Improving Risk Assessment for Metastatic Disease in Endometrioid Endometrial Cancer Patients Using Molecular and Clinical Features: an NRG Oncology / Gynecologic Oncology Group Study
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ABSTRACT: 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
ORGANISM(S): Homo sapiens
PROVIDER: GSE120490 | GEO | 2022/12/30
REPOSITORIES: GEO
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