Impact of rheumatoid arthritis on work capacity impairment and its predictors

Employment of patients with rheumatoid arthritis - a systematic review and meta-analysis

BACKGROUND

Patients with rheumatoid arthritis (RA) have difficulties maintaining employment due to the impact of the disease on their work ability. This review aims to investigate the employment rates at different stages of disease and to identify predictors of employment among individuals with RA.

METHODS

The study was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines focusing on studies reporting employment rate in adults with diagnosed RA. The literature review included cross-sectional and cohort studies published in the English language between January 1966 and January 2023 in the PubMed, Embase and Cochrane Library databases. Data encompassing employment rates, study demographics (age, gender, educational level), disease-related parameters (disease activity, disease duration, treatment), occupational factors, and comorbidities were extracted. Quality assessment was performed employing Newcastle-Ottawa Scale. Meta-analysis was conducted to ascertain predictors for employment with odds ratios and confidence intervals, and test for heterogeneity, using chi-square and I2-statistics were calculated. This review was registered with PROSPERO (CRD42020189057).

RESULTS

Ninety-one studies, comprising of a total of 101,831 participants, were included in the analyses. The mean age of participants was 51 years and 75.9% were women. Disease duration varied between less than one year to more than 18 years on average. Employment rates were 78.8% (weighted mean, range 45.4-100) at disease onset; 47.0% (range 18.5-100) at study entry, and 40.0% (range 4-88.2) at follow-up. Employment rates showed limited variations across continents and over time. Predictors for sustained employment included younger age, male gender, higher education, low disease activity, shorter disease duration, absence of medical treatment, and the absence of comorbidities. Notably, only some of the studies in this review met the requirements for high quality studies. Both older and newer studies had methodological deficiencies in the study design, analysis, and results reporting.

CONCLUSIONS

The findings in this review highlight the prevalence of low employment rates among patients with RA, which increases with prolonged disease duration and higher disease activity. A comprehensive approach combining clinical and social interventions is imperative, particularly in early stages of the disease, to facilitate sustained employment among this patient cohort.

A longitudinal study of distress symptoms and work impairment in immune-mediated inflammatory diseases

OBJECTIVE

We investigated the association between distress symptoms (pain, fatigue, depression, anxiety) and work impairment in four patient populations: multiple sclerosis (N = 107), rheumatoid arthritis (N = 40), inflammatory bowel disease (N = 136) and psychiatric disorders (N = 167).

METHODS

Four waves of data collection were completed over three years. The relationship between distress symptoms and overall work impairment was evaluated with univariate and multivariable quantile logistic regression at the 25th, 50th and 75th percentiles. Models were fit to participant average scores and change scores on distress symptom measures. Covariates included sociodemographic factors, comorbidity, physical disability and cognitive function.

RESULTS

In the primary univariate analyses of overall work impairment at the 50th percentile, greater severity of distress symptoms was associated with greater work impairment: pain (average β = 0.27, p < 0.001; change β = 0.08, p < 0.001), fatigue (average β = 0.21, p < 0.001; change β = 0.09, p < 0.001) depression (average, β = 0.35, p < 0.001; change, β = 0.16, p < 0.001), anxiety (average, β = 0.24, p < 0.001; change, β = 0.08, p < 0 0.01). Findings were similar in multivariable analyses.

CONCLUSION

Pain, fatigue, depression, and anxiety symptoms are important determinants of work impairment in persons with immune-mediated diseases and persons with psychiatric disorders. Successful clinical management of these symptoms has potential to improve work-related outcomes across IMIDs.

Effect of a combination of Atractylodes macrocephala extract with strychnine on the TLR4/NF-κB/NLRP3 pathway in MH7A cells

Rheumatoid arthritis (RA) is now widely recognized as a chronic systemic inflammatory autoimmune disease characterized by swelling, pain and stiffness, which are often disabling. Although the number of drugs available for the treatment of RA has increased in recent years, they are generally expensive, leave patients prone to relapse and can result in severe effects when discontinued. Thus, there is a need for an inexpensive drug with fewer side effects that can be adhered to relieve pain and slow down the progression of the disease. Strychnine, a traditional Chinese medicine, was often used in ancient times to treat swollen and painful joints; however, because of its somewhat toxic nature, it is often combined with Atractylodes macrocephala to reduce its toxicity for safer therapeutic action. The present study performed high-performance liquid chromatography (HPLC)-tandem mass spectrometry (MS/MS) analysis to confirm whether the use of strychnine with Atractylodes macrocephala had the effect of reducing strychnine content. MH7A cells were induced using IL-1β to study the effect of strychnine with Atractylodes macrocephala on the Toll-like receptor 4 (TLR4)/NF-κB/NLR family pyrin domain-containing 3 (NLRP3) pathway in order to verify its role in the treatment of RA. The results indicated that the combined application of HPLC-MS/MS strychnine and Atractylodes macrocephala had a reducing effect on the strychnine content. From the subsequent experimental results, it can be inferred that Strychnine combined with Atractylodes macrocephala extract could promote the apoptosis of synovial cells, and could inhibit the expression levels of TLR4, NF-κB and NLRP3 in the cells as well as reducing the MH7A-positive cells. The expression levels of TLR4, IκB kinase β, NF-κB and NLRP3 were significantly reduced after treatment with each administration group, resulting in a decrease in the phosphorylation levels of TLR4 and NF-κB, indicating that the combination potently inhibited their phosphorylation. The combination of strychnine and atractylenolide II was also revealed to be the main active ingredient in the treatment of RA.

Tolerogenic dendritic cells alleviate collagen-induced arthritis by forming microchimerism and affecting the expression of immune checkpoint molecules

Tolerogenic dendritic cells (tolDCs) have the potential to treat rheumatoid arthritis (RA) by inducing immune tolerance. However, the mechanism of intervention needs further study. Here, we investigated whether tolDCs formed microchimerism and their effect on the expression of immune checkpoint molecules after infusion of tolDCs into rats with collagen-induced arthritis (CIA). TolDCs derived from male SD rats were labeled with fluorescence and infused into female CIA rats. The fluorescence signals as well as the sex-determining region of Y-chromosome (SRY) gene revealed that tolDCs formed microchimerism in the mesenteric lymph nodes and ankle joints. We further explored the effect of tolDCs on the expression of immune checkpoint molecules in mesenteric lymph nodes and ankle joints. For stimulatory immune checkpoint molecules, the expressions of CD86 and CD40 decreased in mesenteric lymph nodes, and the expressions of CD40, CD40L, CD28, CD80, and CD86 also decreased in rat ankle joints. In contrast, the inhibitory immune checkpoint molecule PDL1 increased in mesenteric lymph nodes, and PD1, PDL1, and CTLA4 increased in ankle joints. In conclusion, our results suggested that intervention of tolDCs in CIA is associated with the formation of microchimerism and the effect on immune checkpoints.

Machine learning approaches to improve disease management of patients with rheumatoid arthritis: review and future directions

INTRODUCTION

Although the management of rheumatoid arthritis (RA) has improved in major way over the last decades, this disease still leads to an important burden for patients and society, and there is a need to develop more personalized approaches. Machine learning (ML) methods are more and more used in health-related studies and can be applied to different sorts of data (clinical, radiological, or 'omics' data). Such approaches may improve the management of patients with RA.

AREAS COVERED

In this paper, we propose a review regarding ML approaches applied to RA. A scoping literature search was performed in PubMed, in September 2021 using the following MeSH terms: 'arthritis, rheumatoid' and 'machine learning'. Based on this search, the usefulness of ML methods for RA diagnosis, monitoring, and prediction of response to treatment and RA outcomes, is discussed.

EXPERT OPINION

ML methods have the potential to revolutionize RA-related research and improve disease management and patient care. Nevertheless, these models are not yet ready to contribute fully to rheumatologists' daily practice. Indeed, these methods raise technical, methodological, and ethical issues, which should be addressed properly to allow their implementation. Collaboration between data scientists, clinical researchers, and physicians is therefore required to move this field forward.

Changes of DCE-MRI Parameters in Patients with Rheumatoid Arthritis before and after Therapy and Their Value for the Efficacy Evaluation of Patients

Objective

To explore the changes of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in patients with rheumatoid arthritis (RA) before and after therapy and their value for the efficacy evaluation of patients.

Methods

Totally, 90 patients with RA confirmed in our hospital between January 2018 and January 2020 were enrolled. All of them were examined with a Siemens Magnetom Avanto 1.5T imaging system, and data about the rate of enhancement in early stage (REE) and steep slope maximum (SSmax) were obtained. Then, the disease activity score in 28 joints (DAS-28), REE, and SSmax were analyzed, and the associations of SSmax and REE with erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and DAS-28 were investigated. Additionally, the patients were assigned to the acute-stage group and the chronic-stage group according to their time-signal intensity curves after therapy, and the two groups were compared in SSmax, REE, ESR, CRP, and DAS-28. Corresponding receiver operating characteristic (ROC) curves were drawn for the analysis of potential markers for efficacy improvement in patients.

Results

After therapy, REE, SSmax, ESR, DAS-28, and CRP in the synovium of all patients declined greatly (all P < 0.05), with higher levels observed in the acute-stage group than those in the chronic-stage group (all P < 0.05). SSmax and REE of patients were positively bound up with their ESR, CRP, and DAS-28 (all P < 0.05). Additionally, according to ROC curve-based analysis, both SSmax and REE can be adopted as biological indexes for distinguishing between patients at the acute phase from those at the chronic stage, and joint detection of them can boost the sensitivity of DAS-28.

Conclusion

The SSmax and REE levels in RA patients after treatment were significantly decreased, and the levels in patients in the chronic phase were lower than those in patients in the acute phase. SSmax and REE are highly expressed in RA patients, and the combined detection can enhance the value of DAS-28 in the assessment of RA, and it is worthy of clinical promotion.