Clinical predictors of inadequate response to conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) including methotrexate (MTX) in untreated rheumatoid arthritis patients: A single-center observational study

Baseline bony erosions and time-averaged DAS28 predict discontinuation of TNF inhibitors in rheumatoid arthritis

The present study evaluated the predictive role of baseline radiographic change and disease activity on drug retention and clinical response in patients with rheumatoid arthritis (RA) treated with tumor necrosis factor inhibitor (TNFi). Korean Observational Study Network for Arthritis (KORONA) registry was evaluated to identify RA patients treated with a TNFi. Disease activity score-28 (DAS28) was evaluated at baseline and 1 year after TNFi initiation or at termination of TNFi due to inefficacy (within 1 year). The retention rate of TNFi was compared in patients with and without bony erosions. The hazard ratio (HR) for drug retention was evaluated by Cox regression analysis, as was the odds ratio (OR) for achieving remission (DAS28 < 2.6). This study included 109 RA patients, including 97 (89%) women and 30 (27.5%) with erosions, who were treated with a TNFi. Higher baseline DAS28 was negatively associated with achievement of remission (OR = 0.56, 95% CI 0.35-0.88). The TNFi retention rate was significantly lower in RA patients with than in those without erosions (p = 0.04). Factors significantly associated with drug discontinuation included the presence of erosions (HR = 2.45, 95% CI 1.08-5.51) and higher time-averaged DAS28 (HR = 2.17, 95% CI 1.47-3.20), whereas concomitant methotrexate was associated with lack of drug discontinuation (HR = 0.40, 95% CI 0.17-0.95). The presence of erosions and high time-averaged disease activity could predict poor retention of TNFi by RA patients. Higher baseline DAS28 was associated with a reduced clinical response in patients with RA.Trial registration Clinical Research Information Service of South Korea https://cris.nih.go.kr : KCT0000086, registered May 26, 2009.

Investigation of the Role of the TRPA1 Ion Channel in Conveying the Effect of Dimethyl Trisulfide on Vascular and Histological Changes in Serum-Transfer Arthritis

Rheumatoid arthritis (RA) is one of the most prevalent autoimmune diseases. Its therapy is often challenging, even in the era of biologicals. Previously, we observed the anti-inflammatory effects of garlic-derived organic polysulfide dimethyl trisulfide (DMTS). Some of these effects were mediated by activation of the TRPA1 ion channel. TRPA1 was mostly expressed in a subset of nociceptor neurons. We decided to investigate the action of DMTS in K/BxN serum-transfer arthritis, which is a relevant model of RA. TRPA1 gene knockout (KO) and wild-type (WT) mice were used. The interaction of DMTS and TRPA1 was examined using a patch clamp in CHO cells. Arthritis was characterized by mechanical hyperalgesia, paw swelling, movement range of the ankle joint, hanging performance, plasma extravasation rate, myeloperoxidase activity, and histological changes in the tibiotarsal joint. DMTS activated TRPA1 channels dose-dependently. DMTS treatment reduced paw swelling and plasma extravasation in both TRPA1 WT and KO animals. DMTS-treated TRPA1 KO animals developed milder collagen deposition in the inflamed joints than WT ones. TRPA1 WT mice did not exhibit significant cartilage damage compared to ones administered a vehicle. We concluded that DMTS and related substances might evolve into novel complementary therapeutic aids for RA patients.

Factors predicting addition of disease-modifying antirheumatic drugs after initial methotrexate monotherapy in patients with rheumatoid arthritis

INTRODUCTION

We investigated factors predicting the addition of disease-modifying antirheumatic drugs (DMARDs) after an initial methotrexate (MTX) monotherapy in rheumatoid arthritis (RA) patients to support an early decision on the DMARDs addition.

METHODS

This retrospective cohort study included 311 patients who were diagnosed with RA and started on MTX monotherapy at Showa University Hospital, Japan. The outcome was addition of DMARDs after an initial MTX monotherapy at 6 months. Baseline patient characteristics were compared between the DMARDs addition and MTX monotherapy continuation groups, and significant independent predictive factors for the addition of DMARDs were selected using multivariate analysis.

RESULTS

The median age of patients was 62 years (range 24-90), 170 patients (73%) were women, the median swollen 28-joint count (SJC28) was 3 (0-28), and the median tender 28-joint count (TJC28) was 5 (0-28). DMARDs were added in 65 (27.9%) patients. In the univariate analysis, higher TJC28 and SJC28, concomitant use of nonsteroidal anti-inflammatory drugs, and intra-articular glucocorticoid (GC) injection history were significantly associated with the DMARDs addition. In the multivariate analysis, by adding covariates to the variables identified in the univariate analysis, SJC28 (odds ratio [OR] 1.390 per 5 joints increase; 95% confidence interval [CI], 1.036-1.866) and intra-articular GC injection history (OR 3.678; 95% CI, 1.170-11.557) were independent predictors of DMARDs addition.

CONCLUSION

A higher SJC28 and intra-articular GC injection history may be useful predictors of DMARDs addition after the initial MTX monotherapy. We expect that using these predictors will enable an earlier shift to a more aggressive treatment. Key Points ・We performed a retrospective cohort study with the addition of DMARDs as the outcome in patients with RA who were started on MTX monotherapy. ・A higher SJC28 (OR 1.390; 95% CI, 1.036-1.866) and an intra-articular GC injection history (OR 3.678; 95% CI, 1.170-11.557) may be useful predictors for the addition of DMARDs of initiating MTX monotherapy at 6 months. ・The use of such indicators may support an early decision on the addition of DMARDs after the initial MTX monotherapy.

Complex Machine-Learning Algorithms and Multivariable Logistic Regression on Par in the Prediction of Insufficient Clinical Response to Methotrexate in Rheumatoid Arthritis

The goals of this study were to examine whether machine-learning algorithms outperform multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to investigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Finally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response.