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AB0753 (2024)
VALUE OF T-CELL SUBSETS IN PREDICTING RESPONSE TO MTX AND ANTI-TNF IN EARLY RA
Keywords: Biomarkers, Disease-modifying Drugs (DMARDs), Adaptive immunity, Biological DMARD
F. Tastekin1, B. Saleem2, F. Ponchel1, P. Emery1
1Leeds Institute of Rheumatic and Musculoskeletal Medicine, Rheumatology, Leeds, United Kingdom
2Leeds Teaching Hospitals NHS Trust, Chapel Allerton Hospital, Rheumatology, Leeds, United Kingdom

Background: Rheumatoid arthritis (RA) is a chronic, inflammatory, autoimmune disease. Abnormalities in T-cell subset frequencies have previously demonstrated (1,2) their utility in predicting progression from the at-risk stage, as well as response to methotrexate (MTX) in early RA and flare when in remission (2-5). However, the value of baseline T-cell subsets for predicting response to anti-TNF has not been evaluated.


Objectives: The aim of this study was to assess the value of T-cell subsets for predicting response to anti-TNF in patients with RA, and observe changes in T-cell subtypes over time on MTX or anti-TNF treatment.


Methods: RA patients (ACR/EULAR 2010 classification) were recruited from the Leeds early RA clinic. Patients were managed using NICE guidelines for the MTX. Anti-TNF treatment was part of clinical trials of early intervention (VEDERA/EMPIRE). DAS28(CRP)-remission was used to classify response. Patients not in remission continued treatment when on anti-TNF or received additional DMARDs (synthetic/biologic) when on MTX. T-cell subsets (naive CD4+ cells, T-regulatory cells (Treg) and inflammation related cell (IRC) were measured by flow-cytometry by NHS-services. Baseline data are described using medians and proportion. Predicting of the achievement of remission at 6 months was performed using forward binary logistic regression. Repeated measures over time were analysed using two-way mixed ANOVA test.


Results: 221 patients were treated with MTX and 78 patients with anti-TNF. At 6m in the MTX group 50.7 % patients achieved remission versus 61.5% for anti-TNF. In the MTX-group, baseline TJC, SJC and CRP were associated with remission (p<0.05) as well as naïve T-cell frequencies (p<0.0001). Modelling using clinical data only, suggested predictive value for remission for age, smoking and CRP (Accuracy=67.5%/AUC=0.731). Adding the T-cell subsets to the model, improved accuracy to 71.9%/AUROC=0.767. A similar analysis for anti-TNF induced remission suggested only a significant association with TJC (p=0.019) and weak association with Treg (p=0.253). Modelling did not retain any demographic/clinical parameters and adding T-cell subsets did not allow a model to be built. Over-time in the MTX group, there was a reduction in naïve T-cell frequency in non-responders (Figure 1, Blue, n=21) but not in patients achieving remission (n=13). IRC were stable in the remission but increased in the non-responder group. Treg reduced over time.

In the anti-TNF group, IRC reduced quickly in remission (n=25) but not in patients with active disease (n=5). There was no clear trend for increase/reduction in naïve cells in either group, and Treg remained relatively stable in both groups.


Conclusion: The added value of T-cell subsets for predicting MTX remission was clearly demonstrated by the improvement of accuracy/AUC compared to using clinical data alone, validating previous smaller studies (1,2). There are still no biomarkers of the response to anti-TNF in early RA. Anti-TNF prevented the loss of both Treg and naïve T-cells seen in MTX non-responders. Response to MTX but not anti-TNF, is predicted by T-cell subsets. This is consistent with the fact that anti-TNF is prescribed and works when MTX fails.


REFERENCES: [1] Ponchel F, et al. Blood. 2002;100(13):4550-4556.

[2] Gul HL, et al. Clin Exp Rheumatol. 2023;41(1):126-136.

[3] Ponchel F, et al. Ann Rheum Dis. 2014;73(11):2047-2053.

[4] Szalay B, et al. Clin Rheumatol. 2014;33(2):175-185.

[5] Saleem B, et al. Ann Rheum Dis. 2010;69(9):1636-1642.


Acknowledgements: NIL.


Disclosure of Interests: None declared.


DOI: 10.1136/annrheumdis-2024-eular.5087
Keywords: Biomarkers, Disease-modifying Drugs (DMARDs), Adaptive immunity, Biological DMARD
Citation: , volume 83, supplement 1, year 2024, page 1668
Session: Rheumatoid arthritis (Publication Only)