Clinical observation and retrospective study of the influential factors of liver metastasis in 306 cases of colon cancer

Risk and prognostic factors in patients with colon cancer with liver metastasis

OBJECTIVE

The most common site of metastasis in patients with colon cancer is the liver. This study aimed to identify patients with colon cancer at high risk of developing liver metastasis and to explore their prognosis.

METHODS

The clinical characteristics, treatment methods and survival outcomes of patients diagnosed with colon cancer from 2010 to 2015 were identified from the Surveillance, Epidemiology and End Results (SEER) database. Patients were divided into two groups according to the presence of liver metastasis, and multivariate logistic and Cox regression models were used to identify risk and prognostic factors.

RESULTS

A total of 60,018 patients with colon cancer were selected from the SEER database. The incidence of liver metastasis was 9.2%. African American ethnicity, poor differentiation, higher tumor stage, higher lymph node ratio, and lung metastases were common factors associated with both liver metastasis risk and prognosis.

CONCLUSIONS

Metastasectomy might improve survival among patients with colon cancer with resectable liver metastasis lesions and no other organ involvement.

Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery

Background

To develop a radiomics model based on pretreatment whole-liver portal venous phase (PVP) contrast-enhanced CT (CE-CT) images for predicting metachronous liver metastases (MLM) within 24 months after rectal cancer (RC) surgery.

Methods

This study retrospectively analyzed 112 RC patients without preoperative liver metastases who underwent rectal surgery between January 2015 and December 2017 at our institution. Volume of interest (VOI) segmentation of the whole-liver was performed on the PVP CE-CT images. All 1316 radiomics features were extracted automatically. The maximum-relevance and minimum-redundancy and least absolute shrinkage and selection operator methods were used for features selection and radiomics signature constructing. Three models based on radiomics features (radiomics model), clinical features (clinical model), and radiomics combined with clinical features (combined model) were built by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of models, and calibration curve and the decision curve analysis were performed to evaluate the clinical application value.

Results

In total, 52 patients in the MLM group and 60 patients in the non-MLM group were enrolled in this study. The radscore was built using 16 selected features and the corresponding coefficients. Both the radiomics model and the combined model showed higher diagnostic performance than clinical model (AUCs of training set: radiomics model 0.84 (95% CI, 0.76–0.93), clinical model 0.65 (95% CI, 0.55–0.75), combined model 0.85 (95% CI, 0.77–0.94); AUCs of validation set: radiomics model 0.84 (95% CI, 0.70–0.98), clinical model 0.58 (95% CI, 0.40–0.76), combined model 0.85 (95% CI, 0.71–0.99)). The calibration curves showed great consistency between the predicted value and actual event probability. The DCA showed that both the radiomics and combined models could add a net benefit on a large scale.

Conclusions

The radiomics model based on preoperative whole-liver PVP CE-CT could predict MLM within 24 months after RC surgery. Clinical features could not significantly improve the prediction efficiency of the radiomics model.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-022-00485-z.