Abstract
PurposeBreast cancer risk has conventionally been assessed using family history (FH) and rare high/moderate penetrance pathogenic variants (PVs), notably in BRCA1/2, and more recently PALB2, CHEK2, and ATM. In addition to these PVs, it is now possible to use increasingly predictive polygenic risk scores (PRS) as well. The comparative population-level predictive capability of these three different indicators of genetic risk for risk stratification is, however, unknown. MethodsThe Canadian heritable breast cancer risk distribution was estimated using a novel genetic mixing model (GMM). A realistically representative sample of women was synthesized based on empirically observed demographic patterns for appropriately correlated family history, inheritance of rare PVs, PRS, and residual risk from an unknown polygenotype. Risk assessment was simulated using the BOADICEA risk algorithm for 10-year absolute breast cancer incidence, and compared to heritable risks as if the overall polygene, including its measured PRS component, and PV risks were fully known. ResultsGenerally, the PRS was most predictive for identifying women at high risk, while family history was the weakest. Only the PRS identified any women at low risk of breast cancer. ConclusionPRS information would be the most important advance in enabling effective risk stratification for population-wide breast cancer screening.
Highlights
Risks of breast cancer (BC), are known to be influenced by genetic susceptibility, with three general sources of information for assessing this susceptibility: (1) family history (FH); (2) high-risk but rather uncommon deleterious variants in several susceptibility genes, such as BRCA1 and BRCA2; and most recently (3) common susceptibility variants, which can be efficiently combined into a polygenic risk score (PRS)
Considerable debate remains whether the net benefits of such changes to BC screening programs would be worthwhile in terms of earlier BC detection, false positives, overdiagnosis, costs, feasibility, and acceptability, though recent studies do suggest that tailoring BC screening programs to individual risks would likely be cost-effective compared to current “one size fits all” ageonly based screening programs [3, 4]
We examine which genetic information from amongst FH, pathogenic variants (PVs), and PRS would be most important for assessing a woman’s BC risk at the level of detail usable by BOADICEA, including the possibility of very detailed FH information for all first- and second-degree relatives, for BC, and for prostate, ovarian, and pancreatic cancer, as these are informative for BC risk and can be taken into account by BOADICEA [9]
Summary
Risks of breast cancer (BC), are known to be influenced by genetic susceptibility, with three general sources of information for assessing this susceptibility: (1) family history (FH); (2) high-risk but rather uncommon deleterious variants in several susceptibility genes, such as BRCA1 and BRCA2 (pathogenic variants, PVs); and most recently (3) common susceptibility variants, which can be efficiently combined into a polygenic risk score (PRS). Considerable debate remains whether the net benefits of such changes to BC screening programs would be worthwhile in terms of earlier BC detection, false positives, overdiagnosis, costs, feasibility, and acceptability, though recent studies do suggest that tailoring BC screening programs to individual risks would likely be cost-effective compared to current “one size fits all” ageonly based screening programs [3, 4] Central to such a costeffectiveness assessment is (1) the comparative value of FH, PV, and PRS for risk prediction, which in turn requires (2) valid estimates of the joint distribution of these risk factors in the population. It is these latter two questions that are the focus of this paper
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