Clinical Characteristics in the Prediction of Posttreatment Survival of Patients with Ovarian Cancer

Abstract

Objective. To determine the efficacy of clinical characteristics in the prediction of prognosis in patients with ovarian cancer. Methods. Clinical data were collected from 3 datasets from TCGA database, including 1680 cases of ovarian serous cystadenocarcinoma, and were analyzed. Patients with ovarian cancer admitted to our hospital in 2016 were retrieved and followed up for prognosis analysis. Results. From the datasets, for $\text{patients}>75$ years old at the time of diagnosis, histologic grade and mutation count were good predictors for disease-free survival, while for $\text{patients}>50$ years old at the time of diagnosis, histologic grade, race, fraction genome altered, and mutation count were good predictors for overall survival. In the patients ( $n=38$ ) retrieved from our hospital, the longest dimension of lesion (cm) and body weight at admission were good predictors for overall survival. Conclusions. Those clinical factors, together with the two predictive equations, could be used to comprehensively predict the long-term prognosis of patients with ovarian cancer.