Annals of the Rheumatic Diseases
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Published By Bmj

1468-2060, 0003-4967

2022 ◽  
pp. annrheumdis-2021-221915
Author(s):  
Farzin Khosrow-Khavar ◽  
Seoyoung C Kim ◽  
Hemin Lee ◽  
Su Been Lee ◽  
Rishi J Desai

ObjectivesRecent results from ‘ORAL Surveillance’ trial have raised concerns regarding the cardiovascular safety of tofacitinib in patients with rheumatoid arthritis (RA). We further examined this safety concern in the real-world setting.MethodsWe created two cohorts of patients with RA initiating treatment with tofacitinib or tumour necrosis factor inhibitors (TNFI) using deidentified data from Optum Clinformatics (2012–2020), IBM MarketScan (2012–2018) and Medicare (parts A, B and D, 2012–2017) claims databases: (1) A ‘real-world evidence (RWE) cohort’ consisting of routine care patients and (2) A ‘randomised controlled trial (RCT)-duplicate cohort’ mimicking inclusion and exclusion criteria of the ORAL surveillance trial to calibrate results against the trial findings. Cox proportional hazards models with propensity score fine stratification weighting were used to estimate HR and 95% CIs for composite outcome of myocardial infarction and stroke and accounting for 76 potential confounders. Database-specific effect estimates were pooled using fixed effects models with inverse-variance weighting.ResultsIn the RWE cohort, 102 263 patients were identified of whom 12 852 (12.6%) initiated tofacitinib. The pooled weighted HR (95% CI) comparing tofacitinib with TNFI was 1.01 (0.83 to 1.23) in RWE cohort and 1.24 (0.90 to 1.69) in RCT-duplicate cohort which aligned closely with ORAL-surveillance results (HR: 1.33, 95% CI 0.91 to 1.94).ConclusionsWe did not find evidence for an increased risk of cardiovascular outcomes with tofacitinib in patients with RA treated in the real-world setting; however, tofacitinib was associated with an increased risk of cardiovascular outcomes, although statistically non-significant, in patients with RA with cardiovascular risk factors.Trial registration numberNCT04772248.


2022 ◽  
pp. annrheumdis-2021-221756
Author(s):  
Peter Kvacskay ◽  
Wolfgang Merkt ◽  
Janine Günther ◽  
Norbert Blank ◽  
Hanns-Martin Lorenz

2022 ◽  
pp. annrheumdis-2021-221477
Author(s):  
Denis Mongin ◽  
Kim Lauper ◽  
Axel Finckh ◽  
Thomas Frisell ◽  
Delphine Sophie Courvoisier

ObjectivesTo assess the performance of statistical methods used to compare the effectiveness between drugs in an observational setting in the presence of attrition.MethodsIn this simulation study, we compared the estimations of low disease activity (LDA) at 1 year produced by complete case analysis (CC), last observation carried forward (LOCF), LUNDEX, non-responder imputation (NRI), inverse probability weighting (IPW) and multiple imputations of the outcome. All methods were adjusted for confounders. The reasons to stop the treatments were included in the multiple imputation method (confounder-adjusted response rate with attrition correction, CARRAC) and were either included (IPW2) or not (IPW1) in the IPW method. A realistic simulation data set was generated from a real-world data collection. The amount of missing data caused by attrition and its dependence on the ‘true’ value of the data missing were varied to assess the robustness of each method to these changes.ResultsLUNDEX and NRI strongly underestimated the absolute LDA difference between two treatments, and their estimates were highly sensitive to the amount of attrition. IPW1 and CC overestimated the absolute LDA difference between the two treatments and the overestimation increased with increasing attrition or when missingness depended on disease activity at 1 year. IPW2 and CARRAC produced unbiased estimations, but IPW2 had a greater sensitivity to the missing pattern of data and the amount of attrition than CARRAC.ConclusionsOnly multiple imputation and IPW2, which considered both confounding and treatment cessation reasons, produced accurate comparative effectiveness estimates.


2022 ◽  
pp. annrheumdis-2021-220500
Author(s):  
Changrong Ge ◽  
Sylvia Weisse ◽  
Bingze Xu ◽  
Doreen Dobritzsch ◽  
Johan Viljanen ◽  
...  

ObjectivesRheumatoid arthritis (RA) is an autoimmune disease strongly associated with the major histocompatibility complex (MHC) class II allele DRB1*04:01, which encodes a protein that binds self-peptides for presentation to T cells. This study characterises the autoantigen-presenting function of DRB1*04:01 (HLA-DRA*01:01/HLA-DRB1*04:01) at a molecular level for prototypic T-cell determinants, focusing on a post-translationally modified collagen type II (Col2)-derived peptide.MethodsThe crystal structures of DRB1*04:01 molecules in complex with the peptides HSP70289-306, citrullinated CILP982-996 and galactosylated Col2259-273 were determined on cocrystallisation. T cells specific for Col2259-273 were investigated in peripheral blood mononuclear cells from patients with DRB1*04:01-positive RA by cytofluorometric detection of the activation marker CD154 on peptide stimulation and binding of fluorescent DRB1*0401/Col2259-273 tetramer complexes. The cDNAs encoding the T-cell receptor (TCR) α-chains and β-chains were cloned from single-cell sorted tetramer-positive T cells and transferred via a lentiviral vector into TCR-deficient Jurkat 76 cells.ResultsThe crystal structures identified peptide binding to DRB1*04:01 and potential side chain exposure to T cells. The main TCR recognition sites in Col2259-273 were lysine residues that can be galactosylated. RA T-cell responses to DRB1*04:01-presented Col2259-273 were dependent on peptide galactosylation at lysine 264. Dynamic molecular modelling of a functionally characterised Col2259-273-specific TCR complexed with DRB1*04:01/Col2259-273 provided evidence for differential allosteric T-cell recognition of glycosylated lysine 264.ConclusionsThe MHC-peptide-TCR interactions elucidated in our study provide new molecular insights into recognition of a post-translationally modified RA T-cell determinant with a known dominant role in arthritogenic and tolerogenic responses in murine Col2-induced arthritis.


2022 ◽  
pp. annrheumdis-2021-221817
Author(s):  
Myrto Kostopoulou ◽  
Antonis Fanouriakis ◽  
George Bertsias ◽  
Dimitrios T Boumpas

2022 ◽  
pp. annrheumdis-2021-221558
Author(s):  
Michael Bonelli ◽  
Daniel Mrak ◽  
Selma Tobudic ◽  
Daniela Sieghart ◽  
Maximilian Koblischke ◽  
...  

ObjectivesSARS‐CoV‐2-induced COVID-19 has led to exponentially rising mortality, particularly in immunosuppressed patients, who inadequately respond to conventional COVID-19 vaccination.MethodsIn this blinded randomised clinical trial, we compare the efficacy and safety of an additional booster vaccination with a vector versus mRNA vaccine in non-seroconverted patients. We assigned 60 patients under rituximab treatment, who did not seroconvert after their primary mRNA vaccination with either BNT162b2 (Pfizer–BioNTech) or mRNA-1273 (Moderna), to receive a third dose, either using the same mRNA or the vector vaccine ChAdOx1 nCoV-19 (Oxford–AstraZeneca). Patients were stratified according to the presence of peripheral B cells. The primary efficacy endpoint was the difference in the SARS-CoV-2 antibody seroconversion rate between vector (heterologous) and mRNA (homologous) vaccinated patients by week 4. Key secondary endpoints included the overall seroconversion and cellular immune response; safety was assessed at week 1 and week 4.ResultsSeroconversion rates at week 4 were comparable between vector (6/27 patients, 22%) and mRNA (9/28, 32%) vaccines (p=0.6). Overall, 27% of patients seroconverted; specific T cell responses were observed in 20/20 (100%) vector versus 13/16 (81%) mRNA vaccinated patients. Newly induced humoral and/or cellular responses occurred in 9/11 (82%) patients. 3/37 (8%) of patients without and 12/18 (67%) of the patients with detectable peripheral B cells seroconverted. No serious adverse events, related to immunisation, were observed.ConclusionsThis enhanced humoral and/or cellular immune response supports an additional booster vaccination in non-seroconverted patients irrespective of a heterologous or homologous vaccination regimen.


2022 ◽  
pp. annrheumdis-2021-220004
Author(s):  
Jean-Baptiste Vulsteke ◽  
Yves Piette ◽  
Carolien Bonroy ◽  
Patrick Verschueren ◽  
Daniel Blockmans ◽  
...  

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