Among the applied machine learning approaches, the XGBoost model exhibited the highest performance; in addition to clinical factors such as age, tumor size, NPI, and radiotherapy, molecular biomarkers including ATM, HERC2, AKT2, FOXO3, and CYP3A43 provided critical contributions to survival prediction. Here, AKT2 is linked to neoplasm.