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Combining Gene Expression Profiles and Clinical Parameters for Risk
Stratification in Medulloblastomas
Ana Fernandez-Teijeiro, Rebecca A. Betensky, Lisa M.
Sturla, John Y.H. Kim, Pablo Tamayo, Scott
L. Pomeroy
From the
Division of Neuroscience, Department of Neurology, Department of Medicine,
Children's Hospital; Department of Pediatric Oncology, Dana-Farber Cancer
Institute, Harvard Medical School; Department of Biostatistics, Harvard School
of Public Health, Boston; Whitehead Institute/MIT Center of Biomedical Research,
MA Institute of Technology, Cambridge, MA; and Unidad de Oncologia Pediatrica,
Hospital de Cruces-Baracaldo, Basque Country, Spain.
Address
reprint requests to Scott L. Pomeroy, MD, PhD, Department of Neurology, Enders
260, Children's Hospital, 300 Longwood Ave, Boston MA 02115; e-mail: scott.pomeroy@childrens.harvard.edu
Purpose. Stratification of risk in patients with medulloblastoma remains a
challenge.
As clinical parameters have been proven insufficient for accurately
defining disease risk, molecular markers have become the focus of
interest.
Outcome predictions on the basis of microarray gene expression
profiles have been the most accurate to date.
We ask in a multivariate model whether clinical parameters enhance
survival predictions of gene expression profiles.
Patients
and Methods. In a
cohort of 55 young patients (whose medulloblastoma samples have been
analyzed previously for gene expression profile), associations
between clinical and gene expression variables and survival were
assessed using Cox proportional hazards models.
Available clinical variables included age, stage (ie, the presence of
disseminated disease at diagnosis), sex, histologic subtype, treatment,
and status.
Results. Univariate analysis demonstrated expression profiles to be the only
significant clinical prognostic factor (P = .03).
In multivariate analysis, gene expression profiles predicted outcome
independent of other criteria.
Clinical criteria did not significantly contribute additional
information for outcome predictions, although an exploratory analysis
noted a trend for decreased survival of patients with metastases at
diagnosis but favorable gene expression profile.
Conclusion. Gene
expression profiling predicts medulloblastoma outcome independent of
clinical variables.
These results need to be validated in a larger prospective study.
© 2004
American
Society of Clinical Oncology
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