Apostolos Gaitanidis1, Nikolaos Machairas2, Michail Alevizakos3, Christos Tsalikidis4, Alexandra Tsaroucha4, Michail Pitiakoudis4. 1. Second Department of Surgery, University General Hospital of Alexandroupoli, Democritus University of Thrace Medical School, 681 00, Alexandroupoli, Greece. agaitanidis@gmail.com. 2. Third Department of Surgery, Medical School, Attikon University Hospital, National and Kapodistrian University of Athens, Athens, Greece. 3. Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA. 4. Second Department of Surgery, University General Hospital of Alexandroupoli, Democritus University of Thrace Medical School, 681 00, Alexandroupoli, Greece.
Abstract
BACKGROUND: The risk of distant metastasis may be estimated using predictive nomograms. The purpose of this study is to develop nomograms that may assess the risk of synchronous metastasis in patients with colon cancer. METHODS: A retrospective analysis of the Surveillance Epidemiology and End Results database between 2010 and 2014. Logistic regression was performed to identify factors associated with synchronous liver and lung metastasis. RESULTS: Overall, 117,934 patients with colon cancer (59,076 [50.1%] males, mean age 68.3 ± 13.7 years) were included, of which 16,135 (13.7%) had liver metastasis and 4601 (3.9%) had lung metastasis at diagnosis. Age, sex, race, tumor location, tumor grade, CEA levels, perineural invasion, and T and N stage were associated with the presence of liver metastasis. Age, sex, race, tumor location, tumor grade, CEA levels, perineural invasion, T stage, N stage, and presence of liver metastasis were associated with the presence of lung metastasis. These variables were used to construct predictive nomograms. The c-indexes for both predictive models were 0.97. CONCLUSIONS: In this study, we constructed predictive nomograms for the presence of synchronous liver and lung metastasis in patients with colon cancer that may be used to quantitatively assess the risk of synchronous metastatic disease.
BACKGROUND: The risk of distant metastasis may be estimated using predictive nomograms. The purpose of this study is to develop nomograms that may assess the risk of synchronous metastasis in patients with colon cancer. METHODS: A retrospective analysis of the Surveillance Epidemiology and End Results database between 2010 and 2014. Logistic regression was performed to identify factors associated with synchronous liver and lung metastasis. RESULTS: Overall, 117,934 patients with colon cancer (59,076 [50.1%] males, mean age 68.3 ± 13.7 years) were included, of which 16,135 (13.7%) had liver metastasis and 4601 (3.9%) had lung metastasis at diagnosis. Age, sex, race, tumor location, tumor grade, CEA levels, perineural invasion, and T and N stage were associated with the presence of liver metastasis. Age, sex, race, tumor location, tumor grade, CEA levels, perineural invasion, T stage, N stage, and presence of liver metastasis were associated with the presence of lung metastasis. These variables were used to construct predictive nomograms. The c-indexes for both predictive models were 0.97. CONCLUSIONS: In this study, we constructed predictive nomograms for the presence of synchronous liver and lung metastasis in patients with colon cancer that may be used to quantitatively assess the risk of synchronous metastatic disease.