Tumor enhancement ratio on preoperative abdominal contrast-enhanced CT scan for predicting recurrence risk in stage II colon cancer

Abstract

Purpose: The identification of high recurrence risk stage II colon cancer patients was critical to adjuvant chemotherapy decision. However, current definition of high-risk features remains inadequate. This study aimed to construct a model for predicting recurrence risk based on tumor enhancement ratio (TER) on abdominal contrast-enhanced CT scan.

Method: 282 stage II colon cancer patients were included and randomly divided into training and validation sets in the ratio of 7:3. TER was calculated using maximum tumor attenuation value in contrast-enhanced CT scan divided by the minimum. Kaplan-Meier survival analyses were adopted to evaluate the prognostic value of variables. A model based on TER was built to predict recurrence risk through the LASSO Cox model. The recurrence risk score of patients was calculated based on this model.

Results: The optimal cut-off value of TER was 1.83 derived from the time-dependent ROC (tdROC) curve. Patients with high-TER showed increasingly poorer disease-free survival (DFS) in both training (p < 0.001) and validation (p < 0.001) sets. A model was built based on TER demonstrated satisfactory performance to recurrence risk prediction (C-index: 0.784 in the training set and 0.725 in the validation set). Patients were regrouped into modified high-risk and non-high risk according to recurrence risk score (cut-off value: 1.75) and a significant DFS difference was observed (training set: p < 0.001; validation set: p < 0.001).

Conclusion: TER can serve as a high-risk feature of stage II colon cancer. And a model based on TER provided a new approach to assess recurrence risk of stage II disease.

Keywords: Colonic neoplasms; Models and statistical; Multidetector computed tomography; Prognosis.