Development and validation of a nomogram for predicting fatigue in patients with primary Sjögren's syndrome.

Objective: To develop and validate a nomogram to predict fatigue in patients with primary Sjögren's syndrome (pSS).

Methods: In this cross-sectional study, 251 patients with SS from the Affiliated Hospital of Nantong University were recruited. The patients were randomly divided into two groups: training group (n = 167) and validation group (n = 84). In the training group, univariate analysis and multivariate Cox regression analysis were performed on sociodemographic factors, disease activity, anxiety/depression, clinical indicators, and so on. According to the risk factors of fatigue in SS patients, a nomograph was established. In the training group and validation group, the performance of the nomogram was verified by three forms: receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).

Result: The incidence of fatigue was 40.6%. EULAR Sjögren's Syndrome Disease Activity Index, EULAR SS patient reported index, and depression were independent risk factors of fatigue in SS patients. The C-index of nomogram was 0.8532 in training set and 0.7381 in verification set, respectively. As to the Hosmer-Lemeshow test, the P value of modeling patients is 0.996 in verification (P > 0.05). DCA further validated the clinical utility of this nomogram.

Conclusion: The nomogram constructed in this study can effectively predict the occurrence of fatigue in SS patients, which is helpful for clinical decision-making and subsequent intervention implementation. Key Points • Fatigue was widespread in patients with primary Sjögren's syndrome, and the incidence of fatigue was 40.6%. • Disease activity and depression were independent risk factors of fatigue in patients with Sjögren's syndrome. • This was the first comprehensive nomogram to predict fatigue for Sjögren's syndrome patients.