POS0528 EARLY OPTIMISATION OF METHOTREXATE THERAPY PREVENTS DIFFICULT-TO-TREAT RHEUMATOID ARTHRITIS: A SINGLE-CENTRE, RETROSPECTIVE COHORT STUDY

Background

According to the current EULAR recommendations for the management of rheumatoid arthritis (RA), methotrexate (MTX) should be started as soon as RA is diagnosed and rapidly optimized to achieve remission. Nonetheless, it has been estimated that a difficult-to-treat (D2T) disease occurs in 3-10% of RA patients1. Herein, we hypothesized that D2T-RA can be prevented with an optimal MTX treatment in early stages.

Objectives

The main objective of this study was to demonstrate an association between successful optimization of MTX treatment within two years of RA diagnosis and development of a status of D2T-RA later in the disease course.

Methods

In 2016 we started a ‘Refractory RA’ clinic at the Rheumatology Unit, University of Padua, Italy. In this retrospective cohort study conducted in December 2021, we enrolled patients fulfilling both the ACR/EULAR 2010 criteria for RA and the EULAR definition of D2T-RA2 diagnosed after 2000. We compared D2T-RA patients with non-D2T-RA controls from the same clinic having similar sex distribution and year of diagnosis. The primary outcome was the status of DT2-RA. The exposure was ‘MTX optimization’ after two years from diagnosis, as assessed with a numeric score (the sum of the following binary variables concerning MTX therapy: started within 3, 12 or 24 months from diagnosis; adequate dose (≥15 mg weekly); treatment duration≥6 months; early intolerance (≤3 months); range 0 to 6, with higher scores reflecting better optimization). We used multiple logistic regression analysis to examine the association (odds ratio (OR)) between MTX optimization scores and the outcome, controlling for potential modifiers (age, sex, body mass index, age at onset, and anti-citrullinated peptides antibodies [ACPA]).

Results

There were 37 DT2 RA patients and 107 non-D2T RA controls for the analysis (mean (SD) disease duration 12.8 (4.1) vs. 12.6 (4.6), p=0.621). Per protocol, gender (females 77.3 vs. 82.0%, p=0.247) and year of diagnosis (median [25th, 75th percentile]: 2008 [2004, 2011] vs. 2008 [2003, 2012]) were comparable between groups. Optimization of MTX therapy was poor overall, yet MTX optimization scores were significantly higher in D2T-RA than in non-D2T-RA patients (1.06 (0.21) vs. 0.56 (0.14), p<0.001). In multiple logistic regression, MTX optimization was protective against DT2-RA. Indeed, the likelihood of D2T-RA was decreased by 34%-54% according to MTX optimization scores. Other disease characteristics significantly associated with D2T-RA were an older age at diagnosis and female sex (Table 1). In December 2021 (last follow-up), D2T-RA patients were receiving a significantly higher daily dose of prednisone (4.3 (1.4) vs. 0.5 (0.2), p<0.001), and had a numerically greater burden of comorbidities (median 3 [1, 4] vs. 2 [1, 3], p=0.252) and disease activity (DAS28-ESR: 3.41 (0.40) vs. 2.6 (0.19), p=0.053) than non-D2T-RA patients.

Table 1.

Early factors associated with difficult-to-treat rheumatoid arthritis (multivariable logistic regression)

BSEP-valueOdds ratio95% ICMTX optimization score-0.5990.092<0.0010.5490.459, 0.657Age, years0.0330.008<0.0011.0341.017, 1.051Sex (female vs males)0.7230.2870.0122.0611.174, 3.615BMI, kg/m2-0.0060.0180.7481.0060.970, 1.043ACPA (positive vs negative)0.4310.24500.0791.5390.952, 2.487

ACPA, anti-citrullinated peptide antibodies; B, unstandardised beta coefficient; BMI, body mass index; MTX, methotrexate; SE, standard error.

Conclusion

DT2-RA may be prevented by optimization of MTX therapy within two years of RA management.

References

[1]de Hair MJH, Jacobs JWG, Schoneveld JLM, van Laar JM. Difficult-to-treat rheumatoid arthritis: an area of unmet clinical need. Rheumatology (Oxford);57(7):1135-1144.

[2]Nagy G et al. EULAR definition of difficult-to-treat rheumatoid arthritis. Ann Rheum Dis 2021;80:31-35.

Disclosure of Interests

Alessandro Giollo Consultant of: Galapagos, Novartis, Eli-Lilly, Margherita Zen: None declared, Maddalena Larosa: None declared, Federico Arru: None declared, Konstantinos Botsios: None declared, Antonia Calligaro: None declared, Andrea Doria Consultant of: GSK, Pfizer, Eli Lilly, Roche, Janssen, AstraZeneca, Galapagos.

The De Ritis ratio as prognostic biomarker of in-hospital mortality in COVID-19 patients

Increased concentrations of serum aspartate transaminase (AST) and alanine transaminase (ALT) are common in COVID-19 patients. However, their capacity to predict mortality, particularly the AST/ALT ratio, commonly referred to as the De Ritis ratio, is unknown. We investigated the association between the De Ritis ratio on admission and in-hospital mortality in 105 consecutive patients with coronavirus disease of 2019 (COVID-19) admitted to three COVID-19 referral centres in Sardinia, Italy. The De Ritis ratio was significantly lower in survivors than nonsurvivors (median: 1.25; IQR: 0.91-1.64 vs 1.67; IQR: 1.38-1.97, P = .002) whilst there were no significant between-group differences in ALT and AST concentrations. In ROC curve analysis, the AUC value of the De Ritis ratio was 0.701 (95% CI 0.603-0.787, P = .0006) with sensitivity and specificity of 74% and 70%, respectively. Kaplan-Meier survival curves showed a significant association between the De Ritis ratio and mortality (logrank test P = .014). By contrast, no associations were observed between the ALT and AST concentrations and mortality (logrank test P = .83 and P = .62, respectively). In multivariate Cox regression analysis, the HR in patients with De Ritis ratios ≥1.63 (upper tertile of this parameter) remained significant after adjusting for age, gender, smoking status, cardiovascular disease, intensity of care, diabetes, respiratory diseases, malignancies and kidney disease (HR: 2.46, 95% CI 1.05-5.73, P = .037). Therefore, the De Ritis ratio on admission was significantly associated with in-hospital mortality in COVID-19 patients. Larger studies are required to confirm the capacity of this parameter to independently predict mortality in this group.