Prediction of Pathological Complete Response to Neoadjuvant Immunotherapy-Based Regimens for Non-Metastatic Colon and Rectal Cancer
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Pathological complete response (pCR) after neoadjuvant immunotherapy is associated with improved prognosis in colon and rectal cancer. This study aimed to develop and validate a predictive nomogram for pCR in CRC patients receiving neoadjuvant immunotherapy. Methods: A total of 232 eligible CRC patients who received immune checkpoint inhibitors (ICIs) followed by surgical resection at the Sixth Affiliated Hospital of Sun Yat-sen University (January 2018–December 2024) were retrospectively included, with 162 in the training set and 70 in the validation set. Univariate and multivariate logistic regression analyses were performed to identify factors influencing pCR, and a nomogram was subsequently developed. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the nomogram. Results: The pCR rate in the entire cohort was 53.4%, with rates of 76.8% (73/95) and 37.2% (51/137) in the MSI-H/dMMR and MSS/pMMR subgroups, respectively. In multivariable analysis, MSI-H/dMMR status and pretreatment CEA level < 5 ng/mL were independent predictors of pCR and were used to construct the nomogram. The nomogram achieved AUCs of 0.741 in the training set and 0.730 in the validation set. Calibration curve analysis showed good agreement between predicted and actual pCR in both sets, and decision curve analysis demonstrated favorable net benefit. Conclusions: Our nomogram may predict pCR and help identify likely responders to neoadjuvant immunotherapy-based regimens in non-metastatic CRC patients. Prospective multi-center validation is warranted to confirm its clinical utility.
Source: Journal of Clinical Medicine
DOI: 10.3390/jcm15208022
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7222516360
