IMPACT OF THE 2026 UK EQ-5D-5L VALUE SET ON UTILITY ESTIMATES IN LUPUS RASH AND CUTANEOUS LUPUS ERYTHEMATOSUS
Author(s)
Timon Schicht, MSc1, Ying Sun, MSc1, Namita Tundia, Ph.D2, Yulia Dyachkova, MSc3, Alain H. Cornet, Executive Master4, Annemarie Sluijmers, EUPATI Fellow (Cohort 5)4, Fukumi Furukawa, MD, Ph.D5, Victoria P. Werth, MD6, Dominik Samotij, MD, Ph.D7, Adam Reich, MD, Ph.D7.
1Merck Healthcare KGaA, Darmstadt, Germany, 2EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA, Darmstadt, Germany, 3Merck Gesellschaft mbH, Vienna, Austria, an affiliate of Merck KGaA, Darmstadt, Germany, 4Lupus Europe, Brussels, Belgium, 5Department of Dermatology, Wakayama Medical University, Wakayama, Japan, 6Department of Dermatology, University of Pennsylvania and Philadelphia V.A. Hospital, Philadelphia, PA, USA, 7Department of Dermatology, University of Rzeszów, Rzeszów, Poland.
1Merck Healthcare KGaA, Darmstadt, Germany, 2EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA, Darmstadt, Germany, 3Merck Gesellschaft mbH, Vienna, Austria, an affiliate of Merck KGaA, Darmstadt, Germany, 4Lupus Europe, Brussels, Belgium, 5Department of Dermatology, Wakayama Medical University, Wakayama, Japan, 6Department of Dermatology, University of Pennsylvania and Philadelphia V.A. Hospital, Philadelphia, PA, USA, 7Department of Dermatology, University of Rzeszów, Rzeszów, Poland.
OBJECTIVES: To compare health utility values derived from the 2026 UK EQ-5D-5L value set (UK5L) with those generated using the 3L value set (DSU/EEPRU mapping and vH crosswalk), and to evaluate implications for health technology assessments (HTAs) of treatments in patients with active cutaneous manifestations of lupus with or without systemic disease (lupus rash).
METHODS: EQ-5D-5L data were analysed from two real-world datasets of adults: a clinician-confirmed lupus rash cohort without systemic disease (cohort A) from Europe and Asia (n=137) and the Living with Lupus survey of lupus rash respondents (cohort B) across Europe (n=2,816). For cohort B, only EQ-5D-5L-equivalent questions were available. Utilities were estimated using three UK-relevant approaches: UK5L, DSU/EEPRU mapping (DSU), and van Hout crosswalk (vH). Methods were compared using descriptive statistics, paired mean differences with bootstrap 95% CIs, Bland-Altman analyses, and two-way mixed-effects intraclass correlation coefficients (ICC) for absolute agreement.
RESULTS: In the cohort A, mean utility was 0.874 (UK5L), 0.808 (DSU), and 0.812 (vH). Paired mean differences were 0.066 (95% CI 0.056-0.077; UK5L vs DSU), 0.061 (0.050-0.074; UK5L vs vH), and 0.005 (-0.005-0.013; vH vs DSU). In cohort B, mean utility was 0.475 (UK5L), 0.393 (DSU), and 0.410 (vH). Paired mean differences were 0.081 (95% CI 0.078-0.085; UK5L vs DSU), 0.065 (0.062-0.068; UK5L vs vH), and 0.016 (0.014-0.019; vH vs DSU). Bland-Altmann analyses showed larger differences between UK5L and DSU/vH at higher utility levels, whereas DSU vs vH disagreement was utility independent. ICCs exceeded 0.93 across all comparisons.
CONCLUSIONS: In both cohorts, the 2026 UK EQ-5D-5L value set yielded systematically and meaningfully higher utility estimates than both 3L value set methods, potentially altering the perceived disease burden of lupus rash. It further may reduce incremental utility gains, lower incremental quality-adjusted-life-years, and worsen incremental cost-effectiveness ratios of future lupus rash interventions in HTAs. vH and DSU appeared largely interchangeable.
METHODS: EQ-5D-5L data were analysed from two real-world datasets of adults: a clinician-confirmed lupus rash cohort without systemic disease (cohort A) from Europe and Asia (n=137) and the Living with Lupus survey of lupus rash respondents (cohort B) across Europe (n=2,816). For cohort B, only EQ-5D-5L-equivalent questions were available. Utilities were estimated using three UK-relevant approaches: UK5L, DSU/EEPRU mapping (DSU), and van Hout crosswalk (vH). Methods were compared using descriptive statistics, paired mean differences with bootstrap 95% CIs, Bland-Altman analyses, and two-way mixed-effects intraclass correlation coefficients (ICC) for absolute agreement.
RESULTS: In the cohort A, mean utility was 0.874 (UK5L), 0.808 (DSU), and 0.812 (vH). Paired mean differences were 0.066 (95% CI 0.056-0.077; UK5L vs DSU), 0.061 (0.050-0.074; UK5L vs vH), and 0.005 (-0.005-0.013; vH vs DSU). In cohort B, mean utility was 0.475 (UK5L), 0.393 (DSU), and 0.410 (vH). Paired mean differences were 0.081 (95% CI 0.078-0.085; UK5L vs DSU), 0.065 (0.062-0.068; UK5L vs vH), and 0.016 (0.014-0.019; vH vs DSU). Bland-Altmann analyses showed larger differences between UK5L and DSU/vH at higher utility levels, whereas DSU vs vH disagreement was utility independent. ICCs exceeded 0.93 across all comparisons.
CONCLUSIONS: In both cohorts, the 2026 UK EQ-5D-5L value set yielded systematically and meaningfully higher utility estimates than both 3L value set methods, potentially altering the perceived disease burden of lupus rash. It further may reduce incremental utility gains, lower incremental quality-adjusted-life-years, and worsen incremental cost-effectiveness ratios of future lupus rash interventions in HTAs. vH and DSU appeared largely interchangeable.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
HTA286
Topic
Health Technology Assessment, Patient-Centered Research
Topic Subcategory
Decision & Deliberative Processes
Disease
Systemic Disorders/Conditions (Anesthesia, Auto-Immune Disorders (n.e.c.), Hematological Disorders (non-oncologic), Pain)