Dataset Information

Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

ABSTRACT: The proliferation of gene panel testing precipitates the need for a breast cancer (BC) risk model that incorporates the effects of mutations in several genes and family history (FH). We extended the BOADICEA model to incorporate the effects of truncating variants in PALB2, CHEK2, and ATM.The BC incidence was modeled via the explicit effects of truncating variants in BRCA1/2, PALB2, CHEK2, and ATM and other unobserved genetic effects using segregation analysis methods.The predicted average BC risk by age 80 for an ATM mutation carrier is 28%, 30% for CHEK2, 50% for PALB2, and 74% for BRCA1 and BRCA2. However, the BC risks are predicted to increase with FH burden. In families with mutations, predicted risks for mutation-negative members depend on both FH and the specific mutation. The reduction in BC risk after negative predictive testing is greatest when a BRCA1 mutation is identified in the family, but for women whose relatives carry a CHEK2 or ATM mutation, the risks decrease slightly.The model may be a valuable tool for counseling women who have undergone gene panel testing for providing consistent risks and harmonizing their clinical management. A Web application can be used to obtain BC risks in clinical practice (http://ccge.medschl.cam.ac.uk/boadicea/).Genet Med 18 12, 1190-1198.

SUBMITTER: Lee AJ

PROVIDER: S-EPMC5086091 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

Lee Andrew J AJ Cunningham Alex P AP Tischkowitz Marc M Simard Jacques J Pharoah Paul D PD Easton Douglas F DF Antoniou Antonis C AC

Genetics in medicine : official journal of the American College of Medical Genetics 20160414 12

<h4>Purpose</h4>The proliferation of gene panel testing precipitates the need for a breast cancer (BC) risk model that incorporates the effects of mutations in several genes and family history (FH). We extended the BOADICEA model to incorporate the effects of truncating variants in PALB2, CHEK2, and ATM.<h4>Methods</h4>The BC incidence was modeled via the explicit effects of truncating variants in BRCA1/2, PALB2, CHEK2, and ATM and other unobserved genetic effects using segregation analysis meth ...[more]

PMID: 27464310

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Project description:ImportanceScreening mammography and magnetic resonance imaging (MRI) are recommended for women with ATM, CHEK2, and PALB2 pathogenic variants. However, there are few data to guide screening regimens for these women.ObjectiveTo estimate the benefits and harms of breast cancer screening strategies using mammography and MRI at various start ages for women with ATM, CHEK2, and PALB2 pathogenic variants.Design, setting, and participantsThis comparative modeling analysis used 2 established breast cancer microsimulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate different screening strategies. Age-specific breast cancer risks were estimated using aggregated data from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium for 32 247 cases and 32 544 controls in 12 population-based studies. Data on screening performance for mammography and MRI were estimated from published literature. The models simulated US women with ATM, CHEK2, or PALB2 pathogenic variants born in 1985.InterventionsScreening strategies with combinations of annual mammography alone and with MRI starting at age 25, 30, 35, or 40 years until age 74 years.Main outcomes and measuresEstimated lifetime breast cancer mortality reduction, life-years gained, breast cancer deaths averted, total screening examinations, false-positive screenings, and benign biopsies per 1000 women screened. Results are reported as model mean values and ranges.ResultsThe mean model-estimated lifetime breast cancer risk was 20.9% (18.1%-23.7%) for women with ATM pathogenic variants, 27.6% (23.4%-31.7%) for women with CHEK2 pathogenic variants, and 39.5% (35.6%-43.3%) for women with PALB2 pathogenic variants. Across pathogenic variants, annual mammography alone from 40 to 74 years was estimated to reduce breast cancer mortality by 36.4% (34.6%-38.2%) to 38.5% (37.8%-39.2%) compared with no screening. Screening with annual MRI starting at 35 years followed by annual mammography and MRI at 40 years was estimated to reduce breast cancer mortality by 54.4% (54.2%-54.7%) to 57.6% (57.2%-58.0%), with 4661 (4635-4688) to 5001 (4979-5023) false-positive screenings and 1280 (1272-1287) to 1368 (1362-1374) benign biopsies per 1000 women. Annual MRI starting at 30 years followed by mammography and MRI at 40 years was estimated to reduce mortality by 55.4% (55.3%-55.4%) to 59.5% (58.5%-60.4%), with 5075 (5057-5093) to 5415 (5393-5437) false-positive screenings and 1439 (1429-1449) to 1528 (1517-1538) benign biopsies per 1000 women. When starting MRI at 30 years, initiating annual mammography starting at 30 vs 40 years did not meaningfully reduce mean mortality rates (0.1% [0.1%-0.2%] to 0.3% [0.2%-0.3%]) but was estimated to add 649 (602-695) to 650 (603-696) false-positive screenings and 58 (41-76) to 59 (41-76) benign biopsies per 1000 women.Conclusions and relevanceThis analysis suggests that annual MRI screening starting at 30 to 35 years followed by annual MRI and mammography at 40 years may reduce breast cancer mortality by more than 50% for women with ATM, CHEK2, and PALB2 pathogenic variants. In the setting of MRI screening, mammography prior to 40 years may offer little additional benefit.

Dataset Information

Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

Publications

Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

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