Number Of Rheumatoid Arthritis Research Articles

Surgical intervention for patients with rheumatoid arthritis is declining except for foot and ankle surgery: A single-centre, 20-year observational cohort study.

A global downward trend in the number of rheumatoid arthritis (RA)-related surgeries has been reported. The purpose of our study was to investigate the latest trends in RA-related surgeries in a single-centre Japanese RA cohort. This study was a retrospective analysis of RA-related surgeries between 2001 and 2020 in the Institute of Rheumatology Rheumatoid Arthritis cohort. An average of 4944 patients per semi-annual survey was included in the study. The primary goal was to analyse the half-year period prevalence proportion (HPP) of RA-related surgeries in a 20-year period, and the secondary goal was to analyse the HPP of surgeries by site or by categories of disease activity. There has been a downward trend in the HPP of RA-related surgeries in the 20-year study period. The total HPP of RA-related surgeries decreased by 50.3% during the 20-year study period. There was a significant decrease in knee, hip, shoulder/elbow, and hand procedures. Only foot/ankle joint surgeries significantly increased in volume during this period (p = .001). The HPP of RA-related surgeries remained unchanged in patients with remission or low disease activity. The number of RA-related surgeries decreased over a 20-year period, but foot/ankle joint surgeries increased in the site-specific evaluation.

Machine learning-based prediction model for responses of bDMARDs in patients with rheumatoid arthritis and ankylosing spondylitis

BackgroundFew studies on rheumatoid arthritis (RA) have generated machine learning models to predict biologic disease-modifying antirheumatic drugs (bDMARDs) responses; however, these studies included insufficient analysis on important features. Moreover, machine learning is yet to be used to predict bDMARD responses in ankylosing spondylitis (AS). Thus, in this study, machine learning was used to predict such responses in RA and AS patients.MethodsData were retrieved from the Korean College of Rheumatology Biologics therapy (KOBIO) registry. The number of RA and AS patients in the training dataset were 625 and 611, respectively. We prepared independent test datasets that did not participate in any process of generating machine learning models. Baseline clinical characteristics were used as input features. Responders were defined as those who met the ACR 20% improvement response criteria (ACR20) and ASAS 20% improvement response criteria (ASAS20) in RA and AS, respectively, at the first follow-up. Multiple machine learning methods, including random forest (RF-method), were used to generate models to predict bDMARD responses, and we compared them with the logistic regression model.ResultsThe RF-method model had superior prediction performance to logistic regression model (accuracy: 0.726 [95% confidence interval (CI): 0.725–0.730] vs. 0.689 [0.606–0.717], area under curve (AUC) of the receiver operating characteristic curve (ROC) 0.638 [0.576–0.658] vs. 0.565 [0.493–0.605], F1 score 0.841 [0.837–0.843] vs. 0.803 [0.732–0.828], AUC of the precision-recall curve 0.808 [0.763–0.829] vs. 0.754 [0.714–0.789]) with independent test datasets in patients with RA. However, machine learning and logistic regression exhibited similar prediction performance in AS patients. Furthermore, the patient self-reporting scales, which are patient global assessment of disease activity (PtGA) in RA and Bath Ankylosing Spondylitis Functional Index (BASFI) in AS, were revealed as the most important features in both diseases.ConclusionsRF-method exhibited superior prediction performance for responses of bDMARDs to a conventional statistical method, i.e., logistic regression, in RA patients. In contrast, despite the comparable size of the dataset, machine learning did not outperform in AS patients. The most important features of both diseases, according to feature importance analysis were patient self-reporting scales.

Understanding Chinese Medicine Patterns of Rheumatoid Arthritis and Related Biomarkers.

Background: A considerable number of Rheumatoid Arthritis (RA) patients only experience side effects from treatment, with little to no actual pain relief. The combination of disease diagnosis in biomedicine and multi-disciplinary integrative approaches such as Chinese Medicine (CM), can help to identify different functional diagnosis of RA in the context of biomarker discovery. We aimed to analyse CM patterns in RA and their biomarker profiles. Methods: Four electronic databases (web of science, CINAHL, Scopus and PubMed) were searched. The reference list of all identified reports and articles were searched for additional studies. All study designs were included and no date limits were set. Studies were considered if they were published in English and explored the possible biomarkers profiles in RA patients, classified according to the American College of Rheumatology and categorized in CM as either cold, heat/hot or deficiency patterns. Methodological quality of included studies was assessed using checklists adapted from the ©Critical Appraisal Skills Programme by two independent reviewers. A narrative synthesis was conducted, using thematic analysis. Results: A total of 10 articles were included. The studies examined 77 healthy volunteers and 1150 RA patients categorized as cold, heat/hot or deficiency pattern and related biomarkers were identified individually or concomitantly. Conclusions: CM pattern differentiation based on clinical signs and symptoms showed a diverse range of biomolecules, proteins and genes from RA patients correlated well with cold, heat/hot or deficiency phenotype-based CM patterns and could be used as diagnostic biomarkers for early detection, disease monitoring and therapeutic targets.

Etanercept induced organizing pneumonia in a patient with rheumatoid arthritis

TNF inhibitors are being used in a rapidly expanding number of rheumatoid arthritis (RA) patients due to their effectiveness and acceptable safety profiles. To date, concerns regarding the adverse effects of TNF inhibitors have focused on infections, hematologic malignancies, and demyelinating disorders. Recently, the development of autoantibodies and other autoimmunity has been increasingly reported. Here, we describe a 36-year-old RA patient in whom organizing pneumonia and systemic lupus erythematosus were detected during etanercept treatment.

Analysis of the peptidylarginine deiminase V gene in rheumatoid arthritis

A number of rheumatoid arthritis (RA) sera contain antibodies specific for peptides in which arginine is substituted by the deiminated form citrulline (AKA). These antibodies are a marker of RA, as they are absent in other disorders. The enzyme responsible for the generation of citrulline residues, peptidylarginine deiminase (PAD), has different isoforms, with a specific tissue distribution. PAD V, expressed in monocytes, might be responsible for the deimination of arginine residues of synovial proteins and thus be involved in the generation of epitopes for RA-specific antibodies. The ECRAF genome scan showed suggestive linkage evidence at PAD V locus on chromosome 1 (P < 0.005). We decided to analyze PAD V as a candidate gene for RA, studying a cohort of 100 RA patients (tested for AKA) and their unaffected parents. Investigation (by single-strand conformation polymorphism [SSCP] analysis and sequencing) of the 16 exons, 5' and 3' regions of the PAD V gene provided polymorphisms in the 5', exons 3, 4, and 7 and 3' regions. Analysis used the transmission disequilibrium test and the haplotype relative risk for alleles and haplotypes with Analyze and Genhunter2 programs. We found an association between RA and one PAD V haplotype (38% in RA versus 17% in controls) (P < 0.007). The association was also observed in the AKA+ RA subgroup (41%) (P < 0.03). In conclusion, the PAD V gene may be considered one of the genetic factors that confer susceptibility to RA. Studies are in progress to clarify the relationship between the PAD V haplotypes, the enzyme activity and the production of anticitrulline antibodies.