Volume 29, Issue 5, 2020


DOI: 10.24205/03276716.2020.1009

Prognostic Nomograms for Predicting Survival of Liver-only Ovarian Cancer Metastasis: A Population -Based Study


Abstract
Objective: The present study was aim to construct and validate related nomograms to help individual survival prediction in patients with ovarian cancer liver-only metastasis (OCLM). Methods: OCLM diagnosed between 2010 and 2015 were selected in the study from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox proportional hazard models were performed to screen independent prognostic variables to establish nomograms for predicting overall survival (OS) and cancer-specific survival (CSS). The performance of the established models was evaluated by the calibration curve, Harrell’s concordance (C-index), and decision curve analysis (DCA). Results: A total of 1335 patients with OCLM were final identified. Those individuals were randomly classified into development (n=668) and validation (n=667) cohorts. Nomograms predicting OS and CSS were built based on 4 independent variables. In the development cohort, the C-index for the constructed nomogram to predict OS and CSS was 0.725 and 0.724, respectively. The nomogram achieved perfect discriminative power in the validation cohort to predict OS and CSS, with C-indexes of 0.735 and 0.738, respectively. The calibration plots displayed an acceptable agreement between nomogram-predicted survival probability and the actual observed outcomes. The DCA revealed that the nomogram was clinically useful. Conclusions: The novel proposed nomograms for patients with OCLM can effectively predict the individualized probability of OS and CSS, and this predictive power can help clinicians formulate suitable individual treatments and conduct personalized prognostic evaluation

Keywords
nomogram; ovarian cancer; liver metastasis; survival

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