Guo QY, Zhang W, Fu L, Hu SS, Li L. Predictive value of a nomogram model for treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. World J Gastrointest Oncol 2025; 17(7): 105403 [PMID: 40697224 DOI: 10.4251/wjgo.v17.i7.105403]
Corresponding Author of This Article
Lin Li, MD, Doctor, Department of Emergency Medicine, Henan Provincial People’s Hospital, No. 7 Weiwu Road, Jinshui District, Zhengzhou 450003, Henan Province, China. lilin7002@126.com
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Oncology
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Retrospective Study
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Jul 15, 2025 (publication date) through Feb 28, 2026
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World Journal of Gastrointestinal Oncology
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Guo QY, Zhang W, Fu L, Hu SS, Li L. Predictive value of a nomogram model for treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. World J Gastrointest Oncol 2025; 17(7): 105403 [PMID: 40697224 DOI: 10.4251/wjgo.v17.i7.105403]
World J Gastrointest Oncol. Jul 15, 2025; 17(7): 105403 Published online Jul 15, 2025. doi: 10.4251/wjgo.v17.i7.105403
Predictive value of a nomogram model for treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer
Qiong-Ya Guo, Wei Zhang, Lin Fu, Shan-Shan Hu, Lin Li
Qiong-Ya Guo, Lin Fu, Shan-Shan Hu, Department of Gastroenterology, Henan Provincial People’s Hospital, Zhengzhou 450003, Henan Province, China
Wei Zhang, Department of Gastrointestinal Surgery, Henan Provincial People’s Hospital, Zhengzhou 450003, Henan Province, China
Lin Li, Department of Emergency Medicine, Henan Provincial People’s Hospital, Zhengzhou 450003, Henan Province, China
Author contributions: Guo QY, Zhang W, Fu L, Hu SS, and Li L contributed to the conceptualization of the study; Guo QY, Zhang W, Fu L were responsible for data curation; Guo QY, Zhang W, Hu SS, conducted the formal analysis; Guo QY, Fu L, Hu SS, and Li L contributed to develop methodology; Guo QY, Zhang W, Fu L, Hu SS contributed to resources and software management; Guo QY and Li L contributed to write the original draft, reviewed and edited the manuscript.
Institutional review board statement: This retrospective study was approved by the Ethics Committee of Henan Provincial People’s Hospital (No. 2023-1-137).
Informed consent statement: Written informed consent for publication was obtained from all patients or their families.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: The data sets generated and analyzed during this study are not public, but under reasonable requirements, the correspondence author can provide.
Corresponding author: Lin Li, MD, Doctor, Department of Emergency Medicine, Henan Provincial People’s Hospital, No. 7 Weiwu Road, Jinshui District, Zhengzhou 450003, Henan Province, China. lilin7002@126.com
Received: January 21, 2025 Revised: April 20, 2025 Accepted: June 11, 2025 Published online: July 15, 2025 Processing time: 174 Days and 22.7 Hours
Abstract
BACKGROUND
Locally advanced rectal cancer (LARC) carries a substantial risk of recurrence, prompting the use of neoadjuvant chemoradiotherapy (nCRT) to improve tumor resectability and long-term outcomes. However, individual treatment responses vary considerably, highlighting the need for robust predictive tools to guide clinical decision-making.
AIM
To develop a nomogram model integrating clinical characteristics and biomarkers to predict the likelihood of poor response to nCRT in LARC.
METHODS
A retrospective analysis was performed on 178 patients with stage II-III LARC treated from January 2021 to December 2023. All patients underwent standardized nCRT followed by total mesorectal excision. Clinical data, inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha], and tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 19-9] were collected. Logistic regression was used to identify independent predictors of poor nCRT response. A nomogram was constructed using significant predictors and validated via concordance index (C-index), receiver operating characteristic curve, calibration plot, and decision curve analysis (DCA).
RESULTS
A total of 178 patients were enrolled, with 36 (20.2%) achieving a good response and 142 (79.8%) exhibiting a poor response to nCRT. Baseline factors, including age and comorbidities, showed no significant differences. However, poor responders more frequently had lymph node metastasis, advanced tumor node metastasis/T stage, larger tumor diameter, and elevated CRP, IL-6, and CEA levels. Logistic regression confirmed CRP, IL-6, and CEA as independent predictors of poor response. The nomogram demonstrated high accuracy (area under the curve = 0.928), good calibration (Hosmer-Lemeshow P = 0.928), and a sensitivity of 88.1% with 82.6% specificity. Internal validation via bootstrap resampling (n = 1000) yielded an adjusted C-index of 0.716, and DCA confirmed substantial clinical utility.
CONCLUSION
A nomogram incorporating serum CRP, IL-6, and CEA accurately predicts poor nCRT response in patients with LARC. This model provides a valuable framework for individualized treatment planning, potentially improving clinical outcomes.
Core Tip: Despite advancements in the use of neoadjuvant chemoradiotherapy (nCRT) to improve resectability and outcomes in locally advanced rectal cancer, predicting treatment response remains challenging. We identified key biomarkers: C-reactive protein, interleukin-6, and carcinoembryonic antigen, as independent predictors of poor response to nCRT. Using these factors, we constructed a nomogram model that demonstrated high predictive accuracy (area under the curve = 0.928), good calibration, and strong clinical utility as confirmed by decision curve analysis.
