Evidence map›Paper›PMID 40095340›Full record

ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2025

Health state utilities associated with X-linked retinitis pigmentosa (XLRP).

Louis S Matza, Nan Li, Katie D Stewart, Mahmoud Hashim, Tom Denee, Feng Pan, Qiaoyi Zhang, Jennifer Lee, Michel Michaelides, Hendrik P N Scholl

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Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Louis S MatzaEvidera, 929 North Front Street, Wilmington, NC, 28401-3331, USA. louis.matza@thermofisher.com.ORCID http://orcid.org/0000-0001-6374-5948
Nan LiJanssen Pharmaceutical K.K, Tokyo, Japan.
Katie D StewartEvidera, 929 North Front Street, Wilmington, NC, 28401-3331, USA.
Mahmoud HashimJanssen Global Services, LLC, Beerse, Belgium.
Tom DeneeJanssen Europe, Middle East and Africa, Breda, The Netherlands.
Feng PanJanssen Global Services, LLC, Raritan, NJ, USA.
Qiaoyi ZhangJanssen Global Services, LLC, Raritan, NJ, USA.
Jennifer LeeJanssen Europe, Middle East and Africa, Copenhagen, Denmark.
Michel MichaelidesUCL Institute of Ophthalmology and Moorfields Eye Hospital, London, UK.
Hendrik P N SchollDepartment of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.

Funding

Janssen Pharmaceuticals Janssen Pharmaceuticals
6 · The paper itself

Abstract

backgroundX-linked retinitis pigmentosa (XLRP) is a rare, inherited retinal disease characterized by impairment in visual field and visual acuity with continuous progression leading to blindness. Gene therapies for XLRP are under investigation, and health state utilities are needed for use in cost-utility analyses examining the value of these treatments.

objectiveThis study aimed to estimate utilities associated with XLRP severity.

methodsEleven health state vignettes depicting combinations of impairment in visual field and visual acuity associated with XLRP were developed based on literature review and input from clinicians, patients, and a caregiver. Vignettes included text describing visual acuity impairment, visual field impairment, night blindness, impact on quality of life, and two images representing the combination of visual field and visual acuity impairment for each health state. Health states were valued in time trade-off interviews with general population respondents in the UK.

resultsA total of 245 participants completed interviews (51.0% female; mean age = 41.4 years; Newcastle, n = 80; London, n = 85; Edinburgh, n = 80). In a ranking task, participants preferred health states with less severe visual impairment, and this preference was reflected in the utilities. Mean (standard deviation) utilities ranged from 0.900 (0.121) for the health state with no visual acuity impairment and mild visual field impairment to 0.271 (0.478) for the health state describing blindness.

conclusionResults highlight the substantial impact of visual impairment on health state preference and quality of life. The health state utilities estimated in this study may be appropriate for use in cost-effectiveness models evaluating treatments for XLRP. JEL CLASSIFICATION CODES: I1; I12; I19.

Indexed as

Health StatusQuality of LifeRetinitis PigmentosaAdultAgedCost-Benefit AnalysisFemaleGenetic Diseases, X-LinkedHumansMaleMiddle AgedQuality-Adjusted Life YearsSeverity of Illness IndexUnited KingdomVisual AcuityVisual FieldsHealth state utilityRare diseaseTime trade-offVisual impairmentX-linked retinitis pigmentosaXLRP

Identifiers

PMID40095340
PMCPMC12431885

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.