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Record W4411884051 · doi:10.3899/jrheum.2025-0314.109

Updating the OMERACT Systemic Lupus Erythematosus Core Outcome Set

2025· article· en· W4411884051 on OpenAlexaffvenueabout
Wils Nielsen, Vibeke Strand, Lee S. Simon, Ioannis Parodis, Alfred H.J. Kim, Karina D. Torralba, Maya Desai, Yvonne Enman, Zahi Touma

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsToronto Western HospitalOntario College of Art and DesignUniversity Health Network
Fundersnot available
KeywordsMedicineSystematic reviewFocus groupSystemic lupus erythematosusSet (abstract data type)MEDLINEFamily medicineInternal medicineDiseaseComputer science

Abstract

fetched live from OpenAlex

Objectives 1. Generate a list of preliminary Systemic Lupus Erythematosus (SLE) domains in consideration for the SLE Core Outcome Set (COS). 2. Winnow and bin the preliminary domains into a final list of candidate domains with agreed upon definitions. Methods 1. Preliminary Domain Generation a) In order to review the continued importance of known SLE domains and generate novel candidate domains, a survey assessing the importance of known SLE domains and asking respondents to recommend additional domains was conducted. The survey was administered to 100 patients from the University of Toronto Lupus Clinic and 175 members of the Outcome Measures in Rheumatology (OMERACT) SLE Working Group. b) To identify preliminary domains from the literature, a scoping literature review of SLE clinical trials and systematic reviews since 2010 was conducted extracting domains, definitions, and methods of assessment (measurement tools). c) Domains important to patients living with SLE were identified through focus groups held with 36 SLE patients representing 5 continents. Patients were asked a wide variety of questions to identify all manners of domains and transcripts from interviews were thematically coded. 2. Candidate Domain Sorting a) The OMERACT SLE Advisory Group met regularly to winnow and bin the preliminary SLE domains. b) Definitions for the candidate domains were retrieved from the scoping literature review and from additional literature searches. Definitions were reviewed, modified, and agreed upon by the OEMRACT SLE Advisory Group. Results The domain survey, the scoping literature, and the focus groups generated many preliminary domains which was winnowed and binned into 25 candidate: Adverse Events, Anxiety, Cognition Impact, Cognitive Function, Depression, Economic Cost Impact, Emotional Health, Fatigue, Flares, Frailty, Health-Related Quality of Life, Pain Intensity, Pain Interference, Participation, Patient Global Assessment of Disease Activity, Physical Function, Physician Global Assessment of Disease Activity, Reproductive Health, Sexuality, SLE Disease Activity, Sleep, Stress, Tissue/Organ Damage, Treatment Satisfaction, and Use of Glucocorticoids Including Tapering. Definitions for the 25 candidate domains have been agreed upon (Table 1). Conclusion The domain generation stage of updating the SLE COS is complete. The next stage involves achieving consensus on the core domains to form the SLE COS through a 4-round Delphi consensus exercise with international collaborators (patients, clinicians, researchers, pharmaceutical representatives, and more) beginning in January 2025. Following the establishment of the core domains will be measurement instrument selection where candidate instruments will be identified and appraised for each core domains, yielding the final SLE COS.

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)0.097
metaresearch head score (Gemma)0.169
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.510

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0970.169
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0100.006
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.056
GPT teacher head0.363
Teacher spread0.308 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes3
Has abstractyes

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