Combination of the Circulating Tumor Cell Enumeration and the Fecal Immunochemical Test for Colorectal Neoplasia Prediction and Risk Evaluation of Colorectal Cancer
Abstract Background: Colorectal neoplasia contributes substantially to morbidity and mortality worldwide. Although fecal immunochemical test (FIT) has been adopted as a screening method, its limitations (suboptimal adherence to follow-up colonoscopy among the FIT-positive population and missed diagnosis in the FIT-negative population) hamper its effectiveness in reducing colorectal cancer. To address these issues, a combination of FIT with circulating tumor cell (CTC) enumeration for colorectal neoplasia prediction and colorectal cancer risk evaluation was proposed. Methods: Participants (n = 113) underwent FIT, colonoscopy examination, and CTC enumeration. For the latter, CD45negEpCAMpos CTC and CD45negEpCAMneg cell counts were assayed. For statistical analysis, multivariable logistic regression and area under the ROC curve (AUROC) analyses were used. Results: For colorectal neoplasia prediction, a better performance (AUROC = 0.8371) was achieved when the variables (FIT results and CTC enumeration) were combined, which was significantly improved compared with that of the FIT result–only model (AUROC = 0.7555). For its further use for colorectal cancer risk assessment, among FIT-positive individuals, those with either ≥5 CD45negEpCAMpos CTCs or ≥300 CD45negEpCAMneg cells had significantly increased colorectal cancer risk. For the FIT-negative population, 80% of the FIT-negative colorectal cancer cases in this study could be detected if the thresholds were set at ≥2 CD45negEpCAMpos CTCs and ≥500 CD45negEpCAMneg cells. Its application could thus rescue missed diagnoses due to false-negative FIT results. Conclusions: The method was able to enhance the prediction of colorectal neoplasia. The assessment of colorectal cancer risk was also successfully demonstrated. Impact: The method is promising as a supportive method tackling the problems encountered in current FIT-based screening.