The Beneluxa Initiative domain task force health technology assessment: a comparison of member countries' past health technology assessments.

OBJECTIVE: This study aimed to compare assessments between Beneluxa Initiative member countries' assessments and identify alignments and divergences. METHODS: A retrospective comparative analysis was performed that investigated (i) number and type of assessed indications (for Austria (AT), Belgium (BE), Ireland (IE), and the Netherlands (NL)); (ii) added benefit conclusions (for BE, IE, and NL); and (iii) the main arguments underlying differences in conclusions (for BE, IE, and NL). Data were retrieved directly from agency representatives and from public HTA reports. European Medicines Agency approved indications were included for drugs assessed between 2016 and 2020, excluding veterinary drugs, generics, and biosimilars. RESULTS: Only 44 (10 percent) of the 444 included indications were assessed by all four member countries. Between any pair of two countries, the overlap was higher, from 63 (AT-NL) to 188 (BE-IE). Added benefit conclusions matched exactly in 62-74 percent of the indications, depending on the countries compared. In the remaining cases, most often a difference of one added benefit level was observed (e.g., higher vs. equal relative effect). Contradictory outcomes were very rare: only three cases were observed (lower vs. higher effect). When assessing the underlying arguments for seven cases with different outcomes, differences were attributable to slight differences in weighing of evidence and uncertainties rather than disagreement on aspects within the assessment itself. CONCLUSIONS: Despite high variability in European HTA procedures, collaboration on HTA between the Beneluxa Initiative member countries is very feasible and would likely not result in added benefit conclusions that would be very different from added benefit conclusions in national procedures.

Comparative effectiveness of neutralising monoclonal antibodies in high risk COVID-19 patients: a Bayesian network meta-analysis.

The purpose of this work was to review and synthesise the evidence on the comparative effectiveness of neutralising monoclonal antibody (nMAB) therapies in individuals exposed to or infected with SARS-CoV-2 and at high risk of developing severe COVID-19. Outcomes of interest were mortality, healthcare utilisation, and safety. A rapid systematic review was undertaken to identify and synthesise relevant RCT evidence using a Bayesian Network Meta-Analysis. Relative treatment effects for individual nMABs (compared with placebo and one another) were estimated. Pooled effects for the nMAB class compared with placebo were estimated. Relative effects were combined with baseline natural history models to predict the expected risk reductions per 1000 patients treated. Eight articles investigating four nMABs (bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, sotrovimab) were identified. All four therapies were associated with a statistically significant reduction in hospitalisation (70-80% reduction in relative risk; absolute reduction of 35-40 hospitalisations per 1000 patients). For mortality, ICU admission, and invasive ventilation, the risk was lower for all nMABs compared with placebo with moderate to high uncertainty due to small event numbers. Rates of serious AEs and infusion reactions were comparable between nMABs and placebo. Pairwise comparisons between nMABs were typically uncertain, with broadly comparable efficacy. In conclusion, nMABs are effective at reducing hospitalisation among infected individuals at high-risk of severe COVID-19, and are likely to reduce mortality, ICU admission, and invasive ventilation rates; the effect on these latter outcomes is more uncertain. Widespread vaccination and the emergence of nMAB-resistant variants make the generalisability of these results to current patient populations difficult.

Clinical utility of anti-interleukin 5 monoclonal therapy in asthma using a national, centralised, outcome-based system of drug access.

INTRODUCTION: Interleukin 5 (IL-5) inhibitors are an important therapeutic advance in the management of severe, refractory, eosinophilic asthma. However, their utilisation should be targeted to maximise their benefits. This study used multisite, centralised, national data collected over 18 months to perform an observational integrated, retrospective, cohort study of selection criteria for initiation and continuation of IL-5 inhibitor treatment in Ireland. MATERIALS/PATIENTS AND METHODS: We used data from 230 patients who were given anti-IL-5 monoclonal therapy (reslizumab, mepolizumab or benralizumab) in Ireland between 2018 and 2020. Reimbursement of these drugs in Ireland requires fulfilling eligibility criteria defined by the Acute Hospitals Drugs Management Programme with continued reimbursement requiring ongoing submission of clinical data demonstrating clinical effectiveness. RESULTS: IL-5 inhibitor use for 18 months was associated with a total reduction in asthma-associated hospital admissions of 108 (p=0.036) and in non-hospital exacerbations of 85 in 18 months (p=0.014). Respiratory-associated GP visits were reduced from 637 in 12 months to 89 at 6 months and 210 at 18 months of treatment (p<0.001). Oral corticosteroid requirement was reduced or stopped entirely (p<0.001). Subgroup analysis of one site replicated these results and showed a significant reduction in the Asthma Control Questionnaire Score (p<0.001) CONCLUSIONS: Selected patients continued on IL-5 treatment to 18 months had significantly reduced exacerbations, GP visits, oral corticosteroid use and asthma-associated hospitalisations. These results show that anti-IL-5 therapy, in carefully selected and monitored patients with asthma, results in significant improvements in clinical outcomes in a real-world setting.

Estimating the Theoretical Cost Implications of Funding New Drugs Considered Not to Be Cost-Effective.

This study aims to estimate the theoretical excess expenditure that would be incurred by the Irish state-payer, should drugs be reimbursed at their original asking ("list") price rather than at a price at which the drug is considered cost-effective. In Ireland, all new drugs are evaluated by the National Centre for Pharmacoeconomics. For this study, drugs that were submitted by pharmaceutical companies from 2012 to 2017 and considered not cost-effective at list price were reviewed. A total of 43 such drugs met our inclusion criteria, and their pharmacoeconomic evaluations were further assessed. The price at which the drug could be considered cost-effective (cost-effective price) at the upper cost-effectiveness threshold used in Ireland (€ 45 000/quality adjusted life-year) was estimated for 18 drugs with an available cost-effectiveness model. Then, for each drug, the list price and cost-effective price (both per unit) were both individually applied to 1 year of national real-world drug utilization data. This allowed the estimation of the expected expenditures under the assumptions of list price paid and cost-effective price paid. The resulting theoretical excess expenditure, the expenditure at list price minus the expenditure at the cost-effective price, was estimated to be €108.2 million. This estimate is theoretical because of the confidentiality of actual drug prices. The estimation is calculated using the list price and likely overestimates the actual excess expenditure, which would reduce to zero if cost-effective prices are agreed. Nevertheless, this estimate illustrates the importance of a process to assess the value of new drugs so that potential excess drug expenditure is identified.

Exploring the opportunities for alignment of regulatory postauthorization requirements and data required for performance-based managed entry agreements.

Performance-based managed entry agreements (PB-MEAs) might allow patient access to new medicines, but practical hurdles make competent authorities for pricing and reimbursement (CAPR) reluctant to implement PB-MEAs. We explored if the feasibility of PB-MEAs might improve by better aligning regulatory postauthorization requirements with the data generation of PB-MEAs and by active collaboration and data sharing. Reviewers from seven CAPRs provided structured assessments of the information available at the European Medicines Agency (EMA) Web site on regulatory postauthorization requirements for fifteen recently authorized products. The reviewers judged to what extent regulatory postauthorization studies could help implement PB-MEAs by addressing uncertainty gaps. Study domains assessed were: patient population, intervention, comparators, outcomes, time horizon, anticipated data quality, and anticipated robustness of analysis. Reviewers shared general comments about PB-MEAs for each product and on cooperation with other CAPRs. Reviewers rated regulatory postauthorization requirements at least partly helpful for most products and across domains except the comparator domain. One quarter of responses indicated that public information provided by the EMA was insufficient to support the implementation of PB-MEAs. Few PB-MEAs were in place for these products, but the potential for implementation of PB-MEAs or collaboration across CAPRs was seen as more favorable. Responses helped delineate a set of conditions where PB-MEAs may help reduce uncertainty. In conclusion, PB-MEAs are not a preferred option for CAPRs, but we identified conditions where PB-MEAs might be worth considering. The complexities of implementing PB-MEAs remain a hurdle, but collaboration across silos and more transparency on postauthorization studies could help overcome some barriers.

Systematic review and network meta-analysis of the efficacy of existing treatments for patients with recurrent glioblastoma.

BACKGROUND: Despite advances in the treatment of cancers over the last years, treatment options for patients with recurrent glioblastoma (rGBM) remain limited with poor outcomes. Many regimens have been investigated in clinical trials; however, there is a lack of knowledge on comparative effectiveness. The aim of this systematic review is to provide an overview of existing treatment strategies and to estimate the relative efficacy of these regimens in terms of progression-free survival (PFS) and overall survival (OS). METHODS: We conducted a systematic review to identify randomized controlled trials (RCTs) investigating any treatment regimen in adult patients suffering from rGBM. Connected studies reporting at least one of our primary outcomes were included in a Bayesian network meta-analysis (NMA) estimating relative treatment effects. RESULTS: Forty RCTs fulfilled our inclusion criteria evaluating the efficacy of 38 drugs as mono- or combination therapy. Median OS ranged from 2.9 to 18.3 months; median PFS ranged from 0.7 to 6 months. We performed an NMA including 24 treatments that were connected within a large evidence network. Our NMA indicated improvement in PFS with most bevacizumab (BV)-based regimens compared to other regimens. We did not find any differences in OS between treatments. CONCLUSION: This systematic review provides a comprehensive overview of existing treatment options for rGBM. The NMA provides relative effects for many of these treatment regimens, which have not been directly compared in RCTs. Overall, outcomes for patients with rGBM remain poor across all treatment options, highlighting the need for innovative treatment options.

Understanding the Challenges and Uncertainties of Seroprevalence Studies for SARS-CoV-2.

SARS-CoV-2 continues to widely circulate in populations globally. Underdetection is acknowledged and is problematic when attempting to capture the true prevalence. Seroprevalence studies, where blood samples from a population sample are tested for SARS-CoV-2 antibodies that react to the SARS-CoV-2 virus, are a common method for estimating the proportion of people previously infected with the virus in a given population. However, obtaining reliable estimates from seroprevalence studies is challenging for a number of reasons, and the uncertainty in the results is often overlooked by scientists, policy makers, and the media. This paper reviews the methodological issues that arise in designing these studies, and the main sources of uncertainty that affect the results. We discuss the choice of study population, recruitment of subjects, uncertainty surrounding the accuracy of antibody tests, and the relationship between antibodies and infection over time. Understanding these issues can help the reader to interpret and critically evaluate the results of seroprevalence studies.

A Global eDelphi Exercise to Identify Core Domains and Domain Items for the Development of a Global Registry of Alopecia Areata Disease Severity and Treatment Safety (GRASS).

Importance: A recent expert consensus exercise emphasized the importance of developing a global network of patient registries for alopecia areata to redress the paucity of comparable, real-world data regarding the effectiveness and safety of existing and emerging therapies for alopecia areata. Objective: To generate core domains and domain items for a global network of alopecia areata patient registries. Evidence Review: Sixty-six participants, representing physicians, patient organizations, scientists, the pharmaceutical industry, and pharmacoeconomic experts, participated in a 3-round eDelphi process, culminating in a face-to-face meeting at the World Congress of Dermatology, Milan, Italy, June 14, 2019. Findings: Ninety-two core data items, across 25 domains, achieved consensus agreement. Twenty further noncore items were retained to facilitate data harmonization in centers that wish to record them. Broad representation across multiple stakeholder groups was sought; however, the opinion of physicians was overrepresented. Conclusions and Relevance: This study identifies the domains and domain items required to develop a global network of alopecia areata registries. These domains will facilitate a standardized approach that will enable the recording of a comprehensive, comparable data set required to oversee the introduction of new therapies and harness real-world evidence from existing therapies at a time when the alopecia areata treatment paradigm is being radically and positively disrupted. Reuse of similar, existing frameworks in atopic dermatitis, produced by the Treatment of Atopic Eczema (TREAT) Registry Taskforce, increases the potential to reuse existing resources, creates opportunities for comparison of data across dermatology subspecialty disease areas, and supports the concept of data harmonization.

The Expiry of Humira® Market Exclusivity and the Entry of Adalimumab Biosimilars in Europe: An Overview of Pricing and National Policy Measures.

Background: From October 2018, adalimumab biosimilars could enter the European market. However, in some countries, such as Netherlands, high discounts reported for the originator product may have influenced biosimilar entry. Objectives: The aim of this paper is to provide a European overview of (list) prices of originator adalimumab, before and after loss of exclusivity; to report changes in the reimbursement status of adalimumab products; and discuss relevant policy measures. Methods: Experts in European countries received a survey consisting of three parts: 1) general financing/co-payment of medicines, 2) reimbursement status and prices of originator adalimumab, and availability of biosimilars, and 3) policy measures related to the use of adalimumab. Results: In May 2019, adalimumab biosimilars were available in 24 of the 30 countries surveyed. Following introduction of adalimumab biosimilars, a number of countries have made changes in relation to the reimbursement status of adalimumab products. Originator adalimumab list prices varied between countries by a factor of 2.8 before and 4.1 after loss of exclusivity. Overall, list prices of originator adalimumab decreased after loss of exclusivity, although for 13 countries list prices were unchanged. When reported, discounts/rebates on originator adalimumab after loss of exclusivity ranged from 0% to approximately 26% (Romania), 60% (Poland), 80% (Denmark, Italy, Norway), and 80-90% (Netherlands), leading to actual prices per pen or syringe between €412 (Finland) and €50 - €99 (Netherlands). To leverage competition following entry of biosimilar adalimumab, only a few countries adopted measures specifically for adalimumab in addition to general policies regarding biosimilars. In some countries, a strategy was implemented even before loss of exclusivity (Denmark, Scotland), while others did not report specific measures. Conclusion: Even though originator adalimumab is the highest selling product in the world, few countries have implemented specific policies and practices for (biosimilar) adalimumab. Countries with biosimilars on the market seem to have competition lowering list or actual prices. Reported discounts varied widely between countries.

Bayesian Hierarchical Models for Meta-Analysis of Quality-of-Life Outcomes: An Application in Multimorbidity.

BACKGROUND: Health-related quality of life (HRQoL) is a key outcome in cost-utility analyses, which are commonly used to inform healthcare decisions. Different instruments exist to evaluate HRQoL, however while some jurisdictions have a preferred system, no gold standard exists. Standard meta-analysis struggles with the variety of outcome measures, which may result in the exclusion of potentially relevant evidence. OBJECTIVE: Using a case study in multimorbidity, the objective of this analysis is to illustrate how a Bayesian hierarchical model can be used to combine data across different instruments. The outcome of interest is the slope relating HRQoL to the number of coexisting conditions. METHODS: We propose a three-level Bayesian hierarchical model to systematically include a large number of studies evaluating HRQoL using multiple instruments. Random effects assumptions yield instrument-level estimates benefitting from borrowing strength across the evidence base. This is particularly useful where little evidence is available for the outcome of choice for further evaluation. RESULTS: Our analysis estimated a reduction in quality of life of 3.8-4.1% per additional condition depending on HRQoL instrument. Uncertainty was reduced by approximately 80% for the instrument with the least evidence. CONCLUSION: Bayesian hierarchical models may provide a useful modelling approach to systematically synthesize data from HRQoL studies.

Cost-effectiveness analysis of therapeutic options for chronic hepatitis C genotype 3 infected patients.

BACKGROUND: This study provides a cost-effectiveness analysis of therapeutic strategies for chronic hepatitis C genotype 3 infected patients in Spain. METHODS: A Markov model was designed to simulate the progression in a cohort of patients aged 50 years over a lifetime horizon. RESULTS: Sofosbuvir (SOF) plus peginterferon and ribavirin for 12 weeks was a cost-effective option when compared to standard of care (SoC) in the treatment of both 'moderate fibrosis' and 'cirrhotic' patients. Incremental cost-effectiveness ratios were €35,276/QALY and €18,374/QALY respectively. ICERs for SOF plus daclatasvir (DCV) regimens versus SoC were over the threshold limit considered, at €56,178/QALY and €77,378/QALY for 'moderate fibrosis' and 'cirrhotic' patients respectively. CONCLUSION: Addition of SOF to IFN-based regimens for genotype 3 was cost-effective for both 'moderate fibrosis' and 'cirrhotic' patients. IFN-free options including SOF and DCV association required price reductions lower than the list prices to be considered cost-effective.

Evaluating the neonatal BCG vaccination programme in Ireland.

BACKGROUND: The aim of this study was to compare the cost effectiveness of the current Irish programme of universal BCG vaccination of infants versus a programme which considered selectively vaccinating high risk infants using decision analytical modelling. METHODS: The efficacy of the BCG vaccine was re-evaluated to inform a decision analytical model constructed to follow a birth cohort of vaccinated and unvaccinated infants over a 15 year time horizon. The number of life years gained (LYG) was the primary outcome measure and this was compared to the net cost of the vaccination strategies. RESULTS: In the base case analysis, the incremental cost effectiveness ratios (ICERs) for the universal strategy and selective strategy vs no vaccination were €204,373/LYG and €143,233/LYG respectively. When comparing the incremental difference in moving from the universal to the selective strategy, the selective strategy costs €1,055,692 less per 4.8 life years lost per birth cohort. One way sensitivity analyses highlighted that a move from the universal to the selective strategy was particularly sensitive to the estimate of vaccine efficacy against deaths, the cost of administering the vaccine and the multiplier used to apportion risk of contracting tuberculosis. Probabilistic analysis suggested that a move from a universal based strategy to a selective based strategy could be deemed cost effective (probability of cost effectiveness is 76.8 %). CONCLUSION: The results of the study support the protective effect of the BCG vaccine in infants and quantified the cost effectiveness of the current BCG vaccination strategy and the decremental difference in moving to a selective strategy. This analysis highlights that the additional protection offered by the universal vaccination strategy is small compared to that of the selective strategy. Consideration should therefore be given to the implementation of a selective vaccination strategy, and diverting resources to improve TB case management and control.

Identifying and Revealing the Importance of Decision-Making Criteria for Health Technology Assessment: A Retrospective Analysis of Reimbursement Recommendations in Ireland.

BACKGROUND: Decisions on reimbursement of health interventions in many jurisdictions are informed by health technology assessments (HTAs). Historically, the focus of these has often been cost effectiveness or cost utility, while other criteria were considered informally. More recently, there has been an increasing interest in the formal incorporation of additional criteria using multi-criteria decision analysis. Such an approach has not yet formally been part of decision-making policy in Ireland. OBJECTIVE: The objective of this analysis is to demonstrate that cost effectiveness is not the only criterion influencing reimbursement decisions in Ireland. Furthermore, the aim is to reveal criteria that may have informally influenced reimbursement decisions in the past. METHODS: A list of potential criteria was identified based on the literature, national guidelines and experience of the national HTA agency. Information on each of these criteria was sought for every assessment conducted in Ireland up to July 2015. A logistic regression was fitted to the data to identify influential parameters. Model selection was performed using the Bolasso method. RESULTS: Thirteen criteria were considered in the analysis. Two members of the HTA review team assessed the performance of the interventions against these criteria. Model selection suggests that the incremental cost-effectiveness ratio and quality of evidence could be important drivers of reimbursement recommendations in Ireland. Less important drivers suggested include the year of assessment, the level of uncertainty, as well as safety and tolerability. CONCLUSION: The analysis demonstrates that recommendations for or against the reimbursement of technologies in Ireland are not only driven by cost effectiveness. This highlights the need for more formal inclusion of criteria in the process, to improve transparency and ensure consistency.

Using the Analytic Hierarchy Process to Derive Health State Utilities from Ordinal Preference Data.

BACKGROUND: The EuroQol five-dimensional questionnaire is a standardized instrument used in the economic evaluation of health care to measure health state preferences across disease groups. A time trade-off (TTO) approach is commonly used to elicit preferences from the public. However, there are issues regarding how best to measure worse-than-dead states; at present, extreme valuations are rounded up to more acceptable values. TTO elicitation is also cognitively demanding for respondents and is therefore expensive to investigate. OBJECTIVES: To describe how the analytic hierarchy process approach could be used to generate utilities from the ordinal relationships between the health states instead of the ordinal relationships between health states, allowing potentially useful preference data to be incorporated rather than excluded as they are at present. It was applied to the Measurement and Valuation of Health study data set, measuring health state preferences for the United Kingdom. METHODS: The analytic hierarchy process approach was explained. Five approaches to structure pairwise comparisons of health state preference were described (two concave, two convex, and one linear). RESULTS: All approaches described predicted the rankings of health states well. However, utilities derived followed an unconventional, bunched shape compared with the original Measurement and Valuation of Health TTO study. An approach was identified by optimizing the parameters, minimizing the sum of squared errors between the ordinal "health state ranking" approach and the original TTO-derived utilities. CONCLUSIONS: This approach outlined offers the potential to convert ordinal preference data into cardinal utilities. It is simpler than TTO studies to carry out and removes the need to directly alter results of the preference ranking exercise.

Incorporating data from various trial designs into a mixed treatment comparison model.

Estimates of relative efficacy between alternative treatments are crucial for decision making in health care. Bayesian mixed treatment comparison models provide a powerful methodology to obtain such estimates when head-to-head evidence is not available or insufficient. In recent years, this methodology has become widely accepted and applied in economic modelling of healthcare interventions. Most evaluations only consider evidence from randomized controlled trials, while information from other trial designs is ignored. In this paper, we propose three alternative methods of combining data from different trial designs in a mixed treatment comparison model. Naive pooling is the simplest approach and does not differentiate between-trial designs. Utilizing observational data as prior information allows adjusting for bias due to trial design. The most flexible technique is a three-level hierarchical model. Such a model allows for bias adjustment while also accounting for heterogeneity between-trial designs. These techniques are illustrated using an application in rheumatoid arthritis.

Relating health-related Quality of Life to disability progression in multiple sclerosis, using the 5-level EQ-5D.

BACKGROUND: Increasing use of the Quality-Adjusted Life-Year to inform resource allocation decision-making has highlighted the importance of relating clinical and health-related quality of life (HRQoL) outcomes in multiple sclerosis (MS) patients. OBJECTIVE AND METHODS: To investigate the relationship between the Expanded Disability Status Scale (EDSS) and HRQoL utility, using the 5-level EQ-5D (EQ-5D-5L). The discriminatory power of the EQ-5D-5L was assessed using Shannon's indices. RESULTS: A linear decline in utility was observed with changes in EDSS score from 0 to 6, after which point the relationship exhibited greater variability. Mean utility values ranged from -0.22 at EDSS 9 to 0.88 at EDSS 0. We found that the discriminative capacity of the EQ-5D-5L was considerably lower for the domains self-care and anxiety/depression, compared with other health-related domains. CONCLUSION: In its first reported use in an MS population, the EQ-5D-5L displayed good discriminatory capacity, although performance differed between the various domains of health, with evidence of a ceiling effect present in the domains of self-care and anxiety/depression. The EQ-5D-5L demonstrated a high correlation with EDSS in our MS cohort up to EDSS 6, after which point the utility valuation of severe health states exhibited much greater variability. Utility estimates from this study may be used in economic evaluations of disease-modifying therapies in MS, to inform resource-allocation decisions.

The use of continuous data versus binary data in MTC models: a case study in rheumatoid arthritis.

BACKGROUND: Estimates of relative efficacy between alternative treatments are crucial for decision making in health care. When sufficient head to head evidence is not available Bayesian mixed treatment comparison models provide a powerful methodology to obtain such estimates. While models can be fit to a broad range of efficacy measures, this paper illustrates the advantages of using continuous outcome measures compared to binary outcome measures. METHODS: Using a case study in rheumatoid arthritis a Bayesian mixed treatment comparison model is fit to estimate the relative efficacy of five anti-TNF agents currently licensed in Europe. The model is fit for the continuous HAQ improvement outcome measure and a binary version thereof as well as for the binary ACR response measure and the underlying continuous effect. Results are compared regarding their power to detect differences between treatments. RESULTS: Sixteen randomized controlled trials were included for the analysis. For both analyses, based on the HAQ improvement as well as based on the ACR response, differences between treatments detected by the binary outcome measures are subsets of the differences detected by the underlying continuous effects. CONCLUSIONS: The information lost when transforming continuous data into a binary response measure translates into a loss of power to detect differences between treatments in mixed treatment comparison models. Binary outcome measures are therefore less sensitive to change than continuous measures. Furthermore the choice of cut-off point to construct the binary measure also impacts the relative efficacy estimates.

A mixed treatment comparison of the efficacy of anti-TNF agents in rheumatoid arthritis for methotrexate non-responders demonstrates differences between treatments: a Bayesian approach.

BACKGROUND: A number of tumour necrosis factor α (TNFα) antagonists (anti-TNFα) are available to treat rheumatoid arthritis. All of these have demonstrated considerable efficacy in placebo controlled trials, but few head-to-head comparisons exist to date. This work's objective is to estimate the relative efficacy among licensed anti-TNFs in patients who have had an inadequate response to methotrexate (MTX). Different outcome measures are used to highlight the advantages of continuous measures in such analyses. METHODS: A systematic review identified randomised controlled trials comparing the efficacy of licensed anti-TNFα agents with placebo at 24 weeks in patients who have had an inadequate response to MTX. Relative efficacy was estimated using Bayesian mixed treatment comparison (MTC) models. Three different outcome measures were used: RR of achieving an American College of Rheumatology (ACR) 20 and ACR50 response and the percentage improvement in Health Assessment Questionnaire (HAQ) score. RESULTS: 16 published trials were included in the analysis. All anti-TNFs show considerably improved efficacy over placebo. The MTC results also provide evidence of some differences in efficacy of the TNFα antagonists. Etanercept appears superior to infliximab and golimumab, and certolizumab to infliximab and adalimumab. ACR results indicate improved efficacy of certolizumab over golimumab. On HAQ analysis, adalimumab, certolizumab, etanercept and golimumab appear superior to infliximab, and etanercept shows improved efficacy compared with adalimumab. CONCLUSIONS: There are differences in efficacy among the TNFα antagonists. In a MTC, a continuous outcome measure has more strength to detect such differences than a binomial outcome measure because of its enhanced sensitivity to change.

The impact of a revised EQ-5D population scoring on preference-based utility scores in an inflammatory arthritis cohort.

BACKGROUND AND OBJECTIVE: It is well established that there are problems with the EQ-5D. This is due to the original scoring methods used and how negative time trade-off (TTO) values were treated. A revised scoring method has been published. This article applies this to an inflammatory arthritis cohort. The objective is to examine the impact of a revised scoring system for the EQ-5D (UK) TTO on the utility estimates and in the case of rheumatoid arthritis, to explore the impact of using different utility metrics on the incremental cost-effectiveness ratio (ICER) results of an economic model. METHODS: A total of 504 patients with inflammatory arthritis were rescored using revised EQ-5D scoring, which uses an episodic random utility model to deal with negative TTO values. Differences in utility scores were compared and the new mapping coefficients were obtained. These were then used in an economic model to examine the impact on the ICER. RESULTS: In rheumatoid arthritis, the overall change is less for the revised EQ-5D scoring than with the original EQ-5D (TTO) but greater than the SF-6D: EQ-5D UK -0.22 (95% confidence interval [CI] -0.30 to -0.15), revised EQ-5D UK -0.16 (95% CI -0.21 to -0.10) and SF-6D -0.08 (95% CI -0.11 to -0.05). A similar trend is seen in the psoriatic arthritis group. The economic model produced different ICERs, when different utility measures were used; EQ-5D (TTO) €42,402, SF-6D €111,788, and revised EQ-5D (TTO) €57,747. CONCLUSION: In the context of inflammatory arthritis, this article demonstrates that a revised scoring for EQ-5D may have a significant impact on utility estimates and on the output of the economic model.

Understanding the relationship between the EQ-5D, SF-6D, HAQ and disease activity in inflammatory arthritis.

BACKGROUND: The growth of economic analyses and in particular cost-utility analyses (CUA), which use the QALY as a measure of outcome, has heightened the interest in the methodologies used to calculate the QALY. The EQ-5D has produced quite different utility values from that of the SF-6D. This article seeks to understand these differences using a cohort of patients with inflammatory arthritis. OBJECTIVE: To examine the relationship between the disease-specific measure, Health Assessment Questionnaire (HAQ) disability index (DI) and the preference-based measures, SF-6D, EQ-5D and European League Against Arthritis (EULAR) Disease Activity Score (DAS) in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA). METHODS: Patients with RA and PsA (n = 504) attending a tertiary rheumatology referral centre completed the HAQ, SF-6D and the EQ-5D before starting biological therapy and again 12 months later. The SF-36 was converted into a utility using the preference-based SF-6D. Clinical outcomes such as the DAS, joint counts and laboratory measures were also recorded. We calculated single index utility scores from the preference-based instruments using UK population norms. We used regression analysis to derive a mapping function and calculated utility scores from the HAQDI and the DAS 28. RESULTS: The mean utility observed at baseline for RA was 0.43 for the EQ-5D and 0.54 for the SF-6D and for PsA was 0.49 for the EQ-5D and 0.57 for the SF-6D. The utility gain demonstrated by the EQ-5D was over twice that of the SF-6D. The EQ-5D scored 17% of the RA group as less than 0 (state defined as worse than death); 7% of this group remained less than 0 at follow-up. The distribution of the utility estimates was similar for both RA and PsA. CONCLUSIONS: Our findings draw attention to the impact of states worse than death on the overall distribution for the EQ-5D derived utilities and how these impact on its use in practice. EQ-5D-derived QALY changes are over twice that of the SF-6D. The implication of this for decision makers is that cost-effectiveness evaluations for treatments in this disease class are likely to be very sensitive to the choice of utility measure.