OP0310 DIFFERENCES IN STRUCTURAL LESIONS OF THE SPINE BETWEEN PATIENTS WITH EARLY axSpA AND NON-axSpA CHRONIC BACK PAIN: 2-YEAR RESULTS OF THE SPACE COHORT
Notice bibliographique
Résumé
Background: Structural lesions of the spine on conventional radiography (CR) and magnetic resonance imaging (MRI) are typical characteristics of advanced axSpA. However, in early disease, they are less well understood. It is unknown how structural lesions and their progression over time differ between chronic back pain (CBP) patients with and without early axSpA. Objectives: To compare structural lesions of the spine on CR and MRI over 2 years (2Y), as well as their 2Y-change, between patients with early axSpA and non-axSpA CBP. Methods: Patients included in the Spondyloarthritis Caught Early cohort (CBP ≥3 months and ≤2 years, starting <45 years), were diagnosed with axSpA or non-axSpA CBP by their rheumatologist at 2Y follow-up [1]. Only patients with available imaging (CR and/or MRI) at both BL and 2Y were included. Spinal lesions on CR (BL, 1Y, 2Y) were assessed by three central readers using the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). The mSASSS was calculated based on the average among 3 readers and ≥2 out of 3 reader agreement was used for the presence of syndesmophytes. Structural lesions on spinal MRIs (BL, 1Y, 2Y) were assessed by two central readers using the Canada-Denmark scoring system. The total number of structural lesions, and individually erosions, bone spurs, fat lesions, and ankylosis, was analyzed based on the agreement of both readers. Additionally, the number of patients meeting different cut-offs (≥3 erosions, ≥1 bone spur, ≥3 fat lesions, ≥5 fat lesions, ≥5 fat lesions and/or erosions at BL and 2Y) was assessed using the same strategy. Generalized Estimating Equations (GEE) models were used to assess the progression of structural lesions over 2Y, adjusting for age, sex, NSAID use, and diagnosis. Results: CR data from 318 (214 axSpA, 108 non-axSpA) patients and MRI data from 351 (242 axSpA, 109 non-axSpA) patients were included. Overall, 278 patients had both CR and MRI available at BL and 2Y [mean (SD) age 30 (8) years, 46% males, 61% HLA-B27+]. On CR, the mean (SD) BL mSASSS was 0.6 (1.1) in both axSpA and non-axSpA. Mean mSASSS was slightly higher at 2Y than BL for each diagnostic category, but no differences were found between patients with axSpA and non-axSpA (Figure 1). The proportion of patients with ≥1 new syndesmophyte was comparable between groups (2% in each). On MRI, axSpA patients had a mean of 0.3 (1.1) fat lesions compared with 0.2 (1.1) in non-axSpA at BL (Figure 2A). The 2Y increase in the mean total number structural lesions [0.5 (1.8)] was mainly driven by the increase in fat lesions [0.5 (1.6), p=0.01] in the axSpA group (Figure 2A and 2B). At 2Y, the axSpA group had significantly more fat lesions and total structural lesions compared to the non-axSpA group (p=0.004 for both), and no differences were observed for other lesions. The proportion of axSpA patients with ≥5 fat lesions and ≥5 fat lesions and/or erosions was higher at 2Y compared to BL (from 2% to 5%, p=0.01 for both). In terms of new structural lesions, the proportion of patients with ≥3 and ≥5 new fat lesions were higher in the axSpA than non-axSpA group (10% vs 1%, p=0.001 and 4% vs 0, p=0.03, respectively). In the non-axSpA group, there was no difference from BL to 2Y for any of the MRI structural lesions. Over 2Y, the progression of spinal structural lesions was similar between the axSpA and non-axSpA groups on CR, with overall mSASSS progression being minimal, specifically 0.01 mSASSS units per year. On MRI, fat lesions progressed at a rate of 0.16 units/year in axSpA and -0.02 units/year in non-axSpA. The remaining lesions showed no significant progression. Conclusion: Over 2 years, there is minimal progression of spinal structural damage on CR in both early axSpA and non-axSpA CBP, with similar mSASSS between groups. On MRI, there is a significant increase in the number of fat lesions in axSpA, contrasting with non-axSpA in which no progression is observed. Fat lesions may be important to assess disease progression from early disease onwards. REFERENCES: [1] Marques et al. Ann Rheum Dis. 2024;83(5):589-598. Figure 1Status and change scores of mSASSS and number of syndesmophytes in axSpA and non-axSpA CBP patients. Lines indicate p-values for BL to 2Y differences within groups and between-group differences in 2Y change scores. No significant difference was observed at BL and 2Y between axSpA and non-axSpA. BL, Baseline; 2Y, 2-years; CBP, Chronic back pain; NS, Non-significant Figure 2 A. Status scores of MRI spinal structural lesions in axSpA and non-axSpA CBP. B. 2Y change scores of MRI spinal structural lesions in axSpA and non-axSpA CBP. In Figure 2A; Lines indicate p-values for BL to 2Y differences within groups. Differences between the axSpA and non-axSpA groups at BL or 2Y for individual lesions are marked with a superscript (^). In Figure 2B, lines indicate p-values between the axSpA and non-axSpA -. BL, Baseline; 2Y, 2-years;CBP, Chronic back pain; NS, Non-significant Acknowledgements: NIL . Disclosure of Interests: Gizem Ayan: None declared, Liese de Bruin: None declared, Miranda van Lunteren: None declared, Manouk de Hooge has received consultancy fees from UCB Pharma, Ana Bento da Silva: None declared, Mary Lucy Marques has received speaker fees from Novartis, and consultancy fees from Novartis, Monique Reijnierse: None declared, Victoria Navarro-Compán: None declared, Marleen G.H. van de Sande has received speaker fees from Benecke, Eli Lilly, Janssen, Novartis, UCB, consultancy fees from Abbvie, Janssen, Novartis, UCB, and grants from Janssen, Novartis, UCB, Inger Jorid Berg: None declared, Roberta Ramonda: None declared, Sofia Exarchou has received speaker fees from Novartis and UCB Pharma, and consultancy fees from AbbVie, Amgen, Eli Lilly, Janssen, Novartis and UCB Pharma, Désirée van der Heijde has received consultancy fees from AbbVie, Alfasigma, ArgenX, BMS, Elly-Lilly, Grey-Wolf Therapeutics, Janssen, Novartis, Pfizer, Takeda, UCB Pharma, Floris van Gaalen has received consultancy fees from Novartis, MSD, AbbVie Bristol Myers Squibb and Eli Lilly, and grants from Stichting vrienden van Sole Mio, Stichting ASAS, Novartis, UCB, Sofia Ramiro has received speaker fees from Eli Lilly, Novartis and UCB, consultancy fees from AbbVie, Eli Lilly, Galapagos/Alfasigma, Janssen, MSD, Pfizer, UCB, Sanofi, and grants from AbbVie, Galapagos/Alfasigma, MSD, Novartis, Pfizer, UCB © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».