posted on 2025-01-09, 12:44authored byLv W., Wang Y., Hu F., Huang H., Cui Y., Song Y., Chen L., Wu B., Liang Y.
Accurate prediction of survival in patients with acute myelogenous leukemia (AML) is challenging. Therefore, we developed a predictive survival model using endocrine-related gene expression to identify an endocrine signature for accurate stratification of AML prognosis. RNA matrices and clinical data for AML were downloaded from a training dataset (GEO) and two validation datasets (TCGA and TARGET). In relation to the survival outcome, a risk model was constructed by incorporating seven endocrine-related genes. The model exhibited favorable predictive efficacy in estimating 5-year survival rates, as demonstrated by both the training and validation cohorts. Multivariable analysis revealed that the endocrine signature demonstrated autonomous prognostic significance in the aforementioned cohorts. Prediction accuracy for 5-year overall survival increased using a nomogram combining endocrine risk score and classical prognostic factors compared with using classical prognostic factors alone. The model predictions were confirmed using AML cell lines. The endocrine-related prognostic model established in this study improves AML survival prediction accuracy.