Development of a nomogram for predicting survival of patients with ovarian serous cystadenocarcinoma after based on SEER database.

Abstract

To develop a survival time prediction model for patients with ovarian serous cystadenocarcinoma after surgery. A retrospective analysis of 5906 postoperative patients with ovarian serous cystadenocarcinoma in the surveillance, epidemiology, and end results (SEER) database from 2010 to 2015 was performed. The independent risk factors for long-term survival were analyzed with multivariate Cox proportional hazard regression model. The nomogram of 3-year and 5-year survival was developed by using R language. The receiver operator characteristic (ROC) curve and were used to test the discrimination of the model and the calibration diagram was used to evaluate the degree of calibration of the prediction model. The survival curves was conducted by the risk factors. Cox proportional hazard regression model showed that age, race, histological grade (poorly differentiated and undifferentiated), stage T (T2a, T2b, T2c, T3a, T3b and T3c), and stage M (M1) were independent factors for the prognosis of patients with ovarian serous cystadenocarcinoma after surgery. A nomogram was developed by the R language tool for predicting the 3-year and survival of patients through age, race, histological classification, stage T and stage M. The C-index was 0.688 and the areas under ROC curve of the nomogram for predicting 3-year and 5-year survival were 0.708 and 0.716, respectively. The results of the calibration indicated that the predicted values were consistent with the actual values in the prediction models. The survival time of patients with high-risk factors was shorter than that of patients with low-risk factors (<0.05). The developed nomogram in this study can be used to predict 3-year and 5-year survival of postoperative patients with ovarian serous cystadenocarcinoma, and it may be beneficial to guide clinical treatment.