Zhongguo shi yan xue ye xue za zhi · 2025
[Construction and Validation of a Prognostic Nomogram Model for Chronic Myeloid Leukemia Patients].
СтатьяВалидационное исследованиеАннотация на английскомНазвание и аннотация: Перевод в очереди
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Liu Li-Ying, Ge Zheng, Wei Ji-Feng, Zhao Li-Na, Cai Zhi-Mei
Аннотация
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.
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.