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A Clinicobiological Model Predicting Survival in Medulloblastoma

Divisions of ¹ Neurosurgery, ² Oncology, and ³ Pathology, The Hospital for Sick Children, Toronto, Ontario, Canada; ⁴ Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; and ⁵ Prosserman Centre for Health Research (Epidemiology and Biostatistics), Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada

Purpose: The purpose of this study was to determine the relative contributions of biological and clinical predictors of survival in patients with medulloblastoma (MB).

Experimental Design: Clinical presentation and survival information were obtained for 119 patients who had undergone surgery for MB at the Hospital for Sick Children (Toronto, Ontario, Canada) between 1985 and 2001. A tissue microarray was constructed from the tumor samples. The arrays were assayed for immunohistochemical expression of MYC, p53, platelet-derived growth factor receptor-, ErbB2, MIB-1, and TrkC and for apoptosis (terminal deoxynucleotidyl transferase-mediated nick end labeling). Both univariable and multivariable analyses were conducted to characterize the association between survival and both clinical and biological markers. For the strongest predictors of survival, a weighted predictive score was calculated based on their hazard ratios (HRs). The sum of these scores was then used to give an overall prediction of survival using a nomogram.

Results: The four strongest predictors of survival in the final multivariable model were the presence of metastatic disease at presentation (HR, 2.02; P = 0.01) and p53 (HR, 2.29; P = 0.02), TrkC (HR, 0.65; P = 0.14), and ErbB2 (HR, 1.51; P = 0.21) immunopositivity. A linear prognostic index was derived, with coefficients equal to the logarithm of these HRs. The 5-year survival rate for patients at the 10^th, 50^th, and 90^th percentiles of the score distribution was 80.0%, 71.0%, and 35.7%, respectively, with radiation therapy and 70.5%, 58.5%, and 20.0%, respectively, without radiation therapy.

Conclusions: In this study, we demonstrate an approach to combining both clinical and biological markers to quantify risk in MB patients. This provides further prognostic information than can be obtained when either clinical factors or biological markers are studied separately and establishes a framework for comparing prognostic markers in future clinical studies.

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