Prognostic Factors For Survival In Patients With Metastatic Renal Cell Carcinoma

Objective:This study is to determine the prognostic factors for survival in patients with metastatic renal cell carcinoma in SEER database and establishs a survival prognosis model for such patients,which is intended to predict the overall survival.At the same time,the models can help improve diagnosis and hence the management of patients with metastatic renal cell carcinoma.Methods:For the analysis,8,5000 patients diagnosed with metastatic renal cell carcinoma in 2010-2015 were obtained from the SEER database.After screening for study inclusion and exclusion criteria,2912 patients with metastatic renal cell carcinoma were eventually included in the study.Data was randomly divided into training cohort(n=2040)and validation cohort(n=872).First,univariate and multivariate Cox regression analyses were used to identify independent prognostic variables for the construction of nomogram.Finally,predictive performance was internally validated using validation cohort.The predictive accuracy and discriminative ability of the nomogram were determined by the concordance index(C-index),calibration curve,and area under the receiver operating characteristic(ROC)curve(AUC)of ROC analysis.Results: Age at diagnosis,the proportions of <50 year,50-59 year,60-69 year,70-79 year and ≥80 year were 13.7%,30.6%,32.9%,17.9%and 4.9%,respectively;More than 3/4 of the patients(n=2445,84%)are white;the pathological grade is grade II or grade III or grade IV(20.0%,42.8%,34.8%,respectively);the most common histological type is transparent cell carcinoma(63.9%).In univariate Cox analysis,diagnosis age,T stage,N stage,histological type,surgical status,radiotherapy status,brain metastasis,liver metastasis,and lung metastasis were all related to OS in m RCC patients(P<0.05);A multivariate Cox regression analysis further showed that age at diagnosis,T stage,N stage,histological type,surgery,brain metastasis,liver metastasis and lung metastasis were associated with survival in patients with metastatic renal cell carcinoma.The the C-index and AUC value further supports good model performance.The C-index provided by the nomogram(0.709 for the training cohort and 0.718 for the validation cohort)were higher than the C-index of the AJCC staging system(0.614 and 0.617,respectively).The receiver operating characteristic(ROC)curve analysis demonstrated the predictive ability of the patients with m RCC for3-and 5-year OS with the area under the curve(AUC)provided by the nomogram(0.755 and 0.749 for the training cohort and 0.743 and 0.759 for the validation cohort)were higher than the area under the curve(AUC)of the AJCC staging system(0.659 and 0.678 for the training cohort and 0.667 and 0.664 for the validation cohort,respectively).In conclusion,it can be proven that the prediction model exhibits good discriminate.The calibration plot showed a high consistency between the predicted and the observed events for predictive ability of the patients with m RCC for 3-and 5-year OS.Conclusions: 1.For m RCC,age at diagnosis,T stage,N stage,histological type,surgery,brain metastasis,liver metastasis and lung metastasis were independent factors affecting survival and prognosis.2.Combined m RCC patients with the prognostic factors(age at diagnosis,T stage,N stage,histological type,surgery,brain metastasis,liver metastasis and lung metastasis)to establish combined predictive models successively,the predictive efficiency and accuracy increased significantly.This study showed that the Nomogram survival prediction model for m RCC based on the SEER database had higher accuracy.This study will help to promote personalized treatment and medical decision-making for patients with m RCC.