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To model a personalised screening strategy for breast and prostate cancer based on genetic risk and age, and compare it with a screening strategy based on age alone.

The researchers compared screening approaches based on age (all men aged 47–79 offered prostate cancer screening; all women aged 47–79 offered breast cancer screening) with novel personalised screening approaches based on both age and genetic risk profiles. The number of people eligible to receive screening and the expected number of cancer cases that would be detected for each case were considered.

Under the personalized screening strategy, 16% fewer men would be eligible for prostate cancer screening and 3% fewer cases would be detected, though there would be an increase in cases detected in younger men (<55yrs). Similarly, the personalised strategy would result in 24% fewer women being eligible for breast cancer screening and 14% fewer cases would be detected.

Personalized screening strategies based on age and genetic risk would potentially improve efficiency, substantially reducing the number of people receiving screening with only a small decrease in the overall number of cancer cases detected. Detection of the more aggressive prostate cancers in younger men would improve. Besides being more cost-effective, reducing the number of people screened using this approach would also reduce the harms associated with screening, such as false-positive results, overdiagnosis and unnecessary treatment.

Despite limitations such as the necessity to make certain assumptions in modeling the available data, this study shows that it is feasible to use genetic information (in the form of polygenic risk profiles) to improve screening of the general population for cancer. It would be interesting to see the effect of including other factors in risk estimates, such as lifestyle factors, mammographic data and new genetic markers. Policies are unlikely to change overnight to embrace personalised screening; in addition to further research, many ethical, legal and social issues related to genetic testing and risk prediction would require careful consideration. Nevertheless, this work may be laying the foundations for future use of genetic information to improve cancer detection and survival.