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. Kn owingly “biology is less reproducible than physics and mechanic engineering”, in order to overcome the disagreements and to find common grounds, we s till 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.