[Development of a Prognostic Model for Overall Survival Adult Patients with Core Binding Factor Acute Myeloid Leukaemia].

Lu-Yao Shi, Ling-Ling Li, Tao Li, Ya-Fei Li, Yan-Fang Liu, Zhong-Xing Jiang, Shu-Juan Wang, Chong Wang
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引用次数: 0

Abstract

Objective: To analyze the factors affecting overall survival (OS) of adult patients with core-binding factor acute myeloid leukemia (CBF-AML) and establish a prediction model.

Methods: A total of 216 newly diagnosed patients with CBF-AML in the First Affiliated Hospital of Zhengzhou University from May 2015 to July 2021 were retrospectively analyzed. The 216 CBF-AML patients were divided into the training and the validation cohort at 7∶3 ratio. The Cox regression model was used to analyze the clinical factors affecting OS. Stepwise regression was used to establish the optimal model and the nomogram. Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to evaluate the model performance.

Results: Age(≥55 years old), peripheral blood blast(≥80%), fusion gene (AML1-ETO), KIT mutations were identified as independent adverse factors for OS. The area under the ROC curve at 3-year was 0.772 and 0.722 in the training cohort and validation cohort, respectively. The predicted value of the calibration curve is in good agreement with the measured value. DCA shows that this model performs better than a single factor.

Conclusion: This prediction model is simple and feasible, and can effectively predict the OS of CBF-AML, and provide a basis for treatment decision.

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[核心结合因子急性髓性白血病成人患者总生存期预后模型的开发]。
目的分析影响核心结合因子急性髓性白血病(CBF-AML)成人患者总生存期(OS)的因素,并建立预测模型:方法:对郑州大学第一附属医院2015年5月至2021年7月新确诊的216例CBF-AML患者进行回顾性分析。按 7∶3 的比例将 216 例 CBF-AML 患者分为训练队列和验证队列。采用Cox回归模型分析影响OS的临床因素。采用逐步回归法建立最佳模型和提名图。采用接收者操作特征曲线(ROC)、校准曲线和决策曲线分析(DCA)来评估模型的性能:结果:年龄(≥55岁)、外周血血小板(≥80%)、融合基因(AML1-ETO)、KIT突变被认为是影响OS的独立不利因素。训练队列和验证队列的 3 年 ROC 曲线下面积分别为 0.772 和 0.722。校准曲线的预测值与测量值十分吻合。DCA显示,该模型的表现优于单一因素:该预测模型简单可行,能有效预测 CBF-AML 的 OS,为治疗决策提供依据。
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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
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0.00%
发文量
7331
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