ArticleDiscover oncology2025
Dynamic conditional survival nomogram for primary hepatocellular carcinoma: a population-based analysis.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Beyond traditional survival estimates: conditional survival and individualized prognosis in primary breast lymphoma.Translational cancer research · 2026Article
- Toward individualized prognosis in primary breast diffuse large B-cell lymphoma: incidence trends and a predictive model.Translational cancer research · 2026Article
- Population-Based analysis of conditional survival patterns and dynamic prognostic modeling in primary urinary tract lymphoma.Annals of hematology · 2026Article
- Transcriptomic Analysis Reveals the Role ofHuman mutation · 2026Article
- Dynamic AFP-Defined Disease State Transitions in Hospitalized Patients with Hepatocellular Carcinoma Using the Multi-State Markov Model: A Retrospective Cohort Study.Journal of hepatocellular carcinoma · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeHepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide. While 5-year overall survival (OS) is a common prognostic metric, it does not reflect the evolving prognosis of long-term survivors. The study aimed to evaluate dynamic changes in real-time survival among HCC patients over time using conditional survival (CS) analysis and to develop an individualized, time-updated prognostic model.
methodsA total of 11,926 patients with primary HCC were included and randomly assigned to training (70%) and validation (30%) cohorts. CS was defined as the probability of surviving additional years given time already survived [CS(t
resultsCS analysis showed that real-time survival rate increased significantly with each additional year survived, with 5-year CS rising from 35.1% at diagnosis to 52.9%, 66.7%, 79.2%, and 90.2% after 1-4 years of survival. Eleven prognostic factors were included in the final model (all p < 0.05). The CS-nomogram demonstrated strong discrimination (5-year AUC > 0.84 in both cohorts) and good calibration. An interactive web-based tool was developed to facilitate clinical application.
conclusionCS analysis offers more accurate and dynamic prognostic information for HCC patients. The CS-nomogram provides personalized, time-adjusted survival estimates, supporting more informed decision-making and survivorship care.
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