It Takes 2 to Tango. Setting Out the Conditions in Which Performance-Based Risk-Sharing Arrangements Work for Both Parties.

OBJECTIVES: Faster regulatory approval processes often fail to achieve faster patient access. We seek an approach, using performance-based risk-sharing arrangements, to address uncertainty for payers regarding the relative effectiveness and value for money of products launched through accelerated approval schemes. One important reason for risk sharing is to resolve differences of opinion between innovators and payers about a technology's underlying value. To date, there has been no formal attempt to set out the circumstances in which risk sharing can address these differences. METHODS: We use a value of information framework to understand what a performance-based risk-sharing arrangements can, in principle, add to a reimbursement scheme, separating payer perspectives on cost-effectiveness and the value of research from those of the innovator. We find 16 scenarios, developing 5 rules to analyze these 16 scenarios, identifying cases in which risk sharing adds value for both parties. RESULTS: We find that risk sharing provides an improved solution in 9 out of 16 combinations of payer and innovator expectations about treatment outcome and the value of further research. Among our assumptions, who pays for research and scheme administration costs are key. CONCLUSIONS: Steps should be undertaken to make risk sharing more practical, ensuring that payers consider it an option. This requires additional costs to the health system falling on the innovator in an efficient way that aligns incentives for product development for global markets. Health systems benefits are earlier patient access to cost-effective treatments and payers with higher confidence of not wasting money. Innovators get greater returns while conducting research.

A Guide to Selecting Flexible Survival Models to Inform Economic Evaluations of Cancer Immunotherapies.

OBJECTIVES: Parametric models are routinely used to estimate the benefit of cancer drugs beyond trial follow-up. The advent of immune checkpoint inhibitors has challenged this paradigm, and emerging evidence suggests that more flexible survival models, which can better capture the shapes of complex hazard functions, might be needed for these interventions. Nevertheless, there is a need for an algorithm to help analysts decide whether flexible models are required and, if so, which should be chosen for testing. This position article has been produced to bridge this gap. METHODS: A virtual advisory board comprising 7 international experts with in-depth knowledge of survival analysis and health technology assessment was held in summer 2021. The experts discussed 24 questions across 6 topics: the current survival model selection procedure, data maturity, heterogeneity of treatment effect, cure and mortality, external evidence, and additions to existing guidelines. Their responses culminated in an algorithm to inform selection of flexible survival models. RESULTS: The algorithm consists of 8 steps and 4 questions. Key elements include the systematic identification of relevant external data, using clinical expert input at multiple points in the selection process, considering the future and the observed hazard functions, assessing the potential for long-term survivorship, and presenting results from all plausible models. CONCLUSIONS: This algorithm provides a systematic, evidence-based approach to justify the selection of survival extrapolation models for cancer immunotherapies. If followed, it should reduce the risk of selecting inappropriate models, partially addressing a key area of uncertainty in the economic evaluation of these agents.

Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

The allocation of healthcare resources among competing priorities requires an assessment of the expected costs and health effects of investing resources in the activities and of the opportunity cost of the expenditure. To date, much effort has been devoted to assessing the expected costs and health effects, but there remains an important need to also reflect the consequences of uncertainty in resource allocation decisions and the value of further research to reduce uncertainty. Decision making with uncertainty may turn out to be suboptimal, resulting in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to better inform resource decisions. This value can be quantified using value of information (VOI) analysis. This report from the ISPOR VOI Task Force describes methods for computing 4 VOI measures: the expected value of perfect information, expected value of partial perfect information (EVPPI), expected value of sample information (EVSI), and expected net benefit of sampling (ENBS). Several methods exist for computing EVPPI and EVSI, and this report provides guidance on selecting the most appropriate method based on the features of the decision problem. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing VOI analyses. The software needed to compute VOI is discussed, and areas for future research are highlighted.

Value of Information Analysis for Research Decisions-An Introduction: Report 1 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

Healthcare resource allocation decisions made under conditions of uncertainty may turn out to be suboptimal. In a resource constrained system in which there is a fixed budget, these suboptimal decisions will result in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to make better resource allocation decisions. This value can be quantified using a value of information (VOI) analysis. This report, from the ISPOR VOI Task Force, introduces VOI analysis, defines key concepts and terminology, and outlines the role of VOI for supporting decision making, including the steps involved in undertaking and interpreting VOI analyses. The report is specifically aimed at those tasked with making decisions about the adoption of healthcare or the funding of healthcare research. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing the results of VOI analyses.

Uncertainty and Cures: Discontinuation, Irreversibility, and Outcomes-Based Payments: What Is Different About a One-Off Treatment?

Payers are concerned that one-off "cures" bring great uncertainty with the consequential risk of incorrect adoption decisions, and significant budget impact from large one-off payments. Innovators worry about bias against "cures" in favor of repeat treatment, which is not in patients' interests. We find that even in the absence of a difference in uncertainty of outcomes, adverse pay-offs differ. The greater financial risk associated with a cure is related to the issue of treatment discontinuation, driven by irreversibility. This paper uses a stylized example to illustrate the need to separate three different elements of the issue: (i) one-off versus repeat or ongoing treatment, (ii) duration of treatment effect, and (iii) the potential role of financial arrangements or risk sharing to mitigate the financial risk to the payer. It concludes that: (i) prevalence and discontinuation issues mean that the impact on the payer of an incorrect decision is greater with a one-off treatment than a repeat therapy; (ii) with evidence collection this risk diminishes over time (a form of CED or OWR); and (iii) financial arrangements or risk sharing can eliminate differences for the payer as between one-off and repeat therapy. The impact of (iii) also addresses payer concerns about budget impact.

The CARE Plus study - a whole-system intervention to improve quality of life of primary care patients with multimorbidity in areas of high socioeconomic deprivation: exploratory cluster randomised controlled trial and cost-utility analysis.

BACKGROUND: Multimorbidity is common in deprived communities and reduces quality of life. Our aim was to evaluate a whole-system primary care-based complex intervention, called CARE Plus, to improve quality of life in multimorbid patients living in areas of very high deprivation. METHODS: We used a phase 2 exploratory cluster randomised controlled trial with eight general practices in Glasgow in very deprived areas that involved multimorbid patients aged 30-65 years. The intervention comprised structured longer consultations, relationship continuity, practitioner support, and self-management support. Control practices continued treatment as usual. Primary outcomes were quality of life (EQ-5D-5L utility scores) and well-being (W-BQ12; 3 domains). Cost-effectiveness from a health service perspective, engagement, and retention were assessed. Recruitment and baseline measurements occurred prior to randomisation. Blinding post-randomisation was not possible but outcome measurement and analysis were masked. Analyses were by intention to treat. RESULTS: Of 76 eligible practices contacted, 12 accepted, and eight were selected, randomised and participated for the duration of the trial. Of 225 eligible patients, 152 (68 %) participated and 67/76 (88 %) in each arm completed the 12-month assessment. Two patients died in the control group. CARE Plus significantly improved one domain of well-being (negative well-being), with an effect size of 0.33 (95 % confidence interval [CI] 0.11-0.55) at 12 months (p = 0.0036). Positive well-being, energy, and general well-being (the combined score of the three components) were not significantly influenced by the intervention at 12 months. EQ-5D-5L area under the curve over the 12 months was higher in the CARE Plus group (p = 0.002). The incremental cost in the CARE Plus group was £929 (95 % CI: £86-£1788) per participant with a gain in quality-adjusted life years of 0.076 (95 % CI: 0.028-0.124) over the 12 months of the trial, resulting in a cost-effectiveness ratio of £12,224 per quality-adjusted life year gained. Modelling suggested that cost-effectiveness would continue. CONCLUSIONS: It is feasible to conduct a high-quality cluster randomised control trial of a complex intervention with multimorbid patients in primary care in areas of very high deprivation. Enhancing primary care through a whole-system approach may be a cost-effective way to protect quality of life for multimorbid patients in deprived areas. TRIAL REGISTRATION: ISRCTN 34092919 , assigned 14/1/2013.

A gender-sensitised weight loss and healthy living programme for overweight and obese men delivered by Scottish Premier League football clubs (FFIT): a pragmatic randomised controlled trial.

BACKGROUND: The prevalence of male obesity is increasing but few men take part in weight loss programmes. We assessed the effect of a weight loss and healthy living programme on weight loss in football (soccer) fans. METHODS: We did a two-group, pragmatic, randomised controlled trial of 747 male football fans aged 35-65 years with a body-mass index (BMI) of 28 kg/m(2) or higher from 13 Scottish professional football clubs. Participants were randomly assigned with SAS (version 9·2, block size 2-9) in a 1:1 ratio, stratified by club, to a weight loss programme delivered by community coaching staff in 12 sessions held every week. The intervention group started a weight loss programme within 3 weeks, and the comparison group were put on a 12 month waiting list. All participants received a weight management booklet. Primary outcome was mean difference in weight loss between groups at 12 months, expressed as absolute weight and a percentage of their baseline weight. Primary outcome assessment was masked. Analyses were based on intention to treat. The trial is registered with Current Controlled Trials, number ISRCTN32677491. FINDINGS: 374 men were allocated to the intervention group and 374 to the comparison group. 333 (89%) of the intervention group and 355 (95%) of the comparison group completed 12 month assessments. At 12 months the mean difference in weight loss between groups, adjusted for baseline weight and club, was 4·94 kg (95% CI 3·95-5·94) and percentage weight loss, similarly adjusted, was 4·36% (3·64-5·08), both in favour of the intervention (p<0·0001). Eight serious adverse events were reported, five in the intervention group (lost consciousness due to drugs for pre-existing angina, gallbladder removal, hospital admission with suspected heart attack, ruptured gut, and ruptured Achilles tendon) and three in the comparison group (transient ischaemic attack, and two deaths). Of these, two adverse events were reported as related to participation in the programme (gallbladder removal and ruptured Achilles tendon). INTERPRETATION: The FFIT programme can help a large proportion of men to lose a clinically important amount of weight; it offers one effective strategy to challenge male obesity. FUNDING: Scottish Government and The UK Football Pools funded delivery of the programme through a grant to the Scottish Premier League Trust. The National Institute for Health Research Public Health Research Programme funded the assessment (09/3010/06).

Communicating the parameter uncertainty in the IQWiG efficiency frontier to decision-makers.

The Institute for Quality and Efficiency in Health Care (IQWiG) developed-in a consultation process with an international expert panel-the efficiency frontier (EF) approach to satisfy a range of legal requirements for economic evaluation in Germany's statutory health insurance system. The EF approach is distinctly different from other health economic approaches. Here, we evaluate established tools for assessing and communicating parameter uncertainty in terms of their applicability to the EF approach. Among these are tools that perform the following: (i) graphically display overall uncertainty within the IQWiG EF (scatter plots, confidence bands, and contour plots) and (ii) communicate the uncertainty around the reimbursable price. We found that, within the EF approach, most established plots were not always easy to interpret. Hence, we propose the use of price reimbursement acceptability curves-a modification of the well-known cost-effectiveness acceptability curves. Furthermore, it emerges that the net monetary benefit allows an intuitive interpretation of parameter uncertainty within the EF approach. This research closes a gap for handling uncertainty in the economic evaluation approach of the IQWiG methods when using the EF. However, the precise consequences of uncertainty when determining prices are yet to be defined.

Use of value of information in UK health technology assessments.

OBJECTIVES: The aim of this study was to identify and critically appraise the use of Value of Information (VOI) analyses undertaken as part of health technology assessment (HTA) reports in England and Wales. METHODS: A systematic review of National Institute for Health Research (NIHR) funded HTA reports published between 2004 and 2013 identified the use of VOI methods and key analytical details in terms of: (i) types of VOI methodology used; (ii) parameters and key assumptions; and (iii) conclusions drawn in terms of the need for further research. RESULTS: A total of 512 HTA reports were published during the relevant timeframe. Of these, 203 reported systematic review and economic modeling studies and 25 of these had used VOI method(s). Over half of the twenty-five studies (n = 13) conducted both EVPI (Expected Value of Perfect Information) and EVPPI (Expected Value of Partial Perfect Information) analyses. Eight studies conducted EVPI analysis, three studies conducted EVPI, EVPPI, and EVSI (Expected Value of Sampling Information) analyses and one study conducted EVSI analysis only. The level of detail reporting the methods used to conduct the VOI analyses varied. CONCLUSIONS: This review has shown that the frequency of the use of VOI methods is increasing at a slower pace compared with the published volume of HTA reports. This review also suggests that analysts reporting VOI method(s) in HTA reports should aim to describe the method(s) in sufficient detail to enable and encourage decision-makers guiding research prioritization decisions to use the potentially valuable outputs from quantitative VOI analyses.

Meta-analysis of the association between body mass index and health-related quality of life among children and adolescents, assessed using the pediatric quality of life inventory index.

OBJECTIVE: To explore the relationships between body mass index and overall, physical, and psychosocial health-related quality of life (HRQoL) in children and adolescents. STUDY DESIGN: A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Medline, Embase, PsycINFO, and the Web of Knowledge were searched for relevant articles. Inclusion was restricted to participants under 20 years of age, assessed using the Pediatric Quality of Life Inventory. Random-effects meta-analysis, meta-regression, and cumulative meta-analysis were conducted. Heterogeneity was assessed using the I(2) statistic, and potential publication and small study bias were evaluated using funnel plots and the Egger test. RESULTS: Eleven eligible studies provided 35 estimates of effect size, derived from a total of 13210 study participants. Based on self-reports, children and adolescents with above-normal body mass index had significantly lower total, physical, and psychosocial HRQoL, with a clear dose relationship across all categories. In obese children and adolescents, the overall score was reduced by 10.6 points (95% CI, 14.0-7.2; P < .001). Parents reported the same pattern but a larger effect size. The total parental score for obese children and adolescents was reduced by 18.9 points (95% CI, 26.6-11.1; P < .001). No significant publication or small study bias was observed. CONCLUSION: Parents overestimate the impact of obesity on the HRQoL of their children. Nonetheless, obese children and adolescents have significantly reduced overall, physical, and psychosocial HRQoL.

Double trouble: the impact of multimorbidity and deprivation on preference-weighted health related quality of life a cross sectional analysis of the Scottish Health Survey.

OBJECTIVE: To investigate the association between multimorbidity and Preference_Weighted Health Related Quality of Life (PW_HRQoL), a score that combines physical and mental functioning, and how this varies by socioeconomic deprivation and age. DESIGN: The Scottish Health Survey (SHeS) is a cross-sectional representative survey of the general population which included the SF-12, a survey of HRQoL, for individuals 20 years and over. METHODS: For 7,054 participants we generated PW_HRQoL scores by running SF-12 responses through the SF-6D algorithm. The resulting scores ranged from 0.29 (worst health) to 1 (perfect health). Using ordinary least squares, we first investigated associations between scores and increasing counts of longstanding conditions, and then repeated for multimorbidity (2+ conditions). Estimates were made for the general population and quintiles of socioeconomic deprivation. For multimorbidity, the analyses were repeated stratifying the population by age group (20-44, 45-64, 65+). RESULTS: 45% of participants reported a longstanding condition and 18% reported multimorbidity. The presence of 1, 2, or 3+ longstanding conditions were associated with average reductions in PW_HRQoL scores of 0.081, 0.151 and 0.212 respectively. Reduction in scores associated with multimorbidity was 33% greater in the most deprived quintile compared to the least deprived quintile, with the biggest difference (80%) in the 20-44 age groups. There were no significant gender differences. CONCLUSIONS: PW_HRQoL decreases markedly with multimorbidity, and is exacerbated by higher deprivation and younger age. There is a need to prioritise interventions to improve the HRQoL for (especially younger) adults with multimorbidity in deprived areas. BOX 1: What Is Known?Prevalence and premature onset of multimorbidity increases as socioeconomic position worsens. Previous studies have investigated the effect of multimorbidity on Health Related Quality of Life (HRQoL) on separate physical and mental health states. There is limited data on how HRQoL falls as the number of conditions increase, and how estimates vary across the general population.Leaving physical and mental health as separate categories can inhibit assessment of overall HRQoL. The use of a Preference_Weighted Health Related Quality of Life (PW_HRQoL) score provides a single summary measure of overall health, by weighting mental and physical states by their perceived importance as part of overall HRQoL. The use of a single score enables a simple and consistent assessment of the impact of conditions and how this varies across the population. Economists term PW_HRQoL scores health utilities.What this study adds?This is the first study to estimate how the impact of multimorbidity on PW_HRQoL scores varies by age group and socioeconomic deprivation. Multimorbidity has a substantial negative impact on HRQoL which is most severe in areas of deprivation, especially in younger adults.Measuring the burden of multimorbidity using PW_HRQoL provides consistency with how economists measure HRQoL; changes in which can be used in economic evaluation to assess the cost effectiveness of interventions.

The value of treatment for infertility: A systematic literature review of willingness-to-pay thresholds and approaches for determining the cost effectiveness of fertility therapies.

Willingness to pay (WTP) for an infertility treatment is the maximum amount of money a patient is willing to pay per treatment, or to achieve a live birth or pregnancy. Such thresholds are important to determine the cost effectiveness of a treatment. A systematic review was conducted to identify and explore the studies that attempt to ascertain WTP for infertility and compare them with the cost-effectiveness studies that claimed to use WTP thresholds. For comparison, all the costs were converted and inflated to 2021 euros. The results demonstrated that there were no standard outcomes or WTP thresholds for an outcome/treatment, and the methodologies used vary. Cost-effectiveness studies either used the incremental cost-effectiveness ratio to imply a WTP threshold, or used thresholds that were previously accepted for a quality-adjusted life year outcome converted, inappropriately, to an infertility outcome. There is a need for further research by health economists to develop a consensus for the meaningful assessment of WTP for ART.

Model parameter estimation and uncertainty: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--6.

A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value of information analysis. The article also makes extensive recommendations around the reporting of uncertainty, in terms of both deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.

Cost-effectiveness of aldosterone antagonists for the treatment of post-myocardial infarction heart failure.

OBJECTIVE: To assess the cost-effectiveness of eplerenone versus spironolactone as an adjunctive therapy to standard care in patients with heart failure (HF) following a myocardial infarction (post-MI) from the perspective of the National Health Service in the United Kingdom. METHODS: A systematic review was conducted, and a Bayesian meta-regression approach was used to establish the relative effectiveness of eplerenone and spironolactone by using evidence from randomized controlled trials. A decision analytic model was developed to assess the costs and consequences associated with the primary outcome of the trials over a lifetime time horizon. RESULTS: The incremental cost-effectiveness ratio of eplerenone compared with that of standard care alone was £ 4457 and £ 7893 for each additional quality-adjusted life-year when 2-year and lifetime treatment duration was assumed, respectively. In both scenarios, spironolactone did not appear cost-effective compared with eplerenone. The results were sensitive to the higher relative effectiveness estimated for eplerenone compared with spironolactone from the meta-regression. When a class effect was assumed for the effect on mortality and hospitalizations, spironolactone emerged as the most cost-effective treatment. CONCLUSIONS: Eplerenone appears more cost-effective than spironolactone for the treatment of post-MI HF. These findings, however, remain subject to important uncertainties regarding the effects of treatment on major clinical events. An adequately powered, well-conducted randomized controlled trial that directly compares spironolactone and eplerenone may be required to provide more robust evidence on the optimal management of post-MI HF. Despite these uncertainties, the use of an aldosterone antagonist was consistently demonstrated to be a highly cost-effective strategy for the management of post-MI HF in the National Health Service.

Impact of metabolic comorbidity on the association between body mass index and health-related quality of life: a Scotland-wide cross-sectional study of 5,608 participants.

BACKGROUND: The prevalence of obesity is rising in Scotland and globally. Overall, obesity is associated with increased morbidity, mortality and reduced health-related quality of life. Studies suggest that "healthy obesity" (obesity without metabolic comorbidity) may not be associated with morbidity or mortality. Its impact on health-related quality of life is unknown. METHODS: We extracted data from the Scottish Health Survey on self-reported health-related quality of life, body mass index (BMI), demographic information and comorbidity. SF-12 responses were converted into an overall health utility score. Linear regression analyses were used to explore the association between BMI and health utility, stratified by the presence or absence of metabolic comorbidity (diabetes, hypertension, hypercholesterolemia or cardiovascular disease), and adjusted for potential confounders (age, sex and deprivation quintile). RESULTS: Of the 5,608 individuals, 3,744 (66.8%) were either overweight or obese and 921 (16.4%) had metabolic comorbidity. There was an inverted U-shaped relationship whereby health utility was highest among overweight individuals and fell with increasing BMI. There was a significant interaction with metabolic comorbidity (p = 0.007). Individuals with metabolic comorbidty had lower utility scores and a steeper decline in utility with increasing BMI (morbidly obese, adjusted coefficient: -0.064, 95% CI -0.115, -0.012, p = 0.015 for metabolic comorbidity versus -0.042, 95% CI -0.067, -0.018, p = 0.001 for no metabolic comorbidity). CONCLUSIONS: The adverse impact of obesity on health-related quality of life is greater among individuals with metabolic comorbidity. However, increased BMI is associated with reduced health-related quality of life even in the absence of metabolic comorbidity, casting doubt on the notion of "healthy obesity".

Assessing the value of orphan drugs using conventional cost-effectiveness analysis: Is it fit for purpose?

Conventional cost-effectiveness analysis-i.e., assessing pharmaceuticals through a cost per quality-adjusted life year (QALY) framework-originated from a societal commitment to maximize population health given limited resources. This "extra-welfarist" approach has produced pricing and reimbursement systems that are not well- aligned with the unique considerations of orphan drugs. This framework has been slow to evolve along with our increased understanding of the impact of rare diseases, which in turn has complicated the assessment of orphan drugs meant to treat rare diseases. Herein, we (i) discuss the limitations of conventional cost-effectiveness analysis as applied to assessing access to, as well as the pricing and reimbursement of, orphan drugs, (ii) critically appraise alternative and supplemental approaches, and (iii) offer insights on plausible steps forward.

An Innovative Approach to Modelling the Optimal Treatment Sequence for Patients with Relapsing-Remitting Multiple Sclerosis: Implementation, Validation, and Impact of the Decision-Making Approach.

INTRODUCTION: An innovative computational model was developed to address challenges regarding the evaluation of treatment sequences in patients with relapsing-remitting multiple sclerosis (RRMS) through the concept of a 'virtual' physician who observes and assesses patients over time. We describe the implementation and validation of the model, then apply this framework as a case study to determine the impact of different decision-making approaches on the optimal sequence of disease-modifying therapies (DMTs) and associated outcomes. METHODS: A patient-level discrete event simulation (DES) was used to model heterogeneity in disease trajectories and outcomes. The evaluation of DMT options was implemented through a Markov model representing the patient's disease; outcomes included lifetime costs and quality of life. The DES and Markov models underwent internal and external validation. Analyses of the optimal treatment sequence for each patient were based on several decision-making criteria. These treatment sequences were compared to current treatment guidelines. RESULTS: Internal validation indicated that model outcomes for natural history were consistent with the input parameters used to inform the model. Costs and quality of life outcomes were successfully validated against published reference models. Whereas each decision-making criterion generated a different optimal treatment sequence, cladribine tablets were the only DMT common to all treatment sequences. By choosing treatments on the basis of minimising disease progression or number of relapses, it was possible to improve on current treatment guidelines; however, these treatment sequences were more costly. Maximising cost-effectiveness resulted in the lowest costs but was also associated with the worst outcomes. CONCLUSIONS: The model was robust in generating outcomes consistent with published models and studies. It was also able to identify optimal treatment sequences based on different decision criteria. This innovative modelling framework has the potential to simulate individual patient trajectories in the current treatment landscape and may be useful for treatment switching and treatment positioning decisions in RRMS.

Cost-effectiveness of infliximab for the treatment of active and progressive psoriatic arthritis.

BACKGROUND: Despite its proven efficacy, infliximab is often considered to be an expensive treatment for patients with psoriatic arthritis. OBJECTIVES: To estimate the cost-effectiveness of infliximab among patients with active and progressive psoriatic arthritis. METHODS: A decision analytic model was constructed to simulate disease progression in hypothetical cohorts of patients with psoriatic arthritis receiving infliximab maintenance treatment. The primary response measure was change in Health Assessment Questionnaire score from a baseline estimated from mixed treatment models drawn from published clinical trials. Palliative care, comprising nonbiologic disease-modifying antirheumatic drugs, was used as a comparator. The primary outcome was quality-adjusted life years. The dose of infliximab was estimated for a range of 60 to 80 kg per patient body weight. The costs and outcomes were discounted at 3.5% for a period of 40 years. Uncertainty around the results was explored with probabilistic sensitivity analysis. RESULTS: The mixed treatment comparison showed a significant reduction in Health Assessment Questionnaire score across all patients. The tumor necrosis factor α inhibitors were significantly superior to palliative care but comparable with one another. The incremental cost-effectiveness ratios for etanercept, adalimumab, and infliximab relative to palliative care were £17,327; £19,246; and £16,942 to £23,022, respectively, across all patients with psoriatic arthritis and £16,613; £18,170; and £15,788 to £21,736, respectively, in the subgroup with significant psoriasis. CONCLUSION: Infliximab represents a cost-effective treatment option well within the National Institute for Health and Clinical Excellence threshold relative to palliative care. In light of equivalent outcomes with other tumor necrosis factor α inhibitors, its position in the treatment pathway is likely to be governed by treatment costs.

'Pedometers cost buttons': the feasibility of implementing a pedometer based walking programme within the community.

BACKGROUND: Recent studies have suggested that walking interventions may be effective (at least in the short term) at increasing physical activity amongst those people who are the most inactive. This is a leading objective of contemporary public health policy in the UK and worldwide. However, before committing money from limited budgets to implement walking interventions more widely in the community, policymakers will want to know whether similar impacts can be expected and whether any changes will be required to the process to ensure uptake and success. This paper utilises the findings from a recent community-based pedometer study (Walking for Wellbeing in the West - WWW) undertaken in Glasgow, Scotland to address issues of feasibility. METHODS: An economic analysis of the WWW study assessed the costs of the interventions (minimal and maximal) and combined these with the effects to present incremental cost-effectiveness ratios (cost/person achieving the target of an additional 15,000 steps/week). A qualitative evaluation, involving focus group discussions with WWW participants and short interviews with members of the WWW research team, explored perceived benefits and barriers associated with walking, as well as the successful aspects and challenges associated with the interventions. RESULTS: The incremental cost effectiveness associated with the interventions was estimated as £92 and £591 per person achieving the target for the minimal and maximal interventions respectively. The qualitative evaluation gave insight into the process by which the results were achieved, and identified several barriers and facilitators that would need to be addressed before implementing the interventions in the wider community, in order to ensure their effective transfer. These included assessing the impact of the relationship between researchers and participants on the results, and the motivational importance of monitoring and assessing performance. CONCLUSIONS: The results suggest that pedometer based walking interventions may be considered cost-effective and suitable for implementation within the wider community. However, several research gaps remain, including the importance and impact of the researcher/participant relationship, the impact of assessment on motivation and effectiveness, and the longer term impact on physical and mental health, resource utilisation and quality of life.

What Did Time Tell Us? A Comparison and Retrospective Validation of Different Survival Extrapolation Methods for Immuno-Oncologic Therapy in Advanced or Metastatic Renal Cell Carcinoma.

BACKGROUND: The immuno-oncologic (IO) mechanism of action may lead to an overall survival (OS) hazard that changes over time, producing shapes that standard parametric extrapolation methods may struggle to reflect. Furthermore, selection of the most appropriate extrapolation method for health technology assessment is often based on trial data with limited follow-up. OBJECTIVE: To examine this problem, we fitted a range of extrapolation methods to patient-level survival data from CheckMate 025 (NCT01668784, CM-025), a phase III trial comparing nivolumab with everolimus for previously treated advanced renal cell carcinoma (aRCC), to assess their predictive accuracy over time. METHODS: Six extrapolation methods were examined: standard parametric models, natural cubic splines, piecewise models combining Kaplan-Meier data with an exponential or non-exponential distribution, response-based landmark models, and parametric mixture models. We produced three database locks (DBLs) at minimum follow-ups of 15, 27, and 39 months to align with previously published CM-025 data. A three-step evaluation process was adopted: (1) selection of the distribution family for each method in each of the three DBLs, (2) internal validation comparing extrapolation-based landmark and mean survival with the latest CM-025 dataset (minimum follow-up, 64 months), and (3) external validation of survival projections using clinical expert opinion and long-term follow-up data from other nivolumab studies in aRCC (CheckMate 003 and CheckMate 010). RESULTS: All extrapolation methods, with the exception of mixture models, underestimated landmark and mean OS for nivolumab compared with CM-025 long-term follow-up data. OS estimates for everolimus tended to be more accurate, with four of the six methods providing landmark OS estimates within the 95% confidence interval of observed OS as per the latest dataset. The predictive accuracy of survival extrapolation methods fitted to nivolumab also showed greater variation than for everolimus. The proportional hazards assumption held for all DBLs, and a dependent log-logistic model provided reliable estimates of longer-term survival for both nivolumab and everolimus across the DBLs. Although mixture models and response-based landmark models provided reasonable estimates of OS based on the 39-month DBL, this was not the case for the two earlier DBLs. The piecewise exponential models consistently underestimated OS for both nivolumab and everolimus at clinically meaningful pre-specified landmark time points. CONCLUSIONS: This aRCC case study identified marked differences in the predictive accuracy of survival extrapolation methods for nivolumab but less so for everolimus. The dependent log-logistic model did not suffer from overfitting to early DBLs to the same extent as more complex methods. Methods that provide more degrees of freedom may accurately represent survival for IO therapy, particularly if data are more mature or external data are available to inform the long-term extrapolations.