Development of prediction models for lymph node metastasis in endometrioid endometrial carcinoma.

ABSTRACT:

Background

In endometrioid endometrial cancer (EEC), current clinical algorithms do not accurately predict patients with lymph node metastasis (LNM), leading to both under- and over-treatment. We aimed to develop models that integrate protein data with clinical information to identify patients requiring more aggressive surgery, including lymphadenectomy.

Methods

Protein expression profiles were generated for 399 patients using reverse-phase protein array. Three generalised linear models were built on proteins and clinical information (model 1), also with magnetic resonance imaging included (model 2), and on proteins only (model 3), using a training set, and tested in independent sets. Gene expression data from the tumours were used for confirmatory testing.

Results

LN

SUBMITTER: Berg HF 

PROVIDER: S-EPMC7109044 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature