An online calculator using machine learning for predicting survival in pediatric patients with medulloblastoma

Author:

Kuo Cathleen C.1,Monteiro Andre23,Lim Jaims23,Brown Nolan J.4,Recker Matthew J.23,Ghannam Moleca M.23,Gendreau Julian L.5,Li Veetai26,Reynolds Renée M.26

Affiliation:

1. Jacobs School of Medicine and Biomedical Sciences at University at Buffalo;

2. Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences at University at Buffalo;

3. Department of Neurosurgery, Buffalo General Medical Center, Kaleida Health, Buffalo, New York;

4. Department of Neurosurgery, University of California, Irvine, Orange, California;

5. Department of Biomedical Engineering, Johns Hopkins Whiting School of Engineering, Baltimore, Maryland; and

6. Department of Neurosurgery, John R. Oishei Children’s Hospital, Buffalo, New York

Abstract

OBJECTIVE Medulloblastoma is the most common malignant intracranial tumor affecting the pediatric population. Despite advancements in multimodal treatment over the past 2 decades yielding a 5-year survival rate > 75%, children who survive often have substantial neurological and cognitive sequelae. The authors aimed to identify risk factors and develop a clinically friendly online calculator for prognostic estimation in pediatric patients with medulloblastoma. METHODS Pediatric patients with a histopathologically confirmed medulloblastoma were extracted from the Surveillance, Epidemiology, and End Results database (2000–2018) and split into training and validation cohorts in an 80:20 ratio. The Cox proportional hazards model was used to identify the univariate and multivariate survival predictors. Subsequently, a calculator with those factors was developed to predict 2-, 5-, and 10-year overall survival as well as median survival months for pediatric patients with medulloblastoma. The performance of the calculator was determined by discrimination and calibration. RESULTS One thousand seven hundred fifty-nine pediatric patients with medulloblastoma met the prespecified inclusion criteria. Age, sex, race, ethnicity, median household income, county attribute, laterality, anatomical location, tumor grade, tumor size, surgery status, radiotherapy, and chemotherapy were variables included in the calculator (https://spine.shinyapps.io/Peds_medullo/). The concordance index was 0.769 in the training cohort and 0.755 in the validation cohort, denoting clinically useful predictive accuracy. Good agreement between the predicted and observed outcomes was demonstrated by the calibration plots. CONCLUSIONS An easy-to-use prognostic calculator for a large cohort of pediatric patients with medulloblastoma was established. Future efforts should focus on improving granularity of population-based registries and externally validating the proposed calculator.

Publisher

Journal of Neurosurgery Publishing Group (JNSPG)

Subject

General Medicine

Reference29 articles.

1. Outcome of medulloblastoma in children treated with reduced-dose radiation therapy plus adjuvant chemotherapy;Sirachainan N,2011

2. Childhood medulloblastoma: an overview;Suk Y,2022

3. Survival of children with medulloblastoma in Canada diagnosed between 1990 and 2009 inclusive;Johnston DL,2015

4. What’s new in neuro-oncology? Recent advances in medulloblastoma;Ellison DW,2003

5. Molecular subgroups of medulloblastoma;Northcott PA,2012

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