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Record W4307128057 · doi:10.1002/art.42347

American College of Rheumatology/<scp>EULAR</scp> Remission Criteria for Rheumatoid Arthritis: 2022 Revision

2022· article· en· W4307128057 on OpenAlexaff
Paul Studenic, Daniel Aletaha, Maarten de Wit, Tanja Stamm, Farideh Alasti, Diane Lacaille, Josef S Smolen, David T. Felson

Bibliographic record

VenueArthritis & Rheumatology · 2022
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsArthritis Research Centre of CanadaResearch CanadaUniversity of British Columbia
FundersJanssen BiotechNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMedicineRheumatoid arthritisRheumatologyInternal medicineMethotrexatePlaceboPhysical therapyRandomized controlled trialAlternative medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: In 2011, the American College of Rheumatology (ACR) and EULAR endorsed provisional criteria for remission in rheumatoid arthritis (RA), both Boolean- and index-based. Based on recent studies indicating that a higher threshold for the patient global assessment (PtGA) may improve agreement between the 2 sets of criteria, our goals were to externally validate a revision of the Boolean remission criteria using a higher PtGA threshold and to validate the provisionally endorsed index-based criteria. METHODS: We used data from 4 randomized trials comparing biologic disease-modifying antirheumatic drugs to methotrexate or placebo. We tested the higher proposed PtGA threshold of 2 cm (Boolean2.0) (range 0-10 cm) compared to the original threshold of 1 cm (Boolean1.0). We analyzed agreement between the Boolean- and index-based criteria (Simplified Disease Activity Index [SDAI] and Clinical Disease Activity Index [CDAI]) for remission and examined how well each remission definition predicted later good physical function (Health Assessment Questionnaire [HAQ] score ≤0.5) and radiographic nonprogression. RESULTS: Data from 2,048 trial participants, 1,101 with early RA and 947 with established RA, were included. The proportion of patients with disease in remission at 6 months after treatment initiation increased when using Boolean2.0 compared to Boolean1.0, from 14.8% to 20.6% in early RA and 4.2% to 6.0% in established RA. Agreement between Boolean2.0 and the SDAI or CDAI remission criteria was better than for Boolean1.0, particularly in early disease. Boolean2.0, SDAI, and CDAI remission criteria had similar positive likelihood ratios (LRs) to predict radiographic nonprogression and a HAQ score of ≤0.5 (positive LR 3.8-4.3). The omission of PtGA (BooleanX) worsened the prediction of good functional outcomes. CONCLUSION: Using the Boolean 2.0 criteria classifies more patients as achieving remission and increases the agreement with index-based remission criteria without jeopardizing predictive value for radiographic or functional outcomes. This revised Boolean definition and the previously provisionally endorsed index-based criteria were endorsed by ACR and EULAR.

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)0.017
metaresearch head score (Gemma)0.014
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: Methods · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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
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".

Quick stats

Citations77
Published2022
Admission routes1
Has abstractyes

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