Predictive and Prognostic Factors of Synchronous Colorectal Lung-Limited Metastasis

• Published in: Gastroenterology research and practice Vol. 2020; no. 2020; pp. 1 - 11
• Main Authors: Zhu, Hong, Tan, Fengbo, Zhou, Ming, Liu, Da, Zhou, Zhongyi, Li, Yuqiang, Liu, Wenxue
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 2020; Hindawi; John Wiley & Sons, Inc; Hindawi Limited; Wiley
• Subjects: Analysis; Cancer; Cancer patients; CEA (Oncology); Chemotherapy; Colorectal cancer; Epidemiology; Liver; Lungs; Medical prognosis; Metastasis; Patients; Prognosis; Radiation therapy; Surgery; China; United States > US
• ISSN: 1687-6121; 1687-630X
• DOI: 10.1155/2020/6131485

Aim. 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. Methods. 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. Results. 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. Conclusions. 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.