Li Yuqiang, Zhou Zhongyi, Liu Da, Zhou Ming, Tan Fengbo, Liu Wenxue, Zhu Hong
Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China.
Department of Thoracic Surgery 3 Zone, Cancer Center of Guangzhou Medical University, Guangzhou, China.
Gastroenterol Res Pract. 2020 Nov 23;2020:6131485. doi: 10.1155/2020/6131485. eCollection 2020.
This study is aimed at investigating predictive and prognostic factors of synchronous colorectal lung-limited metastasis (SCLLM) based on The Surveillance, Epidemiology, and End Results (SEER) database.
A multivariate logistic regression model was constructed to identify independent predictors of SCLLM. A multivariate Cox proportional hazards regression model was used to distinguish independent prognostic factors.
This study enrolled 168,007 colorectal cancer (CRC) patients without metastatic diseases and 1,298 cases with SCLLM. Eight features, involving race, tumor location, pathological grade, histological type, T stage, N stage, and tumor size as well as CEA, could be used as the independent predictors. As the nomogram shown, the T4 stage contributed the most to SCLLM, followed by the N2 stage, elevated CEA, and rectal cancer. A multivariate regression analysis discriminated 9 independent prognostic factors, including age, race, marital status, pathological grade, T stage, colectomy/proctectomy, chemotherapy, CEA, and TD. The prognostic nomogram illustrated that nonresection/NOS played as the poorest prognostic factor, followed by nonchemotherapy, ≥75-year old and T4 stage. The cumulative survival curves revealed the influence of each prognostic factor on survival after controlling the other variables.
This study identified independent predictors and prognostic factors for SCLLM based on a large database of the United States. The predictors and prognostic factors can provide supporting evidence for the prevention and treatment of SCLLM.
本研究旨在基于监测、流行病学和最终结果（SEER）数据库，调查同步性结直肠癌肺局限性转移（SCLLM）的预测和预后因素。
构建多变量逻辑回归模型以识别SCLLM的独立预测因素。使用多变量Cox比例风险回归模型区分独立预后因素。
本研究纳入了168,007例无转移性疾病的结直肠癌（CRC）患者和1,298例SCLLM患者。八个特征，包括种族、肿瘤位置、病理分级、组织学类型、T分期、N分期、肿瘤大小以及癌胚抗原（CEA），可作为独立预测因素。如图所示的列线图，T4期对SCLLM的贡献最大，其次是N2期、CEA升高和直肠癌。多变量回归分析鉴别出9个独立预后因素，包括年龄、种族、婚姻状况、病理分级、T分期、结肠切除术/直肠切除术、化疗、CEA和肿瘤分化程度（TD）。预后列线图表明，未切除/NOS是最差的预后因素，其次是未化疗、≥75岁和T4期。累积生存曲线揭示了在控制其他变量后各预后因素对生存的影响。
本研究基于美国的一个大型数据库，识别出了SCLLM的独立预测因素和预后因素。这些预测因素和预后因素可为SCLLM的预防和治疗提供支持性证据。
