ArticleAnnals of surgical oncology2026
Long-Term Survival and Beneficiaries of Adjuvant Anti-PD-1 Therapy in Resected Hepatocellular Carcinoma.
Article in Annals of surgical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Identification of exosomal miRNA-based predictive signatures for gestational diabetes mellitus via multi-algorithm machine learning.BMC pregnancy and childbirth · 2026Article
- Perioperative camrelizumab plus rivoceranib in resectable hepatocellular carcinoma: translating CARES-009 outcomes into a new therapeutic paradigm.Annals of medicine and surgery (2012) · 2026Article
- Prognostic Models for Small Hepatocellular Carcinoma Using Inflammatory Indices and Machine Learning: A Propensity Score-Matched Study.International journal of general medicine · 2026Article
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Authors and funding
17 authors.
Funding
Abstract
backgroundEarly and late hepatocellular carcinoma (HCC) recurrences, which are driven by residual and de novo tumors, respectively, differ in biology and potential treatment susceptibility. The effectiveness of adjuvant PD-1 inhibitors (aPD-1) across these distinct recurrence patterns remains unclear. PATIENTS AND
methodsA total of 3436 cases were included from 9 centers in China. Among these, 1662 patients (2019-2023) were propensity score-matched to compare the effects of aPD-1 versus active surveillance on survival outcomes. Machine learning (ML) models were trained on 1774 patients (2014-2018) to predict early recurrence (≤ 2 years). The efficacy of aPD-1 was further assessed in ML-predicted subgroups, using a 2-year landmark analysis to evaluate its effect on recurrence etiology.
resultsThe logistic regression model achieved the best performance, with an AUC of 0.818 in the test set. Patients classified as high risk showed significantly poorer disease-free survival (DFS) and overall survival. aPD-1 significantly improved DFS in high-risk patients (HR 0.69, 95% CI 0.57-0.84, p < 0.001), but no benefit was observed in low-risk patients (HR 0.99, 95% CI 0.71-1.39, p = 0.950). Landmark analysis further demonstrated that aPD-1 preferentially reduced early recurrence in high-risk HCC (HR 0.67, 95% CI 0.54-0.83, p < 0.001), while showing limited efficacy against late recurrence (HR 0.81, 95% CI 0.49-1.31, p = 0.380).
conclusionsaPD-1 demonstrates time-dependent efficacy, primarily reducing early recurrence through controlling residual micro-metastases rather than preventing de novo tumors. A ML model accurately identified patients most likely to benefit, highlighting the importance of risk-guided adjuvant therapy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.