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152 The OMERACT-OARSI core domain set for measurement in clinical trials of hip and/or knee osteoarthritis

2019· article· en· W2938326659 on OpenAlexaboutno aff
Toby O. Smith, Philip G. Conaghan

Bibliographic record

VenueLara D. Veeken · 2019
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisCore (optical fiber)Physical therapyClinical trialInternal medicineAlternative medicinePathology

Abstract

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Background: It has been over 20 years since the OMERACT core outcome set (COS) to measure in clinical trials with people who have hip and/or knee osteoarthritis (OA) was presented. An OMERACT-OARSI Working Group was established to update this COS using contemporary OMERACT methodologies. Methods: A review of the COMET database of COS was undertaken to identify all domains reported in previous COS that included individuals with hip and/or knee OA. These were presented in a series of patient and public (PP) meetings involving 70 individuals across the UK, Australia and Canada to review the domain list and identify additional important domains. Based on these, a three-round international Delphi survey was undertaken recruiting patients, health professionals, researchers and industry representatives, to gain consensus on key domains which should be included in this core domain set. Using the Delphi results, an OMERACT ‘onion’ was formulated with the following rules: Mandatory (core) Domains (mandatory for all trials) was defined as domains reported as ‘critical’ to assess by over 70% of Delphi responses in the patient AND others stakeholder groups Important but Optional Domains (recommended by optional in trials) was defined as domains reported as ‘critical’ to assess by over 70% of Delphi responses in the patient OR others stakeholder groups Research Agenda inclusion was defined as areas which need further research with insufficient evidence supporting the Important but Optional Domain group placement The findings were discussed at OMERACT2018 and a consensus vote was obtained on the core domain set. Results: From the COMET review, four previous COS were identified including the 1997 OMERACT core outcome set. These were reviewed across the PP meetings to identify 50 potential domains which formed the Delphi survey. In total 424 (217 patients; 207 non-patients) contributed data to the Delphi exercise from 25 different countries. The OMERACT2018 delegates (129 participants) voted on those domains which met the criteria for inclusion. Domains in the Mandatory (core) Domain group, to be measured and reported in all hip and/or knee OA clinical trials, included: ‘pain’, ‘physical function’, ‘quality of life’ and ‘patient global assessment of the target joint’ in addition to the mandated core domain of ‘adverse events including mortality’. ‘Joint structure’ was agreed as mandatory in specific circumstances, stating the specific circumstances, i.e. depending on the intervention. Domains in the Important but Optional Domains group included: ‘participation’, ‘psychosocial impact’, ‘sleep’ and ‘costs’ Domains in the Research Agenda group included: ‘clinician global assessment of target joint’, ‘flare’, ‘inflammation’, ‘cognitive function’, ‘fatigue’ and ‘impact on family/caregivers’. Conclusion: The updated core domain set for hip and/or knee OA has been agreed. We will now determine which instruments should be recommended to measure each of the mandatory (core) domains based on OMERACT guidance. Disclosures: T. Smith: Grants/research support; TS is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre, Oxford. P.G. Conaghan: Consultancies; Abbvie, BMS, Flexion Therapeutics, GlaxoSmithKline, Kolon TissueGene, Medivird, Samumed, Roche, Pfizer, Novartis, Merck Serono. Grants/research support; PGC is supported, in part, by the NIHR Leeds Biomedical Research Centre.

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)0.258
metaresearch head score (Gemma)0.349
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.742
Threshold uncertainty score0.915

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2580.349
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0050.005
Science and technology studies0.0010.003
Scholarly communication0.0040.003
Open science0.0020.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.004

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 head0.140
GPT teacher head0.377
Teacher spread0.237 · 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 designNot applicable
DomainMethods
GenreMethods

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".

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Citations8
Published2019
Admission routes1
Has abstractyes

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