Estimating the minimally important difference for the EQ-5D-5L and EORTC QLQ-C30 in cancer.

BACKGROUND: The minimal important difference (MID) is a useful tool to interpret changes in patients' health-related quality of life. This study aims to estimate MIDs for interpreting within-patient change for both components of the EQ-5D-5L questionnaire [EQ-Visual Analogue Scale (EQ-VAS) and utility index] and domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) for cancer patients. METHODS: Data were obtained from the Cancer 2015 dataset, a longitudinal cohort of Australian cancer patients. Anchor-based approaches were used to estimate MIDs for the EQ-5D-5L index-based utility index [Australia and the United States (US) tariff sets], EQ-VAS scores, and the EORTC QLQ-C30. Clinical [Eastern Cooperative Oncology Group (ECOG) performance status] and patient-reported (items 29 and 30 of the EORTC QLQ-C30 and the EQ-VAS) anchors were assessed for appropriateness by their correlation strength. Clinical change groups (CCGs) were defined a priori for improvement and deterioration based on estimates used in previous literature. MIDs were estimated via linear regression and distribution-based methods. RESULTS: For the index-based utility scores in Australia, the anchor-defined MID estimates were 0.01 to 0.06 for improvement and - 0.04 to -0.03 for deterioration, with a weighted value of 0.03 for improvement and deterioration. The EQ-VAS MID estimate was 5 points for both improvement and deterioration. For the EORTC QLQ-C30, changes of at least 3.64 (improvement) and - 4.28 (deterioration) units on the physical functioning scale, 6.31 (improvement) and - 7.11 (deterioration) units on the role functioning scale, 4.65 (improvement) and - 3.41 (deterioration) units on the emotional functioning scale, and 5.41 (improvement) and - 5.56 (deterioration) units on the social functioning scale were estimated to be meaningful. CONCLUSION: This study identified lower MIDs for the EQ-5D-5L utility index, EQ-VAS, and EORTC QLQ-C30 domain scores, than those reported previously. The use of a real-world cancer-specific panel dataset may reflect smaller MID estimates that are more applicable to cancer patients in the clinical practice, rather than using MIDs that have been estimated from clinical trials.

Economic Assessment in Resource-Constrained Systems: Individual-Level Simulation Model in Wet Age-Related Macular Degeneration and Diabetic Macular Oedema.

INTRODUCTION: Cost-effectiveness analyses typically ignore healthcare system resource constraints. Ophthalmology is affected by resource constraints because of increasing disease prevalence and the use of resource-intensive treatments. This study evaluated the impact of resource constraints on the cost-effectiveness of faricimab 6 mg, compared with aflibercept 2 mg and ranibizumab biosimilar 0.5 mg, for treating wet age-related macular degeneration (wAMD) or diabetic macular oedema (DMO) over a 5-year horizon. METHODS: A microsimulation model estimated the impact of resource constraints on patients visits, delays, costs and quality-adjusted life-year (QALY) losses due to treatment delays at a typical UK National Health Service eye hospital treating 1500 patients with wAMD and 500 patients with DMO. Patient characteristics, treatment regimens and treatment intervals were informed using published literature and expert opinion. Resource constraint was represented by limiting the number of available intravitreal injection appointments per week, with growing demand caused by rising disease prevalence. The model compared outcomes across three scenarios; each scenario involved treating all patients with one of the three treatments. RESULTS: Over 5 years, in a resource-constrained hospital, compared with aflibercept, faricimab use resulted in the avoidance of 12,596 delays, saved GBP/£15,108,609 in cost and avoided the loss of 60.06 QALYs. Compared with ranibizumab biosimilar, faricimab use resulted in the avoidance of 18,910 delays, incurred £2,069,088 extra cost and avoided the loss of 105.70 QALYs, resulting in an incremental cost-effectiveness ratio of £19,574/QALY. CONCLUSIONS: Accounting for resource constraints in health economic evaluation is crucial. Emerging therapies that are more durable and require less frequent clinic visits can reduce treatment delays, leading to improved QALY outcomes and reduced burden on healthcare systems. Faricimab reduced the number of delayed injections, leading to improved QALY outcomes for patients in a healthcare system with resource constraints. Faricimab is cost-saving when compared with aflibercept and cost-effective when compared with ranibizumab biosimilar.

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

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.