Evidence map›Paper›PMID 41060454›Full record

ArticleEuropean journal of pediatrics2025

Prognostic factors and treatment outcomes of hepatoblastoma in children: a SEER database analysis.

Xiao Li, Jianjin Xue, Xilong Tang, Jie Zhang, Jiajia Zhou

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Article in European journal of pediatrics, 2025. 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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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiao Li *Department of Pediatric Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, PR China.
Jianjin Xue *Department of Pediatric Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, PR China.
Xilong TangDepartment of Pediatric Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, PR China.
Jie ZhangDepartment of Pediatric Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, PR China.
Jiajia ZhouDepartment of Pediatric Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, PR China. zhoujj29@mail.sysu.edu.cn.

Funding

National Natural Science Foundation of China 82073062
6 · The paper itself

Abstract

Hepatoblastoma (HB) is the most common primary liver malignancy in children. This study aimed to construct a clinical prediction model to quantitatively assess the overall survival (OS) and cancer-specific survival (CSS) of pediatric patients with HB and to analyze the impact of different treatment methods on prognosis. HB patients' clinical characteristics and treatment data were extracted from the SEER database. Prognostic variables were selected using univariate and multivariate Cox proportional hazards regression analyses, and a survival prediction model was subsequently constructed. The performance of the nomogram was evaluated using the concordance index (C-index), calibration plots, and receiver operating characteristic (ROC) curves. The prognostic impact of different treatment modalities was further assessed through Kaplan-Meier analysis and subgroup analyses. A total of 424 HB patients were included. Univariate Cox regression analysis and multivariate Cox regression analysis identified several independent prognostic factors, including race, surgical intervention, and tumor metastasis, as independent prognostic factors for OS. In contrast, race, surgical intervention, distant metastasis, and chemotherapy were independent predictors for CSS. All AUC values substantially exceeded the 0.7 threshold for satisfactory predictive capacity. Calibration plots revealed close agreement between predicted and observed survival probabilities. Subgroup analysis further revealed that younger patients exhibited significantly better prognoses when treated with chemotherapy, underscoring its critical role in survival outcomes. Conclusion: The study successfully established a clinical prediction model for HB, enabling quantification of the impact of clinical characteristics on OS and CSS, as well as individualized survival prediction and risk stratification. Subgroup analyses highlighting prognostic variations among treatment strategies provide an evidence-based foundation for optimizing therapeutic approaches in pediatric HB patients. What is Known? • Hepatoblastoma (HB) is the most common primary liver malignancy in children. What is New? • A clinical prediction model was constructed to quantitatively assess the overall survival (OS) and cancer-specific survival (CSS) of pediatric patients with HB.

Indexed as

HepatoblastomaLiver NeoplasmsAdolescentChildChild, PreschoolFemaleHumansInfantInfant, NewbornKaplan-Meier EstimateMaleNomogramsPrognosisProportional Hazards ModelsRetrospective StudiesROC CurveCancer-specific survival (CSS)HepatoblastomaNomogramOverall survival (OS)Prognostic factorsSubgroup analysis

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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.