AUTHOR=He Jiawei , Wu Tao , Gao Maofa , Jiao Yunfeng , Yu Qiaoling , Zhao Yaling , Hou Ni , Li Jie 

TITLE=Risk factors and a predictive nomogram for regional lymph node metastasis in deficient mismatch repair colorectal cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1601993

DOI=10.3389/fonc.2025.1601993

ISSN=2234-943X

ABSTRACT=ObjectiveThe present study aims to investigate the risk factors associated with regional lymph node metastasis (LNM) in patients with deficient mismatch repair (dMMR) colorectal cancer (CRC) and develop a nomogram for predicting it preoperatively.Patients and MethodsClinicopathological data of patients who underwent surgical treatment at the Second Affiliated Hospital of Xi’an Jiaotong University between January 2021 and December 2024 were collected, and univariate and multivariate logistic regression analyses were performed to identify the independent risk factors for regional LNM. A clinicopathologic nomogram for preoperatively predicting LNM was established and further validated and evaluated.ResultsA total of 131 patients with stage I to III dMMR/microsatellite instability (MSI) CRC were included in the study. The results showed that age, tumor location, degree of differentiation, depth of invasion, and negative immunohistochemistry staining results for MMR proteins, except for the double-negative of MLH1 and PMS2 or MSH2 and MSH6, were independent risk factors for regional LNM in dMMR/MSI CRC. They were incorporated into the individualized prediction nomogram, which showed sufficient discriminability and good calibration. Decision curve analysis indicated that the nomogram could be used for early clinical prediction of regional LNM.ConclusionThe clinicopathological nomogram, incorporating five independent risk factors, can be widely used to facilitate the preoperative prediction of regional LNM in patients with dMMR/MSI colorectal cancer, thereby developing individual treatment and improving patients’ prognoses. While the model was internally validated, further external validation is also warranted.