Comparison between Janus Kinase Inhibitor Monotherapy and Combination Therapy with Methotrexate in Patients with Rheumatoid Arthritis: Insight from the National Database of Rheumatic Diseases in Japan (NinJa) Registry

Comparison between Janus Kinase Inhibitor Monotherapy and Combination Therapy with Methotrexate in Patients with Rheumatoid Arthritis: Insight from the National Database of Rheumatic Diseases in Japan (NinJa) Registry | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison between Janus Kinase Inhibitor Monotherapy and Combination Therapy with Methotrexate in Patients with Rheumatoid Arthritis: Insight from the National Database of Rheumatic Diseases in Japan (NinJa) Registry Shohei Yamashita, Hirofumi Shoda, Yusuke Yamamoto, Toshihiro Matsui, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9205693/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Background: Janus kinase inhibitors (JAKi) are effective for rheumatoid arthritis (RA) and can be used as monotherapy; however, the clinical benefit of concomitant methotrexate (MTX) and the optimal MTX dose in JAKi-treated patients remain unclear in real-world settings. In this study, we aimed to clarify the roles of MTX by comparing the patient profiles between JAKi monotherapy (Mono) and combination with MTX (Combi) using the National Database of Rheumatic Diseases in Japan (NinJa). Methods: Using the 2022 version of the NinJa database, we analyzed RA patients treated with JAKi. Patients were classified into Mono and Combi groups. Clinical characteristics, disease activity, remission rates, and hospitalization due to serious adverse events (SAEs) were compared. Multivariable logistic regression and propensity score (PS)-matched analyses were performed to adjust for confounding factors. Associations between MTX dose and disease activity were examined using correlation and multiple regression analyses. Results: Among the enrolled patients (n = 1315), 554 (42.1%) received Combi therapy. Patients in the Combi group were younger, had shorter disease duration, and showed lower DAS28 (ESR) and HAQ scores than those in the Mono group. DAS28 (ESR)–defined remission was achieved more frequently in the Combi group (50.0% vs. 38.1%, p < 0.001). Multivariable logistic regression demonstrated that MTX use was independently associated with clinical remission (odds ratio [OR], 1.47; 95% confidence interval [CI], 1.06–2.04). In PS-matched analyses, Combi therapy remained associated with lower DAS28 (ESR) values and higher remission rates. MTX dose was not associated with disease activity among patients receiving Combi therapy. Hospitalization due to SAEs occurred in 11.0% of JAKi-treated patients and was not independently associated with MTX use, whereas glucocorticoid use was a significant risk factor for several SAEs. Conclusions: In real-world clinical practice, Combi therapy with JAKi and MTX was associated with higher remission rates without increasing the risk of SAEs. However, MTX dose did not influence disease activity, suggesting that low-dose MTX may be sufficient when used in combination with JAKi. Although further studies are warranted to evaluate long-term outcomes, Combi therapy appears to be a favorable and well-tolerated option for RA management. Rheumatoid arthritis (RA) Janus kinase inhibitor (JAKi) methotrexate (MTX) serious adverse event (SAE) propensity score matching Background Rheumatoid arthritis (RA) is characterized by erosive polyarthritis caused by a combination of genetic and environmental factors ( 1 , 2 ). Unregulated autoimmune synovial inflammation leads to progress destruction of joint structures and subsequent impairment of joint functions. To modify the natural course of the disease, strict control of disease activity through the early initiation of disease-modifying anti-rheumatic drugs (DMARDs) is thought to be essential ( 1 , 2 ). Methotrexate (MTX) is considered the anchor DMARD for RA, whereas some patients are intolerant to MTX due to adverse effects or comorbidities, such as chronic kidney diseases ( 3 ). Indeed, the recent rate of MTX use was reported to be less than 70% in the National Database of Rheumatic Diseases in Japan (NinJa) ( 4 ). Several randomized controlled trials (RCTs) have evaluated the efficacy of MTX-free regimens. For example, upadacitinib (UPA), a Janus kinase inhibitors (JAKi), demonstrated superior clinical and functional efficacy as monotherapy compared with MTX monotherapy in patients with active RA despite prior MTX treatment ( 5 ). Similarly, baricitinib (BAR), another JAKi, showed sufficient efficacy as monotherapy compared with MTX monotherapy in patients with prior DMARD-resistant RA ( 6 ). These findings suggest that JAKi monotherapy can provide sufficient efficacy even in MTX-resistant patients. However, few RCTs have directly compared JAKi monotherapy with combination therapy consisting JAKi and MTX. The RA-BEAM study demonstrated that combination therapy with BAR and MTX exerted superior protective effects against joint destruction compared with BAR monotherapy, despite no significant difference in clinical efficacy ( 6 ). Although this result suggests a potential advantage of combination therapy, it remain unclear whether the combination with MTX consistently improves outcomes when used with other JAKi agents. For example, it remains unclear whether JAKi monotherapy or combination therapy with MTX provides superior clinical benefit in patients with prior DMARD resistance, including those with MTX-resistant disease. Consequently, evidence guiding the choice between JAKi monotherapy and combination therapy with MTX is limited. Furthermore, the optimal dose of MTX when used in combination therapy has not been established. In addition, recent European League Against Rheumatism (EULAR) recommendation of RA management suggested dose reduction and discontinuation of DMARDs after achieving sustained remission ( 3 ). Importantly, a long-term extension study of BAR indicated the feasibility of successful dose reduction in patients who achieve clinical remission ( 7 ). Given that long-term and high-dose MTX use is associated with an increased risk of serious adverse events, such as MTX-associated lymphoproliferative disorders ( 8 ), MTX dose reduction or discontinuation is often considered, particularly in patients under clinical remission. However, the therapeutic contribution of MTX in patients receiving JAKi therapy remains controversial. Real-world data directly comparing JAKi monotherapy with combination therapy including MTX are still limited. NinJa is one of the largest RA registries in Japan, collecting annual cross-sectional data on treatment regimens, disease activity, patient outcomes, and adverse events ( 4 , 9 – 10 ). Previously, we reported glucocorticoid (GC) dose-sparing effects of JAKi using the NinJa database ( 11 ), suggesting that this large-scale registry provides valuable real-world evidence for clinical practice. The present study aimed to clarify whether combination therapy with JAKi and MTX confers additional clinical benefit by comparing patients receiving JAKi monotherapy with those receiving combination therapy using the latest (2022) version of the NinJa database. Furthermore, we analyzed differences in clinical parameters according to MTX dose among patients treated with JAKi. This study provides clinically relevant insights to optimize the use of JAKi in patients with RA. Methods NinJa database Data from the 2022 version of the NinJa was analyzed. The NinJa database is a national-wide prospective registry that annually collects cross-sectional clinical data from patients with RA across Japan, and its detailed explanation is provided in previous literatures ( 4 , 9 – 10 ). All patients fulfilled the 2010 American College of Rheumatology (ACR)/EULAR classification criteria for RA ( 12 ). Among NinJa database, patients treated with JAKi, including tofacitinib (TOF), BAR, UPA, filgotinib (FIL), and peficitinib (PEF), were included in the study. Clinical and demographic information extracted from the database included age, sex, body mass index (BMI), smoking history (never/ever smoker), treatment, serum C-reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), seropositivity, Steinbrocker’s class and stage ( 13 ), Health Assessment Questionnaire (HAQ) score, swollen joint count (SJC), tender joint count (TJC), patient’s global assessment (PGA), evaluator’s global assessment (EGA), and scores calculated by these measurements, including Disease Activity Score (DAS)28, Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI). Seropositivity was defined as follows: serum rheumatoid factor (RF) more than 15 IU/mL and/or anti-cyclic citrullinated peptide (CCP)2 antibody more than 5 U/m. Additionally, hospitalization due to serious adverse events (SAEs) within the preceding year was recorded. SAEs were defined according to the Rheumatology Common Toxicity Criteria (RCTC) version 2.0 developed by the Outcome Measures in Rheumatology Drug Safety Working Group ( 14 ), with events classified as serious when hospitalization was required. This study was approved by the ethics committees of all participating institutions. The NinJa study protocol was reviewed and approved by the ethics committee of the National Hospital Organization Sagamihara National Hospital (approval number: 2014031816) and the ethics committee of Tokyo Medical University Hospital (T2019-0154). Informed consent was obtained either in written form or through an opt-out approach, depending on the institution's policy. This study was conducted in accordance with the latest version of the Declaration of Helsinki. Propensity score matching To adjust for potential confounding factors between patients treated with and without MTX, propensity score (PS)-matching was performed ( 15 , 16 ). PSs were generated using a multivariable logistic regression model, with MTX use as the dependent variable. The independent variables were determined according to the prior literatures on clinical remission ( 17 – 19 ), and included age, sex, BMI, and seropositivity for calculating PSs. One-to-one matching without replacement was performed using the nearest neighbor matching method, within a caliper width of 0.1 standard deviations of the logit of the PS. For sensitivity analyses, conditional multiple logistic regression analyses were performed under both univariate and multivariate conditions. Statistics All statistical analyses were performed using R software (version 4.3.3). For comparisons between two groups, two-tailed unpaired t-tests were applied. Difference in frequencies were tested using Fisher’s extract test. Pearson’s correlation coefficients were calculated to evaluate correlations between variables. Multiple logistic regression analyses were conducted to identify factors associated with achieving clinical remission and hospitalization due to SAEs. Multiple linear regression analysis was performed with DAS28(ESR) as the dependent variable and age, sex, disease duration, seropositivity, MTX dose, and GC dose as independent variables. Receiver Operating Characteristic (ROC) curves analyses were performed using the pROC package ( 20 ). P-values less than 0.05 were considered statistically significant. Results Comparison between JAKi-treated RA patients with and without MTX Among 17,503 cases registered in the 2022 version of the NinJa database, a total of 1,315 RA patients receiving JAKi were included in this study. The numbers of patients treated with each JAKi were as follows: TOF n = 302, BAR n = 433, UPA n = 305, FIL n = 186, PEF n = 89. The demographic and clinical characteristics of the patients were summarized in Table 1 . The mean age (± standard deviation (SD)) was 69.0 (± 12.4) years old, and 81.1% of the patients was female. The mean disease duration (± SD) was 15.8 ± 11.7 years, and 80.8% of the patients was seropositive. Regarding MTX, 554 patients (42.1%) received combination therapy with JAKi and MTX (Combi) with a mean MTX dose (± SD) of 7.52 ± 3.01 mg/week. Table 1 Summary of JAK inhibitor (JAKi)-treated patients in NinJa database. Age (years) Total (n = 1315) Mono (n = 771) Combi (n = 554) p-value 69.0 ± 12.4 71.4 ± 11.6 65.4 ± 12.7 < 0.001*** Disease duration (years) 15.8 ± 11.7 16.8 ± 12.1 14.7 ± 11.0 0.004** Sex (female) 1066 (81.1%) 621 (80.5%) 445 (81.8%) 0.62 BMI 23.1 ± 4.0 23.3 ± 4.1 23.0 ± 3.8 0.25 Ever smoker 401(34.7%) 223 (33.0%) 178 (37.0%) 0.17 Class 1 2 3 4 176 (24.9%) 368 (52.1%) 145 (20.5%) 18 (2.5%) 176 (24.9%) 368 (52.1%) 145 (20.5%) 18 (2.5%) 158 (31.5%) 252 (50.3%) 80 (16.0%) 11 (2.2%) 0.041* Stage 1 2 3 4 169 (23.7%) 188 (26.3%) 140 (19.6%) 217 (30.4%) 169 (23.7%) 188 (26.3%) 140 (19.6%) 217 (30.4%) 134 (26.6%) 137 (27.2%) 84 (16.7%) 148 (29.4%) 0.46 PtGA 2.48 ± 2.30 2.54 ± 2.34 2.40 ± 2.25 0.30 EGA 1.25 ± 1.35 1.24 ± 1.33 1.26 ± 1.37 0.79 SJC28 1.17 ± 2.80 1.17 ± 2.80 1.18 ± 2.79 0.97 TJC28 0.90 ± 2.18 1.00 ± 2.50 0.75 ± 1.60 0.039* CRP (mg/dL) 2.97 ± 1.13 0.49 ± 1.28 0.40 ± 1.29 0.17 ESR (mm/h) 29.6 ± 23.7 33.6 ± 25.0 24.0 ± 20.4 < 0.001*** DAS28(ESR) 2.97 ± 1.13 3.08 ± 1.11 2.80 ± 1.13 < 0.001*** DAS28(CRP) 2.17 ± 0.98 2.20 ± 1.02 2.12 ± 0.93 0.16 SDAI 6.32 ± 6.63 6.48 ± 6.76 6.10 ± 6.43 0.32 CDAI 5.89 ± 6.30 6.04 ± 6.48 5.68 ± 6.04 0.33 Pain VAS 2.33 ± 2.25 2.35 ± 2.29 2.30 ± 2.20 0.68 Seropositivity 816 (80.8%) 498 (81.5%) 318 (79.7%) 0.51 RF titer (IU/mL) 168.3 ± 373.4 191.1 ± 420.8 133.6 ± 283.6 0.018* Anti-CCP2 Ab titer (IU/mL) 250.9 ± 496.0 268.1 ± 496.9 225.2 ± 494.6 0.29 HAQ 0.47 ± 0.64 0.53 ± 0.68 0.38 ± 0.57 < 0.001*** Treatment GC user mean dose in users (mg/day in PSL) 369 (28.1%) 3.48 ± 2.37 237 (30.7%) 3.47 ± 2.43 132 (24.3%) 3.48 ± 2.28 0.011* 0.96 NSAID user 466 (35.4%) 267 (34.6%) 199 (36.6%) 0.48 Table 1. Summary of JAK inhibitor (JAKi)-treated patients in NinJa database. The demographic and clinical characteristics of the enrolled patients. The strategy of inclusion and exclusion is shown in Supplementary Figure S1. Data are presented as mean ± S.D., or as numbers with percentages. Abbreviations are referenced in the Methods section. The comparison between the patients with Mono and Combi groups were performed by Fisher’s extract test and two-tailed unpaired t-tests were applied for statistical analysis. * p<0.05, ** p<0.01, *** p<0.001. Compared with the patients receiving JAKi monotherapy (Mono), those receiving Combi therapy were significantly younger, and had a shorter disease duration, as well as lower DAS28(ESR) and HAQ scores (Table 1 ). With respect of remission, 210 patients (50.0%) in the Combi group achieved DAS28(ESR)-defined remission, compared with 235 patients (38.1%) in the Mono group (p < 0.001). Notably, ESR and serum RF titers were significantly lower in the Combi group than in Mono group (Table 1 ). In contrast, serum CRP or anti-CCP2 antibody titers did not differ between the two groups, and the proportion of seropositive patients was also comparable (Table 1 ). TJC was lower in the Combi group than those in the Mono group, whereas SJC, PtGA, or EGA were not different between two groups (Table 1 ). Consequently, composite disease activity indices, including SDAI, CDAI or DAS28(CRP), were comparable between two groups (Table 1 ). Sex, BMI, smoking status, and pain VAS scores also showed no significant difference between two groups (Table 1 ). Regarding GC use, the GC doses among GC-treated patients did not differ significantly between the patients, however, the proposition of patients receiving GC therapy was significantly lower in the Combi group than in the Mono group (Mono n = 237, 30.7%, Combi n = 142, 22.9%. p = 0.001) (Table 1 ). Next, multivariate logistic regression analyses were conducted to identify factors associated with clinical remission in the patients treated with JAKi (Table 2 ). Based on the results shown in Table 1 and the previous literatures ( 17 – 19 ), age, sex, disease duration, smoking habit (ever smoker), HAQ score, seropositivity, GC use, and MTX use were included as covariates in the model. Several variables, namely younger age, male sex, shorter disease duration, seronegative status, lower HAQ scores and absence of GC use, were significantly associated with achievement of DAS28(ESR)-defined clinical remission (Table 2 ). Notably, MTX use (i.e., Combi therapy) was independently associated with a higher likelihood of achieving DAS28(ESR)-defined remission (odds ratio (OR) 1.47, 95% confidence interval (CI) 1.06–2.04, p = 0.022). Table 2 Multiple regression analysis for achievement of DAS28(ESR)-defined remission. Univariate Multivariate OR (95%CI) p-value OR (95%CI) p-value Age 0.97 (0.96–0.98) < 0.001*** 0.98 (0.97–0.99) 0.022* Disease duration 0.95 (0.94–0.97) < 0.001*** 0.98 (0.97–0.99) 0.022* Sex (male) 1.97 (1.44–2.69) < 0.001*** 1.56 (1.01–2.42) < 0.001*** Ever smoker 1.52 (1.16–1.98) 0.0023** 1.10 (0.77–1.59) 0.59 Seropositivity 0.57 (0.41–0.80) 0.0010** 0.64 (0.43–0.96) 0.029* HAQ score 0.18 (0.13–0.26) < 0.001*** 0.27 (0.19–0.41) < 0.001*** GC use 0.33 (0.24–0.45) < 0.001*** 0.46 (0.31–0.67) < 0.010** MTX use (Combi therapy) 1.62 (1.26–2.08) < 0.001*** 1.47 (1.06–2.04) 0.022* Table 2. Multiple regression analysis for achievement of DAS28(ESR)-defined remission. The odds ratios (ORs) (95% CI) for achievement of DAS28(ESR)-defined remission were analyzed by logistic regression in univariable and multivariable analyses. In multivariable analyses, all the indicated parameters were included as variables. Abbreviations are referenced in the Methods section. * p<0.05, ** p<0.01, ***p<0.001 Given that multiple potential confounders other than MTX use were associated with disease activity, we additionally performed PS-matched comparison the patients receiving Mono and Combi therapies. After PS matching, there was no differences in baseline clinical characteristics, including age, sex, disease duration, BMI, HAQ, scores, seropositivity, or the proportion of GC use between the two groups (Table 3 ). In the PS-matched cohort, the patients receiving Combi therapy exhibited significantly lower DAS28(ESR) and a higher rate of DAS28(ESR)-defined remission compared with those receiving Mono therapy (DAS28(ESR) (mean ± SD): Mono 3.07 ± 1.09, Combi: 2.88 ± 1.09. p = 0.037. DAS28(ESR)-defined remission rate: Mono 39.1%, Combi 47.9%. p = 0.036) (Table 3 ). In addition, ESR levels were significantly lower in the Combi group than in the Mono group (Table 3 ). Conditional logistic regression analyses using the PS-matched data further demonstrated that Combi therapy was associated with a significantly higher likelihood of achieving DAS28 (ESR)–defined remission compared with Mono therapy (OR, 2.23; 95% CI, 1.22–4.08; p = 0.0089) (Supplementary Table 1). Taken together, the patients receiving Combi therapy exhibited more favorable clinical characteristics, including younger age, shorter disease duration, lower DAS28(ESR) and HAQ scores, and less frequent GC use, compared with those receiving Mono therapy. Importantly, even after adjusting for multiple confounding factors, Combi therapy remained independently associated with achievement of DAS28(ESR)-defined remission. Table 3 Propensity score (PS)-matched comparison between the patients with Mono and Combi therapies. Age (years) Mono (n = 324) Combi (n = 324) P-value 67.5 ± 11.8 67.2 ± 11.5 0.80 Disease duration (years) 15.3 ± 11.0 15.4 ± 11.5 0.99 Sex (female) 272 (84.0%) 267 (82.4%) 0.68 BMI 22.8 ± 3.9 23.0 ± 3.9 0.37 Ever smoker 117 (37.3%) 119 (37.5%) 1.00 Class 1 2 3 4 84 (27.0%) 164 (52.7%) 56 (18.0%) 7 (2.3%) 86 (27.6%) 163 (52.2%) 57 (18.3%) 6 (1.9%) 1.00 Stage 1 2 3 4 83 (26.4%) 86 (27.4%) 48 (15.3%) 97 (30.9%) 83 (26.7%) 85 (27.3%) 48 (15.4%) 95 (30.5%) 1.00 PtGA 2.29 ± 2.26 2.46 ± 2.21 0.33 EGA 1.22 ± 1.24 1.30 ± 1.32 0.45 SJC28 1.28 ± 2.68 1.32 ± 3.08 0.89 TJC28 0.87 ± 2.14 0.78 ± 1.65 0.53 CRP (mg/dL) 0.44 ± 0.91 0.44 ± 1.56 0.99 ESR (mm/h) 32.5 ± 24.1 24.8 ± 20.3 < 0.001*** DAS28(ESR) 3.07 ± 1.09 2.88 ± 1.09 0.037* DAS28(ESR)-defined remission 115 (39.1%) 135 (47.9%) 0.036* DAS28(CRP) 2.17 ± 1.02 2.15 ± 0.97 0.77 SDAI 6.18 ± 6.40 6.39 ± 6.74 0.70 CDAI 5.74 ± 6.14 5.95 ± 6.24 0.68 Pain VAS 2.15 ± 2.20 2.38 ± 2.23 0.21 Seropositivity 263 (81.2%) 259 (79.9%) 0.77 RF titer (IU/mL) 173.1 ± 350.6 128.7 ± 287.6 0.082 Anti-CCP2 Ab titer (IU/mL) 290.4 ± 558.4 232.7 ± 513.3 0.27 HAQ 0.43 ± 0.61 0.40 ± 0.56 0.51 Treatment GC user mean dose in users (mg/day in PSL) 91 (28.1%) 3.39 ± 2.11 84 (25.9%) 3.43 ± 2.15 0.60 0.89 NSAID user 121 (37.3%) 195 (39.8%) 0.57 Table 3. Propensity score (PS)-matched comparison between the patients with Mono and Combi therapies. Comparison between the patients with Mono and Combi therapies after propensity score (PS)-matching. PSs were generated using a multivariable logistic regression model, with MTX use as the dependent variable. The independent variables included age, sex, BMI and seropositivity. One-to-one matching without replacement was performed using the nearest neighbor matching method, within a caliper width of 0.1 standard deviations of the logit of the PS. Fisher’s extract test and two-tailed unpaired t-tests were applied for statistical analysis. * p<0.05. *** p<0.001. Association between MTX doses and disease activity in patients receiving Combi therapy Next, we examined the association between MTX dose and clinical parameters in patients receiving Combi therapy. MTX dose was significantly correlated with age (r = -0.27, p < 0.001). In contrast, MTX dose was not significantly associated with DAS28(ESR) (r = -0.028, p = 0.57) (data not shown). Furthermore, a multiple linear regression analysis was performed to identify factors associated with DAS28(ESR) in patients receiving Combi therapy. Male sex (β = -0.82, p = 0.035) was independently associated with lower DAS28(ESR), whereas MTX dose was not was not significantly associated with DAS28 (ESR) (β = 0.020, p = 0.68) (Supplementary Table 2). These findings indicate that MTX dose did not independently influence disease activity as assessed by DAS28 (ESR). Taken together, MTX dose was not associated with DAS28(ESR) in the patients receiving Combi therapy with JAKi and MTX. Frequencies of hospitalization due to SAEs in JAKi-treated patients Finally, the incidence of hospitalization due to SAEs was compared between the patients receiving Mono and Combi therapies (Table 4 ). Overall, hospitalization due to SAEs occurred in 11.0% of all JAKi-treated patients and was significantly less frequent in the Combi group than in the Mono group (Combi, 7.2%, Mono,13.6%. p < 0.001) (Table 4 ). The incidence of individual SAEs was 3.3% for infection, 1.3% for insufficiency fracture, 1.1% for malignancy, and 0.2% for major adverse cardiovascular events (MACE), with no significant difference between the Mono and Combi groups (Table 4 ). Comparisons between the patients with and without hospitalization due to SAEs identifies several variables as potential confounders, including age, disease duration, disease activity indices, HAQ score, GC use, and MTX use (Supplementary Table 3). Subsequent multivariate logistic regression analyses demonstrated that GC use was significantly associated with an increased risk of several SAEs, including hospitalization due to SAEs (OR 2.20, 95%CI: 1.33–3.62, p = 0.0020), infection (OR 3.03, 95%CI: 1.24–7.41, p = 0.015), and insufficiency fracture (OR 5.35, 95%CI: 1.25–22.9, p = 0.024.) (Table 5 ). Although Combi therapy was associated with lower ORs for several SAE outcomes, MTX use was not independently associated with the incidence of SAEs in the adjusted analyses (Table 5 ). No clinical variables were significantly associated with the incidence of malignancy or MACE (data not shown). Taken together, GC use was identified as a major risk factor for the development of several SAEs, whereas the incidence of SAEs was comparable between patients receiving Mono and Combi therapies after adjustment for confounding factors. Table 4 Frequency of hospitalization due to serious adverse events (SAEs) in JAK inhibitor-treated patients in NinJa database. hospitalization due to SAEs Total (n = 1315) Mono (n = 771) Combi (n = 554) p-value 144 (11.0%) 105 (13.6%) 39 (7.2%) < 0.001*** infection 44 (3.3%) 32 (4.2%) 12 (2.2%) 0.062 insufficiency fracture 17 (1.3%) 12 (1.6%) 5 (0.9%) 0.46 malignancy 14 (1.1%) 11 (1.4%) 3 (0.6%) 0.17 MACE 3 (0.2%) 1 (0.1%) 2 (0.4%) 0.57 Table 4. Frequency of hospitalization due to serious adverse events (SAEs) in JAK inhibitor-treated patients in NinJa database. Frequencies of hospitalization due to SAEs, including all SAEs required for hospitalization, infection, insufficiency fracture, any malignancy, major adverse cardiovascular event (MACE) were compared between the patients with Mono and Combi therapies. Fisher’s extract test was applied for statistical analysis. *** p<0.001. Table 5 Multiple regression analysis for incidences of hospitalization due to serious adverse events (SAEs). hospitalization due to SAEs infection insufficiency fracture OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value Age 1.02 (0.99–1.04) 0.08 1.00 (0.97–1.05) 0.82 1.06 (0.98–1.14) 0.13 Disease duration 1.01 (0.98–1.03) 0.61 1.03 (0.99–1.07) 0.10 0.99 (0.93–1.05) 0.70 Sex (male) 1.62 (0.86–3.05) 0.13 2.83 (1.02–7.88) 0.046* 0.00 (0.00-inf) 0.99 Ever smoker 0.94 (0.53–1.65) 0.83 1.34 (0.50–3.60) 0.56 1.58 (0.37–6.67) 0.53 Seropositivity 1.19 (0.63–2.25) 0.58 1.10 (0.35–3.45) 0.87 2.40 (0.29-20.0) 0.42 DAS28(ESR) 1.09 (0.86–1.38) 0.47 1.18 (0.77–1.80) 0.46 1.06 (0.55–2.04) 0.86 HAQ score 1.23 (0.82–1.85) 0.32 0.62 (0.26–1.44) 0.26 0.98 (0.34–2.83) 0.97 GC use 2.20 (1.33–3.62) 0.0020** 3.03 (1.24–7.41) 0.015* 5.35 (1.25–22.9) 0.024* MTX use (Combi therapy) 0.61 (0.36–1.04) 0.068 0.74 (0.29–1.89) 0.53 0.59 (0.12–3.01) 0.53 Table 5. Multiple regression analysis for incidences of hospitalization due to serious adverse events (SAEs). The odds ratios (ORs) (95% confidence interval (CI)) for hospitalization due to SAEs, including infection and insufficiency fracture, were analyzed by multivariate logistic regression analyses. In multivariable analysis, all the indicated parameters were included as variables. * p<0.05, ** p<0.01. Discussion In this large real-world study, we demonstrated the advantage of Combi therapy with JAKi and MTX. Combi therapy was associated with higher DAS28(ESR)-defined remission rates without an increased risk of SAEs, including infections. Consistent with our findings, several previous studies have suggested potential benefit of Combi therapy. For example, a study of TOF showed that Mono therapy failed to demonstrate non-inferiority to Combi therapy in achieving ACR50 response ( 21 ). In comparison of BAR Mono and Combi therapies, less progression of structural damage was observed in Combi group despite comparable clinical efficacy ( 6 ). Additionally, a long-term extension study reported that the addition of MTX improved disease activity in the patients with insufficient response to BAR Mono therapy ( 22 ). Furthermore, a cohort study demonstrated that concomitant MTX use was associated with significant improvement in CDAI without compromising safety in JAKi-treated patients ( 23 ). Taken together, these reports support the potential advantage of Combi therapy in terms of both clinical efficacy and safety. Our study adds further real-world evidence by characterizing patients receiving Combi therapy in routine clinical practice. Notably, PS-matched analyses demonstrated that Combi therapy was associated with lower DAS28(ESR). Particularly, ESR was significantly lower in the patients receiving Combi therapy than those receiving Mono therapy. ESR is influenced by persistent inflammation and serum immunoglobulin levels, and MTX has been reported to reduce transitional B cells and serum immunoglobulin levels ( 24 ). Therefore, the addition of MTX to JAKi may modulate B cell-related immune responses and contribute to reduced ESR. In contrast, other composite disease activity indices, including DAS28(CRP), SDAI and CDAI, did not differ significantly between the two groups. Thus, the clinical relevance of the observed reduction in DAS28(ESR) requires further evaluation through longitudinal analyses with longer follow-up. Another important finding of this study is the lower frequency of GC use among the patients receiving Combi therapy. Although GC remains recommended as bridging therapy for RA ( 3 , 25 ), its high risk of several AEs warrants caution use ( 26 ). Indeed, our analyses demonstrated that GC use was a significant risk factor for several SAEs, including infections and insufficient fractures. These finding suggest that one clinical advantage of Combi therapy may be its potential to reduce GC exposure. With respect to safety, although Combi therapy was associated with a lower crude incidence of hospitalization due to SAEs, MTX use was not independently associated with SAEs after adjustment, whereas GC use consistently emerged as a major risk factor. Therefore, Combi therapy may contribute indirectly to improve safety by facilitating GC sparing in the patients who can tolerate MTX. Importantly, MTX dose did not significantly influence disease activity among the patients receiving Combi therapy. This finding is consistent with a previous report showing that MTX dose did not affect the efficacy of TOF in Japanese RA patients ( 27 ). Although the optimal MTX dose in Combi therapy remains to be determined, our results suggest that even low-dose MTX may be sufficient to confer additional clinical benefit when used with JAKi. Several limitations of this study should be acknowledged. First, the cross-sectional design precludes causal inference and limits the assessment of longitudinal outcomes, including radiographic progression and long-term safety. Second, residual confounding cannot be completely excluded despite multivariable adjustment and propensity score matching. In particular, renal function and comorbidities, which may influence both MTX use and clinical outcomes, could not be fully evaluated due to data limitations. Third, treatment selection for Mono or Combi therapy was entirely dependent on clinicians’ decisions; consequently, the Mono group likely included both MTX-intolerant patients and patients in whom MTX had been discontinued after achieving sustained remission. Finally, analyses of SAEs may have been underpowered for very rare events, such as malignancies and major adverse cardiovascular events. Conclusions In conclusion, this large real-world study demonstrates that Combi therapy with JAKi and MTX is associated with higher clinical remission rates compared with JAKi Mono therapy, without an increased risk of serious adverse events. Importantly, MTX dose did not influence disease activity among patients receiving Combi therapy, suggesting that low-dose MTX may be sufficient when used with JAKi. These findings provide clinically relevant evidence to support individualized treatment strategies aimed at optimizing concomitant MTX use in patients with RA treated with JAKi. Abbreviations RA rheumatoid arthritis DMARD disease-modifying anti-rheumatic drugs MTX methotrexate NinJa National Database of Rheumatic Diseases in Japan (NinJa) RCT randomized controlled trial UPA upadacitinib JAKi Janus kinase inhibitors BAR baricitinib EULAR European League Against Rheumatism GC glucocorticoid (GC) ACR American College of Rheumatology TOF tofacitinib FIL filgotinib PEF peficitinib BMI body mass index CRP C-reactive protein (CRP) ESR erythrocyte sedimentation rate HAQ health assessment questionnaire SJC swollen joint count TJC tender joint count PGA patient’s global assessment EGA evaluator’s global assessment DAS disease activity score SDAI simplified disease activity index CDAI clinical disease activity index RF rheumatoid factor CCP cyclic citrullinated peptide (CCP) SAE serious adverse events RCTC Rheumatology Common Toxicity Criteria PS propensity score ROC Receiver Operating Characteristic SD standard deviation Combi combination therapy Mono monotherapy CI confidence interval. Declarations Ethical approval and consent to participate This study was approved by the ethics committees of all participating institutions. The NinJa study protocol was reviewed and approved by the ethics committee of the National Hospital Organization Sagamihara National Hospital (approval number: 2014031816) and the ethics committee of Tokyo Medical University Hospital (T2019-0154). Informed consent was obtained either in written form or through an opt-out approach, depending on the institution's policy. This study was conducted in accordance with the latest version of the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials Data can be available from the corresponding author on reasonable request. Competing interests: The authors have declared no conflicts of interest. Funding: No finding. Authors' contributions SY, HS and TM conceived and designed the study. SY, HS and YY performed main analyses and wrote the manuscript with help of TM and TS. TM, ST and TS supervised the project. All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Acknowledgements The authors would like to acknowledge all investigators in NinJa (Investigators are listed in Supplementary File). We also acknowledge Akiko Komiya, who curated the NinJa database, and Satomi Hanawa, who assisted administrative work. References Matteo AD, Bathon JM, Emery P. Rheumatoid arthritis. Lancet. 2023;402:2019–33. Smolen JS, Aletaha D, Barton A, Brumester GR, Emery P, Firestein GS, et al. Rheumatoid arthritis. Nat Rev Dis Primer. 2018;4:18001. Smolen JS, Landewe RBM, Bergstra SA, Kerschbaumer A, Sepriano A, Aletaha D, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2022 update. Ann Rheum Dis. 2023;82:3–18. Matsui T, Yoshida T, Nishino T, Yoshizawa S, Sawada T, Tohma S. Trends in treatment for patients with late-onset rheumatoid arthritis in Japan: Data from the NinJa study. Mod Rheumatol. 2024;34:881–91. Smolen JS, Pangan AL, Emery P, Rigby W, Tanaka Y, Vargas JI, et al. Upadacitinib as monotherapy in patients with active rheumatoid arthritis and inadequate response to methotrexate (SELECT-MONOTHERAPY): a randomised, placebo-controlled, double-blind phase 3 study. Lancet. 2019;393:2303–11. Fleischmann R, Schiff M, van der Heijde D, Ramos-Remus C, Spindler A, Stanislav M, et al. Baricitinib, methotrexate, or combination in patients with rheumatoid arthritis and no or limited prior disease-modifying antirheumatic drug treatment. Arthritis Rheumatol. 2017;69:506–17. Edwards CJ, Krönke G, Avouac J, Li Z, Conti F, Balsa A, et al. Baricitinib Dose Reduction in Patients With Rheumatoid Arthritis Achieving Sustained Disease Control: Final Results From the RA-BEYOND Study. J Rheumatol. 2025;52:316–22. Hoshida Y, Tsujii A, Ohshima S, Saeki Y, Yagita M, Miyamura T, et al. Effect of Recent Antirheumatic Drug on Features of Rheumatoid Arthritis–Associated Lymphoproliferative Disorders. Arthritis Rheum. 2025;76:869–81. Matsui T, Kuga Y, Kaneko A, Nishino J, Eto Y, Chiba N, et al. Disease Activity Score 28 (DAS28) using C-reactive protein underestimates disease activity and overestimates EULAR response criteria compared with DAS28 using erythrocyte sedimentation rate in a large observational cohort of rheumatoid arthritis patients in Japan. Ann Rheum Dis. 2007;66:1221–6. Shoda H, Matsui T, Tohma S, Sawada T. Evaluation of patient-based disease activity score (PDAS) in the Japanese rheumatoid arthritis patient registry (NinJa registry). Rheumatology (Oxford). 2025;64:3415–25. Shoda H, Yamamoto Y, Matsui T, Tohma S, Sawada T. Glucocorticoid Sparing in Rheumatoid Arthritis Patients Treated with Janus Kinase Inhibitors: Insights from the Japanese Patient Registry. Sci Rep. 2026. Accepted. https://doi.org/10.1038/s41598-026-43504-w Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO III, et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Anna Rheum Dis. 2010;69:1580–8. Stenbrocker O, Traeger CH, Batterman RC. Therapeutic criteria in rheumatoid arthritis. J Am Med Assoc. 1949;140:659–62. Woodworth T, Furst DE, Alten R, Bingham CO 3rd, Yocum D, Sloan V, et al. Standardizing assessment and reporting of adverse effects in rheumatology clinical trials II: the Rheumatology Common Toxicity Criteria v.2.0. J Rheumatol. 2007;34:1401–14. Austin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Stat Med. 2008;27:2037–49. Zhao QY, Luo JC, Su Y, Zhang YJ, Tu GW, Luo Z. Propensity score matching with R: conventional methods and new features. Ann Transl Med. 2021;9:812. Sun X, Li R, Cai Y, Al-Herz A, Lahiri M, Choudhury MR, et al. Clinical remission of rheumatoid arthritis in a multicenter real-world study in Asia-Pacific region. Lancet Reg Health West Pac. 2021;15:100240. Khader Y, Beran A, Ghazaleh S, Lee-Smith W, Altorok N. Predictors of remission in rheumatoid arthritis patients treated with biologics: a systematic review and meta-analysis. Clin Rheumatol. 2022;41:3615–27. Pope JE, Movahedi M, Rampakakis E, Cesta A, Sampalis JS, Keystone E, et al. ACPA and RF as predictors of sustained clinical remission in patients with rheumatoid arthritis: data from the Ontario Best practices Research Initiative (OBRI). RMD Open. 2018;4:e000738. Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J, et al. pROC: an open-source package for R and S + to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77. Fleischmann R, Mysler E, Hall S, Kivitz AJ, Moots RJ, Luo Z, et al. Efficacy and Safety of Tofacitinib Monotherapy, Tofacitinib With Methotrexate, and Adalimumab With Methotrexate in Patients With Rheumatoid Arthritis (ORAL Strategy): A Phase 3b/4, Double-Blind, Head-To-Head, Randomised Controlled Trial. Lancet. 2017;390:457–68. Fleischmann R, Takeuchi T, Schiff M, Schlichting D, Xie L, Issa M, et al. Efficacy and Safety of Long-Term Baricitinib With and Without Methotrexate for the Treatment of Rheumatoid Arthritis: Experience With Baricitinib Monotherapy Continuation or After Switching From Methotrexate Monotherapy or Baricitinib Plus Methotrexate. Arthritis Care Res. 2020;72:1112–21. Ebina K, Etani Y, Okita Y, Tsujimoto K, Maeda Y, Noguchi T, et al. Differential Impact of Concomitant Methotrexate and Glucocorticoids Dosages on Biologics and JAK Inhibitors: The ANSWER Cohort Study. Int J Rheum Dis. 2025;28:e70351. Glaesener S, Quách TD, Onken N, Weller-Heinemann F, Dressler F, Huppertz HI, et al. Distinct Effects of Methotrexate and Etanercept on the B Cell Compartment in Patients With Juvenile Idiopathic Arthritis. Arthritis Rheum. 2014;66:2590–600. van Ouwerkerk L, Verschueren P, Boers M, Emery P, de Jong PHP, Landewe RBM, et al. Initial glucocorticoid bridging in rheumatoid arthritis: does it affect glucocorticoid use over time? Ann Rheum Dis. 2024;83:65–71. Santiago T, Voshaar M, de Wit M, Carvalho PD, Cutolo M, Paolino S, et al. Patients' and rheumatologists' perspectives on the efficacy and safety of low-dose glucocorticoids in rheumatoid arthritis-an international survey within the GLORIA study. Rheumatology. 2021;60:3334–42. Takeuchi T, Yamanaka H, Yamaoka K, Arai S, Toyoizumi S, Demasi R, et al. Efficacy and Safety of Tofacitinib in Japanese Patients With Rheumatoid Arthritis by Background Methotrexate Dose: A Post Hoc Analysis of Clinical Trial Data. Mod Rheumatol. 2019;29:756–66. Additional Declarations No competing interests reported. Supplementary Files SuppleTableNinJaKMTXdocx.docx SupplementarydataInvestigatorsinNinJa2022.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 05 May, 2026 Reviews received at journal 03 May, 2026 Reviews received at journal 30 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers agreed at journal 04 Apr, 2026 Reviewers invited by journal 02 Apr, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 23 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Yamamoto","suffix":""},{"id":618993499,"identity":"e9578dde-3d29-4911-9a1e-dd85ab5d2b12","order_by":3,"name":"Toshihiro Matsui","email":"","orcid":"","institution":"National Hospital Organization Sagamihara National Hospital","correspondingAuthor":false,"prefix":"","firstName":"Toshihiro","middleName":"","lastName":"Matsui","suffix":""},{"id":618993500,"identity":"2bdf13d9-db72-4ab7-8f95-27d0b8ad3c4d","order_by":4,"name":"Shigeto Tohma","email":"","orcid":"","institution":"National Hospital Organaization Tokyo National Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shigeto","middleName":"","lastName":"Tohma","suffix":""},{"id":618993501,"identity":"2c175a1c-aaa0-4ad4-b129-6926f1412aa4","order_by":5,"name":"Tetsuji Sawada","email":"","orcid":"","institution":"Tokyo Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tetsuji","middleName":"","lastName":"Sawada","suffix":""}],"badges":[],"createdAt":"2026-03-24 02:24:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9205693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9205693/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106993932,"identity":"0e6e1aed-95fb-4f38-8d6a-c4e336e2b37b","added_by":"auto","created_at":"2026-04-15 15:00:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1349527,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9205693/v1/afa3bb39-63b5-47dd-b08c-086e74915d05.pdf"},{"id":106408665,"identity":"2ac50d97-d671-4b5b-b62b-2b398c112943","added_by":"auto","created_at":"2026-04-08 09:44:03","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25345,"visible":true,"origin":"","legend":"","description":"","filename":"SuppleTableNinJaKMTXdocx.docx","url":"https://assets-eu.researchsquare.com/files/rs-9205693/v1/9e481368319424861f7376d5.docx"},{"id":106408537,"identity":"b002cb86-6835-4c34-b010-26374850e069","added_by":"auto","created_at":"2026-04-08 09:43:31","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17270,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarydataInvestigatorsinNinJa2022.docx","url":"https://assets-eu.researchsquare.com/files/rs-9205693/v1/fc2248d3979b1ef8c435390b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison between Janus Kinase Inhibitor Monotherapy and Combination Therapy with Methotrexate in Patients with Rheumatoid Arthritis: Insight from the National Database of Rheumatic Diseases in Japan (NinJa) Registry","fulltext":[{"header":"Background","content":"\u003cp\u003eRheumatoid arthritis (RA) is characterized by erosive polyarthritis caused by a combination of genetic and environmental factors (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Unregulated autoimmune synovial inflammation leads to progress destruction of joint structures and subsequent impairment of joint functions. To modify the natural course of the disease, strict control of disease activity through the early initiation of disease-modifying anti-rheumatic drugs (DMARDs) is thought to be essential (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Methotrexate (MTX) is considered the anchor DMARD for RA, whereas some patients are intolerant to MTX due to adverse effects or comorbidities, such as chronic kidney diseases (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Indeed, the recent rate of MTX use was reported to be less than 70% in the National Database of Rheumatic Diseases in Japan (NinJa) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Several randomized controlled trials (RCTs) have evaluated the efficacy of MTX-free regimens. For example, upadacitinib (UPA), a Janus kinase inhibitors (JAKi), demonstrated superior clinical and functional efficacy as monotherapy compared with MTX monotherapy in patients with active RA despite prior MTX treatment (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Similarly, baricitinib (BAR), another JAKi, showed sufficient efficacy as monotherapy compared with MTX monotherapy in patients with prior DMARD-resistant RA (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). These findings suggest that JAKi monotherapy can provide sufficient efficacy even in MTX-resistant patients. However, few RCTs have directly compared JAKi monotherapy with combination therapy consisting JAKi and MTX.\u003c/p\u003e \u003cp\u003eThe RA-BEAM study demonstrated that combination therapy with BAR and MTX exerted superior protective effects against joint destruction compared with BAR monotherapy, despite no significant difference in clinical efficacy (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Although this result suggests a potential advantage of combination therapy, it remain unclear whether the combination with MTX consistently improves outcomes when used with other JAKi agents. For example, it remains unclear whether JAKi monotherapy or combination therapy with MTX provides superior clinical benefit in patients with prior DMARD resistance, including those with MTX-resistant disease. Consequently, evidence guiding the choice between JAKi monotherapy and combination therapy with MTX is limited. Furthermore, the optimal dose of MTX when used in combination therapy has not been established.\u003c/p\u003e \u003cp\u003eIn addition, recent European League Against Rheumatism (EULAR) recommendation of RA management suggested dose reduction and discontinuation of DMARDs after achieving sustained remission (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Importantly, a long-term extension study of BAR indicated the feasibility of successful dose reduction in patients who achieve clinical remission (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Given that long-term and high-dose MTX use is associated with an increased risk of serious adverse events, such as MTX-associated lymphoproliferative disorders (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), MTX dose reduction or discontinuation is often considered, particularly in patients under clinical remission. However, the therapeutic contribution of MTX in patients receiving JAKi therapy remains controversial. Real-world data directly comparing JAKi monotherapy with combination therapy including MTX are still limited.\u003c/p\u003e \u003cp\u003eNinJa is one of the largest RA registries in Japan, collecting annual cross-sectional data on treatment regimens, disease activity, patient outcomes, and adverse events (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Previously, we reported glucocorticoid (GC) dose-sparing effects of JAKi using the NinJa database (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), suggesting that this large-scale registry provides valuable real-world evidence for clinical practice. The present study aimed to clarify whether combination therapy with JAKi and MTX confers additional clinical benefit by comparing patients receiving JAKi monotherapy with those receiving combination therapy using the latest (2022) version of the NinJa database. Furthermore, we analyzed differences in clinical parameters according to MTX dose among patients treated with JAKi. This study provides clinically relevant insights to optimize the use of JAKi in patients with RA.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eNinJa database\u003c/h2\u003e \u003cp\u003eData from the 2022 version of the NinJa was analyzed. The NinJa database is a national-wide prospective registry that annually collects cross-sectional clinical data from patients with RA across Japan, and its detailed explanation is provided in previous literatures (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). All patients fulfilled the 2010 American College of Rheumatology (ACR)/EULAR classification criteria for RA (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Among NinJa database, patients treated with JAKi, including tofacitinib (TOF), BAR, UPA, filgotinib (FIL), and peficitinib (PEF), were included in the study. Clinical and demographic information extracted from the database included age, sex, body mass index (BMI), smoking history (never/ever smoker), treatment, serum C-reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), seropositivity, Steinbrocker\u0026rsquo;s class and stage (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), Health Assessment Questionnaire (HAQ) score, swollen joint count (SJC), tender joint count (TJC), patient\u0026rsquo;s global assessment (PGA), evaluator\u0026rsquo;s global assessment (EGA), and scores calculated by these measurements, including Disease Activity Score (DAS)28, Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI). Seropositivity was defined as follows: serum rheumatoid factor (RF) more than 15 IU/mL and/or anti-cyclic citrullinated peptide (CCP)2 antibody more than 5 U/m. Additionally, hospitalization due to serious adverse events (SAEs) within the preceding year was recorded. SAEs were defined according to the Rheumatology Common Toxicity Criteria (RCTC) version 2.0 developed by the Outcome Measures in Rheumatology Drug Safety Working Group (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), with events classified as serious when hospitalization was required.\u003c/p\u003e \u003cp\u003e This study was approved by the ethics committees of all participating institutions. The NinJa study protocol was reviewed and approved by the ethics committee of the National Hospital Organization Sagamihara National Hospital (approval number: 2014031816) and the ethics committee of Tokyo Medical University Hospital (T2019-0154). Informed consent was obtained either in written form or through an opt-out approach, depending on the institution's policy. This study was conducted in accordance with the latest version of the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePropensity score matching\u003c/h3\u003e\n\u003cp\u003eTo adjust for potential confounding factors between patients treated with and without MTX, propensity score (PS)-matching was performed (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). PSs were generated using a multivariable logistic regression model, with MTX use as the dependent variable. The independent variables were determined according to the prior literatures on clinical remission (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and included age, sex, BMI, and seropositivity for calculating PSs. One-to-one matching without replacement was performed using the nearest neighbor matching method, within a caliper width of 0.1 standard deviations of the logit of the PS. For sensitivity analyses, conditional multiple logistic regression analyses were performed under both univariate and multivariate conditions.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eAll statistical analyses were performed using R software (version 4.3.3). For comparisons between two groups, two-tailed unpaired t-tests were applied. Difference in frequencies were tested using Fisher\u0026rsquo;s extract test. Pearson\u0026rsquo;s correlation coefficients were calculated to evaluate correlations between variables. Multiple logistic regression analyses were conducted to identify factors associated with achieving clinical remission and hospitalization due to SAEs. Multiple linear regression analysis was performed with DAS28(ESR) as the dependent variable and age, sex, disease duration, seropositivity, MTX dose, and GC dose as independent variables. Receiver Operating Characteristic (ROC) curves analyses were performed using the pROC package (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). P-values less than 0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eComparison between JAKi-treated RA patients with and without MTX\u003c/h2\u003e \u003cp\u003eAmong 17,503 cases registered in the 2022 version of the NinJa database, a total of 1,315 RA patients receiving JAKi were included in this study. The numbers of patients treated with each JAKi were as follows: TOF n\u0026thinsp;=\u0026thinsp;302, BAR n\u0026thinsp;=\u0026thinsp;433, UPA n\u0026thinsp;=\u0026thinsp;305, FIL n\u0026thinsp;=\u0026thinsp;186, PEF n\u0026thinsp;=\u0026thinsp;89. The demographic and clinical characteristics of the patients were summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age (\u0026plusmn;\u0026thinsp;standard deviation (SD)) was 69.0 (\u0026plusmn;\u0026thinsp;12.4) years old, and 81.1% of the patients was female. The mean disease duration (\u0026plusmn;\u0026thinsp;SD) was 15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7 years, and 80.8% of the patients was seropositive. Regarding MTX, 554 patients (42.1%) received combination therapy with JAKi and MTX (Combi) with a mean MTX dose (\u0026plusmn;\u0026thinsp;SD) of 7.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01 mg/week.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of JAK inhibitor (JAKi)-treated patients in NinJa database.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1315)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMono\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;771)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCombi\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;554)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1066 (81.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e621 (80.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e445 (81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e401(34.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223 (33.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e178 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass 1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176 (24.9%)\u003c/p\u003e \u003cp\u003e368 (52.1%)\u003c/p\u003e \u003cp\u003e145 (20.5%)\u003c/p\u003e \u003cp\u003e18 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176 (24.9%)\u003c/p\u003e \u003cp\u003e368 (52.1%)\u003c/p\u003e \u003cp\u003e145 (20.5%)\u003c/p\u003e \u003cp\u003e18 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158 (31.5%)\u003c/p\u003e \u003cp\u003e252 (50.3%)\u003c/p\u003e \u003cp\u003e80 (16.0%)\u003c/p\u003e \u003cp\u003e11 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.041*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (23.7%)\u003c/p\u003e \u003cp\u003e188 (26.3%)\u003c/p\u003e \u003cp\u003e140 (19.6%)\u003c/p\u003e \u003cp\u003e217 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169 (23.7%)\u003c/p\u003e \u003cp\u003e188 (26.3%)\u003c/p\u003e \u003cp\u003e140 (19.6%)\u003c/p\u003e \u003cp\u003e217 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134 (26.6%)\u003c/p\u003e \u003cp\u003e137 (27.2%)\u003c/p\u003e \u003cp\u003e84 (16.7%)\u003c/p\u003e \u003cp\u003e148 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePtGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSJC28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTJC28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.039*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR (mm/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.6\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.6\u0026thinsp;\u0026plusmn;\u0026thinsp;25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.0\u0026thinsp;\u0026plusmn;\u0026thinsp;20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAS28(ESR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAS28(CRP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.32\u0026thinsp;\u0026plusmn;\u0026thinsp;6.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.04\u0026thinsp;\u0026plusmn;\u0026thinsp;6.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.68\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain VAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e816 (80.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e498 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e318 (79.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRF titer (IU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168.3\u0026thinsp;\u0026plusmn;\u0026thinsp;373.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191.1\u0026thinsp;\u0026plusmn;\u0026thinsp;420.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133.6\u0026thinsp;\u0026plusmn;\u0026thinsp;283.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-CCP2 Ab titer (IU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250.9\u0026thinsp;\u0026plusmn;\u0026thinsp;496.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e268.1\u0026thinsp;\u0026plusmn;\u0026thinsp;496.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e225.2\u0026thinsp;\u0026plusmn;\u0026thinsp;494.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGC user\u003c/p\u003e \u003cp\u003emean dose in users\u003c/p\u003e \u003cp\u003e(mg/day in PSL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e369 (28.1%)\u003c/p\u003e \u003cp\u003e3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237 (30.7%)\u003c/p\u003e \u003cp\u003e3.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132 (24.3%)\u003c/p\u003e \u003cp\u003e3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSAID user\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e466 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199 (36.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1. Summary of JAK inhibitor (JAKi)-treated patients in NinJa database.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe demographic and clinical characteristics of the enrolled patients. The strategy of inclusion and exclusion is shown in Supplementary Figure S1. Data are presented as mean \u0026plusmn; S.D., or as numbers with percentages. Abbreviations are referenced in the Methods section. The comparison between the patients with Mono and Combi groups were performed by Fisher\u0026rsquo;s extract test and two-tailed unpaired t-tests were applied for statistical analysis. * p\u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e \u003cp\u003eCompared with the patients receiving JAKi monotherapy (Mono), those receiving Combi therapy were significantly younger, and had a shorter disease duration, as well as lower DAS28(ESR) and HAQ scores (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). With respect of remission, 210 patients (50.0%) in the Combi group achieved DAS28(ESR)-defined remission, compared with 235 patients (38.1%) in the Mono group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, ESR and serum RF titers were significantly lower in the Combi group than in Mono group (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, serum CRP or anti-CCP2 antibody titers did not differ between the two groups, and the proportion of seropositive patients was also comparable (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). TJC was lower in the Combi group than those in the Mono group, whereas SJC, PtGA, or EGA were not different between two groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Consequently, composite disease activity indices, including SDAI, CDAI or DAS28(CRP), were comparable between two groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sex, BMI, smoking status, and pain VAS scores also showed no significant difference between two groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Regarding GC use, the GC doses among GC-treated patients did not differ significantly between the patients, however, the proposition of patients receiving GC therapy was significantly lower in the Combi group than in the Mono group (Mono n\u0026thinsp;=\u0026thinsp;237, 30.7%, Combi n\u0026thinsp;=\u0026thinsp;142, 22.9%. p\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNext, multivariate logistic regression analyses were conducted to identify factors associated with clinical remission in the patients treated with JAKi (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Based on the results shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and the previous literatures (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), age, sex, disease duration, smoking habit (ever smoker), HAQ score, seropositivity, GC use, and MTX use were included as covariates in the model. Several variables, namely younger age, male sex, shorter disease duration, seronegative status, lower HAQ scores and absence of GC use, were significantly associated with achievement of DAS28(ESR)-defined clinical remission (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Notably, MTX use (i.e., Combi therapy) was independently associated with a higher likelihood of achieving DAS28(ESR)-defined remission (odds ratio (OR) 1.47, 95% confidence interval (CI) 1.06\u0026ndash;2.04, p\u0026thinsp;=\u0026thinsp;0.022).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple regression analysis for achievement of DAS28(ESR)-defined remission.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.96\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.97\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.95 (0.94\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.97\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.97 (1.44\u0026ndash;2.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.56 (1.01\u0026ndash;2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.52 (1.16\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0023**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10 (0.77\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.57 (0.41\u0026ndash;0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0010**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64 (0.43\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAQ score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.18 (0.13\u0026ndash;0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27 (0.19\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGC use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.33 (0.24\u0026ndash;0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.46 (0.31\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.010**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMTX use (Combi therapy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.62 (1.26\u0026ndash;2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.47 (1.06\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 2. Multiple regression analysis for\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eachievement of DAS28(ESR)-defined remission.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe odds ratios (ORs) (95% CI) for achievement of DAS28(ESR)-defined remission were analyzed by logistic regression in univariable and multivariable analyses. In multivariable analyses, all the indicated parameters were included as variables. Abbreviations are referenced in the Methods section. * p\u0026lt;0.05, ** p\u0026lt;0.01, ***p\u0026lt;0.001\u003c/p\u003e\u003cp\u003eGiven that multiple potential confounders other than MTX use were associated with disease activity, we additionally performed PS-matched comparison the patients receiving Mono and Combi therapies. After PS matching, there was no differences in baseline clinical characteristics, including age, sex, disease duration, BMI, HAQ, scores, seropositivity, or the proportion of GC use between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the PS-matched cohort, the patients receiving Combi therapy exhibited significantly lower DAS28(ESR) and a higher rate of DAS28(ESR)-defined remission compared with those receiving Mono therapy (DAS28(ESR) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD): Mono 3.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09, Combi: 2.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09. p\u0026thinsp;=\u0026thinsp;0.037. DAS28(ESR)-defined remission rate: Mono 39.1%, Combi 47.9%. p\u0026thinsp;=\u0026thinsp;0.036) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In addition, ESR levels were significantly lower in the Combi group than in the Mono group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Conditional logistic regression analyses using the PS-matched data further demonstrated that Combi therapy was associated with a significantly higher likelihood of achieving DAS28 (ESR)\u0026ndash;defined remission compared with Mono therapy (OR, 2.23; 95% CI, 1.22\u0026ndash;4.08; p\u0026thinsp;=\u0026thinsp;0.0089) (Supplementary Table\u0026nbsp;1). Taken together, the patients receiving Combi therapy exhibited more favorable clinical characteristics, including younger age, shorter disease duration, lower DAS28(ESR) and HAQ scores, and less frequent GC use, compared with those receiving Mono therapy. Importantly, even after adjusting for multiple confounding factors, Combi therapy remained independently associated with achievement of DAS28(ESR)-defined remission.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePropensity score (PS)-matched comparison between the patients with Mono and Combi therapies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMono\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;324)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCombi\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;324)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e272 (84.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267 (82.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass 1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (27.0%)\u003c/p\u003e \u003cp\u003e164 (52.7%)\u003c/p\u003e \u003cp\u003e56 (18.0%)\u003c/p\u003e \u003cp\u003e7 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (27.6%)\u003c/p\u003e \u003cp\u003e163 (52.2%)\u003c/p\u003e \u003cp\u003e57 (18.3%)\u003c/p\u003e \u003cp\u003e6 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (26.4%)\u003c/p\u003e \u003cp\u003e86 (27.4%)\u003c/p\u003e \u003cp\u003e48 (15.3%)\u003c/p\u003e \u003cp\u003e97 (30.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (26.7%)\u003c/p\u003e \u003cp\u003e85 (27.3%)\u003c/p\u003e \u003cp\u003e48 (15.4%)\u003c/p\u003e \u003cp\u003e95 (30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePtGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.46\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSJC28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTJC28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR (mm/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.5\u0026thinsp;\u0026plusmn;\u0026thinsp;24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAS28(ESR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.037*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAS28(ESR)-defined remission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (47.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAS28(CRP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.18\u0026thinsp;\u0026plusmn;\u0026thinsp;6.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.39\u0026thinsp;\u0026plusmn;\u0026thinsp;6.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.74\u0026thinsp;\u0026plusmn;\u0026thinsp;6.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.95\u0026thinsp;\u0026plusmn;\u0026thinsp;6.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain VAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.38\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e263 (81.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e259 (79.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRF titer (IU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e173.1\u0026thinsp;\u0026plusmn;\u0026thinsp;350.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128.7\u0026thinsp;\u0026plusmn;\u0026thinsp;287.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-CCP2 Ab titer (IU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e290.4\u0026thinsp;\u0026plusmn;\u0026thinsp;558.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232.7\u0026thinsp;\u0026plusmn;\u0026thinsp;513.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGC user\u003c/p\u003e \u003cp\u003emean dose in users\u003c/p\u003e \u003cp\u003e(mg/day in PSL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (28.1%)\u003c/p\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (25.9%)\u003c/p\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSAID user\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e195 (39.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003eTable 3. Propensity score (PS)-matched comparison between the patients with Mono and Combi therapies.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComparison between the patients with Mono and Combi therapies after propensity score (PS)-matching. PSs were generated using a multivariable logistic regression model, with MTX use as the dependent variable. The independent variables included age, sex, BMI and seropositivity. One-to-one matching without replacement was performed using the nearest neighbor matching method, within a caliper width of 0.1 standard deviations of the logit of the PS. Fisher\u0026rsquo;s extract test and two-tailed unpaired t-tests were applied for statistical analysis. * p\u0026lt;0.05. *** p\u0026lt;0.001.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between MTX doses and disease activity in patients receiving Combi therapy\u003c/h2\u003e \u003cp\u003eNext, we examined the association between MTX dose and clinical parameters in patients receiving Combi therapy. MTX dose was significantly correlated with age (r = -0.27, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, MTX dose was not significantly associated with DAS28(ESR) (r = -0.028, p\u0026thinsp;=\u0026thinsp;0.57) (data not shown). Furthermore, a multiple linear regression analysis was performed to identify factors associated with DAS28(ESR) in patients receiving Combi therapy. Male sex (β = -0.82, p\u0026thinsp;=\u0026thinsp;0.035) was independently associated with lower DAS28(ESR), whereas MTX dose was not was not significantly associated with DAS28 (ESR) (β\u0026thinsp;=\u0026thinsp;0.020, p\u0026thinsp;=\u0026thinsp;0.68) (Supplementary Table\u0026nbsp;2). These findings indicate that MTX dose did not independently influence disease activity as assessed by DAS28 (ESR). Taken together, MTX dose was not associated with DAS28(ESR) in the patients receiving Combi therapy with JAKi and MTX.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFrequencies of hospitalization due to SAEs in JAKi-treated patients\u003c/h3\u003e\n\u003cp\u003eFinally, the incidence of hospitalization due to SAEs was compared between the patients receiving Mono and Combi therapies (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Overall, hospitalization due to SAEs occurred in 11.0% of all JAKi-treated patients and was significantly less frequent in the Combi group than in the Mono group (Combi, 7.2%, Mono,13.6%. p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The incidence of individual SAEs was 3.3% for infection, 1.3% for insufficiency fracture, 1.1% for malignancy, and 0.2% for major adverse cardiovascular events (MACE), with no significant difference between the Mono and Combi groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Comparisons between the patients with and without hospitalization due to SAEs identifies several variables as potential confounders, including age, disease duration, disease activity indices, HAQ score, GC use, and MTX use (Supplementary Table\u0026nbsp;3). Subsequent multivariate logistic regression analyses demonstrated that GC use was significantly associated with an increased risk of several SAEs, including hospitalization due to SAEs (OR 2.20, 95%CI: 1.33\u0026ndash;3.62, p\u0026thinsp;=\u0026thinsp;0.0020), infection (OR 3.03, 95%CI: 1.24\u0026ndash;7.41, p\u0026thinsp;=\u0026thinsp;0.015), and insufficiency fracture (OR 5.35, 95%CI: 1.25\u0026ndash;22.9, p\u0026thinsp;=\u0026thinsp;0.024.) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Although Combi therapy was associated with lower ORs for several SAE outcomes, MTX use was not independently associated with the incidence of SAEs in the adjusted analyses (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). No clinical variables were significantly associated with the incidence of malignancy or MACE (data not shown). Taken together, GC use was identified as a major risk factor for the development of several SAEs, whereas the incidence of SAEs was comparable between patients receiving Mono and Combi therapies after adjustment for confounding factors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of hospitalization due to serious adverse events (SAEs) in JAK inhibitor-treated patients in NinJa database.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ehospitalization due to SAEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1315)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMono\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;771)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCombi\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;554)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (11.0%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (13.6%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (7.2%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einsufficiency fracture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emalignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMACE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 4. Frequency of hospitalization due to serious adverse events (SAEs) in JAK inhibitor-treated patients in NinJa database.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrequencies of hospitalization due to SAEs, including all SAEs required for hospitalization, infection, insufficiency fracture, any malignancy, major adverse cardiovascular event (MACE) were compared between the patients with Mono and Combi therapies. Fisher\u0026rsquo;s extract test was applied for statistical analysis. *** p\u0026lt;0.001.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple regression analysis for incidences of hospitalization due to serious adverse events (SAEs).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ehospitalization due to SAEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003einfection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003einsufficiency fracture\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003cp\u003e(0.99\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e(0.97\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003cp\u003e(0.98\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e(0.98\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.99\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003cp\u003e(0.93\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003cp\u003e(0.86\u0026ndash;3.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003cp\u003e(1.02\u0026ndash;7.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003cp\u003e(0.00-inf)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003cp\u003e(0.53\u0026ndash;1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003cp\u003e(0.50\u0026ndash;3.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003cp\u003e(0.37\u0026ndash;6.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003cp\u003e(0.63\u0026ndash;2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003cp\u003e(0.35\u0026ndash;3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003cp\u003e(0.29-20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAS28(ESR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003cp\u003e(0.86\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003cp\u003e(0.77\u0026ndash;1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003cp\u003e(0.55\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHAQ score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003cp\u003e(0.82\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003cp\u003e(0.26\u0026ndash;1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003cp\u003e(0.34\u0026ndash;2.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGC use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003cp\u003e(1.33\u0026ndash;3.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0020**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003cp\u003e(1.24\u0026ndash;7.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003cp\u003e(1.25\u0026ndash;22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.024*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMTX use\u003c/p\u003e \u003cp\u003e(Combi therapy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003cp\u003e(0.36\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003cp\u003e(0.29\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003cp\u003e(0.12\u0026ndash;3.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 5. Multiple regression analysis for incidences of hospitalization due to serious adverse events (SAEs).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe odds ratios (ORs) (95% confidence interval (CI)) for hospitalization due to SAEs, including infection and insufficiency fracture, were analyzed by multivariate logistic regression analyses. In multivariable analysis, all the indicated parameters were included as variables. * p\u0026lt;0.05, ** p\u0026lt;0.01.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large real-world study, we demonstrated the advantage of Combi therapy with JAKi and MTX. Combi therapy was associated with higher DAS28(ESR)-defined remission rates without an increased risk of SAEs, including infections. Consistent with our findings, several previous studies have suggested potential benefit of Combi therapy. For example, a study of TOF showed that Mono therapy failed to demonstrate non-inferiority to Combi therapy in achieving ACR50 response (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In comparison of BAR Mono and Combi therapies, less progression of structural damage was observed in Combi group despite comparable clinical efficacy (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Additionally, a long-term extension study reported that the addition of MTX improved disease activity in the patients with insufficient response to BAR Mono therapy (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Furthermore, a cohort study demonstrated that concomitant MTX use was associated with significant improvement in CDAI without compromising safety in JAKi-treated patients (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Taken together, these reports support the potential advantage of Combi therapy in terms of both clinical efficacy and safety.\u003c/p\u003e \u003cp\u003eOur study adds further real-world evidence by characterizing patients receiving Combi therapy in routine clinical practice. Notably, PS-matched analyses demonstrated that Combi therapy was associated with lower DAS28(ESR). Particularly, ESR was significantly lower in the patients receiving Combi therapy than those receiving Mono therapy. ESR is influenced by persistent inflammation and serum immunoglobulin levels, and MTX has been reported to reduce transitional B cells and serum immunoglobulin levels (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Therefore, the addition of MTX to JAKi may modulate B cell-related immune responses and contribute to reduced ESR. In contrast, other composite disease activity indices, including DAS28(CRP), SDAI and CDAI, did not differ significantly between the two groups. Thus, the clinical relevance of the observed reduction in DAS28(ESR) requires further evaluation through longitudinal analyses with longer follow-up.\u003c/p\u003e \u003cp\u003eAnother important finding of this study is the lower frequency of GC use among the patients receiving Combi therapy. Although GC remains recommended as bridging therapy for RA (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), its high risk of several AEs warrants caution use (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Indeed, our analyses demonstrated that GC use was a significant risk factor for several SAEs, including infections and insufficient fractures. These finding suggest that one clinical advantage of Combi therapy may be its potential to reduce GC exposure. With respect to safety, although Combi therapy was associated with a lower crude incidence of hospitalization due to SAEs, MTX use was not independently associated with SAEs after adjustment, whereas GC use consistently emerged as a major risk factor. Therefore, Combi therapy may contribute indirectly to improve safety by facilitating GC sparing in the patients who can tolerate MTX. Importantly, MTX dose did not significantly influence disease activity among the patients receiving Combi therapy. This finding is consistent with a previous report showing that MTX dose did not affect the efficacy of TOF in Japanese RA patients (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Although the optimal MTX dose in Combi therapy remains to be determined, our results suggest that even low-dose MTX may be sufficient to confer additional clinical benefit when used with JAKi.\u003c/p\u003e \u003cp\u003eSeveral limitations of this study should be acknowledged. First, the cross-sectional design precludes causal inference and limits the assessment of longitudinal outcomes, including radiographic progression and long-term safety. Second, residual confounding cannot be completely excluded despite multivariable adjustment and propensity score matching. In particular, renal function and comorbidities, which may influence both MTX use and clinical outcomes, could not be fully evaluated due to data limitations. Third, treatment selection for Mono or Combi therapy was entirely dependent on clinicians\u0026rsquo; decisions; consequently, the Mono group likely included both MTX-intolerant patients and patients in whom MTX had been discontinued after achieving sustained remission. Finally, analyses of SAEs may have been underpowered for very rare events, such as malignancies and major adverse cardiovascular events.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this large real-world study demonstrates that Combi therapy with JAKi and MTX is associated with higher clinical remission rates compared with JAKi Mono therapy, without an increased risk of serious adverse events. Importantly, MTX dose did not influence disease activity among patients receiving Combi therapy, suggesting that low-dose MTX may be sufficient when used with JAKi. These findings provide clinically relevant evidence to support individualized treatment strategies aimed at optimizing concomitant MTX use in patients with RA treated with JAKi.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erheumatoid arthritis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMARD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edisease-modifying anti-rheumatic drugs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMTX\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethotrexate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNinJa\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Database of Rheumatic Diseases in Japan (NinJa)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erandomized controlled trial\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eupadacitinib\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eJAKi\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eJanus kinase inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBAR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebaricitinib\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEULAR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean League Against Rheumatism\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglucocorticoid (GC)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican College of Rheumatology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTOF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etofacitinib\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFIL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efilgotinib\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epeficitinib\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein (CRP)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eESR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eerythrocyte sedimentation rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHAQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehealth assessment questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSJC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eswollen joint count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTJC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etender joint count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epatient\u0026rsquo;s global assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eevaluator\u0026rsquo;s global assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edisease activity score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDAI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esimplified disease activity index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDAI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eclinical disease activity index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erheumatoid factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecyclic citrullinated peptide (CCP)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eserious adverse events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRCTC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRheumatology Common Toxicity Criteria\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epropensity score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver Operating Characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCombi\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecombination therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMono\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emonotherapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethics committees of all participating institutions. The NinJa study protocol was reviewed and approved by the ethics committee of the National Hospital Organization Sagamihara National Hospital (approval number: 2014031816) and the ethics committee of Tokyo Medical University Hospital (T2019-0154). Informed consent was obtained either in written form or through an opt-out approach, depending on the institution\u0026apos;s policy. This study was conducted in accordance with the latest version of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eData can be available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors have declared no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No finding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;SY, HS and TM conceived and designed the study. SY, HS and YY performed main analyses and wrote the manuscript with help of TM and TS. TM, ST and TS supervised the project. All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors would like to acknowledge all investigators in NinJa (Investigators are listed in Supplementary File). We also acknowledge Akiko Komiya, who curated the NinJa database, and Satomi Hanawa, who assisted administrative work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMatteo AD, Bathon JM, Emery P. Rheumatoid arthritis. Lancet. 2023;402:2019\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmolen JS, Aletaha D, Barton A, Brumester GR, Emery P, Firestein GS, et al. Rheumatoid arthritis. Nat Rev Dis Primer. 2018;4:18001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmolen JS, Landewe RBM, Bergstra SA, Kerschbaumer A, Sepriano A, Aletaha D, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2022 update. Ann Rheum Dis. 2023;82:3\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsui T, Yoshida T, Nishino T, Yoshizawa S, Sawada T, Tohma S. Trends in treatment for patients with late-onset rheumatoid arthritis in Japan: Data from the NinJa study. Mod Rheumatol. 2024;34:881\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmolen JS, Pangan AL, Emery P, Rigby W, Tanaka Y, Vargas JI, et al. Upadacitinib as monotherapy in patients with active rheumatoid arthritis and inadequate response to methotrexate (SELECT-MONOTHERAPY): a randomised, placebo-controlled, double-blind phase 3 study. Lancet. 2019;393:2303\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleischmann R, Schiff M, van der Heijde D, Ramos-Remus C, Spindler A, Stanislav M, et al. Baricitinib, methotrexate, or combination in patients with rheumatoid arthritis and no or limited prior disease-modifying antirheumatic drug treatment. Arthritis Rheumatol. 2017;69:506\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdwards CJ, Kr\u0026ouml;nke G, Avouac J, Li Z, Conti F, Balsa A, et al. Baricitinib Dose Reduction in Patients With Rheumatoid Arthritis Achieving Sustained Disease Control: Final Results From the RA-BEYOND Study. J Rheumatol. 2025;52:316\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoshida Y, Tsujii A, Ohshima S, Saeki Y, Yagita M, Miyamura T, et al. Effect of Recent Antirheumatic Drug on Features of Rheumatoid Arthritis\u0026ndash;Associated Lymphoproliferative Disorders. Arthritis Rheum. 2025;76:869\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsui T, Kuga Y, Kaneko A, Nishino J, Eto Y, Chiba N, et al. Disease Activity Score 28 (DAS28) using C-reactive protein underestimates disease activity and overestimates EULAR response criteria compared with DAS28 using erythrocyte sedimentation rate in a large observational cohort of rheumatoid arthritis patients in Japan. Ann Rheum Dis. 2007;66:1221\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShoda H, Matsui T, Tohma S, Sawada T. Evaluation of patient-based disease activity score (PDAS) in the Japanese rheumatoid arthritis patient registry (NinJa registry). Rheumatology (Oxford). 2025;64:3415\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShoda H, Yamamoto Y, Matsui T, Tohma S, Sawada T. Glucocorticoid Sparing in Rheumatoid Arthritis Patients Treated with Janus Kinase Inhibitors: Insights from the Japanese Patient Registry. Sci Rep. 2026. Accepted. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-026-43504-w\u003c/span\u003e\u003cspan address=\"10.1038/s41598-026-43504-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO III, et al. 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Anna Rheum Dis. 2010;69:1580\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStenbrocker O, Traeger CH, Batterman RC. Therapeutic criteria in rheumatoid arthritis. J Am Med Assoc. 1949;140:659\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoodworth T, Furst DE, Alten R, Bingham CO 3rd, Yocum D, Sloan V, et al. Standardizing assessment and reporting of adverse effects in rheumatology clinical trials II: the Rheumatology Common Toxicity Criteria v.2.0. J Rheumatol. 2007;34:1401\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Stat Med. 2008;27:2037\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao QY, Luo JC, Su Y, Zhang YJ, Tu GW, Luo Z. Propensity score matching with R: conventional methods and new features. Ann Transl Med. 2021;9:812.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun X, Li R, Cai Y, Al-Herz A, Lahiri M, Choudhury MR, et al. Clinical remission of rheumatoid arthritis in a multicenter real-world study in Asia-Pacific region. Lancet Reg Health West Pac. 2021;15:100240.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhader Y, Beran A, Ghazaleh S, Lee-Smith W, Altorok N. Predictors of remission in rheumatoid arthritis patients treated with biologics: a systematic review and meta-analysis. Clin Rheumatol. 2022;41:3615\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePope JE, Movahedi M, Rampakakis E, Cesta A, Sampalis JS, Keystone E, et al. ACPA and RF as predictors of sustained clinical remission in patients with rheumatoid arthritis: data from the Ontario Best practices Research Initiative (OBRI). RMD Open. 2018;4:e000738.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J, et al. pROC: an open-source package for R and S\u0026thinsp;+\u0026thinsp;to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleischmann R, Mysler E, Hall S, Kivitz AJ, Moots RJ, Luo Z, et al. Efficacy and Safety of Tofacitinib Monotherapy, Tofacitinib With Methotrexate, and Adalimumab With Methotrexate in Patients With Rheumatoid Arthritis (ORAL Strategy): A Phase 3b/4, Double-Blind, Head-To-Head, Randomised Controlled Trial. Lancet. 2017;390:457\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleischmann R, Takeuchi T, Schiff M, Schlichting D, Xie L, Issa M, et al. Efficacy and Safety of Long-Term Baricitinib With and Without Methotrexate for the Treatment of Rheumatoid Arthritis: Experience With Baricitinib Monotherapy Continuation or After Switching From Methotrexate Monotherapy or Baricitinib Plus Methotrexate. Arthritis Care Res. 2020;72:1112\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEbina K, Etani Y, Okita Y, Tsujimoto K, Maeda Y, Noguchi T, et al. Differential Impact of Concomitant Methotrexate and Glucocorticoids Dosages on Biologics and JAK Inhibitors: The ANSWER Cohort Study. Int J Rheum Dis. 2025;28:e70351.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlaesener S, Qu\u0026aacute;ch TD, Onken N, Weller-Heinemann F, Dressler F, Huppertz HI, et al. Distinct Effects of Methotrexate and Etanercept on the B Cell Compartment in Patients With Juvenile Idiopathic Arthritis. Arthritis Rheum. 2014;66:2590\u0026ndash;600.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Ouwerkerk L, Verschueren P, Boers M, Emery P, de Jong PHP, Landewe RBM, et al. Initial glucocorticoid bridging in rheumatoid arthritis: does it affect glucocorticoid use over time? Ann Rheum Dis. 2024;83:65\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantiago T, Voshaar M, de Wit M, Carvalho PD, Cutolo M, Paolino S, et al. Patients' and rheumatologists' perspectives on the efficacy and safety of low-dose glucocorticoids in rheumatoid arthritis-an international survey within the GLORIA study. Rheumatology. 2021;60:3334\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakeuchi T, Yamanaka H, Yamaoka K, Arai S, Toyoizumi S, Demasi R, et al. Efficacy and Safety of Tofacitinib in Japanese Patients With Rheumatoid Arthritis by Background Methotrexate Dose: A Post Hoc Analysis of Clinical Trial Data. Mod Rheumatol. 2019;29:756\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"arthritis-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arrt","sideBox":"Learn more about [Arthritis Research \u0026 Therapy](http://arthritis-research.biomedcentral.com/)","snPcode":"13075","submissionUrl":"https://submission.nature.com/new-submission/13075/3","title":"Arthritis Research \u0026 Therapy","twitterHandle":"@ArthritisRes","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rheumatoid arthritis (RA), Janus kinase inhibitor (JAKi), methotrexate (MTX), serious adverse event (SAE), propensity score matching","lastPublishedDoi":"10.21203/rs.3.rs-9205693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9205693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eJanus kinase inhibitors (JAKi) are effective for rheumatoid arthritis (RA) and can be used as monotherapy; however, the clinical benefit of concomitant methotrexate (MTX) and the optimal MTX dose in JAKi-treated patients remain unclear in real-world settings. In this study, we aimed to clarify the roles of MTX by comparing the patient profiles between JAKi monotherapy (Mono) and combination with MTX (Combi) using the National Database of Rheumatic Diseases in Japan (NinJa).\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eUsing the 2022 version of the NinJa database, we analyzed RA patients treated with JAKi. Patients were classified into Mono and Combi groups. Clinical characteristics, disease activity, remission rates, and hospitalization due to serious adverse events (SAEs) were compared. Multivariable logistic regression and propensity score (PS)-matched analyses were performed to adjust for confounding factors. Associations between MTX dose and disease activity were examined using correlation and multiple regression analyses.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eAmong the enrolled patients (n\u0026thinsp;=\u0026thinsp;1315), 554 (42.1%) received Combi therapy. Patients in the Combi group were younger, had shorter disease duration, and showed lower DAS28 (ESR) and HAQ scores than those in the Mono group. DAS28 (ESR)\u0026ndash;defined remission was achieved more frequently in the Combi group (50.0% vs. 38.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariable logistic regression demonstrated that MTX use was independently associated with clinical remission (odds ratio [OR], 1.47; 95% confidence interval [CI], 1.06\u0026ndash;2.04). In PS-matched analyses, Combi therapy remained associated with lower DAS28 (ESR) values and higher remission rates. MTX dose was not associated with disease activity among patients receiving Combi therapy. Hospitalization due to SAEs occurred in 11.0% of JAKi-treated patients and was not independently associated with MTX use, whereas glucocorticoid use was a significant risk factor for several SAEs.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eIn real-world clinical practice, Combi therapy with JAKi and MTX was associated with higher remission rates without increasing the risk of SAEs. However, MTX dose did not influence disease activity, suggesting that low-dose MTX may be sufficient when used in combination with JAKi. Although further studies are warranted to evaluate long-term outcomes, Combi therapy appears to be a favorable and well-tolerated option for RA management.\u003c/p\u003e","manuscriptTitle":"Comparison between Janus Kinase Inhibitor Monotherapy and Combination Therapy with Methotrexate in Patients with Rheumatoid Arthritis: Insight from the National Database of Rheumatic Diseases in Japan (NinJa) Registry","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 09:24:15","doi":"10.21203/rs.3.rs-9205693/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-05T12:08:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-03T09:10:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T16:13:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265997602950006340047246138617777362996","date":"2026-04-07T13:28:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"161642649556166376645905832098867936576","date":"2026-04-05T01:50:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T22:03:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T01:14:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-26T00:45:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"Arthritis Research \u0026 Therapy","date":"2026-03-24T02:11:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"arthritis-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arrt","sideBox":"Learn more about [Arthritis Research \u0026 Therapy](http://arthritis-research.biomedcentral.com/)","snPcode":"13075","submissionUrl":"https://submission.nature.com/new-submission/13075/3","title":"Arthritis Research \u0026 Therapy","twitterHandle":"@ArthritisRes","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33e90b1a-8622-4422-aa60-04a8f8d52b85","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-05T12:08:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-03T09:10:24+00:00","index":23,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T16:13:19+00:00","index":22,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T12:23:59+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 09:24:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9205693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9205693","identity":"rs-9205693","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}