Construction of a Prediction Model for significant increases in pGS scores after radical prostatectomy in low-risk prostate cancer patients
Li Xiaoshan
Liu Wei
Wei Shiping
Abstract：Objective:To develop a predictive model for significant increases in Gleason scores(pGS)follow-ing radical prostatectomy in low-risk prostate cancer(PCa)patients.Methods:A total of 226 low-risk PCa patients who underwent radical prostatectomy at the Yangtze Shipping General Hospital were randomly divided into a training set(n=158)and a validation set(n=68)in a 7∶3 ratio.In the training set,patients were classified into two groups based on the presence or absence of significant post-operative pGS elevation:the"increase"group and the"no in-crease"group.Clinical data were collected and compared between the two groups.Logistic regression analysis was performed to identify factors associated with significant pGS elevation after surgery.A predictive model was devel-oped based on the regression results,and its performance was evaluated using receiver operating characteristic(ROC)curve analysis.Results:Among the 158 patients in the training set,47(29.75%)showed a significant in-crease in pGS after surgery.The"increase"group had significantly higher pre-operative prostate-specific antigen(PSA)levels compared to the"no increase"group(P<0.05),as well as higher age and PSA density(PSAD)(P<0.05),and smaller prostate volume(P<0.05).Logistic regression analysis revealed that age,prostate volume,pre-operative PSA,and PSAD were significant predictors of post-operative pGS elevation(P<0.05).The predictive model was formulated as follows:Logit(P)=1.042+1.732×X1(age)-3.978×X2(prostate volume)+1.168×X3(pre-operative PSA)+6.017×X4(PSAD).ROC curve analysis indicated an area under the curve(AUC)of 0.921(95%CI:0.871-0.970),with a sensitivity of 80.91%and specificity of 97.28%.Internal validation showed an AUC of 0.983(95%CI:0.000-1.000),and external validation demonstrated an AUC of 0.968(95%CI:0.000-1.000).Conclusion:Significant post-radical prostatectomy pGS elevation in low-risk PCa patients is primarily influenced by age,prostate volume,pre-operative PSA,and PSAD.The developed predictive model demonstrates strong perfor-mance and potential clinical utility.
Keywords：prostate cancerradical prostatectomygleason scorepredictive model
Publication Date：2025-02-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 25-30 )