Economic Evaluation Of New Treatments Research Articles

Economic burden and health-related quality of life in patients with epidermolysis bullosa in Spain

Background. Epidermolysis bullosa (EB) is a rare genetic skin disorder characterized by fragility of skin with appearance of acute and chronic wounds. The aim of this study was to determine the economic burden and the health-related quality of life (HRQoL) of patients with epidermolysis bullosa (EB) in Spain from a societal perspective.Methods. We conducted a cross-sectional, retrospective study including 62 patients with EB (62% dystrophic, 9.6% junctional, 3.2% Kindler syndrome, and 26% with simplex EB). Data were collected from questionnaires completed by patients or their caregivers. The costs were estimated, including not only direct healthcare costs but also direct non-healthcare costs and productivity losses. We compared severe EB (Dystrophic, Junctional EB and Kindler syndrome) to non-severe EB (simplex EB) using as reference year 2022. HRQoL was measured by generic (EQ-5D) and specific (QoLEB) questionnaires.ResultsThe average annual cost for an EB patient was €31,352. Direct healthcare costs represented 17.2% of the total cost, direct non-healthcare costs (mainly informal care costs) 71.3% and productivity losses 11.5% of the total cost. Participants in the severe EB group had a slightly higher average cost than participants in the non-severe EB group (€31,706 vs. €30,337). Direct healthcare costs and non-healthcare costs were higher in the severe EB group (€6,205 vs. €3,024 and €23,148 vs. €20,113) while productivity losses were higher in the non-severe EB group (€7,200 vs. €2,353). The mean utility index score, where the maximum value possible is one, was 0.45 for patients with severe EB (0.76 for their caregivers) and 0.62 for those with non-severe EB (0.77 for their caregivers).Conclusions. The social economic burden of EB, resulting from the high direct non-healthcare cost of informal care, and from the loss of productivity, accentuates the importance of not restricting cost analysis to direct healthcare costs. This substantiates that EB, particularly severe EB represents a significant hidden cost that should be revealed to society and should be considered in the support programmes for people who suffer from this disease, and in the economic evaluation of new treatments.

Key considerations for modelling the long-term costs and benefits of treatments for ANCA-associated vasculitis.

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of severe and chronic autoimmune diseases. Patients undergo two treatment phases: inducing remission and maintaining remission to prevent organ damage. Immunosuppressants, including glucocorticoids (GCs) are used as first-line treatment, but long-term GC use is associated with toxic effects. Novel treatments reduce or replace the need for long-term GC, and therefore can reduce GC-related toxicity. The evolving treatment landscape has presented new challenges for health technology assessment (HTA) of new treatments in AAV and long-term modelling of costs and outcomes in this disease. Using the appraisal of avacopan in England (NICE) as a case study, this paper aims to identify the key challenges involved in the economic evaluation of new treatments for AAV, with a particular focus on the long-term modelling of the treatment costs and benefits for the purpose of HTA. The outcome of this study is a set of recommendations for modelling the cost-effectiveness of new treatments for AAV from the HTA perspective. The discussion focuses on the appropriate model structure, approach to modelling end-stage renal disease (ESRD) as a key determinant of costeffectiveness, capturing the impact of GC-related adverse events, and estimation of short and long-term costs of AAV. Economic evaluation of new treatments for AAV needs to capture all relevant downstream effects. ESRD is a key driver of cost-effectiveness but is associated with major uncertainty. Future observational studies need to offer sufficient detail to allow for differentiation in event rates across treatment options.

Developing a Natural History Model for Duchenne Muscular Dystrophy.

The aim of this study was to pool multiple data sets to build a patient-centric, data-informed, natural history model (NHM) for Duchenne muscular dystrophy (DMD) to estimate disease trajectory across patient lifetime under current standard of care in future economic evaluations. The study was conducted as part of Project HERCULES, a multi-stakeholder collaboration to develop tools to support health technology assessments of new treatments for DMD. Health states were informed by a review of NHMs for DMD and input from clinicians, patients and caregivers, and defined using common outcomes in clinical trials and real-world practice. The primary source informing the NHM was the Critical Path Institute Duchenne Regulatory Science Consortium (D-RSC) database. This was supplemented with expert input obtained via an elicitation exercise, and a systematic literature review and meta-analysis of mortality data. The NHM includes ambulatory, transfer and non-ambulatory phases, which capture loss of ambulation, ability to weight bear and upper body and respiratory function, respectively. The NHM estimates patients spend approximately 9.5years in ambulatory states, 1.5 years in the transfer state and the remainder of their lives in non-ambulatory states. Median predicted survival is 34.8 years (95% CI 34.1-35.8). The model includes a detailed disease pathway for DMD, including the clinically and economically important transfer state. The NHM may be used to estimate the current trajectory of DMD in economic evaluations of new treatments, facilitating inclusion of a lifetime time horizon, and will help identify areas for further research.

PP391 Economic Analysis Of Treatment For Spinal Muscular Atrophy: A Scoping Review

IntroductionSpinal muscular atrophy (SMA) is a rare, life-threatening, and seriously debilitating neuromuscular disorder, which has a heavy burden on patients, caregivers and the health system. Technological advances have improved clinical effect, but have also increased the financial burden. There is limited information in the literature on the resource utilization and economic burden of SMA. Our research aims to summarize the current literature on resource use, cost and economic evaluations of treatments for SMA, to inform further research and policy decision making.MethodsDatabases, including PubMed, Embase, Cochrane Library and CRD Database, were searched from inception. Two reviewers undertook title and abstract screening followed by full-text screening, and any disagreement was resolved in consensus. Data extraction was conducted using a customized form. Included studies were summarized using narrative synthesis structured around general and economic characteristics. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were adhered to where applicable.ResultsWe reviewed 552 abstracts and included twenty-six from 2015 to 2019. Four-fifths were published in the United States and Europe. Five full economic evaluations and one budget impact analysis compared nusinersen with AVXS-101 or best supportive care, and the remaining evaluated the economic burden of SMA. The most common outcomes were healthcare resource utilization and direct medical costs, only a few studies evaluated direct non-medical costs or indirect cost.ConclusionsSMA patients have significant medical expenditures and high utilization of healthcare services, including nusinersen-treated patients. The results highlight the substantial burden of treatment for SMA, not only for patients but also for their caregivers. SMA represents a significant hidden cost that society should be made aware of, and that should be considered in the design, implementation and evaluation of support programs for people who suffer from this disease and their families, as well as in the economic evaluation of new treatments.

Mapping the EORTC QLQ-C30 and QLQ-H&N35 to the EQ-5D for head and neck cancer: Can disease-specific utilities be obtained?

IntroductionInnovations in head and neck cancer (HNC) treatment are often subject to economic evaluation prior to their reimbursement and subsequent access for patients. Mapping functions facilitate economic evaluation of new treatments when the required utility data is absent, but quality of life data is available. The objective of this study is to develop a mapping function translating the EORTC QLQ-C30 to EQ-5D-derived utilities for HNC through regression modeling, and to explore the added value of disease-specific EORTC QLQ-H&N35 scales to the model.MethodsData was obtained on patients with primary HNC treated with curative intent derived from two hospitals. Model development was conducted in two phases: 1. Predictor selection based on theory- and data-driven methods, resulting in three sets of potential predictors from the quality of life questionnaires; 2. Selection of the best out of four methods: ordinary-least squares, mixed-effects linear, Cox and beta regression, using the first set of predictors from EORTC QLQ-C30 scales with most correspondence to EQ-5D dimensions. Using a stepwise approach, we assessed added values of predictors in the other two sets. Model fit was assessed using Akaike and Bayesian Information Criterion (AIC and BIC) and model performance was evaluated by MAE, RMSE and limits of agreement (LOA).ResultsThe beta regression model showed best model fit, with global health status, physical-, role- and emotional functioning and pain scales as predictors. Adding HNC-specific scales did not improve the model. Model performance was reasonable; R2 = 0.39, MAE = 0.0949, RMSE = 0.1209, 95% LOA of -0.243 to 0.231 (bias -0.01), with an error correlation of 0.32. The estimated shrinkage factor was 0.90.ConclusionsSelected scales from the EORTC QLQ-C30 can be used to estimate utilities for HNC using beta regression. Including EORTC QLQ-H&N35 scales does not improve the mapping function. The mapping model may serve as a tool to enable cost-effectiveness analyses of innovative HNC treatments, for example for reimbursement issues. Further research should assess the robustness and generalizability of the function by validating the model in an external cohort of HNC patients.

A systematic review and meta-analysis of utility estimates in melanoma.

Health-related quality of life (HRQOL) in melanoma is affected by cancer stage. Previous studies have reported limited data on utility-based HRQOL. To determine pooled estimates of utility-based HRQOL (utilities) for people with American Joint Cancer Committee stage I/II, III or IV melanoma for use in economic evaluations. We performed a systematic review, meta-analysis and metaregression of utilities for patients with melanoma. HRQOL scores reported with the QLQ-C30, SF-36, SF-12, FACT-G and FACT-M instruments were converted to utilities using published mapping algorithms. Meta-analysis was used to calculate mean utilities. Metaregression was used to examine the effects of baseline patient and study characteristics. We identified 33 studies reporting 213 utilities. From meta-analyses, the mean utility for stage I/II melanoma was 0·97 [95% confidence interval (CI) 0·90-0·98]; for stage III melanoma it was 0·77 (95% CI 0·70-0·83); for stage III/IV 0·76 (95% CI 0·76-0·77); and for stage IV melanoma 0·76 (95% CI 0·71-0·81). The difference in utility between stage III and stage IV was not statistically significant (P=0·52). For patients with stage I/II, the utility estimate at the time of surgery was 0·77 (95% CI 0·75-0·79), and at 3-12months postsurgery it was 0·85 (95% CI 0·84-0·86). Utility estimates for patients with stage IV melanoma were 0·65 (95% CI 0·62-0·69) during the first 3months of treatment and 0·83 (95% CI 0·81-0·86) at 4-12months on treatment. For patients with stage IV melanoma treated with chemotherapy, the utility estimate was 0·52 (95% CI 0·51-0·52), while for those treated with targeted therapy it was 0·83 (95% CI 0·82-0·85). These robust, evidence-based estimates of health state utility can be used in economic evaluations of new treatments for patients with early-stage or advanced-stage melanoma.

Use of Intermediate Endpoints in the Economic Evaluation of New Treatments for Advanced Cancer and Methods Adopted When Suitable Overall Survival Data are Not Available.

This study assessed the use of intermediate endpoints in the economic evaluation of new treatments for advanced cancer and the methodological approaches adopted when overall survival (OS) data are unavailable or of limited use. A systematic literature review was conducted to identify economic evaluations of treatments for advanced cancer published between 2003 and 2013. Cost-effectiveness and cost-utility analyses expressed in cost per life-year gained and cost per quality-adjusted life-year using an intermediate endpoint as an outcome measure were eligible. Characteristics of selected studies were extracted and comprised population, treatment of interest, comparator, line of treatment, study perspective, and time horizon. Use of intermediate endpoints and methods adopted when OS data were lacking were analyzed. In total, 7219 studies were identified and 100 fulfilled the eligibility criteria. Intermediate endpoints mostly used were progression-free survival and time to progression, accounting for 92% of included studies. OS data were unavailable for analysis in nearly 25% of economic evaluations. In the absence of OS data, studies most commonly assumed an equal risk of death for all treatment groups. Other methods included use of indirect comparison based on numerous assumptions, use of a proxy for OS, consultation with clinical experts, and use of published external information from different treatment settings. Intermediate endpoints are widely used in the economic evaluation of new treatments for advanced cancer in order to estimate OS. Currently, different methods are used in the absence of suitable OS data and the choice of an appropriate method depends on many factors including the data availability.

A Systematic Review of the Economic and Humanistic Burden of Gout.

Gout is a chronic and inflammatory form of arthritis that is often overlooked despite the associated pain caused by acute flares and associated joint damage caused by the development of debilitating tophi. The increasing burden of gout, due to an aging population and the increased prevalence of known risk factors for hyperuricaemia, means that there is a continued need for new and effective urate-lowering treatments. The evaluation of these treatments will require a comprehensive and comparative evidence base describing the economic and humanistic burden of gout, taken from the perspective of patients, the healthcare system, and wider society. The objective of this study is to review and summarise the current evidence of the disease burden related to chronic gout, assessed in terms of both cost and health-related quality of life (HRQL), and to identify key factors correlated with an increased burden. The overall aim is to support the economic evaluation of new treatments for gout, and to highlight key data gaps that may need further study and exploration. Relevant literature dating from January 2000 to July 2014 was sourced through searches of the MEDLINE database via PubMed and The Cochrane Library. Articles published in English and reporting either the economic burden (cost) or the humanistic burden (HRQL/utility) of gout were identified, and key data were extracted and summarised, with key themes and data gaps identified and discussed. Of the 323 studies identified, 39 met the inclusion criteria, of which 17 and 26 were relevant to the economic and humanistic burden, respectively. The economic burden of gout varied according to numerous factors, most notably serum urate acid levels and number of flares and tophi, resulting in higher healthcare resource use most often attributed to hospitalisation and inpatient stay. The incremental direct cost of gout has been suggested in the range of US$3165 to US$5515 (2004 and 2005 values, respectively) climbing to US$10,222 to US$21,467 (2008 values) per annum where patients are experiencing regular acute flares and have tophi present. The humanistic burden of gout was largely due to physical disability and pain resulting from chronic clinical manifestations. Short Form 6 dimensions (SF-6D) assessed utility weights are estimated at 0.53 for a patient with severe gout (≥3 flares/year and tophi) compared with 0.73 for an asymptomatic gout patient with serum acid levels<6mg/dl. The evidence confirms that gout has a growing overall prevalence and represents a significant burden in terms of both direct healthcare cost and HRQL outcomes. In light of this, effective urate-lowering treatments are likely to be valued if they can be clearly demonstrated to be both clinically effective and cost effective. Published data to support healthcare decision making in non-US countries with regards to treatments for gout are currently limited, which is a key limitation of the current evidence base. More research is also required to extend our understanding of the impact of gout on indirect costs, and a need also exists to develop a more comprehensive set of comparative HRQL utility assessments.

Disease progression and costs of care in Alzheimer’s disease patients treated with donepezil: a longitudinal naturalistic cohort

Improved data and methods are needed for modeling disease progression in Alzheimer's disease (AD) for economic evaluation of treatments. The aim is to estimate prediction models for long-term AD progression and subsequently economic outcomes. Three-year follow-up data on 435 patients treated with the cholinesterase inhibitor donepezil in clinical practise were analyzed. Regression models were estimated for long-term prediction of decline in cognitive function (ADAS-cog) and activities in daily living (ADL) ability, risk of institutionalization and costs of care. The cognitive deterioration was estimated at between 1.6 and 4 ADAS-cog points per every 6months, increasing with disease severity. Cognitive function was an important predictor of ADL-ability, which itself was the most important predictor of the risk of institutionalization and costs of care. Combining all models in a cross-validation process generated accurate predictions of costs of care at each 6months follow-up. The proposed methods for representing AD progression and economic outcomes can be used in micro-simulation models for the economic evaluation of new treatments.

Predictors of costs of care in Alzheimer’s disease: A multinational sample of 1222 patients

Background The costs of care for patients with Alzheimer’s disease are correlated with key measures of disease severity. This relationship is important in the economic evaluation of new treatments and is used to translate treatment efficacy into effects on costs through economic modeling. We aimed to identify what measures of disease severity are the most important predictors of societal costs of care and whether their relationship differs across countries. Methods Interviews were conducted with 1222 patient and caregiver pairs residing in the community or in residential care settings in Spain, Sweden, United Kingdom, and the United States. Assessments included costs of care (Resource Utilization in Dementia) and key disease severity measures: cognitive function (Mini-Mental State Examination), ability to perform Activities of Daily Living (ADL-ability, Disability Assessment for Dementia [DAD]), and behavioral symptoms (Neuropsychiatry Inventory (NPI)-severity). Results ADL-ability was the most important predictor of societal costs of care of community-dwelling patients in all countries. A one-point decrease in DAD resulted in a 1.4% increase in costs of care in Spain, United Kingdom, and the United States on average, and a 2% increase in Sweden. This translated into a 45% increase from a standard deviation decrease in DAD on average. NPI-severity and Mini-Mental State Examination were also significant predictors but with lesser effect. Although mean costs of care differed across countries, the important predictors were the same. Conclusion ADL-ability is the most important predictor of societal costs of care in community dwellings irrespective of country and should therefore be central in the economic evaluation of Alzheimer's disease therapies.

Cost-of-Illness Studies

Cost-of-illness studies measure the overall economic impact of a disease on society. Such studies are important in setting public health priorities and for economic evaluation of new treatments. These studies should take the societal perspective and include both direct and indirect costs. Often indirect costs exceed direct costs. Comparison of cost-of-illness studies from different countries is difficult because of differences in population, currency, the way health care is provided, and other social and political factors.

Cost-of-Illness Studies

Cost-of-illness studies measure the overall economic impact of a disease on society. Such studies are important in setting public health priorities and for economic evaluation of new treatments. These studies should take the societal perspective and include both direct and indirect costs. Often indirect costs exceed direct costs. Comparison of cost-of-illness studies from different countries is difficult because of differences in population, currency, the way health care is provided, and other social and political factors.

Economic evaluation of new treatments: Haematopoietic growth factors

The clinical benefits of new healthcare interventions usually receive considerable attention, but their impact on the economic aspects of care provision are not so well considered. Among the issues that different audiences will want to see addressed are: how clinical benefits translate into resource use savings in practice; the extent to which clinical trial outcomes can be said to be representative or normal practice and the value of the economic impact to purchasers and providers. In this review we consider these elements using the haematopoietic growth factors as an example.