Development and validation of Nomograms for predicting overall survival and Cancer-specific survival in patients with ovarian clear cell carcinoma

Abstract

Background Ovarian clear cell carcinoma (OCCC) is a rare histologic type of ovarian cancer. There is a lack of an efficient prognostic predictive tool for OCCC in clinical work. This study aimed to construct and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with OCCC. Methods Data of patients with primary diagnosed OCCC in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016 was extracted. Prognostic factors were evaluated with LASSO Cox regression and multivariate Cox regression analysis, which were applied to construct nomograms. The performance of the nomogram models was assessed by the concordance index (C-index), calibration plots, decision curve analysis (DCA) and risk subgroup classification. The Kaplan-Meier curves were plotted to compare survival outcomes between subgroups. Results A total of 1541 patients from SEER registries were randomly divided into a training cohort (n = 1079) and a validation cohort (n = 462). Age, laterality, stage, lymph node (LN) dissected, organ metastasis and chemotherapy were independently and significantly associated with OS, while laterality, stage, LN dissected, organ metastasis and chemotherapy were independent risk factors for CSS. Nomograms were developed for the prediction of 3- and 5-year OS and CSS. The C-indexes for OS and CSS were 0.802[95% confidence interval (CI) 0.773–0.831] and 0.802 (0.769–0.835), respectively, in the training cohort, while 0.746 (0.691–0.801) and 0.770 (0.721–0.819), respectively, in the validation cohort. Calibration plots illustrated favorable consistency between the nomogram predicted and actual survival. C-index and DCA curves also indicated better performance of nomogram than the AJCC staging system. Significant differences were observed in the survival curves of different risk subgroups. Conclusions We have constructed predictive nomograms and a risk classification system to evaluate the OS and CSS of OCCC patients. They were validated to be of satisfactory predictive value, and could aid in future clinical practice.

Development and Validation of Nomograms to Predict Overall Survival Outcomes in Serous Ovarian Cancer Patients with Satisfactory Cytoreductive Surgery and Chemotherapy

“…The nomograms were validated and found to be of good predictive value, which could aid in future clinical decisionmaking. 23 The traditional AJCC staging system does not accurately assess tumor prognosis because it only includes a limited subset of critical prognostic factors. Several studies have reported better performance of nomograms than conventional staging systems and have proposed such models as promising tools for evaluating prognosis.…”

Development and Validation of Nomograms to Predict Long-term Oncological Outcomes in Serous Ovarian Cancer

“…Previous studies have reported using the SEER database to establish nomograms to predict the prognosis of EOC. For example, Wang et al developed and internally validated nomograms to predict OS and cancer-speci c survival (CSS) of EOC patients, achieving a C-index of 0.733 for OS and 0.747 for CSS [22]. Chen et al constructed and validated nomograms to predict OS and CSS in patients with ovarian clear cell carcinoma, achieving a C-index of 0.802 (95% CI, 0.773-0.831) for OS and 0.802 (95% CI, 0.769-0.835) for CSS.…”

Nomogram for Predicting Postoperative Cancer-specific Early Death in Patients with Epithelial Ovarian Cancer based on the SEER Database: A Large Cohort Study

“…Chen et al 11 studied all-cause and speci c mortalities of ovarian clear cell carcinoma and constructed a nomogram with the prognostic factors age, laterality, organ metastasis, AJCC stage, number of lymphadenectomies, and chemotherapy. Yuan et al 12 assessed lung metastasis incidence in ovarian cancer and proposed that stage, liver, bone, and brain metastases and TN stage are predictors of lung metastasis.…”

“…0.787, which represents a better degree of differentiation and ability to provide individualized prediction compared with the AJCC stage. In addition, both the training and validation sets showed good consistency with observed values.Nomograms have been widely used to evaluate the prognosis and death risk in malignant tumor patients.Chen et al11 studied all-cause and speci c mortalities of ovarian clear cell carcinoma and constructed a nomogram with the prognostic factors age, laterality, organ metastasis, AJCC stage, number of lymphadenectomies, and chemotherapy. Yuan et al12 assessed lung metastasis incidence in ovarian cancer and proposed that stage, liver, bone, and brain metastases and TN stage are predictors of lung metastasis.…”