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. 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.
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.
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