Background: In recent years, the incidence of pediatric hepatoblastoma has increased significantly. The aims of our study were to analyze the incidence trends, identify independent risk factors affecting the prognosis, and create a nomogram based on these risk factors to guide clinical treatment.
Methods: The Clinicopathological data from children diagnosed with hepatoblastoma between 2000 and 2018 were extracted from the SEER database to analyze the incidence trends. Independent risk factors were screened by COX, LASSO and BSR to construct a nomogram. X-tile software was used to determine the optimal threshold and to identify high-risk and low-risk groups. Kaplan-Meier method was used to draw the subgroup survival curve.
Results: A total of 810 children with hepatoblastoma were included in this study. The APC was 1.6 % (95 % confidence interval [CI] -0.6 %-3.9 %, P < 0.05). Race, age, tumor size, type of surgery, and chemotherapy were independent risk factors. The time-varying AUC (>0.7) and time-varying c index (>0.7) indicate that nomogram has good discriminative ability. The calibration graphs show that the predicted results of the modal graphs are in good agreement with the actual observed results in the training and validation queues. In addition, DCA demonstrated the value of nomogram in clinical application and differentiation.
Conclusion: The incidence of hepatoblastoma in children has increased. We construct a nomogram to predict prognosis and guide treatment. The combination of surgery and chemotherapy is highly likely to extend survival and improve patient outcomes.
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