What Is/Are the Best Oral Anticoagulant/S for Primary Prevention, Treatment

Home , Ethyl biscoumacetate, Otamixaban

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

Protocol

Background and Rationale

Importance of the health problem to the NHS Thrombosis followed by embolization to distant organs occurs in both arterial and venous circulation and these conditions can be treated or prevented by oral anticoagulant treatment. Venous thromboembolic disease Venous thromboembolic disease (VTE) (UK annual incidence 183 per 100,000) encompasses clot formation in deep veins of legs or pelvis (deep vein thrombosis (DVT; annual incidence 123 per 100,000), and their displacement to pulmonary arteries (pulmonary embolism (PE; annual incidence 60 per 100,000). Important risk factors for VTE include major surgery, particularly lower limb orthopaedic surgery and surgery for cancer, as well as hospitalization in acutely ill general medical patients (approximate incidence 15%). VTE costs the NHS £640 million and is responsible for approximately 30,000 (10%) deaths each year in hospitals in England. DVT is also an important cause of long-term morbidity, being a major risk factor for chronic leg ulceration. PE may also lead to long- term morbidity due to pulmonary hypertension. There is an approximately 30% risk of recurrence of VTE within 8 years. The risk of VTE during hospitalisation for surgical or medical treatment can be reduced by low molecular weight heparin (LMWH), fonaparinux or unfractionated heparin.1 Warfarin is the most frequently prescribed anticoagulant for the initial treatment and for the long-term secondary prevention of VTE in those deemed to be at high risk of recurrence. Atrial fibrillation and stroke Atrial fibrillation (AF) is the most common cardiac arrhythmia.2 The prevalence of AF roughly doubles with each decade of age, rising to almost 9% at age 80-90 years. Atrial fibrillation substantially increases (up to 5 times) the risk of thromboembolic stroke (annual incidence 114 per 100,000) due to blood pooling in the left atrium and systemic embolization to the brain. More than 20% of the 130,000 annual strokes in England and Wales are attributed to AF. Approximately 1/3 of stroke patients die in the first 10 days, 1/3 recover in 1 month and 1/3 have disabilities needing rehabilitation making stroke the leading cause of adult disability. Patients with thromboembolic stroke from AF have higher mortality, morbidity and hospital stay than patients with other stroke subtypes. Warfarin is an effective oral anticoagulant for the prevention of stroke in patients with AF.3 Although the incidence and mortality of stroke continue to fall in the UK, the underutilisation of anticoagulation in patients with AF at high-risk of stroke is a major gap in clinical care.4 Cost and limitations of warfarin anticoagulation A 2007 HTA report stated that approximately 950,000 people (2% of the GP population) in the UK are prescribed warfarin; increasing by about 10% per year 5. Warfarin related bleeding is one of the top 5 reasons for hospitalisation for adverse drug effects in England6, because of the narrow therapeutic index and numerous drug/dietary interactions. Although the acquisition cost of warfarin is only approximately £10 per patient per year, the requirement for therapeutic monitoring to ensure optimal efficacy and to reduce the risk of bleeding, through hospital-, primary care-, or pharmacist- based anticoagulation clinics, or by home-monitoring with anticoagulant clinic support, inflates the cost of warfarin treatment substantially. The estimated annual cost of managing patients on warfarin in the NHS in England and Wales is approximately £90 million.7 Partly because of the perception of the risk and inconvenience of warfarin treatment, a 2006 NICE report estimated that 46% of patients who should be on warfarin are not receiving it, and that many receiving anticoagulation are not in optimal therapeutic range.7 New oral anticoagulants Unlike warfarin, new oral anticoagulants dabigatran (a direct inhibitor of clotting factor II) and rivaroxaban, apixaban, edoxaban, otamixaban and betrixaban (factor X inhibitors), have rapid action and predictable dosing requirements, negating the need for therapeutic drug monitoring.8 However, the estimated annual acquisition cost per patient of new anticoagulants will remain substantially

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation? higher than that of warfarin, until patent expiry (for example, 2020 for rivaroxaban). However, the higher acquisition cost may be offset by the reduced need for therapeutic monitoring through anticoagulation services, by increased effectiveness, or by improved safety. Nevertheless potential limitations of newer agents include class- and drug-specific cautions/contraindications, potential for sub-therapeutic dosing, lack of antidotes, added cost of maintaining stocks of numerous different anticoagulants and potential for prescribing errors due to unfamiliarity. Why this research is needed now Limitations of the evidence base (and shortfalls in previous attempts at evidence synthesis) make rational selection from the now wide range of available oral anticoagulants difficult for NHS commissioners, doctors and patients. Much of the existing NICE guidance in this area is limited to individual technology appraisals. Trials in this area have the following limitations: • We have identified no trials making direct comparisons of new oral anticoagulant drugs with one another. This limitation can be addressed through the use of network-meta-analysis to estimate the comparative efficacy and safety of agents, which have been tested against a common comparator, in this case warfarin • Differing rates of sub-therapeutic anticoagulation with warfarin within trials (indexed by the time spent in the therapeutic range) may have artificially inflated the apparent efficacy of newer agents. This limitation can be addressed so some extent by investigating the relation of average time in therapeutic range with efficacy, within network meta-analyses. Prior synthesis research in this area has the following limitations: • Absence of network meta-analysis of novel oral anticoagulants for certain therapeutic indications (e.g. acute treatment and secondary prevention of VTE) • Some meta-analyses preceded recently published, potentially influential trials • Failure to fully incorporate evidence on the adverse effects of oral anticoagulants by including data from all trials, irrespective of indication, to maximise power and provide the most robust evidence on the balance between benefit and harm. • The lack of cost-effectiveness analyses relevant to England and Wales. Thus, there is a need for an up-to-date comprehensive evidence synthesis of all competing treatments to inform the rational choice of a minimum set of oral anticoagulants needed by NHS hospitals for the main therapeutic indications to avoiding unnecessary over-stocking and to reduce the risk of prescription error due to unfamiliarity.

Aims and objectives 1. Identify the most effective, safe and cost-effective oral anticoagulant for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and consider whether the evidence is consistent for both prevention and treatment, and across important patient subgroups (for example cancer surgery, hip and knee replacement, and hospital admission for acute medical illness). 2. Identify the most effective, safe and cost-effective anticoagulant for stroke prevention in atrial fibrillation, and consider whether the evidence is consistent across important patient subgroups (for example presence of comorbidities, age). 3. Identify optimal anticoagulation strategies for use by Trust Drugs and Therapeutics Committees, based on the best drug(s) for each of the main therapeutic indications. 4. Estimate the value of conducting further research on the cost-effectiveness of these drugs, for example by conducting a head-to-head trial of two or more new anticoagulants.

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

Methods

Systematic review: Clinical effectiveness reviews

Systematic reviews of randomised controlled trials addressing questions relevant to the study objectives will be undertaken in accordance with the Centre for Reviews and Dissemination (CRD) guidelines for undertaking systematic reviews38, and the Cochrane Handbook for Systematic Reviews of Interventions39 (as updated online during 2011: see www.cochrane-handbook.org). The following reviews will be carried out: 1. Oral anticoagulants for primary prevention of venous thromboembolic disease 2. Oral anticoagulants for treatment and secondary prevention of venous thromboembolic disease 3. Oral anticoagulants for prevention of stroke in atrial fibrillation

The reviews have been registered in the PROSPERO database (http://www.crd.york.ac.uk/prospero), with registration numbers CRD42013005331, CRD42013005330 and CRD42013005324.

Criteria for considering studies for the reviews Participants Review 1: Primary prevention of VTE Adults (>18 years) considered to be at high risk of VTE, including those with a medical condition (e.g. cancer, major trauma, stroke), or undergoing a surgical procedure (e.g. total knee or hip arthroplasty, hip fracture surgery) that carries a high risk of VTE. Review 2: Treatment or secondary prevention of VTE Adults who have received a new or recurrent diagnosis of VTE (treatment) or have completed six months of anticoagulant treatment for VTE without recurrence (secondary prevention). Review 3: Stroke prevention in AF Adults with AF and no history of stroke or transient ischaemic attack (TIA)

Setting NHS anticoagulation services, which are delivered in hospital-, primary care- and pharmacy-based clinics as well as through home monitoring and telephone support

Interventions and comparators

The following anticoagulants will be included: therapeutic doses of warfarin, low molecular weight heparin, dabigatran rivaroxaban, apixaban, edoxaban, betrixaban, razaxaban, LY517717, YM150 and TAK-442.

No restrictions will be placed on comparator interventions. Studies that compare interventions reported as comparators in any of the included studies will also be eligible.

Outcomes We will develop a comprehensive list of outcomes reported by each trial. The most important outcomes are as follows: VTE: Primary outcomes are incident VTE (for primary prevention studies) and recurrent VTE (for studies of treatment). The primary safety outcome is major bleeding.

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

Key secondary outcomes include death, non-CNS systemic embolism, myocardial infarction, pulmonary embolism, transient ischaemic attack, hospitalisation, liver function, health-related quality of life, PE and DVT as separate components of VTE, and length of hospital stay (for primary prevention studies). AF: The primary outcome is stroke (ischaemic and haemorrhagic). The primary safety outcome is major bleeding. Key secondary outcomes include: death, non-CNS systemic embolism, myocardial infarction, pulmonary embolism, transient ischaemic attack, hospitalisation, liver function, and health-related quality of life. For patients treated with warfarin: we will extract average time in treatment range in order to examine whether this acts as a modifier of relative efficacy of the new oral anticoagulants.

Search Strategy We will update the extensive scoping searches conducted while preparing this application to assemble a database of published and unpublished literature. Electronic searches will be conducted using the following major medical databases: MEDLINE, EMBASE, the Cochrane Register of Controlled Trials, Science Citation Index, BIOSIS Previews and LILACS without language or date restrictions. Two separate search strategies will be used, combining terms for VTE (reviews 1 and 2) or AF (review 3) with those for oral anticoagulants and an RCT filer. Search strategies designed for the MEDLINE scoping searches (Appendix 1) will be adapted to run on other databases. In addition, information on studies in progress, unpublished research or research reported in the grey literature will be sought from a range of relevant databases and trial registers including www.clinicaltrials.gov. Additional studies, including unpublished and grey literature, will be identified by screening reference list of retrieved studies and relevant review articles, contacting drug manufacturers, internet searches, and by searching trial registers. We will also search NHS EED and NICE Technology Appraisals.

Assessing relevance and inclusion The results of the searches will be screened for relevance independently by two reviewers. Disagreements will be resolved through consensus or referral to a third reviewer where necessary. Studies that appear potentially relevant will be ordered and assessed for inclusion by one reviewer and checked by a second. Data extraction Data extraction forms will be developed using Microsoft Access. These will be piloted on a small selection of studies and adjusted as necessary. Data will be extracted by one reviewer and checked by a second. Disagreements will be resolved through consensus or referral to a third reviewer where necessary. Data will be extracted on the following: study details (identifier, study design, location, year, length of follow up, industry sponsorship), participant details (number of participants, age, gender, details of previous tests received, intervention details (drug name, dose, timing), comparator intervention details, and adherence to and withdrawal from randomised allocation (where reported)). Data from all arms of multi-arm trials will be extracted. Dichotomous data will be extracted as number of events in intervention and control groups and numbers of participants, using an intention to treat (ITT) approach to deal with patients lost to follow up. Continuous data will be extracted as mean change from baseline and standard error, where available. Where pre- and post-measures alone are reported we will use these raw results, linking them to the mean difference via the correlation between pre- and post-measures estimated from studies with full information40. A complete-case approach will be taken to the analysis of continuous outcomes where there is loss to follow-up. If these data are not available they will be calculated from the available information. Assessment of risk of bias in included trials Studies will be assessed using the Cochrane Collaboration’s Risk of Bias Tool.41 This is used to assign a rating of high, low or unclear risk of bias for the following domains: selection bias,

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

performance bias, detection bias, attrition bias, and reporting bias. Summary assessments of risk of bias (high, low or unclear) will be derived for each outcome in each trial. Assessments will be carried out by one reviewer and checked by a second. Disagreements will be resolved through consensus or referral to a third reviewer where necessary.

Health Economic reviews As there has been a recent proliferation of decision analytical models, we will conduct an updated systematic search for previous economic evaluations of relevant treatments to identify alternative model structures and key parameters for each of the patient cohorts (VTE primary prevention, VTE treatment, AF) simulated. The results of the searches will be screened independently by two reviewers. Inclusion assessment, data extraction and quality assessment will be done by one reviewer and checked by a second. We will also conduct rapid systematic reviews to identify the best evidence on key model parameters (not measured in the primary RCTs) supplemented by expert opinion if necessary. Unit cost data will be derived from standard national sources (e.g. British National Formulary or NHS reference costs) where possible to maximise generalisability.

Data Analysis and Evidence Synthesis Evidence synthesis will be performed separately for each of the three distinct research questions: (a) What is the relative efficacy and cost-effectiveness of anticoagulants for prevention of primary prevention of venous thromboembolic disease? (b) What is the relative efficacy and cost-effectiveness of anticoagulants for treatment and secondary prevention of venous thromboembolic disease? (c) What is the relative efficacy and cost-effectiveness of anticoagulants for treatment of atrial fibrillation? We will develop decision analysis models based on the review of previous cost-effectiveness models in these areas, and perform cost-effectiveness analyses. We will use the results of these analyses to identify optimal anticoagulation strategies for use by Trust drugs and therapeutics committees. We will use the cost-effectiveness models to perform value of information analyses to assess the need for further research in these areas. Evidence syntheses will commence with standard meta-analyses for each pairwise comparison of treatments that have been compared directly for each outcome and research question. We will present results of both fixed- and random-effects meta-analyses in forest plots. Between-study heterogeneity will be quantified using the between-study variance (τ2) and the I2 statistic42. For each outcome and research question, we will construct a network meta-analysis (NMA)43 44. NMA is a method of synthesising information from a collection of trials by simultaneously combining all the direct (head to head) and indirect evidence. NMA enables estimation of relative intervention effect estimates for every pairwise contrast, regardless of whether or not they have been compared directly in a RCT. It also enables the ranking of treatments according to the probability that each is the best, or worst, for a given outcome. All analyses will be performed within a Bayesian framework, using freely-available WinBUGS software (version 1.4.3). A prerequisite for NMA is that the network is connected by trials that compared different pairs of interventions. Our scoping searches indicate that the anti-coagulants form “star” networks with, warfarin as a common comparator for acute treatment of VTE and stroke prevention in AF, and placebo for secondary prevention of VTE. For prevention of VTE, most trials are compared to LMWH but some are placebo controlled: thus these trials form a “connected” network and trials of LMWH versus placebo will also be relevant. Investigation of heterogeneity and inconsistency: In network meta-analyses we will assume homogeneous between-study variability across studies43, and will report the estimated value of τ (the

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

standard deviation of underlying effects across studies). We will also report the effective number of parameters, PD, which increases with the degree of heterogeneity in random effect models, and so also reflects the extent of heterogeneity. Goodness of fit will be assessed by calculating the posterior mean residual deviance. This is defined as the difference between the deviance for the fitted model and the saturated model, where the deviance measures the fit of the model using the likelihood function. The Deviance Information Criterion (DIC), which is equal to the sum of the posterior mean of the residual deviance and the 45 effective number of parameters PD, will be used as a basis for model comparison . The DIC penalises the posterior mean residual deviance (a measure of model fit) by the effective number of parameters in the model (as measure of complexity) and can therefore be viewed as a trade-off between the fit and complexity of the model. Validity of a NMA depends on the assumption that there is no effect modification of the pairwise intervention effects or, that the prevalence of effect modifiers is similar in the different studies. This key assumption has been referred to variously as transitivity46, similarity47 and consistency48 49. A clinical and epidemiological judgement of the plausibility of this assumption requires assessment of the inclusion/exclusion criteria of every trial in the network, to assess whether the patients, trial protocols, doses, administration etc. are similar in ways that might modify treatment effect. We will compile a table of important trial and patient characteristics and visually inspect the ‘similarity’ of factors we consider likely to modify treatment effect. Evidence inconsistency can be considered an additional layer of heterogeneity that occurs in networks of evidence when there is a discrepancy between a direct and indirect estimate of treatment effect, for example when the consistency assumption describe above is violated. Therefore inconsistency is a property of ‘closed loops’ of evidence. We will visually inspect the network diagram to identify the extent of potential inconsistency (the number of loops) and use model fit and selection statistics to informally assess whether it is evident. If inconsistency is suspected we will explore it formally using a “node-splitting” approach48. Node-splitting allows the analyst to split the network-wide information contributing to summary effect estimate B vs. C into the evidence from studies directly compare B with C and the remaining ‘indirect’ evidence for B vs. C when the direct comparisons are removed. The extent of the disagreement between the direct and indirect estimates defines the magnitude of inconsistency. For the individual dichotomous outcomes we will use the complementary log-log link to account for differential follow-up times in the included studies. This assumes a constant hazard of the outcome over time. Depending on the evidence structure identified, it may also be possible to pool the evidence on the transitions between all states in the multi-state model on a log-rate scale50 51, providing pooled log-rate ratios. We will fit a hierarchical model with individual treatments nested within treatment classes52 53 so that we can look at variability in treatment effects within and between treatment classes. Subgroup analyses: We will use subgroup and meta-regression54 analyses to examine the extent to which study characteristics explain between-study heterogeneity. In particular, we will examine whether relative efficacy of new oral anticoagulants varies according to average time in therapeutic range in the wafarin (comparison) group. We will stratify analyses according to the summary assessment of risk of bias for each outcome. We will also investigate whether treatment effects vary according to key participant characteristics. However use of trial-level means of individual-level characteristics in meta-regression analyses has severe limitations55. For the key characteristics listed above, inferences about subgroup effects will be based primarily on within-trial subgroup analyses (for example, comparing relative intervention effects in older and younger participants), where reported. Other potential covariates identified in the systematic review will also be considered. Economic Evaluation Three separate decision analytic models will be developed to estimate the cost-effectiveness of new oral anticoagulants versus standard anticoagulation (e.g. warfarin/LMWH) for each of the three patient populations. The model structures will be developed in consultation with clinical experts (both within and independent of the project team) to ensure that the final structures reflect a reasonable simplification of the realities of NHS anticoagulation services and the settings in which they are

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

delivered. The parameters needed to populate the models will include outcomes estimated by our network meta-analysis (e.g. DVT events, PE events, major bleeding adverse events, fatal or non-fatal disabling stroke, TIAs) and other parameters (e.g. resource use including INR monitoring and the long term costs of stroke, drug and other unit costs, long term transition probabilities, utility values for disease states) that will not be part of the NMA. We anticipate that Markov models with an annual cycle length will be used to simulate the lifetime transitions to states of ill health (e.g. symptomatic DVT, PE, TIA, disabling stroke) and death. Efficacy and safety parameters in the models will be informed by the results of our network meta-analysis. Other input parameters will be based on a review of the literature using specialist databases (e.g. NHS EED for resource use parameters and the Tufts CEA registry for utility parameters) where applicable. . Uncertainties in all parameter inputs will be accounted for in the analysis by including parametric distributions around each point estimate. In cases where the evidence is not sufficiently detailed, we will use expert opinion to estimate the most plausible distribution. This will enable probabilistic sensitivity analyses and value of information analyses (see below) to be performed. The NMA estimates relative effects jointly, and the full joint distribution of these effects will be used in the economic model in order to preserve correlations56. Management of warfarin anticoagulation within the NHS includes hospital-, primary care- and pharmacy-based clinics as well as home monitoring and telephone support: costs vary both by type and by region. We will identify the range of costs through contact with commissioners and use these in our economic evaluation. If differences in costs are sufficient we will develop separate models for different types of care and examine whether conclusions about optimal therapy or therapies are consistent across these settings. We will estimate cost-effectiveness from the perspective of the NHS and Personal Social Services, excluding costs incurred by patients, employers and other agencies. The project economists and clinicians will jointly review the structure of the final model to ensure that it is clinically plausible. The model will evaluate costs and outcomes over the lifetime of the patient cohorts: costs and benefits in future years will be discounted at an annual rate of 3.5% and varied between 0% and 6% in sensitivity analysis to account for methodological uncertainty. Results from the model will be reported as incremental cost per Quality Adjusted Life Year (QALY) (ICERs) and expected net monetary benefit of drugs and drug classes. The expected net benefit will be presented for a range of “willingness to pay” values per QALY. Uncertainty in the optimal strategy will be represented by cost-effectiveness acceptability curves (CEACs), which show the probability that each drug is the most cost-effective at a given willingness-to-pay threshold. Where subgroup and meta-regression analyses have shown that patient characteristics modify treatment effects, we will use a stratified format for the decision. We will use standard techniques (e.g. extreme value scenarios and double programming) to ensure the internal validity of the model. Monte Carlo simulation will be used to evaluate the model, where simulated treatment effect parameters are taken from the WinBUGS Markov Chain Monte Carlo chains to capture all parameter uncertainties and correlations. Expected Value of Information (EVI) The systematic review and economic model will be used to make recommendations for optimal use of oral anticoagulants based on current evidence. But evidence is incomplete and further research may be valuable. Expected value of information analysis (EVI) uses the current available evidence (and the uncertainty that surrounds it) to estimate the expected benefit of future research.57 Research recommendations (and funding decisions) can then focus on research areas where the benefits of future research, by reducing uncertainty, most clearly outweigh the costs of that research. We will use Monte Carlo simulation to obtain EVI estimates from the decision analysis model. We will firstly calculate the Expected Value of Perfect Information (EVPI) to find the maximum value that can be obtained by eliminating uncertainty on all of the parameters that feed into the cost-effectiveness analysis. If EVPI is large enough to suggest that there may be value in collecting further information, we will also calculate the Expected Value of Perfect Partial Information (EVPPI) to identify which particular parameters or subsets of parameters (for example, relative efficacy on particular classes of interventions, transition probabilities, costs, utility mappings etc.) there is greatest value in collecting further research on. If the EVPPI calculations indicate that there may be value in collecting further information on a particular subset of parameters, we will calculate the Expected Value of Sample

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

Information (EVSI) to identify the optimal study design to collect that further information. All analyses will be carried out using R statistical software. Dissemination and projected outputs The research findings will be presented in a full report to the HTA programme that will highlight any areas for which we recommend further research. We will also disseminate the research results through peer reviewed journals and through methodological and clinical conferences. We will liaise with commissioners and with drugs and therapeutics committees to help translate the results of this project into practice. Our patient representatives will help to ensure that the results of the study are communicated in an accessible way - in particular via charity websites and publicity materials.

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

References

1. National Clinical Guideline Centre - Acute and Chronic Conditions. Venous thromboembolism: reducing the risk of venous thromboembolism (deep vein thrombosis and pulmonary embolism) in patients admitted to hospital. London: Royal College of Physicians, 2010; 2. National Collaborating Centre for Chronic Conditions. Atrial fibriallation: national clinical guideline for management in primary and secondary care. London: Royal College of Physicians, 2006; 3. Hart RG, Benavente O, McBride R, Pearce LA. Antithrombotic therapy to prevent stroke in patients with atrial fibrillation: a meta-analysis. Ann.Intern.Med. 1999;131:492-501. 4. Lee S, Shafe AC, Cowie MR. UK stroke incidence, mortality and cardiovascular risk management 1999-2008: time-trend analysis from the General Practice Research Database. BMJ Open. 2011;1:e000269 5. Connock M, Stevens C, Fry-Smith A, et al. Clinical effectiveness and cost-effectiveness of different models of managing long-term oral anticoagulation therapy: a systematic review and economic modelling. Health Technol.Assess. 2007;11:iii-66 6. Pirmohamed M, James S, Meakin S, et al. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. Br.Med.J. 2004;329:15-19. 7. National Institute for Health and Clinical Excellence. Clinical Guideline 36: National cost impact report to accompany 'Atrial fibrillation: the management of atrial fibrillation'. London: National Institute for Health and Clinical Excellence, 2006; 8. Garcia D, Libby E, Crowther MA. The new oral anticoagulants. Blood 2010;115:15-20. 9. Brito V, Ciapponi A, Kwong J. Factor Xa inhibitors for acute coronary syndromes. Cochrane.Database.Syst.Rev. 2011;CD007038 10. Gomez-Outes A, Terleira-Fernandez AI, Suarez-Gea ML, Vargas-Castrillon E. Dabigatran, rivaroxaban, or apixaban versus enoxaparin for thromboprophylaxis after total hip or knee replacement: systematic review, meta-analysis, and indirect treatment comparisons. Br.Med.J. 2012;344:e3675 11. Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J.Clin.Epidemiol. 1997;50:683- 691. 12. Zindel S, Stock S, Muller D, Stollenwerk B. A Multi-Perspective Cost-Effectiveness Analysis Comparing Rivaroxaban with Enoxaparin Sodium for Thromboprophylaxis after Total Hip and Knee Replacement in the German Healthcare Setting. BMC Health Serv Res 2012;12:192 13. Wolowacz SE, Roskell NS, Maciver F, et al. Economic evaluation of dabigatran etexilate for the prevention of venous thromboembolism after total knee and hip replacement surgery. Clin Ther 2009;31:194-212. 14. McDonald H, Diamantopoulos A, Wells P, et al. Cost-effectiveness of rivaroxaban in the prevention of venous thromboembolism: A Canadian analysis using the Ontario Ministry of Health Perspective. J Med Econ. 2012; 15. McCullagh L, Tilson L, Walsh C, Barry M. A cost-effectiveness model comparing rivaroxaban and dabigatran etexilate with enoxaparin sodium as thromboprophylaxis after total hip and total knee replacement in the irish healthcare setting. Pharmacoeconomics. 2009;27:829-846. 16. Holmes M, Carroll C, Papaioannou D. Dabigatran etexilate for the prevention of venous thromboembolism in patients undergoing elective hip and knee surgery: a single technology appraisal. Health Technol Assess 2009;13 Suppl 2:55-62. 17. Duran A, Sengupta N, Diamantopoulos A, Forster F, Kwong L, Lees M. Cost and outcomes associated with rivaroxaban vs enoxaparin for the prevention of postsurgical venous thromboembolism from a US payer's perspective. J Med Econ. 2011;14:824-834.

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

18. Diamantopoulos A, Lees M, Wells PS, Forster F, Ananthapavan J, McDonald H. Cost- effectiveness of rivaroxaban versus enoxaparin for the prevention of postsurgical venous thromboembolism in Canada. Thromb Haemost. 2010;104:760-770. 19. Ryttberg L, Diamantopoulos A, Forster F, Lees M, Fraschke A, Bjorholt I. Cost-effectiveness of rivaroxaban versus heparins for prevention of venous thromboembolism after total hip or knee surgery in Sweden. Expert Rev Pharmacoecon.Outcomes Res 2011;11:601-615. 20. Kwong LM. Cost-effectiveness of rivaroxaban after total hip or total knee arthroplasty. Am J Manag.Care 2011;17:S22-S26 21. Ridker PM, Goldhaber SZ, Danielson E, et al. Long-term, low-intensity warfarin therapy for the prevention of recurrent venous thromboembolism. N Engl J Med 2003;348:1425-1434. 22. Becattini C, Agnelli G, Schenone A, et al. Aspirin for preventing the recurrence of venous thromboembolism. N Engl J Med 2012;366:1959-1967. 23. Bauersachs R, Berkowitz SD, Brenner B, et al. Oral rivaroxaban for symptomatic venous thromboembolism. N Engl J Med 2010;363:2499-2510. 24. Wells G, Coyle D, Cameron C, et al. Safety, Effectiveness, and Cost-Effectiveness of New Oral Anticoagulants Compared with Warfarin in Preventing Stroke and Other Cardiovascular Events in Patients with Atrial Fibrillation. Ottawa: Canadian Collaborative for Drug Safety, Effectiveness and Network Meta-Analysis, 2012; 25. Granger CB, Alexander JH, McMurray JJ, et al. Apixaban versus warfarin in patients with atrial fibrillation. N.Engl.J.Med. 2011;365:981-992. 26. Patel MR, Mahaffey KW, Garg J, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N.Engl.J.Med. 2011;365:883-891. 27. Connolly SJ, Ezekowitz MD, Yusuf S, et al. Dabigatran versus warfarin in patients with atrial fibrillation. N.Engl.J.Med. 2009;361:1139-1151. 28. Schneeweiss S, Gagne JJ, Patrick AR, Choudhry NK, Avorn J. Comparative efficacy and safety of new oral anticoagulants in patients with atrial fibrillation. Circ.Cardiovasc.Qual.Outcomes. 2012;5:480-486. 29. Mantha S, Ansell J. An indirect comparison of dabigatran, rivaroxaban and apixaban for atrial fibrillation. Thromb Haemost. 2012;108: 30. Shah SV, Gage BF. Cost-effectiveness of dabigatran for stroke prophylaxis in atrial fibrillation. Circulation 2011;123:2562-2570. 31. Pink J, Lane S, Pirmohamed M, Hughes DA. Dabigatran etexilate versus warfarin in management of non-valvular atrial fibrillation in UK context: quantitative benefit-harm and economic analyses. Br.Med.J. 2011;343:d6333 32. Kansal AR, Sorensen SV, Gani R, et al. Cost-effectiveness of dabigatran etexilate for the prevention of stroke and systemic embolism in UK patients with atrial fibrillation. Heart 2012;98:573-578. 33. Kamel H, Johnston SC, Easton JD, Kim AS. Cost-effectiveness of dabigatran compared with warfarin for stroke prevention in patients with atrial fibrillation and prior stroke or transient ischemic attack. Stroke 2012;43:881-883. 34. Jowett S, Bryan S, Mant J, et al. Cost effectiveness of warfarin versus aspirin in patients older than 75 years with atrial fibrillation. Stroke 2011;42:1717-1721. 35. Freeman JV, Zhu RP, Owens DK, et al. Cost-effectiveness of dabigatran compared with warfarin for stroke prevention in atrial fibrillation. Ann Intern Med 2011;154:1-11. 36. Sorensen SV, Kansal AR, Connolly S, et al. Cost-effectiveness of dabigatran etexilate for the prevention of stroke and systemic embolism in atrial fibrillation: a Canadian payer perspective. Thromb Haemost. 2011;105:908-919. 37. Chong LY, Fenu E, Stansby G, Hodgkinson S. Management of venous thromboembolic diseases and the role of thrombophilia testing: summary of NICE guidance. Br.Med.J. 2012;344:e3979

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

38. AnonymousSystematic Reviews: CRD's guidance for undertaking reviews in health care (3rd edition). York: Centre for Reviews and Dissemination, 2009; 39. Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews of Interventions. Chichester: Wiley, 2008; 40. Abrams KR, Gillies CL, Lambert PC. Meta-analysis of heterogeneously reported trials assessing change from baseline. Stat.Med. 2005;24:3823-3844. 41. Higgins JP, Altman DG, Gotzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. Br.Med.J. 2011;343:d5928 42. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Br.Med.J. 2003;327:557-560. 43. Lu G, Ades AE. Combination of direct and indirect evidence in mixed treatment comparisons. Stat.Med. 2004;23:3105-3124. 44. Caldwell DM, Ades AE, Higgins JP. Simultaneous comparison of multiple treatments: combining direct and indirect evidence. Br.Med.J. 2005;331:897-900. 45. Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A. Bayesian measures of model complexity and fit. J.R.Statist.Soc.B 2002;64:583-616. 46. Salanti G, Higgins JP, Ades AE, Ioannidis JP. Evaluation of networks of randomized trials. Stat.Methods Med.Res. 2008;17:279-301. 47. Song F, Altman DG, Glenny AM, Deeks JJ. Validity of indirect comparison for estimating efficacy of competing interventions: empirical evidence from published meta-analyses. Br.Med.J. 2003;326:472 48. Dias S, Welton NJ, Caldwell DM, Ades AE. Checking consistency in mixed treatment comparison meta-analysis. Stat Med 2010;29:932-944. 49. Dias S, Welton NJ, Sutton AJ, Ades AE. NICE DSU Technical Support Document 2: A Generalised Linear Modelling Framework for Pairwise and Network Meta-analysis of Randomised Controlled Trials. London: National Institute for Health and Clinical Excellence, 2011; 50. Price MJ, Welton NJ, Ades AE. Parameterization of treatment effects for meta-analysis in multi-state Markov models. Stat Med 2011;30:140-151. 51. Welton NJ, Ades AE. Estimation of markov chain transition probabilities and rates from fully and partially observed data: uncertainty propagation, evidence synthesis, and model calibration. Med Decis Making 2005;25:633-645. 52. Dakin HA, Welton NJ, Ades AE, Collins S, Orme M, Kelly S. Mixed treatment comparison of repeated measurements of a continuous endpoint: an example using topical treatments for primary open-angle glaucoma and ocular hypertension. Stat Med 2011; 53. Cooper NJ, Sutton AJ, Morris D, Ades AE, Welton NJ. Addressing between-study heterogeneity and inconsistency in mixed treatment comparisons: Application to stroke prevention treatments in individuals with non-rheumatic atrial fibrillation. Stat Med 2009;28:1861-1881. 54. Berkey CS, Hoaglin DC, Mosteller F, Colditz GA. A random-effects regression model for meta-analysis. Stat.Med. 1995;14:395-411. 55. Lambert PC, Sutton AJ, Abrams KR, Jones DR. A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis. J Clin Epidemiol. 2002;55:86-94. 56. Cooper NJ, Sutton AJ, Abrams KR, Turner D, Wailoo A. Comprehensive decision analytical modelling in economic evaluation: a Bayesian approach. Health Econ. 2004;13:203-226. 57. Felli JC, Hazen GB. Sensitivity analysis and the expected value of perfect information. Med Decis Making 1998;18:95-109.

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

Appendix 1. Medline search strategies used for scoping reviews

Venous thromboembolism

Database: Medline 1950 to present Search Strategy: ------1 exp anticoagulants/ (174063) 2 Administration, Oral/ (106218) 3 1 and 2 (3778) 4 exp Coumarins/ (36818) 5 warfarin.tw. (12871) 6 coumarin$.tw. (6594) 7 coumadin.tw. (799) 8 rivaroxaban.tw. (388) 9 dabigatran.tw. (516) 10 dicoumarol.tw. (575) 11 (dicoumarin or dicumarin).tw. (103) 12 otamixaban.tw. (24) 13 dicumarol.tw. (841) 14 oral anticoagula$.tw. (6016) 15 oral anti-coagula$.tw. (50) 16 acenocoumarol.tw. (560) 17 ximelagatran.tw. (440) 18 edoxaban.tw. (46) 19 betrixaban.tw. (13) 20 Pradax$.tw. (31) 21 apixaban.tw. (196) 22 Exanta.tw. (22) 23 phenprocoumon.tw. (641) 24 Ethyl biscoumacetate.tw. (28) 25 "vitamin K antagonist$".tw. (1355) 26 factor Xa inhibitor$.tw. (894) 27 factor 10a inhibitor$.tw. (1) 28 exp Vitamin K/ai [Antagonists & Inhibitors] (1308) 29 Thrombin/ai [Antagonists & Inhibitors] (3249) 30 Factor Xa/ai [Antagonists & Inhibitors] (1904) 31 or/3-30 (54696) 32 exp Venous Thrombosis/ (41796) 33 exp Pulmonary Embolism/ (29387) 34 Venous Thromboembolism/ (3014) 35 (vein$ thrombo$ or venous thrombo$ or DVT or VTE or thrombo$ of deep vein$).ab. /freq=2 (15804) 36 (((vein$ or venous) adj3 thrombo$) or DVT or VTE).ti. (21489) 37 ((lung or lungs) adj3 embol$).tw. (1112) 38 (pulmonary adj3 embol$).tw. (24644) 39 ((leg or legs) adj3 (embol$ or thrombo$)).tw. (1098) 40 or/32-39 (80052) 41 randomized controlled trial.pt. (331300) 42 controlled clinical trial.pt. (84583) 43 randomized.ab. (234775) 44 placebo.ab. (132675) 45 drug therapy.fs. (1548642) 46 randomly.ab. (169129) 47 trial.ab. (243229)

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

48 groups.ab. (1110374) 49 or/41-48 (2877444) 50 exp animals/ not humans/ (3751397) 51 49 not 50 (2443662) 52 31 and 40 and 51 (3710)

Atrial Fibrillation

Database: Medline 1950 to present Search Strategy: ------1 exp anticoagulants/ (174063) 2 Administration, Oral/ (106218) 3 1 and 2 (3778) 4 exp Coumarins/ (36818) 5 warfarin.tw. (12871) 6 coumarin$.tw. (6594) 7 coumadin.tw. (799) 8 rivaroxaban.tw. (388) 9 dabigatran.tw. (516) 10 dicoumarol.tw. (575) 11 (dicoumarin or dicumarin).tw. (103) 12 otamixaban.tw. (24) 13 dicumarol.tw. (841) 14 oral anticoagula$.tw. (6016) 15 oral anti-coagula$.tw. (50) 16 acenocoumarol.tw. (560) 17 ximelagatran.tw. (440) 18 edoxaban.tw. (46) 19 betrixaban.tw. (13) 20 Pradax$.tw. (31) 21 apixaban.tw. (196) 22 Exanta.tw. (22) 23 phenprocoumon.tw. (641) 24 Ethyl biscoumacetate.tw. (28) 25 "vitamin K antagonist$".tw. (1355) 26 factor Xa inhibitor$.tw. (894) 27 factor 10a inhibitor$.tw. (1) 28 exp Vitamin K/ai [Antagonists & Inhibitors] (1308) 29 Thrombin/ai [Antagonists & Inhibitors] (3249) 30 Factor Xa/ai [Antagonists & Inhibitors] (1904) 31 or/3-30 (54696) 32 Atrial Fibrillation/ (29539) 33 Atrial Fibrillation$.tw. (30165) 34 auricular fibrillation$.tw. (743) 35 atrium fibrillation$.tw. (8) 36 atrial flutter/ (4711) 37 auricular flutter$.tw. (216) 38 atrial flutter$.tw. (3928) 39 atrial tachycardia$.tw. (2353) 40 atrial tachyarrhythmia$.tw. (894) 41 atrium tachycardia$.tw. (3) 42 atrial arrhythmia$.tw. (1916) 43 heart fibrillation$.tw. (42) 44 Tachycardia, Ectopic Atrial/ (811)

What is/are the best oral anticoagulant/s for primary prevention, treatment and secondary prevention of venous thromboembolic disease, and for prevention of stroke in atrial fibrillation?

45 typical flutter$.tw. (40) 46 Tachycardia, Ectopic Atrial/ (811) 47 or/32-46 (43445) 48 31 and 47 (3852) 49 randomized controlled trial.pt. (331300) 50 controlled clinical trial.pt. (84583) 51 randomized.ab. (234775) 52 placebo.ab. (132675) 53 drug therapy.fs. (1548642) 54 randomly.ab. (169129) 55 trial.ab. (243229) 56 groups.ab. (1110374) 57 or/49-56 (2877444) 58 exp animals/ not humans/ (3751397) 59 57 not 58 (2443662) 60 48 and 59 (2624)