Development Of A Prognostic Prediction Model For Elderly Patients With Clear Cell Renal Cell Carcinoma And External Validation Of Single Center Clinical Data In China

Background and Objectives: In this study,the clinical data of elderly patients with clear cell renal cell carcinoma(ccRCC)from The Surveillance,Epidemiology and End Results(SEER)database of the National Cancer Institute of the United States were analyzed.A nomogram was constructed to predict 3-and 5-year overall survival(OS)of patients.The accuracy of the nomogram was validated externally in a single center so that clinicians can comprehensively evaluate the survival of patients and formulate individualized treatment plans.Material and Method: According to the inclusion and exclusion criteria,complete clinical data of 8638 elderly patients with ccRCC from 2010 to 2015 were extracted from the SEER database,and all patients were randomly divided into the training cohort and the internal validation cohort at a ratio of 7:3.Univariate and multivariate Cox regression analyses were performed in the training cohort to determine the prognostic factors associated with OS.Finally,a nomogram was constructed to predict OS.Cindex,area under curve(AUC)and calibration curve were used to evaluate the accuracy of the nomogram.Decision curve analysis(DCA)was used to evaluate the clinical practicability of the nomogram.Finally,a risk classification system was established based on the total score of the nomogram to distinguish and identify patients with poor prognoses.A total of 199 elderly patients with ccRCC from the First Affiliated Hospital of Anhui Medical University between December 2014 and May 2021 were collected for external validation(titled the external validation cohort).Kaplan-Meier(KM)survival curve was used to describe the survival differences among the groups and risk layers.Results: Univariate and multivariate Cox regression analyses showed that age,sex,histological differentiation,T stage,N stage,M stage and type of operation were independent prognostic factors in elderly patients with ccRCC.A nomogram was constructed to predict OS based on the seven variables.The C-index and AUC of the nomogram in the training cohort and the internal validation cohort are higher than the TNM staging.The AUC of the nomogram predicting 3-year and 5-year OS in the external validation cohort was 0.823 and 0.688,respectively.The calibration curve showed that there was good consistency between the predicted results and the actual results.DCA results showed that the nomogram was more valuable than the TNM staging in clinical applications.Finally,the nomogram-based risk classification system divided all elderly ccRCC patients into low-,intermediate-,and high-risk groups,and the KM curves in three risk groups showed significant survival differences in different cohorts.Conclusions: 1.Age,sex,histological differentiation,T stage,N stage,M stage and type of operation were independent risk factors affecting the prognosis of elderly ccRCC patients.2.Compared with the traditional TNM staging,the nomogram constructed in this study can predict the 3-and 5-year OS more accurately,which provided a convenient tool for clinicians to evaluate the survival of elderly patients with ccRCC.3.The risk classification system based on the nomogram can help clinicians identify intermediate-risk and high-risk patients accurately and make better interventions and treatments.