Serology-Based Model for Personalized Epithelial Ovarian Cancer Risk Evaluation.

ABSTRACT: This study aimed to establish a prognosis-prediction model based on serological indicators in patients with epithelial ovarian cancer (EOC). Patients initially diagnosed as ovarian cancer and surgically treated in Fudan University Shanghai Cancer Center from 2014 to 2018 were consecutively enrolled. Serological indicators preoperatively were collected. A risk model score (RMS) was constructed based on the levels of serological indicators determined by receiver operating characteristic curves. We correlated this RMS with EOC patients’ overall survival (OS). Finally, 635 patients were identified. Pearson’s χ2 results showed that RMS was significantly related to clinical parameters. Kaplan−Meier analysis demonstrated that an RMS less than 3 correlated with a longer OS (p < 0.0001). Specifical

SUBMITTER: Yan T 

PROVIDER: S-EPMC9029686 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature