Predictive value of a nomogram model for treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

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.