P176 Minimal important difference, minimal detectable change and disease activity thresholds for two novel composite instruments, three visual analogue scale/VAS and four visual analogue scale/VAS, in patients with psoriatic arthritis: pooled analysis of three phase III studies
Notice bibliographique
Résumé
Abstract Background/Aims Although continuous composite measures of disease activity for PsA assessment exist, more feasible abbreviated measures are needed for routine screening. The 3VAS and 4VAS scores, developed by abridging the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) Composite Exercise (GRACE) measure, are the first short multidimensional composite measures specifically for routine PsA care. 3VAS/4VAS showed superior performance vs. several established composite measures using small datasets. However, GRAPPA members recommended further testing of 3VAS/4VAS in observational and trial datasets. Methods This post hoc analysis used pooled data through W24 from all treatment groups in the DISCOVER 1/2 and COSMOS studies. Correlation of 3VAS/4VAS with DAPSA, PASDAS, PhGA and PtGA was assessed with Pearson’s correlation coefficient, minimal important difference (MID) with four distribution-based methods and minimal detectable change (MDC) with the standard formula (Table 1). Clinically relevant thresholds for low, moderate and high disease activity were estimated with receiver operating characteristic analysis and DAPSA (≤4, >4-≤14, >14-≤28, >28), PASDAS (≤1.9, >1.9-≤3.2, >3.2-<5.4, ≥5.4) and PhGA/PtGA (≤1, >1-≤3, >3-≤6, >6 cm) as anchors. Results This analysis included 1405 patients: 51.3% were male, with a mean (sd) age of 47.1 (11.8) and PsA duration of 6.4 (6.5) years. The mean baseline 3VAS, 4VAS, DAPSA, PASDAS, PhGA and PtGA scores reflected high disease activity levels (Table 1). Through W24, 3VAS and 4VAS showed very strong correlation with PtGA (r3VAS=0.92, r4VAS=0.94) and PASDAS (r3VAS=0.81, r4VAS=0.82), strong with PhGA (r3VAS=0.77, r4VAS=0.74) and moderate-to-strong with DAPSA (r3VAS=0.59, r4VAS=0.61). Calculated MIDs were 0.9 for 3VAS and 0.9 for 4VAS; MDCs were 3.3 for 3VAS and 3.2 for 4VAS (Table 1). Cut-off values for low, moderate and high disease activity were 2.0, 3.4 and 4.9 for 3VAS, and 2.1, 3.5 and 5.1 for 4VAS. Conclusion Using a large pooled clinical trial dataset of patients with active PsA, we have calculated clinically relevant thresholds for improvement, as well as disease activity thresholds, for 3VAS and 4VAS. These estimates are generally comparable to those previously reported and may facilitate setting treatment targets and screening disease activity in routine care when resources are limited or in remote patient monitoring. Disclosure W. Tillett: Other; Received research funding, consulting, speaker fees and/or honoraria from AbbVie, Amgen, Celgene, GlaxoSmithKline, Janssen, Lilly, MSD, Novartis, Pfizer and UCB. L. Coates: Consultancies; AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Novartis, Pfizer and UCB. Member of speakers’ bureau; AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Medac, Novartis, Pfizer and UCB. Grants/research support; AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer and UCB. Other; National Institute for Health Research (NIHR) Clinician Scientist award. The research was supported by the NIHR Oxford Biomedical Research Centre, The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health, We acknowledge the support of the NIHR Clinical Research Network. M. Vis: Other; Received research grants and consulting or speaker fees from AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, UCB and the Dutch Arthritis Foundation. J. Merola: Consultancies; Consultant and/or investigator for AbbVie, Arena, Biogen, Bristol Myers Squibb, Dermavant, Lilly, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma. E. Soriano: Consultancies; AbbVie, Janssen, Novartis and Roche. Member of speakers’ bureau; AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, Roche and UCB. Grants/research support; AbbVie, Janssen, Novartis, Pfizer, Roche and UCB. M. Perate: Shareholder/stock ownership; Employee of Janssen and owns stocks in Johnson & Johnson. M. Shawi: Shareholder/stock ownership; Employee of Janssen and owns stocks in Johnson & Johnson. M. Zimmermann: Shareholder/stock ownership; Employee of Janssen and owns stocks in Johnson & Johnson. E. Rampakakis: Consultancies; Employee of JSS Medical Research; paid consultant of Janssen. M. Sharaf: Shareholder/stock ownership; Employee of Janssen and owns stocks in Johnson & Johnson. P. Nash: Other; Received grants for research and clinical trials and honoraria for advice and lectures on behalf of AbbVie, Boehringer-Ingelheim, Gilead/Galapagos, GSK, Janssen, Lilly, MSD, Novartis, Pfizer, Samsung,. P.S. Helliwell: Consultancies; AbbVie, Amgen, Novartis and Janssen. Other; Fees for educational services from AbbVie, Amgen, Novartis and Janssen.
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 | 0,049 | 0,053 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,025 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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 ».