{Reference Type}: English Abstract {Title}: [Development of a Prognostic Model for Overall Survival Adult Patients with Core Binding Factor Acute Myeloid Leukaemia]. {Author}: Shi LY;Li LL;Li T;Li YF;Liu YF;Jiang ZX;Wang SJ;Wang C; {Journal}: Zhongguo Shi Yan Xue Ye Xue Za Zhi {Volume}: 32 {Issue}: 3 {Year}: 2024 Jun 暂无{DOI}: 10.19746/j.cnki.issn.1009-2137.2024.03.007 {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.
CONCLUSIONS: This prediction model is simple and feasible, and can effectively predict the OS of CBF-AML, and provide a basis for treatment decision.
UNASSIGNED: 核心结合因子相关成人急性髓系白血病患者总生存临床预测模型的建立.
UNASSIGNED: 分析影响核心结合因子相关成人急性髓系白血病(CBF-AML)患者总生存(OS)的因素,并建立预测模型。.
UNASSIGNED: 回顾性分析2015年5月至2021年7月在郑州大学第一附属医院新诊断的216例CBF-AML的临床资料。将患者按照7∶3随机分成训练集和验证集。采用Cox回归模型对影响OS的临床因素进行分析。采用逐步回归建立最优模型,画出列线图。使用受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)评估模型性能。.
UNASSIGNED: 年龄≥55 岁、外周血原始幼稚≥80%、AML1-ETO、KIT突变被确定为OS的独立预后不良因素。训练集和验证集3年ROC下面积分别为0.772、0.722;校正曲线预测值与实测值具有较好一致性。DCA表明此模型性能优于单一因素。.
UNASSIGNED: 该预测模型简便易行,可有效预测CBF-AML的OS,为治疗决策提供依据。.