OBJECTIVE: The aim of this study was to predict seminal vesicle invasion (SVI) by developing a new nomogram based on clinical features including the status of cancer at the base of the prostate on systematic biopsy. METHODS: We studied the 466 patients with T1-3N0M0 prostate cancer who were treated with radical prostatectomy at three institutions. Preoperative clinical variables were correlated with the presence or absence of SVI with an area under the curve (AUC) of receiver-operator characteristics analysis. A nomogram was developed to predict SVI based on logistic regression analysis. RESULTS: A total of 81 patients (17%) had SVI. Cancer was present in a biopsy core from the base of the prostate in 209 patients, of whom 32.5% had SVI, compared with only 5% of the 257 patients without cancer at the base of the prostate (P < 0.005). On multivariate analysis, serum prostate-specific antigen, biopsy Gleason score, clinical T stage, and presence or absence of cancer in a biopsy core at the base of the prostate were significant predictors of SVI (P < 0.005 for all). The AUC of a standard model including clinical stage, Gleason score, and prostate-specific antigen was 0.83, which was significantly enhanced by including the presence of cancer at the base of the prostate (none, unilateral or bilateral lobes) (AUC 0.87, P= 0.023). Based on the logistic analysis, we developed the nomogram to predict SVI. The calibration plots appeared to be excellent. CONCLUSION: The information of presence or absence of cancer at the base from prostate biopsy and the resulting nomogram allow an accurate prediction of SVI in patients undergoing radical prostatectomy for prostate cancer.
OBJECTIVE: The aim of this study was to predict seminal vesicle invasion (SVI) by developing a new nomogram based on clinical features including the status of cancer at the base of the prostate on systematic biopsy. METHODS: We studied the 466 patients with T1-3N0M0 prostate cancer who were treated with radical prostatectomy at three institutions. Preoperative clinical variables were correlated with the presence or absence of SVI with an area under the curve (AUC) of receiver-operator characteristics analysis. A nomogram was developed to predict SVI based on logistic regression analysis. RESULTS: A total of 81 patients (17%) had SVI. Cancer was present in a biopsy core from the base of the prostate in 209 patients, of whom 32.5% had SVI, compared with only 5% of the 257 patients without cancer at the base of the prostate (P < 0.005). On multivariate analysis, serum prostate-specific antigen, biopsy Gleason score, clinical T stage, and presence or absence of cancer in a biopsy core at the base of the prostate were significant predictors of SVI (P < 0.005 for all). The AUC of a standard model including clinical stage, Gleason score, and prostate-specific antigen was 0.83, which was significantly enhanced by including the presence of cancer at the base of the prostate (none, unilateral or bilateral lobes) (AUC 0.87, P= 0.023). Based on the logistic analysis, we developed the nomogram to predict SVI. The calibration plots appeared to be excellent. CONCLUSION: The information of presence or absence of cancer at the base from prostate biopsy and the resulting nomogram allow an accurate prediction of SVI in patients undergoing radical prostatectomy for prostate cancer.
Authors: Kosj Yamoah; Amy Walker; Elaine Spangler; Charnita M Zeigler-Johnson; Bruce Malkowicz; David I Lee; Adam P Dicker; Timothy R Rebbeck; Priti Lal Journal: Clin Genitourin Cancer Date: 2014-10-25 Impact factor: 2.872
Authors: Kevin Martell; Soumyajit Roy; Tyler Meyer; Jordan Stosky; Will Jiang; Kundan Thind; Michael Roumeliotis; John Bosch; Steve Angyalfi; Harvey Quon; Siraj Husain Journal: Heliyon Date: 2020-06-07