A nomogram model to predict recurrence of early-onset endometrial cancer after resection based on clinical parameters and immunohistochemical markers: a multi-institutional study.

ABSTRACT:

Objective

This study aimed to investigate the prognosis value of the clinical parameters and immunohistochemical markers of patients with early-onset endometrial cancer (EC) and establish a nomogram to accurately predict recurrence-free survival (RFS) of early-onset EC after resection.

Methods

A training dataset containing 458 patients and an independent testing dataset consisting of 170 patients were employed in this retrospective study. The independent risk factors related to RFS were confirmed using Cox regression models. A nomogram model was established to predict RFS at 3 and 5 years post-hysterectomy. The C-index, area under the curve (AUC) of the receiver operating characteristic (ROC) curve, and calibration curve were calculated to assess the predictive accuracy of t

SUBMITTER: Zheng Y 

PROVIDER: S-EPMC11586258 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature