Should quantitative assessment of rheumatoid arthritis include measures of joint damage and patient distress, in addition to measures of apparent inflammatory activity?
Notice bibliographique
Résumé
Recent controversies concerning patient global assessment (PATGL) in rheumatoid arthritis (RA) remission criteria (1, 2) largely ignore issues that emerge when, as noted by Felson et al, “remission criteria designed and validated in clinical trials are applied to…help assess treatment ‘success’ in clinical practice…and could serve as a ‘treat-to-target’ goal” (1). All six RA core data measures and indices—including swollen joint count and tender joint count, as well as PATGL, Disease Activity Score in 28 (DAS 28) Joints, and other indices—are elevated significantly not only by inflammatory activity, but also by secondary osteoarthritis (3-5), depression (6), and/or fibromyalgia (FM) (7, 8), regardless of levels of inflammatory activity (see Table 1 of representative reports). This phenomenon has limited impact in clinical trials, in which PATGL is as efficient as any measure (including swollen and tender joint counts) to distinguish active from control treatments (9) in patient groups toward meeting regulatory requirements to market a new agent. However, only 5% to 30% of all patients with RA meet eligibility criteria for clinical trials (10, 11), whereas more than 50% of patients seen in routine care have clinically important osteoarthritis, FM, and/or depression (3, 5-8), which elevate all clinical RA measures, affecting a goal “low activity or remission” according to RA indices in individual patients (12). Furthermore, self-report measures of patients with RA are elevated in 35% to 60% of normal elderly people who do not report any arthritis (13). Quantitative, pragmatic measures are available to assess joint damage and/or patient distress in order to better interpret whether elevated RA measures and indices result from these problems, rather than from—or in addition to—inflammatory activity. Joint damage may be quantitated as deformed and/or limited motion on a 28-joint count, as described in the initial report (14). Patient distress may be quantitated by disease-specific questionnaires for FM (15) and depression (16), and/or by indices for FM and depression on a single multidimensional health assessment questionnaire (MDHAQ) which agree more than 80% with reference questionnaires (17, 18). A RheuMetric checklist includes pragmatic 0-10 physician estimates for global status, inflammation, damage, and distress (19, 20). Quantitative assessment of comorbid joint damage and patient distress may be informative even in clinical trials, eg, to explain in part why 30% to 40% of patients treated with powerful biological therapies do not meet American College of Rheumatology 20 (ACR 20) response criteria (21), a relatively low target. Quantitative measurement of joint damage and patient distress—in addition to inflammatory activity—in routine care, long-term databases, and even clinical trials may clarify RA management, outcomes, and possible new remission criteria. All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,056 | 0,104 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,007 |
| Communication savante | 0,004 | 0,013 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».