Li Zhen, Huang Yixin, Zhao Diwei, Luo Xin, Wu Zeshen, Zheng Xinyi, Xie Ye, Liu Yixuan, Wu Jianwei, Peng Yulu, Li Yonghong, Zhou Fangjian
Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou, China.
State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Front Oncol. 2023 May 8;13:1186319. doi: 10.3389/fonc.2023.1186319. eCollection 2023.
BACKGROUND: Few studies have focused on the performance of Briganti 2012, Briganti 2017 and MSKCC nomograms in the Chinese population in assessing the risk of lymph node invasion(LNI) in prostate cancer(PCa) patients and identifying patients suitable for extended pelvic lymph node dissection(ePLND). We aimed to develop and validate a novel nomogram based on Chinese PCa patients treated with radical prostatectomy(RP) and ePLND for predicting LNI. METHODS: We retrospectively retrieved clinical data of 631 patients with localized PCa receiving RP and ePLND at a Chinese single tertiary referral center. All patients had detailed biopsy information from experienced uropathologist. Multivariate logistic-regression analyses were performed to identify independent factors associated with LNI. The discrimination accuracy and net-benefit of models were quantified using the area under curve(AUC) and Decision curve analysis(DCA).The nonparametric bootstrapping were used to internal validation. RESULTS: A total of 194(30.7%) patients had LNI. The median number of removed lymph nodes was 13(range, 11-18). In univariable analysis, preoperative prostate-specific antigen(PSA), clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa, percentage of positive cores, percentage of positive cores with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy differed significantly. The multivariable model that included preoperative PSA, clinical stage, biopsy Gleason grade group, maximum percentage of single core involvement with highest-grade PCa and percentage of cores with clinically significant cancer on systematic biopsy represented the basis for the novel nomogram. Based on a 12% cutoff, our results showed that 189(30%) patients could have avoided ePLND while only 9(4.8%) had LNI missing ePLND. Our proposed model achieved the highest AUC (proposed model vs Briganti 2012 vs Briganti 2017 vs MSKCC model: 0.83 vs 0.8 vs 0.8 vs 0.8, respectively) and highest net-benefit DCA in the Chinese cohort compared with previous nomograms. In internal validation of proposed nomogram, all variables had a percent inclusion greater than 50%. CONCLUSION: We developed and validated a nomogram predicting the risk of LNI based on Chinese PCa patients, which demonstrated superior performance compared with previous nomograms.
背景：很少有研究关注Briganti 2012、Briganti 2017和MSKCC列线图在中国人群中评估前列腺癌（PCa）患者淋巴结转移（LNI）风险以及识别适合扩大盆腔淋巴结清扫术（ePLND）患者方面的表现。我们旨在基于接受根治性前列腺切除术（RP）和ePLND的中国PCa患者开发并验证一种用于预测LNI的新型列线图。 方法：我们回顾性检索了在中国一家三级转诊中心接受RP和ePLND的631例局限性PCa患者的临床资料。所有患者均有经验丰富的泌尿病理学家提供的详细活检信息。进行多因素逻辑回归分析以确定与LNI相关的独立因素。使用曲线下面积（AUC）和决策曲线分析（DCA）对模型的判别准确性和净效益进行量化。采用非参数自助法进行内部验证。 结果：共有194例（30.7%）患者发生LNI。切除淋巴结的中位数为13个（范围为11 - 18个）。在单因素分析中，术前前列腺特异性抗原（PSA）、临床分期、活检Gleason分级组、最高级别PCa单核受累的最大百分比、阳性核心百分比、最高级别PCa阳性核心百分比以及系统活检中有临床意义癌症的核心百分比存在显著差异。包含术前PSA、临床分期、活检Gleason分级组、最高级别PCa单核受累的最大百分比以及系统活检中有临床意义癌症的核心百分比的多因素模型构成了新型列线图的基础。以12%为临界值，我们的结果显示，189例（30%）患者本可避免接受ePLND，而仅有9例（4.8%）发生LNI却未接受ePLND。与之前的列线图相比，我们提出的模型在中国队列中实现了最高的AUC（提出的模型vs Briganti 2012 vs Briganti 2017 vs MSKCC模型：分别为0.83 vs 0.8 vs 0.8 vs 0.8）和最高的净效益DCA。在对提出的列线图进行内部验证时，所有变量的纳入百分比均大于50%。 结论：我们开发并验证了一种基于中国PCa患者预测LNI风险的列线图，其表现优于之前的列线图。
Beijing Da Xue Xue Bao Yi Xue Ban. 2025-8-18
CA Cancer J Clin. 2021-1
Zotero 插件