In this population-based cohort study on comparative osteoporotic fracture risks between different biologic diseasemodifying drugs among patients with rheumatoid arthritis (RA), we did not find a significant difference in the risk of osteoporotic fractures between RA patients receiving TNF inhibitors versus abatacept or tocilizumab. Introduction We aimed to investigate the comparative risk of osteoporotic fractures between rheumatoid arthritis (RA) patients who initiated TNF inhibitors (TNFis) versus abatacept or tocilizumab. Methods Using the Korea National Health Insurance Service datasets from 2002 to 2016, RA patients who initiated TNFis, abatacept, or tocilizumab were identified. The primary outcome was a composite end point of non-vertebral fractures and hospitalized vertebral fractures; secondary outcomes were two components of the primary outcome and fractures occurring at the humerus/forearm. Propensity score (PS) matching with a variable ratio up to 10 TNFi initiators per 1 comparator drug initiator was used to adjust for > 50 baseline confounders. We estimated hazard ratios (HRs) and 95% confidence interval (CI) of fractures comparing TNFi initiators to abatacept and to tocilizumab by Cox proportional hazard models stratified by a matching ratio. Results After PS-matching, 2307 TNFi initiators PS-matched on 588 abatacept initiators, and 2462 TNFi initiators on 640 tocilizumab initiators were included. A total of 77 fractures occurred during a mean follow-up of 454 days among TNFi and abatacept initiators and 83 fractures during 461 days among TNFi and tocilizumab initiators. The PS-matched HR (95% CI
Background:Lenabasum is an oral CB2 agonist that attenuates inflammation and fibrosis in SSc animal models and showed clinical benefit with acceptable safety in a Phase 2 trial in dcSSc.Objectives:Test efficacy and safety of lenabasum in a Phase 3 trial in dcSSc.Methods:Subjects ≥18 years old with disease duration ≤ 6 years were randomized 1:1:1 to lenabasum 5 mg, 20 mg, or placebo (PBO), all BID, with stable background immunosuppressant therapy (IST) allowed. The primary efficacy endpoint was ACR CRISS score, and secondary endpoints were ΔmRSS, ΔHAQ-DI, and ΔFVC, all at Week 52 for lenabasum 20 mg vs PBO.Results:363 adults were dosed; 37 (10%) stopped study drug early, with only 1 subject (PBO cohort) stopping due to adverse event (AE). Baseline demographics were similar among groups. Disease duration was ≤ 3 years in 60% and 66%, mean mRSS score was 22.0 and 23.3, and background IST was used by 89% and 84% of lenabasum 20 mg and PBO groups, respectively.Safety results showed serious AEs and severe AEs occurred in 9.2% and 5.8% vs 14.6% and 13.0%, respectively, of lenabasum 20 mg and PBO groups.Efficacy results (Table) demonstrated:Table 1.Primary and secondary efficacy endpoints and post-hoc analyses, Week 52Group, by IST treatmentCohortNΔmRSS, mean (SD)ΔFVC% mean (SD)ΔFVC, mL mean (SD)ΔHAQ-DI mean (SD)ACR CRISS medianmITT population, MMRM primary analysis methodAllPlacebo123-8.1 (7.72)-1.0 (8.68)-51 (317)-0.13 (0.468)0.887Lenabasum 20 mg120-6.7 (6.59)-1.6 (6.91)-78 (265)-0.13 (0.436)0.888Placebo subjects, per protocol completers, LOCFNo ISTPlacebo16-2.3 (9.4)-2.8 (7.4)-97 (244)0.12 (0.34)0.417All ISTPlacebo97-8.9 (7.07)-1.0 (9.2)-43 (330)-0.17 (0.474)0.936MMF, no other ISTPlacebo29-10.7 (8.1)-0.58 (7.1)-37 (235)-0.12 (0.456)0.935MMF ≤ 2 years, no other ISTPlacebo23-11.7 (8.1)-0.3 (6.0)-41 (197)-0.13 (0.495)0.935Non-MMF ≤ 2 yearsPlacebo24-6.7 (6.2)-1.4 (7.87)-52 (281)-0.15 (0.357)0.931Post-hoc comparisons, per protocol completers, LOCFNo ISTPlacebo16-2.3 (9.4)-2.8 (7.4)-97 (244)0.12 (0.34)0.417Lenabasum 20 mg10-6.3 (6.02)-2.3 (5.58)-99 (209)-0.06 (0.498)0.811Established IST1Placebo26-6.1 (5.35)-4.6 (10.11)-170 (350)-0.17 (0.445)0.619Lenabasum 20 mg38-7.4 (5.08)-0.4 (5.70)2-21 (233)3-0.07 (0.357)0.941Established IST, subjects with ILDPlacebo22-5.9 (5.28)-3.7 (5.43)-133 (206)-0.10 (0.372)0.553Lenabasum 20 mg33-7.2 (5.70)-1.0 (10.5)-47 (365)-0.06 (0.391)0.8192 P = 0.0386 two-sample t-test; 3 P = 0.0481 two-sample t-test; other comparisons were not significant• No significant differences were seen in primary and secondary efficacy endpoints. Primary MMRM analyses with treatment-by-time-by-subgroup interactions showed that background mycophenolate (MMF) significantly influenced the outcome•oSubjects on no IST with disease duration ≤3 years were only 7% of PBO subjects and showed little improvement on PBO, in line with other dcSSc trials in which IST was restricted. Post-hoc subgroup analyses of these subjects on no IST suggested improvement in ΔmRSS and ΔHAQ-DI, for lenabasum 20 mg vs PBO•uUnexpectedly high improvement occurred in PBO subjects receiving IST, notably those on MMF started within 2 years of baseline•nPost-hoc analyses of subjects on established IST (MMF or, if no MMF, ≥ 1 non-MMF IST started > 2 years before baseline) suggested improvement in ΔFVC% (nominal P = 0.0386) and ΔFVC mL (nominal P = 0.0481) for lenabasum 20 mg vs PBO. Improvement in FVC was also seen in subjects on established IST who had ILD at baseline, lenabasum 20 mg vs PBO•mACR CRISS score demonstrated a ceiling effect and correlated most highly with ΔmRSS (r = -0.739) and moderately with MDGA (-0.432), HAQ-DI (-0.362), FVC% (0.366), and PtGA (-0.288)Conclusion:Lenabasum was safely used in this study. Unexpectedly high improvement on background IST, especially MMF, has not been previously reported at this level. The primary endpoint was not met. Post-hoc analyses showed greater improvement in lenabasum- vs PBO-treated subjects who were not on background IST and those on established IST, including subjects with ILD.Disclosure of Interests:Robert Spiera Consultant of: Abbvie, Roche-Genetech, GSK, CSL Behring, Sanofi, Janssen, Chemocentryx, Formation Biologics, Mitsubishi Tanabe, Grant/research support from: Roche-Genetech, GSK, Boehringer Ingelheim, Chemocentryx, Corbus, Formation Biologics, Sanofi, Inflarx, Astra Zeneca, Kadmon, Masataka Kuwana Speakers bureau: Boehringer-Ingelheim, Chugai, Janssen, Consultant of: Boehringer-Ingelheim, Chugai, Corbus, Grant/research support from: Boehringer-Ingelheim, Chugai, MBL, Ono Pharmaceuticals, Tanabe-Mitsubishi, Dinesh Khanna Shareholder of: Eicos Sciences, Inc (less than 5%). Leadership/Equity position – Chief Medical Officer, CiviBioPharma/Eicos Sciences, Inc, Consultant of: Acceleron, Actelion, Abbvie, Amgen, Bayer, Boehringer Ingelheim, CSL Behring, Corbus, Gilead, Galapagos, Genentech/Roche, GSK, Horizon, Merck, Mitsubishi Tanabe Pharma, Sanofi-Aventis, and United Therapeutics, Grant/research support from: NIH, Immune Tolerance Network, Bayer, BMS, Horizon, Pfizer, Laura Hummers Consultant of: CSL Behring, Boehringer Ingelheim, Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals. Corbus, Boehringer Ingelheim, Medpace, Kadmon, Cumberland, CSL Behring, Tracy Frech Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Wendy Stevens Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Jessica Gordon Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals. Research funding for EICOS Pharmaceuticals and Cumberland Pharmaceuticals., Suzanne Kafaja Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Marco Matucci-Cerinic Consultant of: Actelion, Janssen, Inventiva, Bayer, Biogen, Boehringer, CSL Behring, Corbus, Galapagos, Mitsubishi, Samsung, Regeneron, Acceleron, MSD, Chemomab, Lilly, Pfizer, Roche, Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Oliver Distler Consultant of: Consultancy relationship and/or has received research funding in the area of potential treatments for systemic sclerosis and its complications from (last three years): Abbvie, Acceleron Pharma, Amgen, AnaMar, Arxx Therapeutics, Baecon Discovery, Blade Therapeutics, Bayer, Boehringer Ingelheim, ChemomAb, Corbus Pharmaceuticals, CSL Behring, Galapagos NV, Glenmark Pharmaceuticals, GSK, Horizon (Curzion) Pharmaceuticals, Inventiva, iQvia, Italfarmaco, iQone, Kymera Therapeutics, Lilly, Medac, Medscape, Mitsubishi Tanabe Pharma, MSD, Novartis, Pfizer, Roche, Sanofi, Serodapharm, Topadur, Target Bioscience and UCB., Eun Bong Lee Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Yair Levy Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Jae-Bum Jun Consultant of: Consultant to Boehringer Ingelheim Korea, Jeil Pharma, Dae Woong Pharma, Kwangdong Pharma, and Sama Pharma., Grant/research support from: Investigator for study sponsored by Corbus Pharmaceuticals, Scott Constantine Employee of: Employee of Corbus Pharmaceuticals, Nancy Dgetluck Employee of: Employee of Corbus Pharmaceuticals, Barbara White Employee of: Employee and stockholder of Corbus Pharmaceuticals, Daniel Furst Consultant of: Corbus, Galapagos, Pfizer, CSL Behring, Mitsubishi Tanabi, Actelion, Amgen, Novartis, Roche/Genentech, Gilead, Talaris, and Boehringer Ingelheim., Grant/research support from: grants from Corbus, Galapagos, GSK, Pfizer, Talaris, CSL Behring, Mitsubishi Tanabi, Christopher Denton Consultant of: Consultancy fees and/or honoraria from Corbus, Actelion, GlaxoSmithKline, Bayer, Sanofi, Galapagos, Inventiva, Boehringer Ingelheim, Roche, CSL Behring, Acceleron, Horizon, Arxx Therapeutics
Decreased TNF-α production by circulating monocytes and CD163 overexpression by tissue monocytes/macrophages in granulomatous pulmonary lesions may suggest that monocytes/macrophages are alternatively activated in GPA.
Background Previous genome wide association studies (GWASs) have demonstrated the association between IL-10 region and Behcet’s disease (BD) in Turkish and Japanese populations. However, our recent GWAS result obtained from a Korean population [1] did not replicate this finding, suggesting a significant ethnic difference in genetic susceptibility for BD. Objectives To fully examine the relationship between IL-10 and BD, the associations between BD and single nucleotide polymorphisms (SNPs) in IL-10 mediated signaling pathways were examined in Korean BD patients. Methods DNA samples were obtained from 181 patients who met the international study group criteria for BD and 181 age- and sex-matched healthy controls. Eighteen tag SNPs in JAK1 (rs17127024, rs310245, rs2991269, rs2230587, rs2780898, rs2274948, rs310222, rs2256298, rs3818753, rs2780831, rs10889502, rs12563017, rs11208537, rs11208538, rs1353595, rs17127171, rs7553101, and rs4244165), five in TYK2 (rs34536443, rs12720356, rs2304256, rs280523, and rs12720217), and five in STAT3 (rs3744483, rs2293152, rs6503695, rs744166, and rs12948909) selected using the Japanese panel of international HapMap data with a minor allele frequency of more than 5% and with r2 > 0.8 were genotyped using PCR and RFLP method. Results The mean (± standard deviation) age of BD patients was 43.4 ± 10.3 years. Eighty five (47.0%) patients were male. The mean age and gender distribution of controls were similar. Genetic loci with a deviation from Hardy-Weinberg equilibrium in controls (rs11208538 in JAK1), or without any polymorphism in study subjects (rs34536443 and rs12720356 in TYK2) were not included in the analysis. The frequency of C allele at rs12948909 in STAT3 was higher in BD patients than in controls (odds ratio = 1.54, 95% confidence interval [1.00-2.38], p = 0.047), which, however, lost statistical significance after permutation-based correction for multiple testing. No significant associations were found between alleles of the rest 24 SNPs and BD. In addition, there was no genotype found to have a significant association with BD. In linkage disequilibrium (LD) analysis, eight haplotypes from two LD blocks in JAK1 and three haplotype from one LD block in STAT3 were identified but showed no association with BD. Conclusions Together with our GWAS finding, the result of this study further suggests that genetic dysregulation of IL-10 or IL-10 mediated intracellular signaling is not a predominant pathogenic mechanism for BD in Koreans. References Lee YJ, Horie Y, Wallace GR, Choi YS, Park JA, Song R, Kang YM, Kang SW, Baek HJ, Kitaichi N, Meguro A, Mizuki N, Namba K, Ishida S, Kim J, Niemczek E, Lee EY, Song YW, Ohno S, Lee EB. Genome-wide association study identifies GIMAP as a novel susceptibility locus for Behcet’s disease. Ann Rheum Dis. 2012 Oct 6. [Epub ahead of print] Disclosure of Interest None Declared
BackgroundWith the increasing number of treatment options for rheumatoid arthritis (RA), safety is one of the important consideration for decision-making.ObjectivesTo compare infectious risk between JAK inhibitors (JAKi) versus TNF inhibitors (TNFi) among patients with RA in Korea.MethodsUsing 2009-2019 Korea National Health Insurance Service database, we conducted a cohort study on RA patients initiating JAKi or TNFi. The outcomes of interest were 1) serious bacterial, 2) opportunistic, and 3) herpes zoster infections. Propensity-score fine-stratification (PSS) based weighting was applied to adjust for >60 baseline covariates. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazard models comparing JAKi versus TNFi users.ResultsAmong 2,967 JAKi initiators and 13,152 TNFi initiators, 2,963 JAKi initiators PSS-weighted on 5,169 TNFi initiators were included. During a mean follow-up of 1.16 years, the most frequent type of infections was herpes zoster with an incidence rate (IR) per 100 person-years of 11.54 and 4.88 in JAKi and TNFi users, respectively, followed by serious bacterial infections with an IR of 1.39 and 1.32, respectively. The opportunistic infection was rare with a majority being tuberculosis, and showed an IR of 0.12 and 0.49 in JAKi and TNFi users, respectively. The PSS-weighted HR [95% CI] for individual types of infections was 2.37 [2.00-2.80] for herpes zoster, 1.04 [0.71-1.52] for serious bacterial infections, and 0.25 [0.09-0.73] for opportunistic infections, comparing JAKi to TNFi initiators. The risk of hospitalized herpes zoster was even higher among JAKi than TNFi initiators with a HR of 7.43 [3.91-14.11].ConclusionIn this nationally-representative cohort study on RA patients, we found an exceptionally high IR of herpes zoster among JAKi initiators in Korea, showing a doubled risk compared to that in TNFi initiators. Although the risk of serious bacterial infections was comparable between the two treatment groups, the risk of opportunistic infections, particularly tuberculosis, was less among JAKi than TNFi initiators.Reference[1]Smolen JS, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Ann Rheum Dis. 2020;79(6):685-99.Table 1.JAK inhibitor n = 2 963TNF inhibitor (Ref)n = 5 169HR [95% CI]EventsPYaIR [95% CI]EventsPYaIR [95% CI]As-treated analysisSerious bacterial infection4834451.39 [1.03-1.85]6146291.32 [1.01-1.69]1.04 [0.71-1.52]Opportunistic infection434890.11 [0.03-0.29]2346860.49 [0.31-0.74]0.25 [0.09-0.73]Herpes zoster361312811.54 [10.38-2.80]22145284.88 [4.26-5.57]2.37 [2.00-2.80]Serious zoster6234351.81 [1.38-2.31]1146820.24 [0.12-0.42]7.43 [3.91-14.11]365-day ITTSerious bacterial infection3622601.59 [1.12-2.21]6141331.48 [1.13-1.90]1.08 [0.72-1.63]Opportunistic infection322740.13 [0.03-0.39]1641550.39 [0.22-0.63]0.35 [0.10-1.20]Herpes zoster242217311.14 [9.78-12.63]21140725.18 [4.51-5.93]2.15 [1.79-2.59]Serious zoster3722631.64 [1.15-2.25]1241560.29 [0.15-0.50]5.77 [3.00-11.12]aIR is per 100 person-years.Acknowledgements:NIL.Disclosure of InterestsNone Declared.
BackgroundPrevious studies have suggested that primary prophylaxis against pneumocystis pneumonia (PCP) using trimethoprim-sulfamethoxazole (TMP-SMX) is beneficial in patients with rheumatologic diseases receiving immunosuppressive drugs[1]. However, there is little evidence for an optimal prophylaxis duration or a time point of prophylaxis withdrawal.ObjectivesThis study aims to investigate the risk factors that are associated with PCP occurrence despite its primary prophylaxis, and, ultimately, to provide evidence regarding the ideal schedule for primary PCP prophylaxis.MethodsThis case-control study included treatment episodes of patients with rheumatic diseases who received prophylactic TMP-SMX with immunosuppressive treatment between 2010 and 2022 in a tertiary referral center in South Korea. The index date was defined as the date of starting the prophylactic dose of TMP-SMX. We captured PCP cases that occurred within 1 year from the index date based on the review of the medical record by two independent expert investigators. The effect of clinical factors, such as demographics, underlying disease, immunosuppressive treatment, and pattern of prophylaxis on the PCP occurrence was examined using binary logistic regression.ResultsA total of 1,379 treatment episodes were analyzed, and eleven cases of PCP occurred during the observation—a one-year PCP incidence of 0.80 (95% CI=0.40-1.43) per 100 person-years. In 10 cases (90.9%), PCP occurred after discontinuation of TMP-SMX prophylaxis, with a mean (SD) interval of 185.6 (90.9) days. The mean (SD) duration of prophylaxis in the PCP group was 108.5 (132.3) days. The main reasons for prophylaxis withdrawal in the PCP group were adverse events (5 cases) and treating physicians’ decisions (5 cases). The dose of glucocorticoid at the time of prophylaxis cessation was the most critical risk factor for PCP. Patients who were receiving glucocorticoid more than 15 mg/day of prednisone equivalent at the time of TMP-SMX discontinuation showed a significantly higher odds of developing PCP (OR=15.06; 95% CI=1.92-117.94). The prophylaxis duration and presence of structural lung disease were not associated with PCP. This result was consistent in the multivariable analysis adjusted for age, underlying disease, rituximab treatment, azotemia, and lymphopenia (adjusted OR=12.21; 95% CI=1.52-98.24) (Table 1).ConclusionDiscontinuation of TMP-SMX during glucocorticoid treatment greater than 15 mg of prednisone equivalent significantly increases the risk of PCP, which suggests that a time when glucocorticoids are tapered to less than 15mg/day of prednisone dosage equivalent may be a reasonable time to consider withdrawing PCP prophylaxis.Reference[1]Park JW, Curtis JR, Moon J, Song YW, Kim S, Lee EB. Prophylactic effect of trimethoprim-sulfamethoxazole for pneumocystis pneumonia in patients with rheumatic diseases exposed to prolonged high-dose glucocorticoids. Ann Rheum Dis. 2018;77(5):644-9.Table 1.Factors associated with PCP despite primary prophylaxisUnivariableMultivariableOR (95% CI)POR (95% CI)PAge1.06 (1.01-1.11)0.021.05 (0.10-1.10)0.08Sex, female0.71 (0.22-2.35)0.58SLE0.34 (0.04-2.64)0.30AAV4.19 (1.27-13.84)0.020.50 (0.08-3.07)0.46Other vasculitis0.65 (0.14-3.02)0.58Inflammatory myopathies0.55 (0.07-4.33)0.57Rheumatoid arthritis3.01 (0.38-24.03)0.30Others3.81 (0.47-30.57)0.21Rituximab6.03 (1.82-19.99)<0.014.06 (0.87-18.99)0.08Cyclophosphamide1.55 (0.41-5.87)0.52Mycophenolate mofetil0.99 (0.13-7.76)0.99Azathioprine1.00 (0.13-7.90)1.00Prophylaxis duration0.10 (0.99-1.00)0.16Last Gc dose ≤ 15 mg15.06 (1.92-117.94)0.0112.21 (1.52-98.24)0.02Azotemia9.88 (2.13-45.94)0.007.04 (1.31-37.71)0.02Lymphopenia5.18 (1.51-17.81)0.013.13 (0.86-11.39)0.08Structural lung disease2.34 (0.71-7.70)0.16* Adjusted for clinical factors with relevant association (P < 0.1) in univariable analysisAAV, ANCA associated vasculitis; Gc, glucocorticoid; SLE, systemic lupus erythematosusAcknowledgements:NIL.Disclosure of InterestsNone Declared.
Background There are currently limited treatment options for rheumatoid arthritis (RA) patients with chronic hepatitis B (CHB). Numerous recommendations or consensus have been published for selecting conventional and biologic disease modifying anti-rheumatic agents (DMARDs) for these patients. However, there is limited data demonstrating what DMARDs are practically prescribed within the population of an endemic region of CHB. Objectives To study the prescription characteristics of conventional and biologic DMARDs, as well as the rate of combination of anti-viral agents in RA patients with CHB in Korea. Methods We analyzed the Korean National Health Insurance claims database (2007-2009) of RA patients through the co-work with Korean Health Insurance Review and Assessment Service. Patients with CHB were defined by an algorithm including prescription information, blood tests, and the ICD-10 code. Among biologic DMARDs, data of etanercept, adalimumab, infliximab, and rituximab data were only available during the study period. Results There were 8,677 CHB patients (3.8%) among 226,592 RA patients in the database. The age distribution or gender difference in CHB patients was comparable to the general RA population. Hydroxychloroquine was the most frequently (66.2%) prescribed DMARD. Thirty four percent of CHB patients had been prescribed with methotrexate (MTX) during the study period, only 7.6% with concomitant anti-viral treatment. About 3% of RA patients with CHB were prescribed with TNF inhibitors, which was significantly lower compared with the rate in the general RA population in Korea. Conclusions MTX is yet one of the DMARDs frequently prescribed to Korean RA patients with CHB. Our data also indicate that biologic DMARDs are indeed seldom prescribed in this particular subgroup of patients. Disclosure of Interest None Declared
BackgroundUnderstanding the dynamics of humoral immunity after COVID-19 vaccination is crucial in developing vaccination strategies. Antibody response patterns are more complex in patients with rheumatoid arthritis (RA) because of their underlying autoimmunity and immunosuppressive medications. The kinetics of vaccine response in RA patients are not well understood.ObjectivesTo construct a model of antibody response to COVID-19 vaccination in patients with RA.MethodsTwo patient groups were included for the study. The first group was composed of RA patients who were enrolled for influenza vaccination study between Oct 6, 2021 and November 3, 2021, in whom serial serum samples were obtained 0, 4, 16 weeks after vaccination. The second group was consecutively enrolled from outpatient clinic between October 6, 2021 and June 3, 2022, in whom serum sample was obtained once. After collecting data on demographics, vaccination and infection history of COVID-19 were obtained by self-report via questionnaire and data from Korean center for disease control. We then measured antibody titers against receptor binding domain of spike protein (anti-RBD) and nucleocapsid (anti-N), using Chemiluminescence microparticle immunosaasy (Abbott, USA) and Electrochemiluminescence immunoassay (Roche, Germany) respectively. The anti-RBD titer was log-transformed to improve normality. Time from vaccination and log of anti-RBD titer was modeled using fractional polynomial. Covariates including age, sex, BMI, underlying disease and immunosuppressive drugs were analyzed using Generalized Estimating Equations to account for repeated measured from a subject.ResultsA total of 736 patients (1042 samples) were enrolled. After excluding patients who experienced COVID-19 infection before sampling (n=84), those unvaccinated (n=44) and uncertain COVID-19 infection history (n=59), the data on 778 samples from 549 patients were analyzed (Group 1: 125, Group 2: 424). Antibody titer reached peak at 12 days after vaccination and decreased exponentially (Figure 1) which fell to 36.5% from peak after 2 months. Compared to the first vaccination, the 3rd and 4th vaccination significantly shifted anti-RBD antibody response curve (28 times, 95% CI 4~195; 32 times 95% CI 4~234, respectively). However, there was no significant shift after the 4th vaccination from the 3rd vaccination (p=0.6405). Multivariable analysis showed that number of vaccinations and sulfasalazine (coefficient: 0.40, 95% CI 0.12~0.68) increased vaccine response but age (coefficient: -0.03, 95% CI -0.04~-0.02), abatacept (coefficient: -2.07, 95% CI -3.30~-0.84) and, JAK inhibitor (coefficient: -0.82, 95% CI -1.34~-0.31) decreased vaccine response.ConclusionAnti-RBD response to COVID-19 vaccination showed a peak at 12 days after vaccination and then exponentially decreased in patient with RA. The antibody response is affected by age and medications used for the treatment of RA.Table 1.ln[RBD (U/ml)]coefficient(univariable)95% CIp-valuecoefficient(multivariable)95% CIp-valuesex (female)0.17-0.22, 0.550.393---age-0.02-0.03, -0.01<.001**-0.03-0.04, -0.02<.001**DM0.11-0.27, 0.500.568---HTN-0.38-0.69, -0.070.018*---CKD0.680.07, 1.290.030*---RA duration (yr)-0.04-0.06, -0.010.001**---Pd (mg/d)-0.06-0.11, 0.000.035*---MTX use-0.23-0.52, 0.050.105---HCQ use0.01-0.28, 0.290.965---SSZ use0.450.07, 0.840.022*0.400.12,0.680.005**LEF use0.00-0.37, 0.370.988---TNF inhibitors use0.29-0.16, 0.730.208---Abatacept use-2.07-3.14, -0.99<.001**-2.07-3.30, -0.840.001**JAK inhibitors use-0.88-1.52, -0.240.007**-0.82-1.34, -0.310.002**Time (months)log(t)-1.96-2.37, -1.54<.001**-1.90-2.29, -1.50<.001**t^(-0.5)-2.45-3.30, -1.60<.001**-2.40-3.21, -1.60<.001**Vaccination dose21.95-0.26, 4.150.0841.77-0.16, 3.710.07233.471.26, 5.680.002**3.331.40, 5.270.001**43.471.20, 5.740.003**3.461.48, 5.450.001**Figure 1.AcknowledgementsThis work was supported by a National Research Foundation of Korea (NRF) grant funded by the government of Korea (Ministry of Science and ICT) (grant number: 2021R1A2C2004874).Disclosure of InterestsNone Declared.
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