Establishment Of Prognostic Model And Pathological Upstaging Model Using Inflammation-coagulation Index And Tumor Characteristics For Patients With Localized Renal Cell Carcinoma

? Chapter I Combination of hematology indicators and oncological characteristics as a new promising prognostic model in localized clear cell renal cell carcinomaPurpose:This study aimed to construct a predictive model for recurrence and metastasis in patients with localized clear cell renal cell carcinoma(ccRCC)based on multiple preoperative blood indexes and oncological characteristics.Patients and methods:Overall,442 patients with localized ccRCC between 2013 and 2015 were included.Using least absolute shrinkage and selection operator(LASSO)Cox regression analysis,the top three risk factors from the peripheral blood indicators were screened to construct a risk score,and a prognostic model was established.We further counted 504 patients with localized ccRCC from April 2015 to March 2017 for external validation.Harrell's concordance index(C-index)was applied to evaluate the predictive accuracy of the model for predicting disease-free survival(DFS)in ccRCC.Results:Out of 38 blood indexes,the top three predictors were fibrinogen(FIB),C-reactive protein(CRP)and neutrophil-lymphocyte ratio(NLR).The FIB-CRP-NLR(FCN)score(hazard ratio[HR]:1.86,95%confidence interval[CI]:1.21-2.9,P=0.005)was an independent prognostic factor in multivariate analysis.Furthermore,the FIB-CRP-NLR-T-Grade(FCNTG)risk model combining FCN score,T stage and Furhman grade achieved a higher prognostic accuracy(mean C-index,0.728)than both the FCN score alone(mean C-index,0.675)and the stage,size,grade,and necrosis(SSIGN)score(mean C-index,0.686)in the internal validation cohort.The same conclusion were found in the external validation cohort.Conclusion:The FCN score combining peripheral blood indicators of inflammation and coagulation is an independent prognostic marker of ccRCC.The FCNTG model,which systemically incorporates preoperative blood indexes to oncological characteristics,shows its advantages of convenience and high prediction efficiency.? Chapter ? Combination of coagulation indicators and oncological characteristics as a prediction model in renal cell carcinoma from clinical Tla to pathological T3aPurpose:This study aimed to establish preoperative factors and develop a predictive model associated with pathological T3a(pT3a)upstaging in patients with clinical T1a(cT1a)renal cell carcinoma(RCC)based on multiple preoperative blood indexes and oncological characteristics.Patients and methods:Overall,510 patients with cT1a RCC between 2010 and 2019 were included.Using least absolute shrinkage and selection operator(LASSO)regression analysis,the most important risk factor,fibrinogen(FIB),from the peripheral blood indicators was screened,and a predictive model was established.Harrell's concordance index(C-index)was applied to evaluate the predictive accuracy of the model for predicting pT3a upstaging in patients with cT1a RCC.Results:Out of 40 tumor and blood indexes,the first predictor was FIB.Age(Odds Ratio[OR]:1.06,95%confidence interval(CI):1.02-1.1,P=0.001),the ratio of the maximum and minimum diameter(ROD)(OR:3.93,95%CI:1.4-11.35,P=0.01),FIB(OR:1.74,95%CI:1.01-3.01,P=0.04)and tumor size(OR:1.76,95%CI:1.13-2.88,P=0.02)were all independent risk factors for pT3a upstaging in multivariate analysis.Furthermore,the C-index of the predictive ARFS model that combined the Age,ROD,FIB,and tumor Size was 0.756(95%CI,0.68-0.83)and 0.712(95%CI,0.64-0.79)in the training and validation cohorts respectively.Conclusion:Older age,higher ROD,increased FIB level,and larger tumor size were independent risk factors for pT3a upstaging in patients with cT1a RCC.The ARFS model showed its advantages of convenience and high prediction efficiency for pT3a upstaging in patients with cT1a RCC and further large-scale studies may be needed to confirm this model.