Secular trend of mortality and incidence of rheumatoid arthritis in global ,1990-2019: an age period cohort analysis and joinpoint analysis

Unlocking the Future: New Biologic Therapies for Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that leads to joint destruction and functional disability. Traditional treatments, including disease-modifying antirheumatic drugs (DMARDs), often fail, leaving many patients without remission. The advent of biologic therapies that target specific immune system components (e.g., cytokines, T cells) has transformed RA treatment by offering new management options. These biologics (e.g., TNF inhibitors, interleukin blockers) are highly effective in controlling disease activity and preventing joint destruction. However, their use comes with safety concerns, particularly regarding immunosuppression and infection risks. Although still experimental, studies predict that future research will focus on enhancing the clinical response and safety of these agents through personalized approaches or novel mechanisms of action.

Treating Cardiovascular Disease in the Inflammatory Setting of Rheumatoid Arthritis: An Ongoing Challenge

Despite progress in treating rheumatoid arthritis, this autoimmune disorder confers an increased risk of developing cardiovascular disease (CVD). Widely used screening protocols and current clinical guidelines are inadequate for the early detection of CVD in persons with rheumatoid arthritis. Traditional CVD risk factors alone cannot be applied because they underestimate CVD risk in rheumatoid arthritis, missing the window of opportunity for prompt intervention to decrease morbidity and mortality. The lipid profile is insufficient to assess CVD risk. This review delves into the connection between systemic inflammation in rheumatoid arthritis and the premature onset of CVD. The shared inflammatory and immunologic pathways between the two diseases that result in subclinical atherosclerosis and disrupted cholesterol homeostasis are examined. The treatment armamentarium for rheumatoid arthritis is summarized, with a particular focus on each medication's cardiovascular effect, as well as the mechanism of action, risk-benefit profile, safety, and cost. A clinical approach to CVD screening and treatment for rheumatoid arthritis patients is proposed based on the available evidence. The mortality gap between rheumatoid arthritis and non-rheumatoid arthritis populations due to premature CVD represents an urgent research need in the fields of cardiology and rheumatology. Future research areas, including risk assessment tools and novel immunotherapeutic targets, are highlighted.

Trends in rheumatoid arthritis associated cardiovascular mortality in the United States from 1999 to 2020

INTRODUCTION

Rheumatoid Arthritis (RA) is a risk enhancing factor for cardiovascular diseases (CVD). However, data regarding the magnitude and trends of RA associated CVD-related mortality in the United States (U.S) remains scarce.

METHODS

A retrospective analysis was conducted using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) dataset. We extracted age-adjusted mortality rates (AAMR) per 100,000 persons and calculated the annual percentage change (APC) through Joinpoint regression. The outcomes were stratified to discern temporal, sex-based, racial, and geographic patterns in RA-associated CVD mortality.

RESULTS

Between 1999 and 2020, 128,058 deaths related to CVD in RA patients aged 25 and above were recorded. The AAMR decreased from 3.50 in 1999 to 2.79 in 2020. However, sex disparities persisted, with females consistently experiencing a higher AAMR (3.35) compared to males (1.74). Non-Hispanic (NH) American Indian/Alaska Native had the highest AAMR (4.44) followed by NH White (2.83), NH Black or African American (2.47) and Hispanic or Latino (2.13), while NH Asian/Pacific Islander had the lowest AAMR (1.28). Geographically, the Midwestern region had the highest AAMR (3.12), while the Northeast had the lowest (2.19) with micropolitan (3.47) and nonmetropolitan (3.37) areas exhibiting higher AAMRs compared to large metropolitans (2.28). Notably, states with the highest AAMRs included North Dakota, South Dakota, Vermont, Minnesota and Wyoming.

CONCLUSION

Recent trends reveal an upward incline in RA-associated CVD-related mortality with profound disparities related to sex, race, geography and regions. Redressing these disparities necessitates the implementation of targeted population level interventions.

A cross-sectional study of predictive factors of health literacy among rheumatoid arthritis patients in China

Objective

To investigate the factors that influence health literacy (HL) among Chinese patients with rheumatoid arthritis (RA) and furnish theoretical underpinnings for the development of intervention strategies aimed at enhancing patients' quality of life.

Methods

From May 2022 to December 2022, a comprehensive survey was conducted among both outpatients and inpatients diagnosed with (RA) in a tertiary hospital in China. The survey utilized various instruments, including a general information questionnaire, a chronic disease patient health literacy scale, the Health Assessment Questionnaire-Disability Index (HAQ-DI), the Chinese-translated Rheumatoid Arthritis Self-Efficacy Scale, the Chinese-translated Rheumatoid Arthritis Stigma Scale, and the Chinese-translated Compliance Questionnaire for Rheumatology Treatments.

Results

The average scores of HL, self-efficacy, medication adherence, and disability index were 83.54 ± 17.43, 84.91 ± 14.37, 70.16 ± 11.24, and 0.26 ± 0.44, respectively. HL in Chinese RA patients was negatively correlated with age, erythrocyte sedimentation rate (ESR), number of tender joints, number of swollen joints, and disease activity, while positively correlated with self-efficacy and medication adherence. Age, disease activity, disability index, self-efficacy, and medication adherence are predictive factors of HL, and a predictive model has been initially constructed.

Conclusion

In the management of RA, healthcare professionals should develop and implement effective intervention measures by focusing on improving medication adherence, enhancing patients' self-efficacy, improving patients' physical function, and reducing disease activity. This will help enhance the health literacy and promote clinical outcomes in RA patients.

Treatment of Rheumatoid Arthritis Based on the Inherent Bioactivity of Black Phosphorus Nanosheets

Rheumatoid arthritis (RA) is an autoimmune disease that affects the living quality of patients, especially the elderly population. RA-related morbidity and mortality increase significantly with age, while current clinical drugs for RA are far from satisfactory and may have serious side effects. Therefore, the development of new drugs with higher biosafety and efficacy is demanding. Black phosphorus nanosheets (BPNSs) have been widely studied because of their excellent biocompatibility. Here, we focus on the inherent bioactivity of BPNSs, report the potential of BPNSs as a therapeutic drug for RA and elucidate the underlying therapeutic mechanism. We find that BPNSs inhibit autophagy at an early stage via the AMPK-mTOR pathway, switch the energy metabolic pathway to oxidative phosphorylation, increase intracellular ATP levels, suppress apoptosis, reduce inflammation and oxidative stress, and down-regulate senescence-associated secretory phenotype (SASP)-related genes in rheumatoid arthritis synovial fibroblasts (RA-SFs). Further, BPNSs induce the apoptosis of macrophages and promote their transition from the M1 to the M2 phenotype by regulating related cytokines. Significantly, the administration of BPNSs can alleviate key pathological features of RA in mice, revealing great therapeutic potential. This study provides a novel option for treating RA, with BPNSs emerging as a promising therapeutic candidate.

Development of a novel predictive model for interstitial lung disease in ANCA-associated vasculitis prognostications within the Chinese population

Antineutrophil cytoplasmic antibody vasculitis-associated interstitial lung disease (AAV-ILD) is a potentially life-threatening disease. However, very little research has been done on the condition's mortality risk. Hence, our objective is to find out the factors influencing the prognosis of AAV-ILD and employ these findings to create a nomogram model. Patients with AAV-ILD who received treatment at the First Affiliated Hospital of Zhengzhou University during the period from March 1, 2011, to April 1, 2022 were selected for this research. The development of nomogram entailed a synergistic integration of univariate, Lasso, and multivariate Cox regression analyses. Internal validation ensued through bootstrap techniques involving 1000 re-sampling iterations. Discrimination and calibration were assessed utilizing Harrell's C-index, receiver operating characteristic (ROC) curve, and calibration curve. Model performance was evaluated through integrated discrimination improvement (IDI), net reclassification improvement (NRI), and likelihood ratio test. The net benefit of the model was evaluated using decision curve analysis (DCA). A cohort comprising 192 patients was enrolled for analysis. Throughout observation period, 32.29% of the population died. Key factors such as cardiac involvement, albumin, smoking history, and age displayed substantial prognostic relevance in AAV-ILD. These factors were incorporated to craft a predictive nomogram. Impressively, the model exhibited robust performance, boasting a Harrell's C index of 0.826 and an AUC of 0.940 (95% CI 0.904-0.976). The calibration curves depicted a high degree of harmony between predicted outcomes and actual observations. Significantly enhancing discriminative ability compared to the ILD-GAP model, the nomogram was validated through the IDI, NRI, and likelihood ratio test. DCA underscored the superior predictive value of the predictive model over the ILD-GAP model. The internal validation further affirmed this efficacy, with a mean Harrell's C-index of 0.815 for the predictive model. The nomogram model can be employed to predict the prognosis of patients with AAV-ILD. Moreover, the model performance is satisfactory. In the future, external datasets could be utilized for external validation.