Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively.

ABSTRACT:

Purpose

The preoperative diagnosis of endometriosis associated ovarian cancer (EAOC) remains challenging for lack of effective diagnostic biomarker. We aimed to study clinical characteristics and develop a nomogram for diagnosing EAOC before surgery.

Methods

A total of 87 patients with EAOC and 348 patients with ovarian endometrioma (OEM) were enrolled in our study. Least absolute shrinkage and selection operator (LASSO) regression and Logistic regression were utilized to select variables and construct the prediction model. The performance of the model was assessed using receiver operating characteristic (ROC) analyses and calibration plots, while decision curve analyses (DCAs) were conducted to assess clinical value. Bootstrap resampling was used to evaluated the stability

SUBMITTER: Xu T 

PROVIDER: S-EPMC10799100 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature