Abstract
OBJECTIVE: Hyper-progression recurrence (HPR) after hepatectomy is a specific recurrence pattern associated with extremely poor prognosis in patients with hepatocellular carcinoma (HCC). This study was aimed at investigating the probable risk factors and establishing comprehensive models for formulating clinical strategies. METHODS: Overall, 16,158 patients with HCC from 8 hospitals were screened, among whom 3,125 patients who underwent R0 resection were included, and divided into development (n = 2,113) and validation (n = 1,012) cohorts. A comprehensive study of HPR predictive models and biological features was conducted. RESULTS: Among the 3,125 enrolled patients, 506 (16.19%) developed HPR. The influence of HPR on extremely poor prognosis was reflected by recurrence features, adverse effects on systemic and liver function, and limited therapeutic options. Nine variables closely associated with HPR were identified, and incorporated into nomogram and conditional inference tree models, which successfully achieved pre- and post-operative HPR risk stratification and facilitated clinical decision-making. Multi-dimensional verification also confirmed the predictive accuracy of model combinations and their reliability in clinical applications. Furthermore, biological analyses revealed that HCCs with HPR exhibited hyperactive biological processes, inactive metabolism, and immune exhaustion features, together with high MYCN/HMGA2 co-expression, thereby enhancing understanding of the molecular events leading to HPR and providing valuable knowledge for HPR management. CONCLUSIONS: HPR after hepatectomy is associated with extremely poor prognosis and requires substantial attention. We constructed comprehensive predictive models and propose a clinical strategy for guiding HPR prevention and management.