Chuan Zeng,1,2 Jia Ji,3 Yusheng Huang,1,2 Yuan Peng,1,2 Xiaoyue Zhang,1,2 Zhenzhou Yang,1,2 Zhengjun Guo1,2,4 

1Department of Cancer Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Chongqing Key Laboratory of Immunotherapy, Chongqing, People’s Republic of China; 3Department of Neuro-Oncology, Chongqing University Cancer Hospital, Chongqing, People’s Republic of China; 4Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, People’s Republic of China

Correspondence: Zhengjun Guo, Email guozhengjun@hospital.cqmu.edu.cn

Purpose: To establish a pragmatic and effective predictive model for monitoring the recovery of radiation enteritis (RE) in cervical cancer patients undergoing concurrent chemoradiotherapy (CCRT).
Methods: This study included 105 cervical cancer patients undergoing CCRT. We assessed baseline clinicopathologic characteristics, evaluated the effects of CCRT on circulating immune cells, tumor biomarkers, and inflammatory cytokines, and developed a predictive scoring system, the Immune-Tumor-Score (ITS), using the LASSO-Cox regression model. The model performance of LASSO-Cox and nomogram was compared via ROC curve and calibration curve.
Results: The median age of the patients was 55 years, with 53.3% having a normal BMI and 46.7% having positive lymph nodes. Post-CCRT, significant decreases were observed in lymphocyte counts, T-cell subpopulations, and tumor markers (CA125, TPA, SCCA, CYFRA21). The CD4/CD8 ratio and IL10 levels were significantly higher post-CCRT, while inflammation indexes (NLR, ELR) increased, and LMR decreased. The ITS, derived from 11 significant parameters, effectively predicted RE recovery, outperforming a traditional nomogram. Higher ITS scores correlated with shorter RE recovery times, as validated by Kaplan–Meier analyses and ROC curves (AUC = 0.822).
Conclusion: The ITS system provides a robust and reliable tool for predicting RE recovery in cervical cancer patients undergoing CCRT, surpassing traditional models in accuracy and reliability. This tool enables better patient management by allowing for timely interventions and personalized treatment strategies. Future research should focus on validating these findings in larger cohorts and integrating additional clinical parameters to enhance the predictive power of the ITS.

Keywords: radiation enteritis, cervical cancer, concurrent chemoradiotherapy, inflammatory-tumor score, LASSO-Cox regression model