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Construction and validation of nomogram prognostic model for predicting survival in hepatoblastoma patients: a population-based study

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Abstract

For patients with hepatoblastoma (HB), current staging system is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making. A retrospective analysis of 424 HB patients was performed from 2004 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. Univariate and multivariate Cox regression analysis was used to screen for variables. The identified variables were used to build survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, and receiver operating characteristic (ROC) curve. The Cox regression analysis identified six variables affecting overall survival (OS) in HB patients, including race, tumor size, lymph node involvement, distant metastases, surgery and chemotherapy. And the Cox regression analysis identified five variables including race, lymph node involvement, distant metastases, surgery, and chemotherapy that affect cancer-specific survival (CCS) in HB patients. In the training cohort, the C-index of the nomogram in predicting the OS was 0.791 [95% confidence intervals (95% CI) 0.717–0.865], CSS was 0.805(95% CI 0.728–0.882). In the validation cohort, the C-index of the nomogram in predicting the OS was 0.712 (95% CI 0.511–0.913), the CSS was 0.751 (95% CI 0.566–0.936). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1-, 3-, and 5-year OS were 0.842 (95% CI 0.739–0.944), 0.759 (95% CI 0.670–0.849), and 0.770 (95% CI 0.686–0.852), respectively. In the validation cohort, the AUC values for prediction of the 1-, 3-, and 5-year OS were 0.920 (95% CI 0.806–1.034), 0.863 (95% CI 0.750–0.976), and 0.844 (95% CI 0.721–0.967), respectively. Two nomogram models were developed and validated in this study which provided accurate prediction of the OS and CSS in HB patients. The constructed models can be used for predicting survival outcomes and guide treatment for HB patients.

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Data availability

Publicly available datasets were analyzed in this study. These data can be found here: https://seer.cancer.gov/data/.

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Acknowledgements

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Funding

This work was supported by the General Program of the National Natural Science Foundation of China (82070554 and 81770537); the Major Scientific and Technological Special Project for Public Health in Tianjin (21ZXGWSY00080); the Tianjin Medical University General Hospital Clinical Research Program (22ZYYLCCG06) to Daqing Sun. The funding bodies played no role in the study design, data collection, analysis, interpretation, or manuscript writing.

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  1. Song Wang and Siqi Fu contributed equally to this work.

Authors and Affiliations

  1. Department of Pediatric Surgery, Tianjin Medical University General Hospital, Tianjin, China

    Song Wang, Siqi Fu, Rui Li, Zheng Guo, Yuchao Wang, Wei Sun & Daqing Sun

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  1. Song Wang
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Contributions

DS and SW: conception and design. SW and SF: development of methodology. RL and WS: acquisition of data. ZG, YW and WS: analysis and interpretation of data. SW: writing, review, and/or revision of the manuscript. DS and SW: administrative, technical, or material support. DS: study supervision. All authors participated in the writing of the final manuscript and approved the final submission.

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Correspondence to Daqing Sun.

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The study contained in this manuscript has no human participants, which waives the need for ethics approval and written informed consent from participants to take part in the study.

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Wang, S., Fu, S., Li, R. et al. Construction and validation of nomogram prognostic model for predicting survival in hepatoblastoma patients: a population-based study. Updates Surg (2024). https://doi.org/10.1007/s13304-024-01814-6

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