A nomogram for predicting cancer-specific survival in patients with uterine clear cell carcinoma: a population-based study

Abstract

AbstractUterine clear cell carcinoma (UCCC) is a relatively rare endometrial cancer. There is limited information on its prognosis. This study aimed to develop a predictive model predicting the cancer-specific survival (CSS) of UCCC patients based on data from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018. A total of 2329 patients initially diagnosed with UCCC were included in this study. Patients were randomized into training and validation cohorts (7:3). Multivariate Cox regression analysis identified that age, tumor size, SEER stage, surgery, number of lymph nodes detected, lymph node metastasis, radiotherapy and chemotherapy were independent prognostic factors for CSS. Based on these factors, a nomogram for predicting the prognosis of UCCC patients was constructed. The nomogram was validated using concordance index (C-index), calibration curves, and decision curve analyses (DCA). The C-index of the nomograms in the training and validation sets are 0.778 and 0.765, respectively. Calibration curves showed good consistency of CSS between actual observations and nomogram predictions, and DCA showed that the nomogram has great clinical utility. In conclusion, a prognostic nomogram was firstly established for predicting the CSS of UCCC patients, which can help clinicians make personalized prognostic predictions and provide accurate treatment recommendations.