A prognostic survival model based on endocrine-related gene expression in acute myelogenous leukemia.

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.