Zhang Shaoyuan, Sun Linyi, Cai Danjie, Liu Guobing, Jiang Dongxian, Yin Jun, Fang Yong, Wang Hao, Shen Yaxing, Hou Yingyong, Shi Hongcheng, Tan Lijie
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Ann Surg Oncol. 2023 Nov;30(12):7452-7460. doi: 10.1245/s10434-023-13694-y. Epub 2023 Jun 25.
This study was conducted to predict the lymph node status and survival of esophageal squamous cell carcinoma before treatment by PET-CT-related parameters.
From January 2013 to July 2018, patients with pathologically diagnosed ESCC at our hospital were retrospectively enrolled. Completed esophagectomy and two- or three-field lymph node dissections were conducted. Those with neoadjuvant therapy were excluded. The first 65% of patients in each year were regarded as the training set and the last 35% as the test set. Nomogram was constructed by the "rms" package. Five-year, overall survival was analyzed based on the best cutoff value of risk score determined by the "survivalROC" package.
Ultimately, 311 patients were included with 209 in the training set and 102 in the test set. The positive rate of the lymph node in the training set was 36.8% and that in the test set was 32.4%. The C-index of the training set was 0.763 and the test set was 0.766. The decision curve analysis showed that it was superior to the previous methods based on lymph node uptake or long/short axis diameter or axial ratio. Risk score > 0.20 was significantly associated with 5-year, overall survival (p = 0.0015) in all patients.
The nomogram constructed from PET-CT parameters including primary tumor metabolic length and thickness can accurately predict the risk of lymph node metastasis in ESCC. The risk score calculated by our model accurately predicts the patient's 5-year overall survival.
本研究旨在通过PET-CT相关参数预测食管鳞状细胞癌治疗前的淋巴结状态和生存率。
回顾性纳入2013年1月至2018年7月在我院经病理诊断为食管鳞状细胞癌的患者。行完整的食管切除术及二野或三野淋巴结清扫术。排除接受新辅助治疗的患者。每年前65%的患者作为训练集,后35%作为测试集。使用“rms”软件包构建列线图。根据“survivalROC”软件包确定的风险评分最佳临界值分析5年总生存率。
最终纳入311例患者,其中训练集209例,测试集102例。训练集淋巴结阳性率为36.8%,测试集为32.4%。训练集的C指数为0.763,测试集为0.766。决策曲线分析表明,该模型优于以往基于淋巴结摄取、长短径或纵横比的方法。风险评分>0.20与所有患者的5年总生存率显著相关(p = 0.0015)。
由包括原发肿瘤代谢长度和厚度在内的PET-CT参数构建的列线图可准确预测食管鳞状细胞癌淋巴结转移风险。我们模型计算的风险评分能准确预测患者的5年总生存率。