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

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

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).

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.

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.