Preprint Article Version 1 NOT YET PEER-REVIEWED

Predictors of Survival in Children with Ependymoma from a Single Center: Using Random Survival Forests

  1. Pediatric Hemato-oncology Service, Hospital Infantil Albert Sabin, R Alberto Montezuma, 350 - Vila Uniao, 60410-770, Fortaleza - CE, Brazil
  2. Department of Pharmacy, Faculdade de Farmácia, Odontologia e Enfermagem, Universidade Federal do Ceara, Av. da Universidade, 2853 - Benfica, 60020-180, Fortaleza - CE, Brazil
Version 1 : Received: 2 November 2016 / Approved: 3 November 2016 / Online: 3 November 2016 (11:02:12 CET)

How to cite: Felix, F.; Fontenele, J. Predictors of Survival in Children with Ependymoma from a Single Center: Using Random Survival Forests. Preprints 2016, 2016110028 (doi: 10.20944/preprints201611.0028.v1). Felix, F.; Fontenele, J. Predictors of Survival in Children with Ependymoma from a Single Center: Using Random Survival Forests. Preprints 2016, 2016110028 (doi: 10.20944/preprints201611.0028.v1).

Abstract

Ependymoma is responsible for 8–10% of all pediatric brain tumors and constitutes the third most common brain tumor in children. No robust molecular markers are yet in routine clinical use. Surgical resection and adjuvant radiotherapy cure approximately 40-70% of pediatric patients with ependymoma. In our centre, we have been using prophylactic valproic acid treatment for brain tumor patients. Initial observations indicated that valproate could have a beneficial effect in the survival of patients. Recent observations by other authors have shown that patients with glioblastoma benefited from the treatment with valproic acid, a histone deacetylase inhibitor. We have used random survival forest, a novel ensemble survival modelling method to study a single- center, small number cohort of pediatric patients with ependymoma. This analysis has confirmed surgery resection extent and treatment with radiotherapy as independent predictors of overall survival. Treatment with valproic acid was also a predictor of higher survival in this cohort. These results highlight the potential usefullness of the random survival forest model in gathering information from retrospective data. More data is needed about the possible influence of histone deacetylase inhibition by valproic acid in the survival of patients with ependymoma.

Subject Areas

random survival forests; ependymoma; predictors; valproic acid

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