Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Department of Epidemiology-Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
J Urol. 2019 Jan;201(1):77-82. doi: 10.1016/j.juro.2018.07.062.
To our knowledge the ideal methodology of quantifying secondary Gleason pattern 4 in men with Grade Group 2/Gleason score 3 + 4 = 7 on biopsy remains unknown. We compared various methods of Gleason pattern 4 quantification and evaluated associations with adverse pathology findings at radical prostatectomy.
A total of 457 men with Grade Group 2 prostate cancer on biopsy subsequently underwent radical prostatectomy at our institution. Only patients with 12 or more reviewed cores were included in analysis. We evaluated 3 methods of quantifying Gleason pattern 4, including the maximum percent of Gleason pattern 4 in any single core, the overall percent of Gleason pattern 4 (Gleason pattern 4 mm/total cancer mm) and the total length of Gleason pattern 4 in mm across all cores. Adverse pathology features at radical prostatectomy were defined as Gleason score 4 + 3 = 7 or greater (Grade Group 3 or greater), and any extraprostatic extension, seminal vesical invasion and/or lymph node metastasis. A training/test set approach and multivariable logistic regression were used to determine whether Gleason pattern 4 quantification methods could aid in predicting adverse pathology.
On multivariable analysis all Gleason pattern 4 quantification methods were significantly associated with an increased risk of adverse pathology (p <0.0001) and an increased AUC beyond the base model. The largest AUC increase was 0.044 for the total length of Gleason pattern 4 (AUC 0.728, 95% CI 0.663-0.793). Decision curve analysis demonstrated an increased clinical net benefit with the addition of Gleason pattern 4 quantification to the base model. The total length of Gleason pattern 4 clearly provided the largest net benefit.
Our findings support the inclusion of Gleason pattern 4 quantification in the pathology reports and risk prediction models of patients with Grade Group 2/Gleason score 3 + 4 = 7 prostate cancer. The total length of Gleason pattern 4 across all cores provided the strongest benefit to predict adverse pathology features.
据我们所知,对于活检中 Gleason 评分 3+4=7(组织学分级 2 组)的男性,量化次要 Gleason 模式 4 的理想方法尚不清楚。我们比较了不同的 Gleason 模式 4 量化方法,并评估了它们与根治性前列腺切除术后不良病理结果的关系。
本研究共纳入 457 例在我院接受根治性前列腺切除术的组织学分级 2 组前列腺癌患者。仅纳入分析了至少有 12 个以上评估核心的患者。我们评估了量化 Gleason 模式 4 的 3 种方法,包括:单个核心中 Gleason 模式 4 最大百分比、Gleason 模式 4 总百分比(Gleason 模式 4mm/总肿瘤 mm)和所有核心中 Gleason 模式 4 的总长度(mm)。根治性前列腺切除术后的不良病理特征定义为 Gleason 评分 4+3=7 或更高(组织学分级 3 组或更高),以及任何前列腺外延伸、精囊侵犯和/或淋巴结转移。采用训练/测试集方法和多变量逻辑回归来确定 Gleason 模式 4 量化方法是否有助于预测不良病理。
多变量分析显示,所有 Gleason 模式 4 量化方法均与不良病理的风险增加显著相关(p<0.0001),并使基础模型的 AUC 增加。Gleason 模式 4 总长度的 AUC 增加最大,为 0.044(AUC 0.728,95%CI 0.663-0.793)。决策曲线分析表明,在基础模型中加入 Gleason 模式 4 量化可提高临床净获益。Gleason 模式 4 总长度可提供最大的净获益。
我们的研究结果支持在组织学分级 2 组/Gleason 评分 3+4=7 的前列腺癌患者的病理报告和风险预测模型中纳入 Gleason 模式 4 量化。所有核心中 Gleason 模式 4 的总长度对预测不良病理特征提供了最强的获益。