Abstract: Objective: To analyze the risk factors of clinical progression to systemic lupus erythematosus (systemiclupuserythematosus, SLE) in patients with cutaneous lupus erythematosus (cutaneouslupuserythematosus, CLE) and establish predictive models. Methods: The patients who were first diagnosed as CLE in our hospital from January 2010 to December 2019 were collected, and the clinical and laboratory data were statistically analyzed. They were divided into two groups according to their progression to SLE or not. The clinical and laboratory data of the two groups at the first visit were compared, and they were incorporated into five predictive modeling to verify the effectiveness. Results: A total of 183 patients with CLE were analyzed, including non-progressive group (n=120) and progressive group (n=63). Univariate regression analysis showed that sex, WBC, RBC, HGB, PLT , complement 3, complement C4, ANA, anti-U1RNP antibody, anti-Ro-52 antibody and alopecia were related to the progression of lupus erythematosus (Ps＜0.05). According to the above characteristics, the prediction models were established, and the test results showed that the areas under the curve (AUC) of KNN, logistic, Bagging, BP, SVM  models were 0.7200, 0.7861, 0.6035, 0.8191, 0.6591, respectively. Conclusion: The risk factors of the progression from CLE to SLE include female patients, alopecia, and laboratory data such as blood routine, complement and ANA, anti-U1RNP antibody and anti-Ro-52 antibody et al. The lupus  progression prediction models we constructed have high accuracy and differentiation.

Key words: cutaneous lupus erythematosus, systemic lupus erythematosus, disease outcome, risk factors, predictive model