Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China.
Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China.
EBioMedicine. 2020 Dec;62:103126. doi: 10.1016/j.ebiom.2020.103126. Epub 2020 Nov 22.
The high heterogeneity of acute myeloid leukaemia (AML) reflected in the patient- and disease-related factors accounts for the unsatisfactory prognosis despite the introduction of novel therapeutic approaches and drugs in recent years.
In the development set (n = 412), parameters including age, hematopoietic cell transplantation-comorbidity index, white blood cell count, hemoglobin, biallelic CEBPA mutations, DNMT3A mutations, FLT3-ITD/NPM1 status, and ELN cytogenetic risk status were identified as independent prognostic factors for overall survival (OS) in the multivariable Cox regression analysis. A nomogram combining these predictors for individual risk estimation was established thereby.
The prognostic model demonstrated promising performance in the development cohort. The calibration plot, C-index (0.74), along with the 1-, 2- and 3-year area under the receiver operating characteristic curve (AUC, 0.76, 0.79, and 0.74, respectively) in the validation set (n = 238) substantiated the robustness of the model. In addition to stratifying young (age ≤ 60 years) and elderly patients (age > 60 years) into three and two risk groups with significant distinct outcomes, the prognostic model succeeded in distinguishing eligible candidates for hematopoietic stem cell transplantation.
The prognostic model is capable of survival prediction, risk stratification and helping with therapeutic decision-making with the use of easily acquired variables in daily clinical routine.
This work was supported in part by grants from the National Natural Science Foundation of China (81770141), the National Key R&D Program of China (2016YFE0202800), and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20161406).
尽管近年来引入了新的治疗方法和药物,但急性髓系白血病(AML)患者和疾病相关因素的高度异质性导致预后仍不理想。
在开发集(n=412)中,多变量 Cox 回归分析确定了年龄、造血细胞移植合并症指数、白细胞计数、血红蛋白、双等位基因 CEBPA 突变、DNMT3A 突变、FLT3-ITD/NPM1 状态和 ELN 细胞遗传学风险状态等参数是总生存(OS)的独立预后因素。从而建立了一个结合这些预测因子进行个体风险估计的列线图。
该预后模型在开发队列中表现出良好的性能。校准图、C 指数(0.74)以及验证集(n=238)中的 1 年、2 年和 3 年接受者操作特征曲线下面积(AUC,分别为 0.76、0.79 和 0.74)表明该模型具有稳健性。除了将年轻(年龄≤60 岁)和老年(年龄>60 岁)患者分层为具有显著不同结局的三个和两个风险组外,该预后模型还成功区分了适合进行造血干细胞移植的候选者。
该预后模型能够通过使用日常临床常规中易于获得的变量进行生存预测、风险分层和帮助治疗决策。
这项工作部分得到了中国国家自然科学基金(81770141)、中国国家重点研发计划(2016YFE0202800)和上海市教育委员会-高峰高原学科建设计划(20161406)的支持。