Wen Junmiao, Chen Jiayan, Chen Donglai, Jabbour Salma K, Xue Tao, Guo Xufeng, Ma Haitao, Ye Fei, Mao Yiming, Shu Jian, Liu Yangyang, Lu Xueguan, Zhang Zhen, Chen Yongbing, Fan Min
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Ther Adv Med Oncol. 2021 Nov 5;13:17588359211054895. doi: 10.1177/17588359211054895. eCollection 2021.
We aim to assess the prognostic ability of three common lymph node-based staging algorithms, namely, the number of positive lymph nodes (pN), the lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) in patients with esophageal squamous cell carcinoma (ESCC).
A total of 3902 ESCC patients treated at 10 Chinese institutions between 2003 and 2013 were included, along with 2465 patients from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic ability of the aforementioned algorithms was evaluated using time-dependent receiver operating characteristic (tdROC) curves, , Harrell's concordance index (C-index), and the likelihood ratio chi-square score. The primary outcomes included cancer-specific survival (CSS), overall survival (OS), and CSS with a competing risk of death by non-ESCC causes.
LODDS had better prognostic performance than pN or LNR in both continuous and stratified patterns. In the multicenter cohort, the multivariate analysis showed that the model based on LODDS classification was superior to the others in predictive accuracy and discriminatory capacity. Two nomograms integrating LODDS classification and other clinicopathological risk factors associated with OS as well as cancer-specific mortality were constructed and validated in the SEER database. Finally, a novel TN classification which incorporates the LODDS classification was built and categorized patients in to three new stages.
Among the three lymph node-based staging algorithms, LODDS demonstrated the highest discriminative capacity and prognostic accuracy for ESCC patients. The nomograms and novel TN classification based on LODDS classification could serve as precise evaluation tools to assist clinicians in estimating the survival time of individual patients and improving clinical outcomes postoperatively in the future.
我们旨在评估三种常见的基于淋巴结的分期算法，即阳性淋巴结数量（pN）、淋巴结比率（LNR）和阳性淋巴结对数比值（LODDS）在食管鳞状细胞癌（ESCC）患者中的预后评估能力。
纳入了2003年至2013年间在中国10家机构接受治疗的3902例ESCC患者，以及来自监测、流行病学和最终结果（SEER）数据库的2465例患者。使用时间依赖性受试者工作特征（tdROC）曲线、Harrell一致性指数（C指数）和似然比卡方评分来评估上述算法的预后评估能力。主要结局包括癌症特异性生存（CSS）、总生存（OS）以及存在非ESCC原因导致死亡竞争风险的CSS。
在连续和分层模式下，LODDS的预后表现均优于pN或LNR。在多中心队列中，多变量分析显示基于LODDS分类的模型在预测准确性和鉴别能力方面优于其他模型。构建了两个整合LODDS分类以及与OS和癌症特异性死亡率相关的其他临床病理危险因素的列线图，并在SEER数据库中进行了验证。最后，构建了一种纳入LODDS分类的新型TN分类，并将患者分为三个新的阶段。
在三种基于淋巴结的分期算法中，LODDS对ESCC患者表现出最高的鉴别能力和预后准确性。基于LODDS分类的列线图和新型TN分类可作为精确的评估工具，以帮助临床医生估计个体患者的生存时间，并在未来改善术后临床结局。
