Prognostic nomogram of the young renal cell carcinoma patient: a SEER-based study

Abstract

Abstract Objective We have constructed and verified nomograms to predict survival in young renal cancer survivors. METHODS We used the US SEER database to conduct a population-based cohort study. Patients diagnosed with young renal cancer were abstracted from the 2000–2018 Surveillance, Endemic Epidemiology, and End Results (SEER) data base, and variables were screened by both univariate and multivariate logistic regression analysis. Risk factors that were statistically meaningful were used to establish predictive models. The areas of the curve (AUC) of the working characteristics of the subjects were used to assess the models' performance.Accuracy and clinical usability were evaluated based on the results of ROC curve, C-index and DCA curve. RESULTS The training cohort in this study includes 3306 patients with a validation cohort of 1416 patients.Multifactorial analysis indicated that patients who were young, married, well-differentiated, low T, N, M stage, and surgery had improved prognosis. The nomogram included 12 independent factors affecting overall survival. The model had a c-index of 0.82, which represents predictive accuracy.The AUC values in the validation set were 0.91, 0.85 and 0.82 for 1, 3 and 5 years, depending on the type of the validation set.The model was shown to have high computational accuracy.The DCA results indicated that the model had a favorable net benefit for patients with renal cell carcinoma. CONCLUSION We have successfully structured the accurate and effective nomograms to predict the prognosis of young renal cancer patients, which helps physicians to choose individualized treatment strategies for young renal cancer patients.