Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

Abstract

Purpose Ovarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in patients with ovarian cancer. Methods We used data from the Surveillance, Epidemiology, and End Results database of patients with ovarian cancer registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves. Results A total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: American Joint Committee on Cancer (AJCC) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The concordance indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death. Conclusion Compared with predictions made based on AJCC stage or residual lesion size, the nomogram could provide more robust predictions for early death in patients with ovarian cancer.

Nomograms for predicting overall survival and cancer-specific survival in elderly patients with epithelial ovarian cancer

“…Compared with the FIGO stage and AJCC stage system, the nomogram model can predict the survival rate for each patient individually. At present, although several nomograms had been constructed for EOC patients in younger [12], under postoperative [13], and with sitedistant metastases [14], there are no nomograms for the elderly EOC patient currently. Elderly patients were often attached to comorbidity, immunosenescence, and organ dysfunction, which lead to more treatmentrelated toxicity and poor prognosis for elderly patients [15].…”

Nomograms for predicting overall survival and cancer-specific survival in elderly patients with epithelial ovarian cancer

“…Compared with the FIGO stage and AJCC stage system, the nomogram model can predict the survival rate for each patient individually. At present, although several nomograms had been constructed for EOC patients in younger [12], under postoperative [13], and with site-distant metastases [14], there are no nomograms for the elderly EOC patient currently. Elderly patients were often attached to comorbidity, immunosenescence, and organ dysfunction, which lead to more treatment-related toxicity and poor prognosis for elderly patients [15].…”