Survival prediction model of children with diffuse intrinsic pontine glioma based on clinical and radiological criteria

Marc H Jansen; Sophie E Veldhuijzen van Zanten; Esther Sanchez Aliaga; Martijn W Heymans; Monika Warmuth-Metz; Darren Hargrave; Erica J van der Hoeven; Corrie E Gidding; Eveline S de Bont; Omid S Eshghi; Roel Reddingius; Cacha M Peeters; Antoinette Y N Schouten-van Meeteren; Rob H J Gooskens; Bernd Granzen; Gabriel M Paardekooper; Geert O Janssens; David P Noske; Frederik Barkhof; Christof M Kramm; W Peter Vandertop; Gertjan J Kaspers; Dannis G van Vuurden

doi:10.1093/neuonc/nou104

Survival prediction model of children with diffuse intrinsic pontine glioma based on clinical and radiological criteria

Neuro Oncol. 2015 Jan;17(1):160-6. doi: 10.1093/neuonc/nou104. Epub 2014 Jun 5.

Authors

Marc H Jansen¹, Sophie E Veldhuijzen van Zanten¹, Esther Sanchez Aliaga¹, Martijn W Heymans¹, Monika Warmuth-Metz¹, Darren Hargrave¹, Erica J van der Hoeven¹, Corrie E Gidding¹, Eveline S de Bont¹, Omid S Eshghi¹, Roel Reddingius¹, Cacha M Peeters¹, Antoinette Y N Schouten-van Meeteren¹, Rob H J Gooskens¹, Bernd Granzen¹, Gabriel M Paardekooper¹, Geert O Janssens¹, David P Noske¹, Frederik Barkhof¹, Christof M Kramm¹, W Peter Vandertop¹, Gertjan J Kaspers¹, Dannis G van Vuurden¹

Affiliation

¹ Department of Pediatric Oncology and Hematology, VU University Medical Center, Amsterdam, Netherlands (M.H.A.J., S.E.M.V.v.Z., E.J.v.d.H., G.J.L.K., D.G.v.V.); Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands (E.S.A., F.B.); Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands (M.W.H.); Department of Neuroradiology, Reference Center for Neuroradiology, Uniklinikum Wurzburg, University of Würzburg, Wurzburg, Germany (M.W-M.); Department of Oncology, Great Ormond Street Hospital London, London, UK (D.H.); Department of Pediatric Oncology and Hematology, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands (C.E.G.); Department of Pediatric Oncology and Hematology, University Medical Center Groningen, Groningen, Netherlands (E.S.J.M.d.B.); Department of Radiology, University Medical Center Groningen, Groningen, Netherlands (O.S.E.); Department of Pediatric Oncology and Hematology, Erasmus Medical Centre Rotterdam, Rotterdam, Netherlands (R.R.); Department of Pediatric Neurology, Leiden University Medical Center Rotterdam, Leiden, Netherlands (C.M.P.C.D.P.); Department of Pediatric Oncology and Hematology, Academic Medical Center Amsterdam, Emma Children's Hospital AMC, Amsterdam, Netherlands (A.Y.N.S-v.M.); Department of Pediatric Neurology, University Medical Center Utrecht, Utrecht, Netherlands (R.H.J.G.); Department of Pediatric Oncology and Hematology, University Hospital Maastricht, Maastricht, Netherlands (B.G.); Department of Radiotherapy, Isala Clinics Zwolle, Zwolle, Netherlands (G.M.R.N.P.); Department of Radiation Oncology (874), Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands (G.O.J.); Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, Netherlands (D.P.N., W.P.V.); University Children's Hospital, Halle, Germany (C.M.K.); Division of Pediatric Hematology and Oncology, Department of Pediatrics and Adolescent Medi

Abstract

Background: Although diffuse intrinsic pontine glioma (DIPG) carries the worst prognosis of all pediatric brain tumors, studies on prognostic factors in DIPG are sparse. To control for confounding variables in DIPG studies, which generally include relatively small patient numbers, a survival prediction tool is needed.

Methods: A multicenter retrospective cohort study was performed in the Netherlands, the UK, and Germany with central review of clinical data and MRI scans of children with DIPG. Cox proportional hazards with backward regression was used to select prognostic variables (P < .05) to predict the accumulated 12-month risk of death. These predictors were transformed into a practical risk score. The model's performance was validated by bootstrapping techniques.

Results: A total of 316 patients were included. The median overall survival was 10 months. Multivariate Cox analysis yielded 5 prognostic variables of which the coefficients were included in the risk score. Age ≤3 years, longer symptom duration at diagnosis, and use of oral and intravenous chemotherapy were favorable predictors, while ring enhancement on MRI at diagnosis was an unfavorable predictor. With increasing risk score categories, overall survival decreased significantly. The model can distinguish between patients with very short, average, and increased overall survival (medians of 7.0, 9.7, and 13.7 mo, respectively). The area under the receiver operating characteristic curve was 0.68.

Conclusions: We developed a DIPG survival prediction tool that can be used to predict the outcome of patients and for stratification in trials. Validation of the model is needed in a prospective cohort.

Keywords: brainstem neoplasms; glioma; magnetic resonance imaging; pons; prognosis.

Publication types

Multicenter Study
Research Support, Non-U.S. Gov't

MeSH terms

Adolescent
Brain Stem Neoplasms / diagnosis*
Brain Stem Neoplasms / mortality*
Brain Stem Neoplasms / radiotherapy
Child
Child, Preschool
Cohort Studies
Female
Glioma / diagnosis*
Glioma / mortality*
Glioma / radiotherapy
Humans
Infant
Infant, Newborn
Magnetic Resonance Imaging
Male
Proportional Hazards Models*
Retrospective Studies
Treatment Outcome