Novel prognostic nomograms to assess survival in high-grade serous ovarian carcinoma after surgery and chemotherapy: a retrospective cohort study from SEER database.

ABSTRACT:

Background

Despite high-grade serous ovarian carcinoma (HGSOC) being the most common epithelial ovarian cancer, it is a heterogenous group of tumors with several histological subtypes. The goal of our study was to develop specifical models to predict the survival of actively treated, HGSOC.

Methods

This retrospective cohort study included patients with HGSOC who had undergone surgery and chemotherapy between the years of 2010 and 2016 using the Surveillance, Epidemiology, and End Results (SEER) database. A total of 3,788 cases were randomly divided into a training (n=2,591) and test set (n=1,197). Cox-LASSO algorithm and cross validation (based on lambda.1se) were used to identify survival factors in the training set. Nomograms were created and internally validated. We used

SUBMITTER: Huang W 

PROVIDER: S-EPMC9358519 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature