Abstract
ObjectiveA proportional hazard model was applied to develop a large-scale prognostic model and nomogram incorporating clinicopathological characteristics, histological type, tumor differentiation grade, and tumor deposit count to provide clinicians and patients diagnosed with colon cancer liver metastases (CLM) a more comprehensive and practical outcome measure.MethodsUsing the Transparent Reporting of multivariable prediction models for individual Prognosis or Diagnosis (TRIPOD) guidelines, this study identified 14,697 patients diagnosed with CLM from 1975 to 2017 in the Surveillance, Epidemiology, and End Results (SEER) 21 registry database. Patients were divided into a modeling group (n=9800), an internal validation group (n=4897) using computerized randomization. An independent external validation cohort (n=60) was obtained. Univariable and multivariate Cox analyses were performed to identify prognostic predictors for overall survival (OS). Subsequently, the nomogram was constructed, and the verification was undertaken by receiver operating curves (AUC) and calibration curves.ResultsHistological type, tumor differentiation grade, and tumor deposit count were independent prognostic predictors for CLM. The nomogram consisted of age, sex, primary site, T category, N category, metastasis of bone, brain or lung, surgery, and chemotherapy. The model achieved excellent prediction power on both internal (mean AUC=0.811) and external validation (mean AUC=0.727), respectively, which were significantly higher than the American Joint Committee on Cancer (AJCC) TNM system.ConclusionThis study proposes a prognostic nomogram for predicting 1- and 2-year survival based on histopathological and population-based data of CLM patients developed using TRIPOD guidelines. Compared with the TNM stage, our nomogram has better consistency and calibration for predicting the OS of CLM patients.
Highlights
Colon cancer is the third most common tumor and the second leading cause of cancer-related deaths [1, 2]
The prognosis of cancer liver metastases (CLM) varies significantly such that personalized prediction of CLM has become the focus of various studies, including those of the American Joint Committee on Cancer (AJCC) TNM system, which has been applied worldwide as the most authorized tool [5]
A total of 14,697 patients from SEER database were involved in this study
Summary
Colon cancer is the third most common tumor and the second leading cause of cancer-related deaths [1, 2]. The 5-year survival rate for colon cancer is 64.6%, while for synchronous metastasis, the patient’s survival is only 14.3%. Liver metastasis is the most frequently (17%) observed synchronous metastasis [3]. It occurs in over 25% of patients initially and 50% of patients throughout the disease [4]. The prognosis of CLM varies significantly such that personalized prediction of CLM has become the focus of various studies, including those of the American Joint Committee on Cancer (AJCC) TNM system, which has been applied worldwide as the most authorized tool [5]. The prediction accuracy of TNM staging is not satisfactory enough to predict outcomes (C-index=0.453) [6], which can relate to less predictors and classification on continuous variables [7]
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