Development and validation of a prognostic model for adult patients with acute myeloid leukaemia
Ting-Ting Ma,
Xiao-Jing Lin,
Wen-Yan Cheng,
Qing Xue,
Shi-Yang Wang,
Fu-Jia Liu,
Han Yan,
Yong-Mei Zhu,
Yang Shen
Affiliations
Ting-Ting Ma
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
Xiao-Jing Lin
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
Wen-Yan Cheng
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
Qing Xue
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
Shi-Yang Wang
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
Fu-Jia Liu
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
Han Yan
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
Yong-Mei Zhu
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
Yang Shen
Corresponding author.; 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
Background: 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. Methods: 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. Findings: 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. Interpretation: 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. Funding: 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).
