Work

Development and Validation of Nomogram Models Incorporating the Inflammatory Nutritional Index CALLY for Predicting Survival in Locally Advanced Rectal Cancer After Neoadjuvant Chemoradiotherapy

Year: 2025

Type: article

Abstract: Background: Patients with locally advanced rectal cancer (LARC) have considerable rates of postoperative recurrence and metastasis, and existing scoring systems lack specificity. This study aims to establish and validate a prognostic model using inflammatory nutritional index CALLY for overall survival (OS) and progression-free survival (PFS) in patients with LARC following neoadjuvant chemoradiotherapy (NACRT), with the goal of enabling early risk assessment and intervention in LARC patients. Methods: One hundred and thirty-one LARC patients were analyzed undergoing NACRT followed by surgery (January 2020-May 2024). The median follow-up was 27 months. LASSO regression and multivariate Cox analysis identified prognostic factors. Nomograms for 2-/3-year OS and PFS were constructed and validated using KM, time-dependent ROC curves, calibration plots, and decision curve analysis (DCA). Bootstrap method was used to internally verify the nomogram model. Results: The study's multifactorial analysis revealed high CALLY were independently associated with improved OS (HR = 0.344, 95% CI: 0.133-0.893; P = 0.028) and PFS (HR = 0.492, 95% CI: 0.266-0.912; P = 0.024). OS nomogram (CALLY/CEA/CCI) achieved AUCs of 0.83 (2-year) and 0.76 (3-year). PFS nomogram (CALLY/PLR/CEA/CA724/vascular invasion) showed superior 3-year accuracy (AUC = 0.81) but lower 2-year accuracy (AUC = 0.71). Calibration curves confirmed good prediction-observation agreement. DCA revealed wider clinical applicability for 3-year PFS. Survival KM curve for OS suggested that high-risk patients had 8.25-fold higher mortality (95% CI: 3.05-22.30). Conclusion: A prognostic nomogram of LARC patients after NACRT in terms of OS and PFS was established based on the inflammatory nutritional Index CALLY, in which the PFS model showed excellent long-term predictive accuracy and clinical utility, providing individualized risk stratification and advance intervention to guide adjuvant therapy.

Source: Cancer Management and Research

DOI: 10.2147/cmar.s555346