OBJECTIVES: The accurate preoperative prediction of the extent of cancer by pathologic examination is essential for choosing the optimal treatment for patients with prostate cancer. Currently available clinical staging methods are not adequate and more precise staging is required. METHODS: Using the log likelihood ratio test and receiver operating characteristic (ROC) curve analysis, preoperative variables, including biopsy pathologic findings, were assessed for predicting final pathologic stage in prostate cancer. A multivariate model for predicting disease organ confinement status was established for easy clinical use. RESULTS: The use of the number of cores with cancer and maximum cancer length in conjunction with the three variables (prostate-specific antigen, clinical stage, and biopsy Gleason score) was found to significantly improve predictability of extracapsular extension and seminal vesicle involvement in clinically resectable (n = 96) and localized prostate cancers (n = 81) (P < 0.05). Areas under ROC curves for the above two parameter sets (five- versus three-variable model) were 0.8395 and 0.7109, respectively, for capacity for extracapsular extension prediction in clinically localized cancer. These values for seminal vesicle involvement were 0.7861 and 0.6927, respectively. The logistic model gave positive and negative predictive values of 73% and 78%, and 64% and 83%, respectively, for extracapsular extension and seminal vesicle involvement in clinically localized cancer at a predicted probability of 0.5 or greater. CONCLUSIONS: The present method may be used to predict non-organ-confined prostate cancer with greater accuracy than the previously reported model using three variables.
OBJECTIVES: The accurate preoperative prediction of the extent of cancer by pathologic examination is essential for choosing the optimal treatment for patients with prostate cancer. Currently available clinical staging methods are not adequate and more precise staging is required. METHODS: Using the log likelihood ratio test and receiver operating characteristic (ROC) curve analysis, preoperative variables, including biopsy pathologic findings, were assessed for predicting final pathologic stage in prostate cancer. A multivariate model for predicting disease organ confinement status was established for easy clinical use. RESULTS: The use of the number of cores with cancer and maximum cancer length in conjunction with the three variables (prostate-specific antigen, clinical stage, and biopsy Gleason score) was found to significantly improve predictability of extracapsular extension and seminal vesicle involvement in clinically resectable (n = 96) and localized prostate cancers (n = 81) (P < 0.05). Areas under ROC curves for the above two parameter sets (five- versus three-variable model) were 0.8395 and 0.7109, respectively, for capacity for extracapsular extension prediction in clinically localized cancer. These values for seminal vesicle involvement were 0.7861 and 0.6927, respectively. The logistic model gave positive and negative predictive values of 73% and 78%, and 64% and 83%, respectively, for extracapsular extension and seminal vesicle involvement in clinically localized cancer at a predicted probability of 0.5 or greater. CONCLUSIONS: The present method may be used to predict non-organ-confined prostate cancer with greater accuracy than the previously reported model using three variables.
Authors: Maisa M Q Quintal; Luciana R Meirelles; Leandro L L Freitas; Luis A Magna; Ubirajara Ferreira; Athanase Billis Journal: Int Urol Nephrol Date: 2011-02-22 Impact factor: 2.370
Authors: Demetrios N Simopoulos; Anthony E Sisk; Alan Priester; Ely R Felker; Lorna Kwan; Merdie K Delfin; Robert E Reiter; Leonard S Marks Journal: BJU Int Date: 2019-02-24 Impact factor: 5.969