Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study

Frontiers in Oncology

Hongli Liu¹  Wentai Cai²  Yinghao Cao³  Junnan Gu³  Ke Wu³  Yifan Xue³  Fuwei Mao³  Kailin Cai³  Shenghe Deng³  Ning Zhao³  Lizhao Yan³  Fumei Shang⁴  Zhuolun Sun⁵  Han Li⁶  Changmin Zheng⁷  Songqing Ke⁸ 

[1] Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China;College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China;Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China;Department of Medical Oncology, Nanyang Central Hospital, Nanyang, China;Department of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China;Rizhao City Hospital of Traditional Chinese Medicine (TCM), Rizhao City, China;School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China;Wuhan Blood Center, Wuhan, China;

关键词: colorectal cancer;    liver metastasis;    primary tumpur site;    nomogram;    overall survival;    cancer-specific survival;   

DOI  :  10.3389/fonc.2021.719638

来源: DOAJ

【 摘 要 】

Liver metastasis in colorectal cancer (CRC) is common and has an unfavorable prognosis. This study aimed to establish a functional nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer liver metastasis (CRCLM). A total of 9,736 patients with CRCLM from 2010 to 2016 were randomly assigned to training, internal validation, and external validation cohorts. Univariate and multivariate Cox analyses were performed to identify independent clinicopathologic predictive factors, and a nomogram was constructed to predict CSS and OS. Multivariate analysis demonstrated age, tumor location, differentiation, gender, TNM stage, chemotherapy, number of sampled lymph nodes, number of positive lymph nodes, tumor size, and metastatic surgery as independent predictors for CRCLM. A nomogram incorporating the 10 predictors was constructed. The nomogram showed favorable sensitivity at predicting 1-, 3-, and 5-year OS, with area under the receiver operating characteristic curve (AUROC) values of 0.816, 0.782, and 0.787 in the training cohort; 0.827, 0.769, and 0.774 in the internal validation cohort; and 0.819, 0.745, and 0.767 in the external validation cohort, respectively. For CSS, the values were 0.825, 0.771, and 0.772 in the training cohort; 0.828, 0.753, and 0.758 in the internal validation cohort; and 0.828, 0.737, and 0.772 in the external validation cohort, respectively. Calibration curves and ROC curves revealed that using our models to predict the OS and CSS would add more benefit than other single methods. In summary, the novel nomogram based on significant clinicopathological characteristics can be conveniently used to facilitate the postoperative individualized prediction of OS and CSS in CRCLM patients.

【 授权许可】

Unknown