Improving Risk Assessment for Metastatic Disease in Endometrioid Endometrial Cancer Patients Using Molecular and Clinical Features: an NRG Oncology / Gynecologic Oncology Group Study

Accurate methods to predict nodal and distant metastasis are needed in endometrioid endometrial cancer (EEC) patients to advance personalized care and reduce both overtreatment and undertreatment. A transcript-based classifier for predicting risk of nodal and distant metastasis in EEC patients was developed, and shown to outperform a panel of clinical and molecular features We used microarrays to detail the gene expression in EEC patients and identified a classifer to predict nodal and distant metastasis Frozen primary endometioid endometrial cancer tissues acquired at the time of primary surgical staging undrwent transcriptomic analysis using the Affymetrix U133 Plus 2.0 microarray platform. contributor: GYNCOE contributor: GOG