Jones Timothy D, Koch Michael O, Lin Haiqun, Cheng Liang
Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
BJU Int. 2005 Dec;96(9):1253-7. doi: 10.1111/j.1464-410X.2005.05825.x.
To analyse tumour extent as a predictor of cancer progression after radical prostatectomy (RP), using a multivariate Cox regression model, as several variables (e.g. Gleason grade and tumour stage) are well-established prognostic factors in prostate cancer but it is uncertain if the visual estimation of tumour extent (percentage of carcinoma) is an independent predictor for prostate cancer recurrence.
Tumour extent was estimated in the RP specimens from 504 men with clinically localized prostate cancer; clinical follow-up data were available for 459 men. The mean (range) follow-up was 44.3 (1.5-144) months. Cancer progression was defined by the development of biochemical recurrence, local recurrence, or distant metastasis. Multivariate analysis was used to assess tumour extent as a predictor of cancer progression.
Of the 459 patients, 157 had cancer progression; the mean tumour extent was 36% and 24% in those with and without cancer progression, respectively (P < 0.001). Univariate analysis showed a significant association between the visual estimation of tumour extent and tumour stage, Gleason grade, surgical margins, extraprostatic extension, seminal vesicle invasion, lymph node metastasis, and preoperative serum prostate-specific antigen level (all P < 0.001). However, in a multivariate Cox regression model controlling for pathological stage, Gleason score, and surgical margin status, the visual estimation of tumour extent was no longer a significant predictor of cancer progression (P = 0.84).
The visual estimation of tumour extent was associated with various established prognostic factors for prostate cancer, and with cancer progression in a univariate analysis, but it was not a significant predictor of cancer progression in the multivariate analysis controlling for pathological stage, Gleason score, and surgical margin status.
使用多变量Cox回归模型分析肿瘤范围作为根治性前列腺切除术(RP)后癌症进展的预测指标,因为一些变量(如Gleason分级和肿瘤分期)是前列腺癌中公认的预后因素,但肿瘤范围的视觉估计(癌组织百分比)是否为前列腺癌复发的独立预测指标尚不确定。
对504例临床局限性前列腺癌男性患者的RP标本进行肿瘤范围估计;459例男性患者有临床随访数据。平均(范围)随访时间为44.3(1.5 - 144)个月。癌症进展定义为生化复发、局部复发或远处转移的发生。采用多变量分析评估肿瘤范围作为癌症进展的预测指标。
459例患者中,157例出现癌症进展;有和没有癌症进展的患者,其平均肿瘤范围分别为36%和24%(P < 0.001)。单变量分析显示,肿瘤范围的视觉估计与肿瘤分期、Gleason分级、手术切缘、前列腺外侵犯、精囊侵犯、淋巴结转移及术前血清前列腺特异性抗原水平之间存在显著关联(均P < 0.001)。然而,在控制病理分期、Gleason评分和手术切缘状态的多变量Cox回归模型中,肿瘤范围的视觉估计不再是癌症进展的显著预测指标(P = 0.84)。
肿瘤范围的视觉估计与前列腺癌的多种既定预后因素相关,在单变量分析中与癌症进展相关,但在控制病理分期、Gleason评分和手术切缘状态的多变量分析中,它不是癌症进展的显著预测指标。