Construction of a Prognostic Risk Prediction Model for Multiple Myeloma Patients after Bortezomib Treatment Based on Decision Tree Algorithm - Jiang, Tao; Luo, Yuan; Wang, Huan; Li, Hui (Zhongguo shi yan xue ye xue za zhi, 2025)
To explore the influencing factors on the prognosis of patients with multiple myeloma (MM) after bortezomib treatment, and construct a decision tree risk prediction model based on the influencing factors. One hundred and seventy MM patients admitted to the People's Hospital of Jianyang City from January 2019 to June 2022 were selected as research subjects, and divided into poor prognosis group and good prognosis group according to the prognosis after bortezomib treatment. The clinical data of the patients were analyzed, univariate and logistic regression analysis were used to screen influencing factors, SPSS Modeler software was used to construct a decision tree prediction model, and the diagnostic performance of the decision tree risk prediction model was analyzed. The incidence of poor prognosis in 170 MM patients after bortezomib-based chemotherapy was 21.18%. Kappa light chain level≥19.4 mg/L, platelet count (PLT) ≤100×10 /L, homocysteine (Hcy) >22 μmol/L, serum creatinine (Scr) ≥176 μmol/L, lactate dehyd