Establishment And Evaluation Of Preoperative Hematological Prognostic Score Model In Patients With Prostate Cancer

Objective:Prostate cancer(Pca)is the most common urinary system tumor in elderly men.Clinically,patients are usually classified according to the characteristics of baseline PSA,pathological Gleason score,clinical TNM stage,and castration resistance,so as to formulate appropriate treatment plans.However,Even within the same clinical subgroup of patients,there are still large differences in prognosis and clinical outcomes.Therefore,more prognostic indicators are needed to help risk stratification of prostate cancer patients,thereby improving the long-term survival of patients.Substantial evidence have found that hematological markers are associated with the prognosis of prostate cancer and can effectively predict the clinical outcome of patients.However,most studies only explored the prognostic value of two or three or even single hematological index,which is one-sided.Therefore,this study established a prognostic scoring system that included multiple meaningful hematological indicators,to predict the prognosis of patients with prostate cancer,more comprehensively and precisely.Methods:This retrospective study included 280 newly diagnosed prostate cancer patients in Henan Provincial People’s Hospital from December 2016 to December 2019.We collected informations from the electronic medical record system of each patient:,such as age at initial diagnosis,medical historytheir,Gleason score,clinical TNM stage,and hematological index results.Receiver operating characteristic(ROC)curve was used to determine the optimal cutoff value of each laboratory index,and the cut-off value was used to adjust each index as a binary variable.The Kaplan-Meier method was used to analyze the statistical significance of each factor for survival.Univariate and multivariate Cox regression analysis was used to find independent prognostic factors for prostate cancer.Least absolute shrinkage and selection operator Cox proportional hazards regression analysis were used to screen for the best covariates to construct this prognostic score.According to the results of Cox regression analysis,a survival prediction nomogram based on the Hematology prognostic score model(HPS)combined with clinical index score quantification was constructed;and tested the predictive power of the nomogram.Finally,the relationship between HPS and various clinical prognostic factors was further analyzed.All statistical analyses in this study were performed by R software and SPSS.Result:1.10 hematological indicators were used to construct HPS.According to the ROC curve,the best cutoff value of HPS in prostate cancer patients was 0.99.Patients were divided into high-risk and low-risk groups according to this cutoff value.According to the univariate and multivariate survival analysis results,the overall survival(OS)of the low HPS group was significantly longer than that of the high HPS group(P<0.001).2.In prostate cancer patients,the C-index of the nomogram based on HPS and other clinical prognostic factors was 0.82;The 2-and 3-year OS predicted by the calibration plot of the nomogram model,was consistent with the actual survival time of prostate cancer patients shown by the K-M analysis.the results of the decision curve analysis showed that the nomogram could produce a certain net clinical benefit.;the decision curve analysis showed that the nomogram could produce a certain net clinical benefit.3.All prostate cancer patients are grouped according to T stage,lymph node metastasis and distant metastasis,and the violin diagram shows the risk score of HPS in different groups.T4 stage group(P<0.001),lymph node metastasis group(P<0.001),and distant metastasis group(P<0.001)had higher HPS scores.4.According to age,radical surgery,Gleason score,PSA,T stage,N stage,and M stage,HPS can divide patients into low-risk subgroups and high-risk subgroups.The results of subgroup analysis showed that HPS could be combined with clinical characteristics to more accurately predict the prognosis of prostate cancer patients.Conclusion:1.The 10 hematological indexes of ALP,G,MLR,LDH,BUA,DD,NLR,PLR,FIB and PT reflect the state of inflammation,nutrition,coagulation and other aspects of the body,which are closely related to the prognosis of prostate cancer.2.The HPS constructed in this study is an independent prognostic factor affecting OS in patients with prostate cancer,and it has been verified to have reliable prognostic performance.3.The HPS-based nomogram model has a high predictive ability for the survival rate of prostate cancer patients.4.When predicting the prognosis of patients with different types of prostate cancer,HPS is robust and can further stratify patients with various clinical characteristics.