Development and validation of a prognostic scoring model to risk stratify childhood acute myeloid leukaemia
Jun Li1, Lipeng Liu1, Ranran Zhang1
1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China.
Insights
A new prognostic model for pediatric acute myeloid leukemia (AML) improves risk stratification and survival prediction. This model aids in personalizing treatment selection for better patient outcomes.
Area of Science:
- Oncology
- Genetics
- Biostatistics
Background:
- Pediatric acute myeloid leukemia (AML) requires accurate prognostic models for effective treatment.
- Current risk stratification methods may not fully capture individual patient prognoses.
Purpose of the Study:
- To develop and validate a personalized prognostic model for pediatric AML.
- To improve risk stratification and guide treatment decisions.
Main Methods:
- Utilized data from 597 pediatric AML patients (TARGET database) for training and 189 patients for validation.
- Identified key prognostic factors including age, chromosomal abnormalities, gene mutations (FLT3-ITD, NPM1, WT1, CEBPA), and fusion genes.
- Constructed a prognostic model and assessed its discriminative ability using Harrell's concordance index and ROC curves.
Main Results:
- The model demonstrated strong discriminative ability (C-index=0.68, 3/5-year AUC=0.71/0.72).
- Validated effectively, outperforming existing prognostic systems.
- Successfully stratified patients into distinct low, intermediate, and high-risk groups.
- Identified suitable candidates for hematopoietic stem cell transplantation.
Conclusions:
- The developed prognostic model offers robust survival prediction and risk stratification for pediatric AML.
- This tool can potentially refine treatment selection in clinical practice.
- Personalized risk assessment is crucial for optimizing pediatric AML management.
Abstract:
To create a personal prognostic model and modify the risk stratification of paediatric acute myeloid leukaemia, we downloaded the clinical data of 597 patients from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database as a training set and included 189 patients from our centre as a validation set. In the training set, age at diagnosis, -7/del(7q) or -5/del(5q), core binding factor fusion genes, FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD)/nucleophosmin 1 (NPM1) status, Wilms tumour 1 (WT1) mutation, biallelic CCAAT enhancer binding protein alpha (CEBPA) mutation were strongly correlated with overall survival and included to construct the model. The prognostic model demonstrated excellent discriminative ability with the Harrell's concordance index of 0.68, 3- and 5-year area under the receiver operating characteristic curve of 0.71 and 0.72 respectively. The model was validated in the validation set and outperformed existing prognostic systems. Additionally, patients were stratified into three risk groups (low, intermediate and high risk) with significantly distinct prognosis, and the model successfully identified candidates for haematopoietic stem cell transplantation. The newly developed prognostic model showed robust ability and utility in survival prediction and risk stratification, which could be helpful in modifying treatment selection in clinical routine.
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