[Construction and Validation of a Prognostic Nomogram Model for Chronic Myeloid Leukemia Patients].

Q4 Medicine
Li-Ying Liu, Zheng Ge, Ji-Feng Wei, Li-Na Zhao, Zhi-Mei Cai
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引用次数: 0

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.

慢性髓系白血病患者预后Nomogram模型的构建与验证
目的:筛选影响慢性髓性白血病(CML)患者预后的因素,构建无事件生存(EFS)的nomogram模型。方法:对CML患者进行单因素和多因素Cox回归分析,筛选出有意义的变量,并利用R软件构建nomogram模型。采用一致性指数(C-index)、受试者工作特征(ROC)曲线、ROC曲线下面积(AUC)、校准曲线、决策曲线分析(DCA)和风险分层分析对nomogram进行验证。结果:本研究分析了116例CML患者的数据。单因素和多因素Cox回归分析显示,年龄、外周血嗜碱性粒细胞百分比、3个月时BCR-ABL1 IS和红细胞分布宽度(RDW)是EFS的独立预后因素。随后,基于上述预测因子构建了一个模态图。nomogram C-index为0.733(95%CI: 0.676 ~ 0.790)。预测1年、3年和5年EFS率的AUC值分别为0.765、0.855和0.827。校正曲线和DCA曲线结果表明,该预测模型具有较好的一致性,具有较强的临床实用性。根据模型总分将患者分为高危组和低危组,两组间EFS比较差异有统计学意义(P < 0.001)。结论:年龄、外周血嗜碱性粒细胞百分比、3个月时BCR-ABL1 IS、RDW与CML患者预后相关。本研究构建的nomogram模型能够准确预测CML患者的预后状况,但其广泛应用仍需要外部和前瞻性的验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
中国实验血液学杂志
中国实验血液学杂志 Medicine-Medicine (all)
CiteScore
0.40
自引率
0.00%
发文量
7331
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