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.

Keywords: Cancer-specific survival; Nomogram; Ovarian clear cell carcinoma; Overall survival; Predict.

Fig. 1

The LASSO regression used to select prognostic factors for OS and CSS; a LASSO coefficient profiles of 11 variables for OS; b LASSO Cox analysis identified 8 variables for OS; c LASSO coefficient profiles of 11 variables for CSS; d LASSO Cox analysis identified 8 variables for CSS. OS: overall survival; CSS: cancer-specific survival

Fig. 2

Predictive nomograms. a Nomogram for predicting 3- and 5-year OS; b Nomogram for predicting 3- and 5-year CSS. Met: metastasis; AJCC: American Joint Commission on Cancer; LN: lymph node; OS: overall survival; CSS: cancer-specific survival

Fig. 3

Calibration plots. a 3-year and (b) 5-year OS nomogram calibration plots for training cohort; c 3-year and (d) 5-year OS nomogram calibration plots for validation cohort; e 3-year and (f) 5-year CSS nomogram calibration plots for training cohort; g 3-year and (H) 5-year CSS nomogram calibration plots for validation cohort. OS: overall survival; CSS: cancer-specific survival

Fig. 4

DCA curve of the nomogram and AJCC stage for (a) OS and (b) CSS. DCA: decision curve analysis; AJCC: American Joint Commission on Cancer; OS: overall survival; CSS: cancer-specific survival

Fig. 5

Kaplan-Meier curves. a Overall survival and (b) cancer-specific survival for patients stratified by the risk stratification system