基于淋巴结转移指标的膀胱癌患者预后列线图：一项 SEER 人群研究和外部验证。

PURPOSE: This study aimed to compare the prognostic value of multiple lymph node metastasis (LNM) indicators and to develop optimal prognostic nomograms for bladder cancer (BC) patients. METHODS: BC patients were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and randomly partitioned into training and internal validation cohorts. Genomic and clinical data were collected from The Cancer Genome Atlas (TCGA) as external validation cohort. The predictive efficiency of LNM indicators was compared by constructing multivariate Cox regression models. We constructed nomograms on basis of the optimal models selected for overall survival (OS) and cause-specific survival (CSS). The performance of nomograms was evaluated with calibration plot, time-dependent area under the curve (AUC) and decision curve analysis (DCA) in three cohorts. We subsequently estimated the difference of biological function and tumor immunity between two risk groups stratified by nomograms in TCGA cohort. RESULTS: Totally, 10,093 and 107 BC patients were screened from the SEER and TCGA databases. N classification, positive lymph nodes (PLNs), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) were all independent predictors for OS and CSS. The filtered models containing LODDS had minimal Akaike Information Criterion, maximal concordance indexes and AUCs. Age, LODDS, T and M classification were integrated into nomogram for OS, while nomogram for CSS included gender, tumor grade, LODDS, T and M classification. The nomograms were successfully validated in predictive accuracy and clinical utility in three cohorts. Additionally, the tumor microenvironment was different between two risk groups. CONCLUSIONS: LODDS demonstrated superior prognostic performance over N classification, PLN and LNR for OS and CSS of BC patients. The nomograms incorporating LODDS provided appropriate prediction of BC, which could contribute to the tumor assessment and clinical decision-making.

目的：本研究旨在比较多个淋巴结转移（LNM）指标的预后价值，并为膀胱癌（BC）患者开发最佳的预后列线图。

方法：从 2004 年至 2015 年的监测、流行病学和最终结果（SEER）数据库中获取 BC 患者，并将其随机分为训练和内部验证队列。从癌症基因组图谱（TCGA）中收集基因组和临床数据作为外部验证队列。通过构建多变量 Cox 回归模型比较 LNM 指标的预测效率。我们基于为总生存（OS）和特定原因生存（CSS）选择的最佳模型构建了列线图。在三个队列中，通过校准图、时间依赖性曲线下面积（AUC）和决策曲线分析（DCA）评估了列线图的性能。随后，我们在 TCGA 队列中根据列线图分层的两个风险组估计了生物功能和肿瘤免疫的差异。

结果：从 SEER 和 TCGA 数据库中筛选出 10093 名和 107 名 BC 患者。N 分类、阳性淋巴结（PLN）、淋巴结比率（LNR）和对数阳性淋巴结比（LODDS）均为 OS 和 CSS 的独立预测因子。包含 LODDS 的过滤模型具有最小的 Akaike 信息准则、最大的一致性指数和 AUC。年龄、LODDS、T 和 M 分类被整合到 OS 列线图中，而 CSS 列线图包括性别、肿瘤分级、LODDS、T 和 M 分类。列线图在三个队列中的预测准确性和临床实用性方面均得到了成功验证。此外，两个风险组之间的肿瘤微环境存在差异。

结论：LODDS 与 N 分类、PLN 和 LNR 相比，在 OS 和 CSS 方面对 BC 患者具有更好的预后性能。纳入 LODDS 的列线图为 BC 提供了适当的预测，有助于肿瘤评估和临床决策。