Abstract 102P
Background
Current pediatric acute myeloid leukemia (pAML) risk stratification heavily relies on cytogenetic findings. However, despite the generally low-risk feature associated with the RUNX1-RUNX1T1 fusion gene, a substantial proportion of patients still experience unfavorable overall survival (OS) and/or event-free survival (EFS). Hence, a specific clinical decision support tool is crucial for the precise evaluation of survival in RUNX1-RUNX1T1+ pAML patients, aiming for enhanced outcomes.
Methods
The study included 2009 pAML patients, of whom 284 carried the RUNX1-RUNX1T1 fusion gene (RR-pAML). The patient data was randomly divided into training and validation subsets; the primary endpoints were OS and EFS. The prognostic model was constructed using univariate and multivariate Cox analyses. Model performance was evaluated using C-index and AUC values.
Results
The RR-pAML model was constructed based on two clinical factors. This model effectively categorized patients into low- and high-risk groups, which exhibited distinct clinical characteristics, response rates, relapse risk and mortality. The 5-year OS rates for the low- and high-risk groups were 91.0% and 73.0%, respectively (p=0.024, AUC 0.69). For EFS, the 5-year rates were 76.8% and 50.2%, respectively (p<0.001, AUC 0.70). Compared to previous prognostic models, the new model demonstrated superior performance in C-index and AUCs. It reclassified 31.7% of patients into the high-risk category and predicted relapse risk.
Conclusions
The new model is a straightforward yet effective clinical stratification tool for pAML patients carrying the RUNX1-RUNX1T1 fusion gene; it enhances risk assessment and facilitates more informed decision-making in the management of RUNX1-RUNX1T1+ patients.
Editorial acknowledgement
Clinical trial identification
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
35P - Whole exome sequencing reveals high frequency of Notch pathway mutations in Indian breast cancer cases
Presenter: Harsh Goel
Session: Cocktail & Poster Display session
Resources:
Abstract
36P - Abacavir potentiates the efficacy of doxorubicin in breast cancer cells via KDM5B Inhibition
Presenter: Anmi Jose
Session: Cocktail & Poster Display session
Resources:
Abstract
37P - Identification of immune profile in advanced cutaneous squamous cell carcinoma predicting immunotherapy response
Presenter: Alfonso Esposito
Session: Cocktail & Poster Display session
Resources:
Abstract
39P - MicroRNA as a promising molecular biomarker for liquid biopsy in breast cancer
Presenter: Giorgia Vesca
Session: Cocktail & Poster Display session
Resources:
Abstract
40P - Patient-based models to study infiltration heterogeneity in gliomas
Presenter: Ivana Manini
Session: Cocktail & Poster Display session
Resources:
Abstract
42P - HER2 aberration as a potential predictive biomarker for extrapulmonary small cell neuroendocrine carcinoma
Presenter: Jiri Dvorak
Session: Cocktail & Poster Display session
Resources:
Abstract
43P - Assessment of methylation-specific genetic markers for reliable colorectal cancer detection and their potential in liquid biopsy applications
Presenter: Jiri Dvorak
Session: Cocktail & Poster Display session
Resources:
Abstract
44P - Calculated numerical karyotype with ultra low-coverage whole genome sequencing undercovers recurrent chromosomal aberrations in resectable colorectal cancer
Presenter: Thomas Samer Tarawneh
Session: Cocktail & Poster Display session
Resources:
Abstract
46P - Promising epi(genetic) biomarkers for ovarian tumor prognosis
Presenter: Ieva Vaicekauskaitė
Session: Cocktail & Poster Display session
Resources:
Abstract
47P - Integration of miRNA profiles and p53 mutations as biomarkers for predicting sensitivity and resistance to FGFR inhibitor CPL110 in cancer therapy
Presenter: Monika Skupinska
Session: Cocktail & Poster Display session
Resources:
Abstract