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Record W2599328871 · doi:10.3899/jrheum.161112

OMERACT Quality-adjusted Life-years (QALY) Working Group: Do Current QALY Measures Capture What Matters to Patients?

2017· article· en· W2599328871 on OpenAlexaffvenue
Logan Trenaman, Annelies Boonen, Françis Guillemin, Mickaël Hiligsmann, Alison M. Hoens, Carlo A. Marra, W. S. Taylor, Jennifer L. Barton, Peter Tugwell, George A. Wells, Nick Bansback

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsWilfrid Laurier UniversityUniversity of OttawaArthritis Research Centre of CanadaUniversity of British Columbia, Okanagan CampusMemorial University of NewfoundlandOkanagan University CollegeUniversity of British Columbia
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsPromMedicineAnkylosing spondylitisRheumatologyQuality of life (healthcare)Physical therapyInternal medicineTest (biology)Family medicineQuality-adjusted life yearPediatricsCost effectivenessRisk analysis (engineering)

Abstract

fetched live from OpenAlex

OBJECTIVE: To understand the limitations with current patient-reported outcome measures (PROM) used to generate quality-adjusted life-years (QALY) in rheumatology, and set a research agenda. METHODS: Two activities were undertaken. The first was a scoping review of published studies that have used PROM to generate QALY in rheumatology between 2011 and 2016. The second was an interactive "eyeball test" exercise at Outcome Measures in Rheumatology 13 that compared subdomains of widely used generic PROM, as identified through the scoping review, to subdomains of the Assessment of SpondyloArthritis Health Index (ASAS-HI) condition-specific PROM for ankylosing spondylitis. RESULTS: The scoping review included 39 studies. Five different PROM have been used to generate QALY in rheumatology; however, the EQ-5D and Short Form 6 Dimensions (SF-6D) were used most frequently (in 32 and 9 of included studies, respectively). Special interest group participants identified energy/drive and sleep as 2 key subdomains of the ASAS-HI instrument that may be missed by the EQ-5D, and sexual function as potentially missed by the SF-6D. Participants also expressed concerns that aspects of the process of care and non-health outcomes may be missed. Three ways of incorporating additional subdomains were discussed, including using an alternative generic PROM, modifying an existing generic PROM with "bolt-on" subdomain(s), and generating societal weights for a condition-specific PROM. CONCLUSION: Three priorities for future research were identified: understanding whether the EQ-5D and SF-6D identify what matters to patients with different rheumatic conditions, analyzing how much patients value process or non-health outcomes, and identifying which approaches to incorporating a greater number of subdomains into the QALY are being undertaken in other disease areas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.072
metaresearch head score (Gemma)0.160
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0720.160
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0030.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.318
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2017
Admission routes2
Has abstractyes

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