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INTRODUCTION

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A primary goal of health care is to prevent disease or detect it early enough that intervention will be more effective. Tremendous progress has been made toward this goal over the last 50 years. Screening tests are available for many common diseases and encompass biochemical (e.g., cholesterol, glucose), physiologic (e.g., blood pressure, growth curves), radiologic (e.g., mammogram, bone densitometry), and cytologic (e.g., Pap smear) approaches. Effective preventive interventions have resulted in dramatic declines in mortality from many diseases, particularly infections. Preventive interventions include counseling about risk behaviors, vaccinations, medications, and, in some relatively uncommon settings, surgery. Preventive services (including screening tests, preventive interventions, and counseling) are different than other medical interventions because they are proactively administered to healthy individuals instead of in response to a symptom, sign, or diagnosis. Thus, the decision to recommend a screening test or preventive intervention requires a particularly high bar of evidence that testing and intervention are both practical and effective.

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Image not available. Because population-based screening and prevention strategies must be extremely low risk to have an acceptable benefit-to-harm ratio, the ability to target individuals who are more likely to develop disease could enable the application of a wider set of potential approaches and increase efficiency. Currently, there are many types of data that can predict disease incidence in an asymptomatic individual. Genomic data have received the most attention to date, at least in part because mutations in high-penetrance genes have clear implications for preventive care (Chap. 84). Women with mutations in either BRCA1 or BRCA2, the two major breast cancer susceptibility genes identified to date, have a markedly increased risk (5- to 20-fold) of breast and ovarian cancer. Screening and prevention recommendations include prophylactic oophorectomy and breast magnetic resonance imaging (MRI), both of which are considered to incur too much harm for women at average cancer risk. Some women opt for prophylactic mastectomy to dramatically reduce their breast cancer risk. Although the proportion of common disease explained by high-penetrance genes appears to be relatively small (5–10% of most diseases), mutations in rare, moderate-penetrance genes, and variants in low-penetrance genes, also contribute to the prediction of disease risk. The advent of affordable whole exome/whole genome sequencing is likely to speed the dissemination of these tests into clinical practice and may transform the delivery of preventive care.

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Other forms of “omic” data also have the potential to provide important predictive information, including proteomics and metabolomics. These fields are earlier in development and have yet to move into clinical practice. Imaging and other clinical data may also be integrated into a risk-stratified paradigm as evidence grows about the predictive ability of these data and the feasibility of their collection. Of course, all of these data may also be helpful in predicting the risk of harms from screening or prevention, such as the risk of a false-positive mammogram. To the degree that this information can be incorporated into personalized screening and prevention ...

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