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Taylor A. Wilson
  1. Department of Neurosurgery, New York University School of Medicine, New York, USA

Correspondence Address:
Taylor A. Wilson
Department of Neurosurgery, New York University School of Medicine, New York, USA

DOI:10.4103/2152-7806.137196

Copyright: © 2013 Wilson TA This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

How to cite this article: Wilson TA. Glioblastoma – A tale of two tumors: Case comparison and literature review. Surg Neurol Int 19-Jul-2014;5:110

How to cite this URL: Wilson TA. Glioblastoma – A tale of two tumors: Case comparison and literature review. Surg Neurol Int 19-Jul-2014;5:110. Available from: http://sni.wpengine.com/surgicalint_articles/glioblastoma-a-tale-of-two-tumors-case-comparison-and-literature-review/

Date of Submission
23-May-2014

Date of Acceptance
03-Jun-2014

Date of Web Publication
19-Jul-2014

In the paper entitled “Glioblastoma – A tale of two tumors: Case comparison and literature review,” the authors discuss several molecular biomarkers for glioblastoma (GBM), and the role of these markers clinically for directing treatment and predicting prognosis. Currently, there are many molecular tests that can be performed and are routinely reported with the histopathological analysis of GBM. As demonstrated in the existing literature and further highlighted by this paper, there are both benefits and limitations to using molecular testing in GBM.[ 1 2 ] Thus, the authors raise the question of cost versus utility of more extensive routine molecular testing on patients with GBM. Furthermore, this raises the issue of how the results of these tests impact patient care and clinical management of patients with GBM, as well as whether the data acquired from these tests are worth the additional cost.

Clinically, the role of molecular testing remains unclear; however, this is not to undermine the importance of understanding the molecular biology and genomics of GBM. Molecular biomarkers can be useful in identifying GBM subtypes, which can be used to better drive treatment on an individual basis.[ 2 ] For example, many of these molecular biomarkers also function as therapeutic targets. In these cases, testing for specific molecular alterations does play an important role in directing treatment. In other cases, the molecular biomarkers have a less meaningful impact on care and prognosis. Many of these tests are expensive and not covered under insurance. Thus, it is important to consider how the molecular test ordered will impact the clinical management of the patient when ordering these tests.

As stated by the authors, there is currently little data regarding cost versus utility analysis of molecular testing for GBM. In a study done by Holdhoff et al. in the Journal of Neuro-Oncology assessing the use of molecular biomarkers in the clinical care of patients with GBM, they found that only small proportion of physicians ordering these tests found that the results impacted clinical management of their patients.[ 1 ] Understanding the genomics of GBM is critical for research in order to develop new therapeutic targets and approaches to treating GBM, but until particular biomarkers are used in a way where the result of the test directly alters patient management, such as a clinical trial for a small molecular inhibitor or monoclonal antibody, routine molecular testing may not be necessary for all patients. There is a lot of information available, but understanding how to use this information to guide patient care is critical to maximize treatment benefits for the patients as well as avoid unnecessary costs.

References

1. Holdhoff M, Ye X, Blakeley JO, Blair L, Burger PC, Grossman SA. Use of personalized molecular biomarkers in the clinical care of adults with glioblastomas. J Neurooncol. 2012. 110: 279-85

2. Kim YW, Koul D, Kim SH, Lucio-Eterovic AK, Freire PR, Yao J. Identification of prognostic gene signatures of glioblastoma: A study based on TCGA data analysis. Neuro Oncol. 2013. 15: 829-39

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