Evaluation of the prognostic nutritional index (PNI) as a tool for assessing disease activity in rheumatoid arthritis patients.

Abstract

Rheumatoid arthritis (RA) is an autoimmune disease of unknown exact cause, characterized by chronic inflammation. The prognostic nutritional index (PNI), reflecting albumin concentration and lymphocyte count, is a newly established inflammation-based nutritional score. This study aimed to determine the relationship between PNI and disease activity in RA patients. This cross-sectional study included 138 RA patients who met the 2010 revised criteria of the American College of Rheumatology (ACR) for RA. PNI was calculated using the following formula: 10 × serum albumin value (g/dL) + 0.005 × total lymphocyte count in the peripheral blood (per mm3). The study population was divided into two groups: DAS28-ESR ≤ 3.2 (group 1 with remission and low disease activity) and DAS28-ESR > 3.2 (group 2 with moderate and high disease activity). A total of 138 patients with a mean age of 52.1years were recruited. While the female gender was more prevalent in both groups, it was significantly higher in group 2 (p < 0.05). Group 2 exhibited a lower PNI compared to those in group 1 (42.17 ± 3.46 vs. 44.02 ± 2.92; p = 0.001). Multivariate logistic regression analyses revealed that PNI was an independent predictor of disease activity (OR, 0.850; 95% CI, 0.735-0.983; p = 0.029). ROC curve analysis determined that the optimal cutoff value of PNI for disease activity was 43.01, with a sensitivity of 69.1% and specificity of 57.7% (AUC, 0.66; 95% CI, 0.57-0.75, p = 0.001). This study demonstrates that the simple and readily available PNI could serve as an independent predictor of disease activity in rheumatoid arthritis patients. Key Points •The relationship between disease activity and the prognostic nutritional index, which is a nutritional indicator, in rheumatoid arthritis patients was investigated. •It has been shown that there is a connection between low PNI and high disease activity. •It has been shown that PNI can be used to evaluate disease severity with a simple calculation.