Abstract
Exciting discoveries in genetics and genomics continue to translate into novel predictions of disease susceptibility and increasing use of targeted therapeutics. BRCA1 and BRCA2 gene testing provide timely opportunities for breast and ovarian cancer prevention strategies [1]. CYP1A1 gene testing to assess favorable therapeutic response to imatinib, a targeted therapy for chronic myelogenous leukemia, is improving survival rates [2]. The cost–effectiveness of KRAS gene testing for colorectal cancer has been demonstrated [3]. Our own research with the Coriell Personalized Medicine Collaborative (CPMC) has shown genetic information to be a motivating factor for positive health behavior change in melanoma prevention [4] and coronary artery disease prevention [ Scheinfeldt LB, Schmidlen TJ, Gharani N et al. Unpublished Data ], identified genes associated with sleep duration [5], and generated new models for genomic counseling and education [6,7]. Pharmacogenomics (PGx) to predict and optimize therapeutic response and reduce risk of adverse events is rarely utilized in the clinic despite that as of May 2015, 137 US FDA-approved drugs have PGx information in their labeling [8]. The opportunity to practice meaningful patientcentric care is here; seizing that opportunity could mean easing the chronic disease burden consuming 86% of our nation’s healthcare resources [9]. Genetic testing is a central element of precision medicine. The myriad challenges in moving diagnostics from development to clinical application are many and complex. Physician adoption is one such challenge, frequently highlighted by the startling finding that intervention discovery to utilization takes on average 17 years [10]. It is hardly surprising that genetic testing is experiencing a similar adoption timeline. Acronyms such as genome-wide association studies (GWAS), variant call format (VCF) file and SNP, terms such as haplotype and amplification or the prospect of deciphering analytic algorithms are unlikely to motivate physicians. Moreover, the range of testing available, the steady entrance of new tests and controversies such as FDA warning letters and the use of secondary findings complicate this nascent field of medicine. Do physicians perceive the adoption learning curve for genetic testing to be overwhelming? Learning curves demonstrate performance as a function of volume of training. The upward trajectory of ‘learning’ along the vertical axis before it curves right and plateaus across the horizontal axis of ‘experience’ represents the speed at which the knowledge is acquired and not ‘difficulty’ of knowledge as often supposed. In short, a steep learning curve exhibits one’s rapid movement from low to high performance. Our genetic testing learning curve is composed of six practical learning points to acquire a working knowledge of genetic testing. It begins simply: what is genetic testing? No need for a deep dive in molecular biology; physicians should understand that genetic testing is the analysis of human DNA, RNA Encouraging physician adoption of genetic testing for precision medicine
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