Construction and Validation of a Prognostic Nomogram Model for Chronic Myeloid Leukemia Patients.
10.19746/j.cnki.issn.1009-2137.2025.03.018
- Author:
Li-Ying LIU
1
;
Zheng GE
2
;
Ji-Feng WEI
1
;
Li-Na ZHAO
1
;
Zhi-Mei CAI
1
Author Information
1. Department of Hematology, The Affiliated Lianyungang Hospital of Xuzhou Medical University/ The First People's Hospital of Lianyungang, Lianyungang 222000, Jiangsu Province，China.
2. Department of Hematology, Zhongda Hospital, School of Medicine, Southeast University, Institute of Hematology Southeast University, Nanjing 210009, Jiangsu Province， China.
- Publication Type:English Abstract
- Keywords:
chronic myeloid leukemia
- MeSH:
Nomograms;
Leukemia, Myelogenous, Chronic, BCR-ABL Positive/mortality*;
Proportional Hazards Models;
Erythrocyte Indices;
Risk Assessment/methods*;
Fusion Proteins, bcr-abl/genetics*;
Basophils;
Leukocyte Count;
Humans
- From:
Journal of Experimental Hematology
2025;33(3):745-752
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To screen factors affecting the prognosis of chronic myeloid leukemia (CML) patients, and construct a nomogram model for event-free survival (EFS).
METHODS:To screen out meaningful variables by univariate and multivariate Cox regression analysis in CML patients, and construct a nomogram model using R software. The nomogram was validated using consistency index (C-index), receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), calibration curve, decision curve analysis (DCA), and risk stratification analysis.
RESULTS:This study analyzed data from 116 CML patients. Univariate and multivariate Cox regression analysis demonstrated that age, peripheral blood basophil percentage, BCR-ABL1 IS at 3 months, and red blood cell distribution width (RDW) were independent prognostic factors of EFS. Subsequently, a nomogram was constructed based on the above predictors. The C-index of the nomogram was 0.733(95%CI : 0.676-0.790). The AUC values for predicting 1-, 3-, and 5-year EFS rate were 0.765, 0.855, and 0.827, respectively. The results of the calibration curve and DCA curve showed that the predictive model had good consistency, as well as strong clinical utility. The patients were stratified into high-risk group and low-risk group based on the total score of the model, there was a significant difference in EFS between the two groups (P < 0.001).
CONCLUSION:Age, peripheral blood basophil percentage, BCR-ABL1 IS at 3 months, and RDW were associated with the prognosis of CML patients. The nomogram model constructed in this study can accurately predict the prognostic status of CML patients, but its widespread application still requires external and prospective validation.
