Abstract: Objective: To analyze the prognostic factors of patients with bullous pemphigoid using random forest model and Logistic regression model, so as to provide a basis for treatment and prognosis judgment. Methods: Inpatients who were diagnosed with bullous pemphigoid in our hospital from January 2015 to April 2021 were enrolled in this study. The factors on bullous pemphigoid were analyzed through  random forest model and Logistic regression model, and the predictive efficacy of the two models was compared. Results: The results of random forest model showed that the top five factors were age, mucous membrane involvement, neurological disease, blood calcium, and local skin infection. Logistic regression model showed that advanced age, decreased blood calcium level, and neurological diseases were risk factors for poor prognosis in BP patients and patients with mucosal involvement had lower mortality with 1 year. The difference between the training set and the test set of the Logistic regression model was smaller than that of the random forest model and the model is more stable. Conclusion: Age, mucous membrane involvement, neurological diseases, blood calcium and local skin infection are the most important factors affecting the prognosis of patients with bullous pemphigoid. The combination of random forest and logistic regression moolels to predict the prognosis of bullous pemphigoid patients is of practical significance.

Key words: bullous pemphigoid, prognosis, Logistic regression, Random forest