Evidence Based Medicine, in Precision Oncology ()
ABSTRACT
The disagreements in clinical data and therapy recommendations extracted
from different sources/studies are a
common finding in oncology research. Knowingly
“biology is less reproducible than physics and mechanic engineering”, in order
to overcome the disagreements and to find common grounds, we still rely
on meta-analysis and systemic reviews for the highest level of evidence. To gather systemic review data base, a
bibliographic search usually is conducted in the PubMed and in Cochrane Central
Register of Controlled Trials databases to address a common clinical challenge.
That said, frequently due to common conflicts between articles outcomes, an
opinion of a third investigator is sought. Here in this article, we propose
a rationale that could explain the differences in outcomes as a result of imperfect
understanding of the current research database secondary to the unique biology
of the tumor, rather than statistical interpretation on findings. We believe
that the differences in findings merely are based on blinded inclusion criteria, and lack of accurate companion
diagnostics to correlate the magnitude of response to each therapy. The
objective of this article is to discuss a strategy to overcome such discordance
by providing quantitative biological measures for genomic classification and
correlation of tumor response to the selected targeted therapy. We further
review such analysis in a case series of Her 2 positive breast cancer and
conclude that translational research would be clinically relevant when
customized to the biological findings.
Share and Cite:
Nezami, M. and Hager, S. (2018) Evidence Based Medicine, in Precision Oncology.
Journal of Cancer Therapy,
9, 689-705. doi:
10.4236/jct.2018.99057.
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