ArticleFrontiers in pediatrics2023
Establishment and validation of a nomogram to predict cancer-specific survival in pediatric neuroblastoma patients.
Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Comprehensive analysis identifies ubiquitin ligase FBXO42 as a tumor-promoting factor in neuroblastoma.Scientific reports · 2024Article
- Development and validation of nomogram-based models for personalized survival assessment in pediatric hepatoblastoma patients.Translational cancer research · 2024Article
- Development and validation of a nomogram to predict the recurrence of eyelid sebaceous gland carcinoma.Cancer medicine · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The term "neuroblastoma (NB)" refers to a type of solid pediatric tumor that develops from undivided neuronal cells. According to the American Cancer Society report, between 700 and 800 children under the age of 14 are diagnosed with NB every year in the United States (U.S.). About 6% of all cases of pediatric cancer in the U.S. are caused by NB. NB is the most frequent malignancy in children younger than 1 year; however, it is rarely found in those over the age of 10 and above. Objective: To accurately predict cancer-specific survival (CSS) in children with NB, this research developed and validated an all-encompassing prediction model. Methods: The present retrospective study used the Surveillance, Epidemiology, and End Results (SEER) database to collect information on 1,448 individuals diagnosed with NB between 1998 and 2019. The pool of potentially eligible patients was randomly split into two groups, a training cohort ( Results: In this study, we found that age, primary location, tumor size, summary stage, chemotherapy, and surgery were all significant predictors of CSS outcomes and integrated them into our model accordingly. The C-index for the validation cohort was 0.812 (95% CI: 0.773-0.851), while for the training cohort it was 0.795 (95% CI: 0.767-0.823). The C-indexes and AUC values show that the nomogram is able to discriminate well enough. The calibration curves suggest that the nomogram is quite accurate. Also, the DCA curves demonstrated the prediction model's value. Conclusion: A novel nomogram was developed and validated in this work to assess personalized CSS in NB patients, and it has been indicated that this model could be a useful tool for calculating NB patients' survival on an individual basis and enhancing therapeutic decision-making.
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