Nomogram for predicting overall and cancer-specific survival in elderly patients (≥65 years) with epithelial ovarian cancer

Abstract Background: Current evidence suggests that the morbidity and mortality of ovarian cancer in elderly patients have increased over the past few years. To date, there are no standard treatment guidelines for elderly (65 years and older) patients with ovarian cancer. This study aimed to use the SEER database to extract relevant clinicopathological data and construct a nomogram to predict the prognosis of elderly patients with ovarian cancer that could assist clinicians during clinical decision-making and improve the prognosis of this patient population.Methods: We screened a total of 22,181 eligible patients. The collected patient information was randomly assigned to a training cohort (n = 15529) and validation cohort (n = 6652) at a ratio of 7:3. COX and LASSO analyses were used to screen the overall survival rate and tumor-specific survival rate of elderly ovarian cancer patients. The independent risk factors were used to establish a nomogram using the rms package. The predictive and clinical utility of nomograms was assessed using concordance index, area under the curve (AUC), calibration curve and Decision curve analysis. Kaplan Meier analysis further stratified and analyzed the overall survival rates of patients in the high and low-risk groups to evaluate the stratification ability of the nomogram.Results: Our nomogram yielded significantly better performance than the AJCC staging system in predicting overall survival and tumor-specific survival prognosis in elderly (65 years and older) ovarian cancer patients. Survival curve analysis showed that the nomogram has excellent risk stratification ability.Conclusions: Our nomogram could effectively predict the overall survival rate and tumor-specific survival rate of elderly patients with ovarian cancer (65 years old and above) to help clinicians make individual survival predictions and provide improved treatment recommendations.