Effect of sarcopenia and poor balance on vertebral spinal osteoporotic fracture in female rheumatoid arthritis

Development and validation of a predictive model assessing the risk of sarcopenia in rheumatoid arthritis patients

Background

Sarcopenia is linked to an unfavorable prognosis in individuals with rheumatoid arthritis (RA). Early identification and treatment of sarcopenia are clinically significant. This study aimed to create and validate a nomogram for predicting sarcopenia risk in RA patients, providing clinicians with a reliable tool for the early identification of high-risk patients.

Methods

Patients with RA diagnosed between August 2022 and January 2024 were included and randomized into training and validation sets in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and multifactorial logistic regression analysis were used to screen the risk variables for RA-associated muscle loss and to create an RA sarcopenia risk score. The predictive performance and clinical utility of the risk model were evaluated by plotting the receiver operating characteristic curve and calculating the area under the curve (AUC), along with the calibration curve and clinical decision curve (DCA).

Results

A total of 480 patients with RA were included in the study (90% female, with the largest number in the 45-59 age group, about 50%). In this study, four variables (body mass index, disease duration, hemoglobin, and grip strength) were included to construct a nomogram for predicting RA sarcopenia. The training and validation set AUCs were 0.915 (95% CI: 0.8795-0.9498) and 0.907 (95% CI: 0.8552-0.9597), respectively, proving that the predictive model was well discriminated. The calibration curve showed that the predicted values of the model were basically in line with the actual values, demonstrating good calibration. The DCA indicated that almost the entire range of patients with RA can benefit from this novel prediction model, suggesting good clinical utility.

Conclusion

This study developed and validated a nomogram prediction model to predict the risk of sarcopenia in RA patients. The model can assist clinicians in enhancing their ability to screen for RA sarcopenia, assess patient prognosis, make early decisions, and improve the quality of life for RA patients.

Damaged bone microarchitecture by Trabecular Bone Score (TBS) and low appendicular muscle mass: main risk factors for vertebral and non-vertebral fractures in women with long-standing rheumatoid arthritis

We ascertained the fracture risk factors stratified by vertebral and non-vertebral sites in rheumatoid arthritis (RA) females. Bone/muscle features, but not disease activity, were the main markers for fractures in this long-standing RA population: low trabecular bone score (TBS) for vertebral fracture and decreased appendicular muscle mass for non-vertebral fracture.

PURPOSE

To assess risk factors for fractures, including clinical, laboratory and dual energy X-ray absorptiometry (DXA) parameters (bone mass, trabecular bone score-TBS, muscle mass) in women with established rheumatoid arthritis (RA).

METHODS

Three hundred females with RA (ACR, 2010) were studied. Clinical data were obtained by questionnaire and disease activity by composite indices (DAS28, CDAI, SDAI), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). Bone mineral density (BMD), TBS, body composition and Vertebral Fracture Assessment (VFA) were performed by DXA. Logistic regression models were constructed to identify factors independently associated with vertebral (VF) and non-vertebral fractures (NVF), separately.

RESULTS

Through rigorous eligibility criteria, a total of 265 women were yielded for final data analysis (median age, 55 [22-86] years; mean disease duration, 16.2 years). Prevalence of VF and NVF were 30.6% and 17.4%, respectively. In multivariate analyzes, TBS (OR = 1.6, 95%CI = 1.09-2.36, p = 0.017), CRP (OR = 1.54, 95%CI = 1.15-2.08, p = 0.004), and parathormone (OR = 1.24, 95%CI = 1.05-1.45, p = 0.009) were risk factors for VF, whereas low appendicular muscle mass (OR = 2.71; 95%CI = 1.01-7,28; p = 0.048), body mass index (BMI) (OR = 0.90, 95%CI = 0.82-0.99; p = 0.025), ESR (OR = 1.18, 95%CI = 1.01-1,38, p = 0,038) and hip BMD (OR = 1.82, 95%CI = 1.10-3.03, p = 0.02) were associated with NVF.

CONCLUSION

In women with long-term RA, markers of fractures differed between distinct skeletal sites (vertebral and non-vertebral). The magnitude of association of bone/muscle parameters with fracture (TBS for VF and appendicular muscle mass for NVF) was greater than that of the association between RA activity and fracture. TBS seems to have greater discriminative power than BMD to identify subjects with VF in long-standing RA.

The Effect of Rheumatoid Arthritis on Features Associated with Sarcopenia: A Mendelian Randomization Study

Previous epidemiological evidence suggests rheumatoid arthritis is associated with sarcopenia-related features. However, most of the current evidence is from cross-sectional studies, and the causal link of this association is still to be determined. Therefore, this study was committed to a two-sample Mendelian randomization analysis to assess the causal effect of rheumatoid arthritis on sarcopenia-related features. In this two-sample Mendelian randomization study, instrumental variables for rheumatoid arthritis were obtained from the Non-Cancer Disease Study, and data for the five relevant characteristics of sarcopenia were pooled from UKBiobank. Inverse variance weighting is the primary analysis method for assessing causal effects. MR-Egger regression and weighted median are complementary analysis methods for causal effects. Leave-one-out analysis, horizontal pleiotropy test, and Heterogeneity test are applied as a sensitivity analysis to assess the robustness of causal effect estimates. The inverse variance weighted results for the five characteristics associated with sarcopenia and rheumatoid arthritis were: hand grip strength (right) (beta = - 2.309, se = 0.206, p = 3.340E-29), hand grip strength (left) (beta = - 2.046, se = 0.205, p = 2.166E-23), whole body lean mass (beta = - 0.843, se = 0.135, p = 4.67E-10), appendicular lean mass (beta = - 2.444, se = 0.208, p = 6.069E-32), Usual walking pace (OR 0.340, 95% CI (0.238, 0.484), p = 2.471E-09). The sensitivity analyses did not support that horizontal pleiotropy distorted causal effect estimates. The beta coefficient quantifies the number of standard deviations of the continuous outcome variables (hand grip strength, whole body lean mass, and appendicular lean mass) that change on average with each increase in the standard deviation of the binary exposure variable (rheumatoid arthritis). The odds ratios indicate the increased risk of the binary outcome variable (usual walking pace) per rheumatoid arthritis standard deviation increase. This study has demonstrated a negative causal effect of rheumatoid arthritis with five major sarcopenia-related features in a European population.