Prediction of Pathological Complete Response to Neoadjuvant Immunotherapy-Based Regimens for Non-Metastatic Colon and Rectal Cancer
5 affiliations
- 1Department of Pharmacy, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510655, China
- 2Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510655, China
- 3Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510655, China
- 4School of Pharmaceutical Science, Sun Yat-Sen University, Guangzhou 510275, China
- 5School of Pharmaceutical Science, Guangdong Pharmaceutical University, Guangzhou 510006, China
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.
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BibTeX
@article{huang2026prediction,
title = {{Prediction of Pathological Complete Response to Neoadjuvant Immunotherapy-Based Regimens for Non-Metastatic Colon and Rectal Cancer}},
author = {Xiaoyan Huang and Meiling Ye and Zhikun Liang and Ling Yang and Weiming Huang and Li Qin and Jingwen Xie and Xiaoyan Li},
journal = {Journal of Clinical Medicine},
year = {2026},
month = oct,
doi = {10.3390/jcm15208022},
url = {https://www.mdpi.com/2077-0383/15/20/8022},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Prediction of Pathological Complete Response to Neoadjuvant Immunotherapy-Based Regimens for Non-Metastatic Colon and Rectal Cancer
AU - Xiaoyan Huang
AU - Meiling Ye
AU - Zhikun Liang
AU - Ling Yang
AU - Weiming Huang
AU - Li Qin
AU - Jingwen Xie
AU - Xiaoyan Li
PY - 2026
DA - 2026/10/01
JO - Journal of Clinical Medicine
DO - 10.3390/jcm15208022
UR - https://www.mdpi.com/2077-0383/15/20/8022
AB - 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.
SN - 2077-0383
ER -