Development of a nomogram integrating immune checkpoints, fibrosis indicators, and clinicopathological characteristics to predict overall survival in pancreatic cancer: a retrospective analysis

Background Pancreatic cancer (PC) remains a highly aggressive disease with a poor postoperative 5-year survival of around 25%, attributable to its immunosuppressive and fibrotic tumor microenvironment. Prognostic models that combine immune checkpoint markers with fibrotic features are still needed. Methods We analyzed qualifying surgically resected PC specimens. Immunohistochemistry was used to evaluate PD-L1, CTLA-4, and α-SMA expression. Extracellular matrix volume (ECV) at the tumor center (ECVC) and peritumoral region (ECVP) was measured by three radiologists using single-energy CT. Collagen fraction (CF) was assessed via Masson’s trichrome staining. Multivariate Cox regression identified independent predictors of overall survival (OS); a prognostic nomogram was then developed. Results Among 268 enrolled patients, divided into training (n=215) and validation (n=53) sets via Five-fold cross-validation, PD-L1 expression correlated positively with α-SMA, T stage, and N stage. Multivariate analysis identified α-SMA H-score, Masson-CF, ECVC, ECVP, T stage, N stage, CA19-9, neutrophil-to-lymphocyte ratio (NLR), vascular invasion, and chemotherapy as independent OS predictors. The nomogram integrating these factors outperformed TNM staging in predicting OS. Conclusion High PD-L1 expression is associated with enhanced fibrosis, greater tumor burden, and nodal metastasis in PC. Patients exhibiting elevated PD-L1 levels, significant fibrotic burden, advanced T or N stage, or increased NLR demonstrate reduced OS. The developed nomogram enhances individualized prediction of OS. These findings support the hypothesis that combining immune checkpoint blockade, TGF-β inhibition, and chemotherapy may represent a promising therapeutic strategy for PC patients with high PD-L1 expression and pronounced fibrosis.