A novel hybrid model for predicting tertiary lymphoid structures and targeted immunotherapy outcomes in hepatocellular carcinoma: a multicenter retrospective study
摘要
To develop a novel hybrid model for preoperative prediction of tertiary lymphoid structures (TLSs) of hepatocellular carcinoma (HCC), and to identify patients who may benefit from postoperative targeted immunotherapy.
MethodsRetrospective data were gathered from 332 patients with HCC who underwent surgical resection and gadoxetate disodium (Gd-EOB-DTPA) enhanced MRI at two tertiary hospitals (training cohort, n = 205; internal validation cohort, n = 90; and external validation cohort, n = 37) between March 2020 and January 2023. Radiomic features were extracted from Gd-EOB-DTPA-enhanced MRI sequences. These signatures were integrated with clinical–radiologic (CR) factors into a hybrid model and nomogram for clinical application. The performance of the model was assessed using the area under the curve (AUC) and 95% confidence intervals (CI).
ResultsThe hybrid model outperformed the radiomics and CR models in the training cohort (AUC = 0.860 [95% CI: 0.805, 0.904], 0.784 [95% CI: 0.721, 0.838], and 0.809 [95% CI: 0.748, 0.860]). The hybrid model showed optimal performance, with AUCs of 0.823 (95% CI: 0.728, 0.895) and 0.875 (95% CI: 0.725, 0.960) in the internal and external validation cohorts, respectively. The calibration curve demonstrated that the nomogram had good diagnostic ability, and decision curve analysis indicated good clinical utility across all cohorts. Importantly, patients with a predicted high risk of TLSs from the hybrid model gained a survival benefit from targeted immunotherapy.
ConclusionThe hybrid model showed satisfactory performance in predicting intra-tumoral TLS positivity and targeted immunotherapy benefit in patients with HCC, potentially assisting clinicians in selecting precise individualized therapies.
Key Points