ArticleScientific reports2026
Conditional survival after radiofrequency ablation for early-stage hepatocellular carcinoma.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Predictors of True Early Recurrence in Patients Undergoing Radiofrequency Ablation for Hepatocellular Carcinoma.JGH open : an open access journal of gastroenterology and hepatology · 2026Article
- Risk Group Stratification for True Early Recurrence After Ablation for Hepatomas.Canadian journal of gastroenterology & hepatology · 2026Article
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Authors and funding
9 authors.
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Abstract
We analyzed how conditional survival (CS) after radiofrequency ablation (RFA) for early-stage hepatocellular carcinoma (HCC) predicts survival estimates over time. We enrolled 791 patients with newly diagnosed early-stage HCC (i.e., within Milan criteria) and Child-Pugh class A liver disease undergoing RFA. Three-year CS, calculated as CS = S(x + 3)/S(x), was the probability of surviving an additional three years, given that the patient had already survived x years. One-, three-, and five-year overall survival rates were 96.3, 72.3, and 59.7%, respectively, and were lower for patients with a MELD score of > 9, BCLC stage A disease, and AFP level of ≥ 20 ng/ml. However, three-year CS showed that patients ablated for BCLC stage A or AFP ≥ 20 ng/ml had the same survival probabilities as patients with BCLC stage 0 or AFP < 20 ng/ml from the third year onward after RFA. In contrast, the three-year CS of patients with a MELD score of ≤ 9 was always better than that of patients with a MELD score of > 9. We concluded that CS showed that the impact of different variables on survival after RFA is not linear over time. Information derived from CS can be used to dynamically predict the prognosis of patients with HCC.
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