ArticleScientific reports2025
Development and validation of a dynamic prognostic nomogram for conditional survival in hepatocellular carcinoma: an analysis from the Korea Liver Cancer Registry.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
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2 citing papers in PubMed.
- Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence.NPJ digital medicine · 2026Article
- Dynamic postoperative prognosis and follow-up optimization for gastric cancer patients after neoadjuvant therapy: a multicenter retrospective study.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
Compared to overall survival, conditional survival is a more relevant measure of prognosis in surviving patients over time. This study developed and validated a nomogram-based dynamic prognostic model to predict the conditional survival estimates of patients with hepatocellular carcinoma (HCC) through an analysis of a nationwide cancer registry. This retrospective cohort study included 2492 patients with HCC registered in the Korea Liver Cancer Registry. Patients underwent hepatic resection (HR) from 2008 to 2017, were followed up until December 2019, and were divided into development and validation cohorts. Univariate and multivariate Cox regression analyses were conducted to determine the risk factors for conditional survival of patients who underwent HR. The patients were scored based on the Cox regression coefficients; the nomogram was predicted by calculating the survival probability with Cox model. Our dynamic prognostic model nomogram for predicting conditional overall survival demonstrated Harrell's C-index of 0.622 and 0.674 in the development and validation sets; for conditional disease-specific survival, it was 0.623 and 0.686 in the development and validation sets. The prediction power of the model is applicable in clinical practice. Factors incorporated in our nomogram included age, albumin, the ADV score, lymph node metastasis, and T stage in American Joint Commission on Cancer staging system. We developed and validated a nomogram to predict conditional survival estimates for overall survival and disease-specific survival. The proposed nomogram incorporating the ADV score presents a more accurate and useful prognostic prediction for patients with HCC who received HR.
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