Development and Validation of a Predictive Scoring System for Colorectal Cancer Patients With Liver Metastasis: A Population-Based Study
| Autor: | Wentai Cai, Yinghao Cao, Zheng Changmin, Han Li, Ke Wu, Hongli Liu, Songqing Ke, Zhao Ning, Fumei Shang, Zhuolun Sun, Gu Junnan, Mao Fuwei, Xue Yifan, Deng Shenghe, Yan Lizhao, Kailin Cai |
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| Rok vydání: | 2021 |
| Předmět: |
Oncology
Cancer Research medicine.medical_specialty Multivariate analysis Colorectal cancer overall survival colorectal cancer Metastasis nomogram cancer-specific survival Internal medicine medicine Stage (cooking) RC254-282 Original Research Receiver operating characteristic business.industry Univariate Neoplasms. Tumors. Oncology. Including cancer and carcinogens Nomogram medicine.disease liver metastasis Cohort primary tumpur site business |
| Zdroj: | Frontiers in Oncology Frontiers in Oncology, Vol 11 (2021) |
| ISSN: | 2234-943X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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