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Updated: Jul 19, 2026

Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer
Published on: February 12, 2022
Risk factors of pathologic complete response for neoadjuvant chemoradiotherapy in locally advanced rectal cancer
Liangjing Zhou1, Gaoyang Cao2, Liming Shi3
1Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Background:
Global cancer statistics indicate colorectal cancer as the second leading cause of cancer-related deaths, with rectal cancer accounting for approximately 30% of cases. Despite neoadjuvant chemoradiotherapy (nCRT) being standard for locally advanced rectal cancer (LARC), only 10-30% of patients achieve pathologic complete response (pCR). The aim of this research was to identify variables for predicting pCR in rectal cancer patients after nCRT.
Methods:
This retrospective study analyzed 285 LARC patients treated with nCRT and total mesorectal excision (TME). Univariate and multivariate logistic regression was performed to identify the association between clinicopathological characteristics and pCR. A nomogram based on the univariate logistics regression was built to estimate the likelihood of pCR prior to treatment decisions.
Results:
Univariate logistic regression revealed a significant association between pCR and multiple factors, including histology, CEA levels, clinical N stage, circumferential resection margin (CRM), and the neutrophil-to-lymphocyte ratio (NLR). Upon further multivariate logistic regression, histology, CEA levels, and NLR emerged as the independent predictive factors. A predictive nomogram was developed based on these factors, achieving good predictive ability with an AUC of 0.786.
Conclusion:
Clinical factors including histology, CEA levels, clinical N stage, circumferential resection margin, and NLR are important predictors of treatment response to nCRT for locally advanced rectal cancer. Furthermore, the developed nomogram aims to facilitate individualized and more effective treatment planning.
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