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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and risk stratification of a prognostic nomogram for hepatoblastoma: analysis of the SEER database
1Department of Pediatric Surgery, Chengdu Women'S and Children'S Central Hospital, School of Medicine, University of Electronic Science and Technology of China, No. 1617 Riyue Avenue, Qingyang District, Chengdu, 611731, Sichuan, China.
Abstract:
Hepatoblastoma, the most common primary liver malignancy in children, exhibits significant clinical and biological heterogeneity, leading to varying prognoses. This study aimed to identify independent prognostic factors for overall survival in pediatric hepatoblastoma patients, develop and validate a nomogram prediction model, and establish a risk stratification system. We conducted a retrospective analysis of patients aged ≤18 years with hepatoblastoma using data from the Surveillance, Epidemiology, and End Results (SEER) database (2000-2020). Univariate and multivariate Cox regression analyses identified age, race, tumor stage, tumor size, surgery, and chemotherapy as independent prognostic factors. We developed a nomogram prediction model based on these factors, which underwent internal and external validation. The model accurately predicts 1-, 3-, and 5-year overall survival rates. We also established a risk classification system that stratifies patients into low, intermediate, and high-risk groups. Subgroup analysis revealed that low-risk patients had better survival outcomes with hepatectomy, while intermediate-risk patients benefited more from liver transplantation. The developed nomogram enables individualized prediction of overall survival rates in pediatric hepatoblastoma patients, and the risk stratification system can guide early and accurate prognostic assessment.
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