A Nomogram for Predicting Multiple Metastases in Metastatic Colorectal Cancer Patients: A Large Population-Based Study - Ge, Yuhang; Xiang, Renshen; Ren, Jun; Song, Wei; Lu, Wei; Fu, Tao (Frontiers in Oncology, 2021)
Objectives: The present study aims to discover the risk factors of multiple metastasis and develop a functional nomogram to forecast multiple metastasis in metastatic colorectal cancer (mCRC) patients. Methods: mCRC cases were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016. Survival times between multiple metastasis and single metastasis were compared using Kaplan-Meier analysis and log-rank tests. Risk factors for multiple metastases were determined by univariate and multivariate logistic regression analysis and a nomogram was developed to forecast the probability of multiple metastasis in mCRC patients. We assessed the nomogram performance in terms of discrimination and calibration, including concordance index (C-index), area under the curve (AUC), decision curve analysis (DCA), and calibration curves with 1000 bootstraps. Results: A total of 5302 cases were included in this study. The patients with single metastasis and multiple metastasis were 3531 and 1771, respectively. The median overall survival (OS) and cancer-specific survival (CSS) for patients with multiple metastasis or single metastasis were 19 vs. 31 months, and 20 vs. 33 months, respectively. Based on the univariate and multivariate analyses, clinicopathological characteristics were associated with number of metastasis and were used to establish nomograms to predict the risk of multiple metastases. The C-indexes and AUC for the forecast of multiple metastasis were 0.715 (95% confidence interval (CI), 0.707-0.723), which showed the nomogram had good discrimination. And calibration curves of the nomogram showed no significant bias from the reference line, indicating a good degree of calibration. Conclusions We developed a new nomogram to predict the risk of multiple metastasis. The nomogram shows the good prediction effect and can provide assistance for clinical diagnosis and treatment.