Introduction The management of advanced cholangiocarcinoma (CCA) remains a clinical challenge. Prognostic biomarkers are needed to guide treatment decisions. The C-reactive protein–albumin–lymphocyte (CALLY) index reflects nutritional, immune, and inflammatory status and has shown prognostic value in other cancers. However, its role in CCA patients receiving chemoimmunotherapy is unexplored. Methods We conducted a retrospective propensity score-matched (PSM) cohort study involving advanced CCA patients who were treated with chemoimmunotherapy. Participants were stratified into high- or low-CALLY groups based on an optimal cut-off value of 1.42. PSM (1:1) was applied to balance baseline covariates. Overall survival (OS) and progression-free survival (PFS) were compared between groups using Kaplan-Meier analysis, and Cox regression analysis was employed to identify prognostic factors. The prognostic models underwent comprehensive internal validation, including bootstrap resampling (1,000 iterations) for calibration and discrimination assessment. Health-related quality of life (HRQoL) was assessed using a mixed model for repeated measures. Results After 1:1 propensity matching, 55 patients were retained in each group, with balanced baseline characteristics. The high-CALLY group exhibited significantly longer median OS (13.00 months vs. 11.50 months; P = 0.019) and PFS (7.50 months vs. 6.00 months; P = 0.020). Cox analysis confirmed the CALLY index as a valuable prognostic factor for both OS (hazard ratio (HR), 0.68; 95% confidence interval (CI), 0.50 to 0.93; P = 0.014) and PFS (HR, 0.70; 95% CI, 0.58 to 0.85; P 0.001). Internal validation demonstrated good model performance, with optimism-corrected C-indices of 0.704 for OS and 0.716 for PFS. Furthermore, patients with a high CALLY index showed significantly slower deterioration in HRQoL from week 18 onward (P 0.05). Conclusion The CALLY index is a robust prognostic biomarker for advanced CCA patients undergoing chemoimmunotherapy, associated with significantly improved survival and better-preserved quality of life. Its integration into clinical practice could enhance risk stratification and facilitate personalized treatment strategies.
Fan et al. (Tue,) studied this question.