Sci Rep. 2026 Jun 16. doi: 10.1038/s41598-026-54999-8. Online ahead of print.
ABSTRACT
In order to provide an additional tool for clinical prognosis evaluation, this research attempts to build a nomogram for predicting the survival of patients with advanced (stage Ⅲ/Ⅳ) pancreatic cancer and to preliminary evaluate its predictive impact. Data from 336 patients diagnosed with stage III/IV pancreatic cancer (2018-2025) across two Chinese hospitals were analyzed. Multivariate Cox regression identified independent predictors in the training set, which were used to construct a nomogram estimating 6-, 12-, and 24-month overall survival. The model underwent internal and external validation via ROC curves, calibration plots, and decision curve analysis. Multivariate Cox regression analysis of the training set revealed that serum albumin (P = 0.001), liver metastasis (P = 0.023), ALT≥40U/L (P = 0.010), and CA199 level (P = 0.037) were independent predictors of overall survival. Based on this, a nomogram model was constructed in the training cohort, with a C-index of 0.741. In the internal validation, the AUC values for predicting 6, 12, and 24-month survival rates were 0.806, 0.753, and 0.628, respectively, and in the external validation, they were 0.922, 0.662, and 0.650, respectively. The calibration curve showed that the predicted probabilities were in good agreement with the actual observed results. The discrimination and calibration of this model in internal verification are acceptable, but its incremental value for clinical decision-making is limited, and large-scale multi-center studies are required to further verify its generalizability.
PMID:42304037 | DOI:10.1038/s41598-026-54999-8