Department of Urology, Tokyo Medical University, Tokyo, Japan.
Int J Urol. 2010 Jun;17(6):534-40. doi: 10.1111/j.1442-2042.2010.02513.x. Epub 2010 Mar 29.
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.
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.
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.
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.
本研究旨在通过建立一个新的列线图来预测精囊侵犯(SVI),该列线图基于包括前列腺基底系统活检中癌症状态在内的临床特征。
我们研究了在三个机构接受根治性前列腺切除术治疗的 466 名 T1-3N0M0 前列腺癌患者。通过受试者工作特征曲线(ROC)分析,将术前临床变量与 SVI 的有无进行相关性分析。基于逻辑回归分析,建立预测 SVI 的列线图。
共有 81 名患者(17%)发生 SVI。209 名患者的前列腺基底活检中有癌症,其中 32.5%有 SVI,而 257 名前列腺基底无癌症的患者中只有 5%有 SVI(P<0.005)。多变量分析显示,血清前列腺特异性抗原、活检 Gleason 评分、临床 T 分期以及前列腺基底活检中癌症的有无是 SVI 的显著预测因素(所有 P<0.005)。包括临床分期、Gleason 评分和前列腺特异性抗原的标准模型的 AUC 为 0.83,而包括前列腺基底有无癌症(无、单侧或双侧叶)的模型 AUC 为 0.87(P=0.023)。基于逻辑分析,我们开发了预测 SVI 的列线图。校准图似乎非常出色。
前列腺活检中前列腺基底有无癌症的信息以及由此产生的列线图可准确预测接受根治性前列腺切除术治疗前列腺癌的患者的 SVI。