A Novel Online Nomogram Established with Five Features before Surgical Resection for Predicating Prognosis of Neuroblastoma Children: A Population-Based Study

Background: Neuroblastoma (NB) is the most common childhood cancer, but doctors are unable to predict its overall survival (OS) rate before surgery. We aimed to predict the OS of NB children with some clinical features obtained from biopsy before surgery. Methods: Clinical features of NB children we...

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Bibliographic Details
Published in:Technology in cancer research & treatment 2023-01, Vol.22, p.15330338221145141-15330338221145141
Main Authors: Zhou, Yu, Gao, Jing
Format: Article
Language:English
Subjects:
Biopsy
Child
Children
Histology
Humans
Medical prognosis
Mitosis
Neural networks
Neuroblastoma
Neuroblastoma - diagnosis
Neuroblastoma - surgery
Nomograms
Original
Ploidy
Population studies
Prognosis
Retrospective Studies
Risk factors
Risk groups
Surgery
Survival
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Summary:Background: Neuroblastoma (NB) is the most common childhood cancer, but doctors are unable to predict its overall survival (OS) rate before surgery. We aimed to predict the OS of NB children with some clinical features obtained from biopsy before surgery. Methods: Clinical features of NB children were retrospectively collected from the Therapeutically Applicable Research to Generate Effective Treatments database. The C-index, area under the receiver operating characteristic curve (AUC), calibration curves, and decision curves analysis were used to estimate nomogram models. Results: A total of 488 NB children were evaluated, and the Boruta algorithm was used to detect risk factors. The results showed that artificial neural networks with selected features were able to predict more than 90% of NB children. Five risk factors were used in the construction of the nomogram, including age at diagnosis, MYCN status, ploidy value, histology, and mitosis-karyorrhexis index (MKI). The C-index of the nomogram in training cohort and validation cohort was 0.716 and 0.731. AUC values for 1-, 3-, and 5-years OS predictions were 0.706, 0.755, and 0.762, respectively, and showed good calibrations. Decision curve analysis indicated a better predictability with the nomogram model based on Cox regression compared with one that included all variables and histology only. Also, the Kaplan–Meier curves showed a significantly higher survival probability in the low-risk group (total score
ISSN:1533-0346
1533-0338
DOI:10.1177/15330338221145141