AUTHOR=Weng Wenwen , Chen Yanfei , Wang Yuwen , Ying Peiting , Guo Xiaoping , Ruan Jinfei , Song Hua , Xu Weiqun , Zhang Jingying , Xu Xiaojun , Tang Yongmin 

TITLE=A scoring system based on fusion genes to predict treatment outcomes of the non-acute promyelocytic leukemia pediatric acute myeloid leukemia

JOURNAL=Frontiers in Medicine

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2023.1258038

DOI=10.3389/fmed.2023.1258038

ISSN=2296-858X

ABSTRACT=Background: Fusion genes are considered to be one of the major drivers behind cancer initiation and progression. While non- acute promyelocytic leukemia (APL) pediatric patients with acute myeloid leukemia (AML) in children had limited treatment efficacy. Hence, we developed and validated a simple clinical scoring system based on for predicting outcomes in non-APL pediatric patients with AML.
Method: A total of 184 non-APL pediatric patients with AML who were admitted to our hospital and an independent dataset (318 patients) from TARGET database were included. Least absolute shrinkage and selection operation (LASSO) and Cox regression analysis were used to identify prognostic factors. Then, a nomogram score was developed to predict the 1-, 3-, and 5-year overall survival (OS) based on their clinical characteristics and fusion genes. The accuracy of the nomogram score was determined by calibration curves and receiver operating characteristic (ROC) curves. Additionally, an internal verification cohort was used to assess its applicability. 
Results: On the basis of Cox and LASSO regression analyses, a nomogram score was constructed using clinical characteristics and OS‐related fusion genes (CBFβ::MYH11, RUNX1::RUNX1T1, KMT2A::ELL, and KMT2A::MLLT10), yielded good calibration and concordance for predicting OS of non-APL pediatric patients with AML. Furthermore, patients with higher scores exhibited worse outcomes. The nomogram score also demonstrated good discrimination and calibration in the whole cohort and internal validation. Furthermore, artificial neural networks demonstrated that this nomogram score exhibits good predictive performance.
Conclusion: Our model based on the fusion gene is a prognostic biomarker for non-APL pediatric patients with AML. The nomogram score can provide personalized prognosis prediction, thereby benefiting clinical decision-making.