Metabolic and Inflammatory Risk Stratification in Resected Cholangiocarcinoma: A Retrospective Exploratory Analysis
Abstract
Background: Cholangiocarcinoma (CCA) frequently recurs after curative-intent resection. Metabolic alterations and systemic inflammation may contribute to aggressive disease, but their combined prognostic relevance remains unclear. Methods: We retrospectively reanalyzed 88 patients with resected CCA and documented recurrence, including 37 with early and 51 with late recurrence. A metabolite-based risk score was developed from recurrence-associated serum metabolites identified previously. Model development and internal validation used all 88 patients, whereas analyses involving preoperative neutrophil-to-lymphocyte ratio (NLR), clinicopathological variables, and survival outcomes included 85 patients with complete clinical data. Performance was assessed using repeated nested cross-validation, bootstrap validation, discrimination, calibration, and survival analyses. Results: The 10-metabolite risk score (MRS-10) showed moderate internally validated discrimination for distinguishing early from late recurrence, with a pooled patient-level out-of-fold AUC of 0.828 (95% CI, 0.725–0.911), with limited calibration. High MRS was associated with shorter disease-free survival (DFS) and overall survival (OS) (both p < 0.001) and remained independently associated with DFS events (HR, 7.92; 95% CI, 3.94–15.92) and mortality (HR, 4.05; 95% CI, 2.08–7.89). High MRS was also associated with elevated NLR (p < 0.001). The combined MRS–NLR framework improved prognostic discrimination and stratified patients into groups with stepwise differences in DFS and OS. Exploratory subgroup analyses showed broadly consistent adverse associations across selected clinicopathological strata. Conclusions: In this retrospective exploratory analysis, a metabolite-based risk score combined with preoperative NLR was associated with recurrence and survival outcomes in resected CCA. This metabolic–inflammatory framework may provide complementary prognostic information alongside conventional clinicopathological factors. However, the findings remain hypothesis-generating and require validation in larger independent cohorts before clinical application.
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Authors: Piya Prajumwongs, Attapol Titapun, Vasin Thanasukarn, Apiwat Jareanrat, Natcha Khuntikeo, Nisana Namwat, Poramate Klanrit, Arporn Wangwiwatsin, Jarin Chindaprasirt, Prakasit Sa-Ngiamwibool, Nattha Muangritdech, Sittiruk Roytrakul, Watcharin Loilome
Institutions: Khon Kaen University, National Science and Technology Development Agency, National Center for Genetic Engineering and Biotechnology