 23 11 2 1 0 Based on medical costs Preference information: based on utility functions:24 – 34 mortality intracranial haemorrhage ischaemic stroke myocardial infarction major extracranial haemorrhage systemic embolism. Based on medical costs:35 – 37 mortality major extracranial haemorrhage ischaemic stroke myocardial infarction intracranial haemorrhage systemic embolism. The rank acceptabilities represent, given the preference information, the probability (in per cent) that each treatment is best (rank 1), the second highest (rank 2), etc. Rank probabilities sum to 100%, both within a rank over treatments and within a treatment over ranks. In grey are the most relevant results. 28 A. Dogliotti and R.P. Giugliano Table A3 Central weight vectors and confidence factors Based on utility functions Confidence factor Mortality Intracranial haemorrhage Ischaemic stroke Myocardial infarction Extracranial haemorrhage Systemic embolism Apixaban ASA 17% 0% 0.39 0.33 0.24 0.24 0.16 0.19 0.1 0.12 0.02 0.01 0.06 0.07 ASA+ clopidogrel 0.3% 0.54 0.19 0.12 0.07 0.01 0.04 Control 0.6% 0.37 0.25 0.15 0.1 0.03 0.07 Dabigatran 110 Dabigatran 150 13% 21% 0.41 0.4 0.24 0.24 0.15 0.16 0.09 0.1 0,00 0.02 0.06 0.05 Edoxaban 30 16% 0.42 0.24 0.15 0.09 0.02 0.05 Edoxaban 60 Rivaroxaban 16% 17% 0.4 0.4 0.24 0.24 0.16 0.16 0.1 0.1 0.02 0.02 0.06 0.06 Vitamin K antagonist Based on medical costs Apixaban 0.3% 0.4 0.23 0.16 0.1 0.03 0.06 Confidence factor 17% Mortality 0.39 Extracranial haemorrhage 0.23 Ischaemic stroke 0.16 Myocardial infarction 0.1 Intracranial haemorrhage 0.06 Systemic embolism 0.02 ASA 0% 0.53 0.21 0.08 0.08 0.05 0.02 ASA+ clopidogrel 0.3% 0.41 0.24 0.15 0.1 0.05 0.02 Control Dabigatran 110 0.8% 13% 0.38 0.41 0.26 0.24 0.15 0.15 0.1 0.09 0.06 0.05 0.02 0.02 Dabigatran 150 17% 0.41 0.23 0.15 0.1 0.06 0.02 Edoxaban 30 Edoxaban 60 17% 17% 0.42 0.4 0.24 0.23 0.15 0.16 0.09 0.1 0.05 0.06 0.02 0.02 Rivaroxaban 18% 0.4 0.23 0.15 0.1 0.06 0.02 Vitamin K antagonist 0.3% 0.39 0.23 0.16 0.1 0.06 0.02 Preference information based on utility functions:24 – 34 mortality intracranial haemorrhage myocardial infarction ischaemic stroke major extracranial haemorrhage systemic embolism. Based on medical costs:35 – 37 mortality major extracranial haemorrhage ischaemic stroke myocardial infarction intracranial haemorrhage systemic embolism. Central weights represent a typical weighting that favours a specific alternative. The CF is the probability that an alternative rank first if the decision-maker’s preferences agree with the alternative’s central weight vector.
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