Combining Circulating Tumour DNA with Clinical Pathological Risk Factors for Developing Peritoneal Metastasis Prediction Model in Patients with Colorectal Cancer.

Abstract

Aims/Background Peritoneal metastasis in colorectal cancer (CRC) indicates a poor prognosis for patients. Circulating tumour DNA (ctDNA) effectively predicts recurrence and metastasis. Therefore, this study aims to construct a predictive model for peritoneal metastasis by integrating ctDNA with clinicopathological factors in stage I-III CRC patients. Methods We conducted a retrospective analysis of 299 CRC patients who underwent ctDNA detection at The Sixth Affiliated Hospital, Sun Yat-sen University between January 2010 and December 2022. Patients were randomly divided into training (n = 209) and validation (n = 90) sets in a 7:3 ratio using a random number table method. The least absolute shrinkage and selection operator (LASSO) regression model optimized feature selection, and multivariable logistic regression constructed the predictive model. Results Among the study cohort, 59 patients were ctDNA-positive. Postoperative ctDNA positivity was associated with an 8.522-fold increased risk of peritoneal metastasis (p < 0.001, odds ratio (OR) 8.522, 95% confidence interval (CI) 4.371-16.615). The model included preoperative carbohydrate antigen 125 (CA-125), pathological lymph node staging, perineural invasion, and ctDNA levels, achieving an area under the curve (AUC) of 0.808 (95% CI 0.727-0.888) in the training set and 0.784 (95% CI 0.658-0.910) in the validation set. Conclusion This model can accurately identify high-risk patients for peritoneal metastasis in postoperative CRC, facilitating early detection and timely intervention.