Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: A study based on the SEER database and a Chinese cohort

Abstract Background: Based on the SEER database of patients diagnosed with OCCC from 2000 to 2018, the overall survival (OS) and cancer-specific survival (CSS) nomograms were constructed, and the OCCC patients from our hospital were used for external validation. We aim to develop scientifically valid prognostic models for OCCC. Methods: Data were extracted from the SEER database for patients diagnosed with OCCC. Cox regression analyses were used to identify independent risk factors for OCCC. Two nomograms were developed and the results were evaluated comprehensively by C-index, ROC curve, calibration curve, and DCA curve. Finally, patients diagnosed with OCCC in our hospital were used as the validation set to verify the model. Results: A total of 1855 OCCC patients from the SEER database were used as the training set and 101 patients from our hospital were used as the validation set. Cox regression analysis of the independent risk factors affecting the prognosis of OCCC was used to construct nomograms. The C-index of the training set OS was 0.76, and the validation set OS was 0.75. The AUC of the training set OS is 0.803, 0.794, and 0.802 for 1, 3, and 5 years, and 0.774, 0.800, and 0.923 for the validation set. The calibration curve and DCA curve also show that OS and CSS have good predictive power. Conclusions: We constructed nomograms to predict the prognosis of OCCC. The nomograms have satisfactory accuracy and clinical practicability, which can guide the decision of clinicians.