Partin A W, Epstein J I, Cho K R, Gittelsohn A M, Walsh P C
Department of Urology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
J Urol. 1989 Feb;141(2):341-5. doi: 10.1016/s0022-5347(17)40761-0.
Although tumor volume is an important factor in predicting prognosis in carcinoma of the prostate, direct and accurate estimation of tumor volume is not practical clinically at present because the tumor may not always be palpable (stage A) and when palpable it is difficult to estimate volume in 3 dimensions. For this reason the clinical staging of prostate cancer currently is based on estimations of the per cent of gland involved with tumor: in stage A by per cent of tissue involved with cancer and in stage B by digital palpation (less than 1 lobe, 1 lobe and 2 lobes). In stage A prostate cancer the per cent of the specimen involved with tumor and the volume of tumor have been shown to correlate with tumor progression. Our study was designed to determine if either or both of these morphometric factors would be good predictors of pathological stage in stage B prostate cancer. We analyzed 56 step-sectioned radical prostatectomy specimens: 28 without capsular penetration, 15 with capsular penetration only and 13 with seminal vesicle involvement. The per cent of gland involved with tumor (correlation coefficient 0.67, p less than 0.001) and tumor volume (correlation coefficient 0.55, p less than 0.001) correlated well with pathological stage. Stepwise linear regression showed that the combination of the per cent of gland involved with tumor and the total Gleason grade was statistically the best predictor of pathological stage.
尽管肿瘤体积是预测前列腺癌预后的一个重要因素,但目前临床上直接准确地估计肿瘤体积并不实际,因为肿瘤可能并不总是可触及的(A期),而且当可触及肿瘤时,很难从三维角度估计其体积。因此,目前前列腺癌的临床分期是基于对肿瘤累及腺体百分比的估计:A期根据癌组织累及的组织百分比,B期则通过直肠指诊(小于1叶、1叶和2叶)来判断。在A期前列腺癌中,标本中肿瘤累及的百分比和肿瘤体积已被证明与肿瘤进展相关。我们的研究旨在确定这两个形态学因素中的一个或两个是否是B期前列腺癌病理分期的良好预测指标。我们分析了56个经连续切片的前列腺癌根治性切除术标本:28个无包膜侵犯,15个仅侵犯包膜,13个侵犯精囊。肿瘤累及腺体的百分比(相关系数0.67,p<0.001)和肿瘤体积(相关系数0.55,p<0.001)与病理分期密切相关。逐步线性回归显示,肿瘤累及腺体的百分比和总的Gleason分级相结合在统计学上是病理分期的最佳预测指标。