ASSOCIATION BETWEEN IMPROVEMENT IN HEALTH-RELATED QUALITY OF LIFE OUTCOMES AND DISEASE ACTIVITY IN SLE: A REAL-WORLD COHORT STUDY
Notice bibliographique
Résumé
PV178 / #702 Poster Topic: AS19 - Patient-Reported Outcome Measures Background/Purpose Systemic Lupus Erythematosus (SLE) is a chronic autoimmune disorder associated with significant morbidity and mortality. The use of patient-reported outcome (PRO) measures in SLE to assess health-related quality of life (HRQoL) is particularly relevant for capturing aspects of the disease that are not fully reflected by traditional disease activity measures, such as Type 2 SLE features. This study aimed to evaluate the association between clinically important improvements in HRQoL scores, assessed by the Short-Form 36 (SF-36), and disease activity, assessed by SLEDAI-2K, in patients with SLE in a real-world clinical setting. Methods This was a retrospective analysis of prospectively collected data in SLE patients followed at a single center in Toronto. Clinical and laboratory data were collected every 3-6 months, with SF-36 annually. We included patients with active disease (defined as SLEDAI-2K ≥ 6) from 2005- 2024 (marking the advent of mycophenolate mofetil use), with the availability of baseline and 1-year follow-up data for SF-36. Minimum clinically important differences (MCID) in SF-36 scores were defined as increases in SF-36 Physical (PCS) and Mental Component Summary (MCS) scores by ≥2.5, individual domain scores by ≥5, and minimum important difference (MID) for SLEDAI-2K as a decrease by ≥4. Associations between improvements in SF-36 (2 summary, 8 domain) scores and SLEDAI-2K responses at 1 year were analyzed using chi-square tests. Two separate regression models were used to study the least squares mean differences in SLEDAI-2K scores for PCS and MCS score responders vs nonresponders at 1 year. Results Among 247 patients included, median age was 37.1 years (IQR 28.5-46.5) at the study visit, female-to-male ratio of 8.8:1, and median SLE duration from diagnosis of 9.25 years (IQR 4.39-16.07). The median SLEDAI-2K score was 8 (IQR 6-12), with common organ involvements being mucocutaneous (46.6%), renal (44.9%), and musculoskeletal (23.5%). Most patients had active serology (79.4%) and a median SDI of 1 (IQR 0-2) at the study visit. The majority received hydroxychloroquine (83%), with mycophenolate mofetil (49.4%) being the most commonly prescribed immunosuppressant, followed by azathioprine (44.9%). Among MCS score responders, a significantly greater proportion achieved SLEDAI-2K responses compared to MCS nonresponders (52 of 101, 51.5 % vs 47 of 146, 32.2%, p<0.01). This association was not observed between PCS score responders and nonresponders. For individual SF-36 domains, significantly more patients who reported clinically meaningful improvements in physical function (53 of 111, 47.7 vs. 46 of 136, 33.8%, p=0.04) and mental health (45 of 86, 52.3% vs. 69 of 189, 33.5%, p<0.01) domains also achieved SLEDAI-2K responses. No significant differences were reported for other domains, although there was a trend in vitality and role emotional responders to achieve SLEDAI-2K responses (Figure 1). In the 2 regression models, a significant difference in SLEDAI-2K scores from baseline to 1 year was observed between PCS responders vs nonresponders (-5.13 and -3.09, p<0.01) and MCS responders vs nonresponders (-5.19 and -3.14, p<0.01). Figure 1: Proportion of SLEDAI-2K responders and non-responders in patients reporting improvements ≥ MCID versus non-responders in SF-36 summary and domain scores Conclusions In patients with active SLE, clinically important improvements in disease activity were notable among those who reported clinically meaningful improvements in MCS scores, physical function, and mental health domains of the SF-36 at 1 year. Those who demonstrated clinically meaningful improvements in both, SF-36 MCS and PCS scores had greater reductions in SLEDAI-2K scores at 1 year. These findings indicate that improvements in some aspects of HRQoL are associated with significant reductions in disease activity in SLE patients.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,024 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».