Metabolic syndrome as a prognostic factor in advanced pancreatic cancer: a predictive model and chemotherapy evaluation

Abstract

Objective: This study aimed to identify independent prognostic factors for advanced unresectable pancreatic ductal adenocarcinoma (PDAC) and construct a nomogram-based prediction model. The efficacy of different chemotherapy regimens was evaluated based on metabolic risk levels. Methods: Clinical data from 276 patients with unresectable PDAC treated between 2020 and 2022 were retrospectively analyzed. Cox proportional hazards regression identified prognostic factors, and survival analysis was performed using Kaplan-Meier methods. A nomogram was developed, and ROC analysis assessed its predictive performance. Two-way ANOVA evaluated chemotherapy efficacy, and TCGA transcriptomic data explored metabolic correlations. Results: Metabolic syndrome (MetS) and distant metastasis were independent prognostic factors. Patients with MetS had significantly shorter survival. The nomogram showed good discrimination (AUC: 0.815 training, 0.793 validation). Patients without MetS had better outcomes with FOLFIRINOX or GS regimens. Transcriptomic analysis revealed metabolic pathways linked to PDAC progression. Conclusions: MetS and distant metastasis significantly impact PDAC prognosis. Patients without MetS benefit more from specific chemotherapy regimens. Our predictive model may aid personalized treatment strategies.