Department of Urology, University of California San Francisco Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California 94143-1695, USA.
Cancer. 2012 Dec 15;118(24):6046-54. doi: 10.1002/cncr.27670. Epub 2012 Jun 6.
In the current study, the authors propose the quantitative Gleason score (qGS), a modification of the current Gleason grading system for prostate cancer, based on the weighted average of Gleason patterns present in the pathology specimen. They hypothesize that the qGS can improve prostate cancer risk stratification and help prevent the overtreatment of patients with clinically indolent tumors.
The qGS was applied to patients in the University of California San Francisco urologic oncology database with tumors determined to have a GS of 7 on prostate biopsy or final pathology after radical prostatectomy (RP). Using multivariable logistic regression, Cox proportional hazards regression, receiver operating characteristic (ROC), and decision curve analyses, the ability of qGS to predict pathological GS and the risk of disease recurrence after RP was assessed.
A total of 225 men were included in the analysis of biopsy specimens and 618 men were included in the assessment of RP specimens. Compared with traditional Gleason scoring, the qGS improved concordance between biopsy and pathological GS on decision curve and ROC analyses (area under the curve ROC curve, 0.79 vs 0.71). On regression analysis, the qGS of biopsy specimens was found to be significantly associated with pathological grade after RP (hazard ratio [HR], 1.78; 95% confidence interval [95% CI], 1.49-2.12) and the qGS of RP specimens was significantly associated with the risk of biochemical disease recurrence after RP (HR, 1.13; 95% CI, 1.04-1.24).
The qGS, a simple modification of the current Gleason system, appears to improve the correlation between biopsy and pathological GS, as well as the prediction of biochemical disease recurrence after RP. This scoring system may allow more men to pursue active surveillance, thereby avoiding the morbidity of prostate cancer treatment modalities.
在目前的研究中,作者提出了定量 Gleason 评分(qGS),这是对当前前列腺癌 Gleason 分级系统的一种修改,基于病理标本中存在的 Gleason 模式的加权平均值。他们假设 qGS 可以改善前列腺癌风险分层,并有助于防止对具有临床惰性肿瘤的患者进行过度治疗。
qGS 应用于加利福尼亚大学旧金山泌尿科肿瘤数据库中的患者,这些患者的肿瘤在前列腺活检或根治性前列腺切除术后的最终病理中被确定为 GS 为 7。使用多变量逻辑回归、Cox 比例风险回归、接受者操作特征(ROC)和决策曲线分析,评估 qGS 预测病理 GS 和 RP 后疾病复发风险的能力。
共纳入 225 例接受活检标本分析的男性和 618 例接受 RP 标本评估的男性。与传统的 Gleason 评分相比,qGS 在决策曲线和 ROC 分析(ROC 曲线下面积,0.79 与 0.71)上提高了活检和病理 GS 之间的一致性。回归分析发现,活检标本的 qGS 与 RP 后病理分级显著相关(风险比[HR],1.78;95%置信区间[95%CI],1.49-2.12),RP 标本的 qGS 与 RP 后生化疾病复发的风险显著相关(HR,1.13;95%CI,1.04-1.24)。
qGS,是当前 Gleason 系统的一个简单修改,似乎提高了活检和病理 GS 之间的相关性,以及预测 RP 后生化疾病复发的能力。这种评分系统可能使更多的男性能够接受积极监测,从而避免前列腺癌治疗方式的发病率。