AUTHOR=Ge Yuhang , Xiang Renshen , Ren Jun , Song Wei , Lu Wei , Fu Tao 

TITLE=A Nomogram for Predicting Multiple Metastases in Metastatic Colorectal Cancer Patients: A Large Population-Based Study

JOURNAL=Frontiers in Oncology

VOLUME=Volume 11 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.633995

DOI=10.3389/fonc.2021.633995

ISSN=2234-943X

ABSTRACT=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.