J Cancer 2021; 12(23):7223-7236. doi:10.7150/jca.63224 This issue

Research Paper

Clinical Nomograms for Predicting the Overall Survival and Cancer-specific Survival of patients with Ovarian Carcinosarcoma patients after Primary Surgery

Fang Ren1, Shengtan Wang2, Feifei Li3, Jian Gao1, Haoya Xu1, Xianli Li1, Liancheng Zhu1✉

1. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning, China.
2. Department of Gynecology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou 570011, Hainan, China.
3. Department of Gynecology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China.

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Citation:
Ren F, Wang S, Li F, Gao J, Xu H, Li X, Zhu L. Clinical Nomograms for Predicting the Overall Survival and Cancer-specific Survival of patients with Ovarian Carcinosarcoma patients after Primary Surgery. J Cancer 2021; 12(23):7223-7236. doi:10.7150/jca.63224. Available from https://www.jcancer.org/v12p7223.htm

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Abstract

Graphic abstract

Background: At present, there is no clinical prediction model for ovarian carcinosarcoma (OCS) that is based on a large sample of real data. This study aimed to construct nomograms using data extracted from the Surveillance, Epidemiology, and End Results (SEER) database that can be used to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with OCS and further guide the choice of clinical treatment.

Methods: We selected 2753 cases of OCS from the SEER database from 1998 to 2016. Patients were randomly divided in a 7:3 ratio into a training cohort (n = 1929) and a validation cohort (n = 824). Cox analysis was used to select prognostic factors for OS and CSS, and nomograms were then established. The performance of nomogram models was assessed using the concordance index, the area under the receiver operating characteristic curve, calibration curves, and by decision curve analysis. Data from 21 OCS patients at Shengjing Hospital from 2001 to 2021 were collected for external verification. Kaplan-Meier curves were plotted to compare survival outcomes between subgroups.

Results: Nomograms based on independent prognostic factors showed good predictive power and clinical practicality. Internal and external validation indicated that the nomograms performed better than staging and grading systems. Significant differences were observed in the survival curves of different risk subgroups.

Conclusions: The developed nomograms will enable individualized evaluation of the OS and CSS, thus guiding the treatment of patients with OCS.

Keywords: Ovarian carcinosarcoma, Nomogram, Overall survival, Cancer-specific survival, Validation