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Record W4388716571 · doi:10.3899/jrheum.2023-0947

More Evidence on the Validity of the Measurement Properties of PROMIS Computerized Adaptive Tests in Systemic Lupus Erythematosus

2023· editorial· en· W4388716571 on OpenAlexaffvenueabout
Zahi Touma, Ioannis Parodis, Vibeke Strand

Bibliographic record

VenueThe Journal of Rheumatology · 2023
Typeeditorial
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineRheumatologyQuality of life (healthcare)Computerized adaptive testingInternal medicineLupus erythematosusAdverse effectSystemic lupus erythematosusDiseasePhysical therapyImmunologyPsychometricsClinical psychologyNursing

Abstract

fetched live from OpenAlex

Systemic lupus erythematosus (SLE) significantly affects different aspects of patients’ health-related quality of life (HRQOL).1 In 1998, Outcome Measures in Rheumatology (OMERACT) proposed the first Core Domain Set (CDS) for SLE, which included disease activity, organ damage, adverse events, HRQOL, and economic costs.2 The SLE OMERACT working group (WG) was established in 2018 and includes 160 members representing over 25 countries in 5 continents. Currently the group is working on updating the CDS and will then proceed to evaluate the measurement properties of instruments specific for each domain to form the new OMERACT SLE Core Outcome Set.3 Both physician evaluation and patient perceptions of their health condition and well-being are important and complement each other for a holistic health assessment. Studies have shown a considerable discordance between physicians’ and patients’ assessments of health status and priorities. Whereas physician assessments of disease activity, damage, and adverse effects of therapies are based primarily on clinical and laboratory findings, patients’ assessment of their health can be ascertained with the use of different patient-reported outcomes (PROs). PROs can offer insight into a spectrum of domains such as fatigue, depressive symptoms, pain, and physical function among others. Different generic and disease-specific HRQOL questionnaires have been developed and validated for patients with SLE.1,4 Commonly used generic questionnaires include the 36-item Short-Form Health Survey (SF-36),5 a legacy instrument, as well as the EuroQol 5-Dimensional questionnaire (EQ-5D), both commonly used questionnaires in SLE randomized controlled trials (RCTs)4,6 and observational studies.7 SLE-specific instruments have also been used, albeit less commonly, in SLE RCTs and research studies and include the Lupus Quality of Life (LupusQoL),8 SLE-specific Quality of Life Questionnaire (SLE-QOL),9 SLE Quality of Life Questionnaire (L-QoL),10 LupusPRO, and Lupus Impact Tracker.11 PROs can also … Address correspondence to Dr. Z. Touma, Division of Rheumatology, Schroeder Arthritis Institute, Krembil Research Institute, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Lupus Program, EW 1-412, 399 Bathurst Street, Toronto, ON M5T 2S8, Canada. Email: Zahi.Touma{at}uhn.ca.

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)0.341
metaresearch head score (Gemma)0.583
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.659
Threshold uncertainty score0.813

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3410.583
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0050.011
Science and technology studies0.0020.009
Scholarly communication0.0080.008
Open science0.0040.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0130.002

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 head0.146
GPT teacher head0.319
Teacher spread0.173 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
GenreEditorial

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

Citations0
Published2023
Admission routes3
Has abstractyes

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