Establishment and validation of a novel nomogram for survival prediction of ovarian carcinosarcoma

Abstract

Background: Ovarian carcinosarcoma (OCS) is a rare and aggressive histological type of ovarian cancer.Current prognostic methods for OCS are insufficient. This study was undertaken to establish and validate a novel nomogram for predicting the overall survival (OS) of OCS patients. Methods:We extracted 820 patients with OCS from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly assigned them to a training set (n=574) and a validation set (n=246) at a ratio of 7-to-3. Univariate and multivariate regression analyses were utilized to verity independent prognostic factors, and a prognostic nomogram was constructed based on the results. The performance of the new model was compared with that of the AJCC staging system using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA).Results: Cox regression analysis suggested that age, grade, tumor size, AJCC stage, surgery, and chemotherapy were the independent prognostic factors. These factors were integrated into a prognostic nomogram to determine the 1-, 3-, and 5-year OS of OCS patients. The AUC, NRI, IDI, calibration curves, and DCA data demonstrated that our nomogram had better discriminative ability than the AJCC staging system alone. The calibration curves indicate that the nomogram was well-calibrated. The DCA verified the clinical applicability of the nomogram.Conclusions: Our current study is the first to establish and internally validate a novel nomogram for predicting the 1-, 3-, and 5-year OS probabilities of OCS patients. Our prognostic nomogram was of good performance and can be an accurate tool to predict individualized survival time of OCS in clinical work.

Nomograms to predict overall survival for patients with endometrial carcinosarcoma

“…Recently, Chen et al [2] in their multivariate analysis showed that age, race, year of diagnosis, FIGO stage, and treatment type can also be associated with survival and formed a similar nomogram with a good predictive capacity. Another study formed a nomogram predicting the overall survival of patients with ovarian carcinosarcoma including the following parameters: age, grade, tumor site, surgery, and chemotherapy [3]. We would like to ask the authors whether the addition of patients' age and surgery might improve the prognostic performance of their nomogram.…”