Individualized Prediction of Postoperative Survival in Gallbladder Cancer: A Nomogram Based on SEER Data and External Validation.

BACKGROUND

Gallbladder cancer (GBC) is a rare but aggressive malignancy. Prognostic tools are essential for optimizing postoperative treatment strategies. We aim to develop and validate a prognostic nomogram to estimate 1-, 3-, and 5-year overall survival (OS) in GBC patients and explore the role of adjuvant chemotherapy across different subgroups.

METHODS

A total of 1848 postoperative GBC patients from the SEER database (2000-2020 17 regions) were analyzed, with an additional external validation cohort of 108 patients from China (2010-2020). Prognostic factors were identified using LASSO regression and multivariable Cox analysis. A nomogram was constructed and validated using the concordance index (C-index), time-dependent ROC curves, calibration curves, and decision curve analysis (DCA). Subgroup analyses were performed to evaluate the impact of adjuvant chemotherapy.

RESULTS

The nomogram demonstrated strong predictive performance, with C-indices of 0.767 (training), 0.798 (internal validation), and 0.750 (external validation). Time-dependent ROC curves in the training cohort showed AUCs of 0.777, 0.769, and 0.800 for 1-, 3-, and 5-year OS, respectively. In the internal validation cohort, the corresponding AUCs were 0.763, 0.743, and 0.803. External validation using the independent Chinese cohort of 108 patients showed consistent results, with AUCs of 0.771, 0.835, and 0.810 for 1-, 3-, and 5-year OS. Subgroup analysis revealed that adjuvant chemotherapy significantly improved survival in patients with TNM stage >IIB. In contrast, patients with early-stage disease (TNM ≤ IIB) showed no significant survival benefit from chemotherapy.

CONCLUSIONS

This study developed a validated prognostic nomogram for postoperative GBC patients, demonstrating strong discrimination and calibration. Subgroup analysis suggests that adjuvant chemotherapy benefits select high-risk patients, aiding personalized decision-making in clinical practice.