2013
DOI: 10.1038/gim.2012.167
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Incorporating genomics into breast and prostate cancer screening: assessing the implications

Abstract: Individual risk prediction and stratification based on polygenic profiling may be useful in disease prevention. Risk-stratified population screening based on multiple factors including a polygenic risk profile has the potential to be more efficient than age-stratified screening. In this article, we summarize the implications of personalized screening for breast and prostate cancers. We report the opinions of multidisciplinary international experts who have explored the scientific, ethical, and logistical aspec… Show more

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Cited by 85 publications
(111 citation statements)
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“…Genetic testing for cancer susceptibility may have utility for risk stratification, thereby allowing for a more focused application of screening tests to those at greatest disease risk. [13][14][15][16] For example, estimating an individual's cancer risk based on genetic markers and traditional risk factors may lead to a more refined use of currently recommended screening tests (e.g., mammography). 17,18 Information derived from genetic testing could also shift the balance of harms and benefits for some individuals such that screening tests like the PSA test, which is not recommended for the general population, may have utility in those with greatest genetic risk for prostate cancer.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Genetic testing for cancer susceptibility may have utility for risk stratification, thereby allowing for a more focused application of screening tests to those at greatest disease risk. [13][14][15][16] For example, estimating an individual's cancer risk based on genetic markers and traditional risk factors may lead to a more refined use of currently recommended screening tests (e.g., mammography). 17,18 Information derived from genetic testing could also shift the balance of harms and benefits for some individuals such that screening tests like the PSA test, which is not recommended for the general population, may have utility in those with greatest genetic risk for prostate cancer.…”
Section: Introductionmentioning
confidence: 99%
“…We limited the review to genetic testing related to breast, colorectal, and prostate cancer because these represent cancers of high incidence and mortality, 27 and for which genetic information may be particularly useful in risk-stratification decisions for the frequency and/or modality of screening tests. [13][14][15]28 …”
Section: Introductionmentioning
confidence: 99%
“…Risk prediction allows classification of individuals into risk groups (e.g., high risk, intermediate risk), leading to the potential for discrimination of individuals in such groups, and possibly also for their biological family members [13]. For instance, insurance companies could use results on cancer risk as a basis for setting higher premiums [13].…”
Section: Legal Regulatory and Policy Framework Shouldmentioning
confidence: 99%
“…Risk prediction allows classification of individuals into risk groups (e.g., high risk, intermediate risk), leading to the potential for discrimination of individuals in such groups, and possibly also for their biological family members [13]. For instance, insurance companies could use results on cancer risk as a basis for setting higher premiums [13]. Having anti-discrimination legislation in place, or other means of adequate protection (e.g., restricting access and use of results by insurers [14,15]), can help protect individuals [16].…”
Section: Legal Regulatory and Policy Framework Shouldmentioning
confidence: 99%
“…Concerning secondary prevention, there may be scope to refine existing screening programmes by the incorporation of genomic information, though so far success in the search for effective strategies using polygenic inheritance data has been limited [10]. Evans and colleagues have recently proposed, however, some ways in which the potential of PHG might be realized [17].…”
Section: The Potential For Genomics In Improving Population Healthmentioning
confidence: 99%