domingo, 3 de mayo de 2015

JAMA Network | JAMA | The Precision Medicine Initiative:  A New National Effort


JAMA Network | JAMA | The Precision Medicine Initiative:  A New National Effort

The Precision Medicine InitiativeA New National Effort FREE ONLINE FIRST

Euan A. Ashley, MRCP, DPhil1
JAMA. Published online April 30, 2015. doi:10.1001/jama.2015.3595
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The recent announcement by President Obama of a precision medicine initiative created excitement in the medical community. The president referred not to personalized medicine but to “precision medicine,” a term given profile by a recent publication from the National Research Council,1 in which the authors explain that their use of “precision” was intended to avoid the implication that medications would be synthesized personally for single patients. Rather, they hoped to convey a broader concept that would include precisely tailoring therapies to subcategories of disease, often defined by genomics.
In one sense, medicine has always been personalized (if not always as precise as physicians and patients would like). Clinicians integrate signs and symptoms, evidence, their experience, and patient preference to facilitate decision making. What is new is that biomedical technology now allows a deeper understanding of many diseases. Drug development costs have increased sharply, leading pharmaceutical companies to focus on rarer diseases. In parallel, the significant decrease in the cost of genome sequencing has facilitated the discovery of many new, rare genetic diseases. Together, these advances have provided the necessary and sufficient conditions for the new model of precision medicine.
The need for such a change has been apparent for some time. While groupwise statistical comparison of outcomes in randomized clinical trials provides the rationale for US Food and Drug Administration (FDA) approval of many medications, when those same data are analyzed to reveal the proportion who actually responded to the drug, it is often found that a minority of study participants drive the cohort effect.2 The number needed to treat in many trials is greater than 10, suggesting that at least 10 patients need to be treated for 1 to benefit. In screening and prevention studies the corresponding numbers are often vastly higher. This suggests considerable health benefits and cost savings might be accrued from more effective selection of individuals based on a priori potential for drug response or baseline disease risk.


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