Assessing Individual Breast Cancer Risk within the U.K. National Health Service Breast Screening Program: A New Paradigm for Cancer Prevention

The aim of this study is to determine breast cancer risk at mammographic screening episodes and integrate standard risk factors with mammographic density and genetic data to assess changing the screening interval based on risk and offer women at high risk preventive strategies. We report our experience of assessing breast cancer risk within the U.K. National Health Service Breast Screening Program using results from the first 10,000 women entered into the "Predicting Risk Of breast Cancer At Screening" study. Of the first 28,849 women attending for screening at fifteen sites in Manchester 10,000 (35%) consented to study entry and completed the questionnaire. The median 10-year Tyrer–Cuzick breast cancer risk was 2.65% (interquartile range, 2.10–3.45). A total of 107 women (1.07%) had 10-year risks 8% or higher (high breast cancer risk), with a further 8.20% having moderately increased risk (5%–8%). Mammographic density (percent dense area) was 60% or more in 8.3% of women. We collected saliva samples from 478 women for genetic analysis and will extend this to 18% of participants. At time of consent to the study, 95.0% of women indicated they wished to know their risk. Women with a 10-year risk of 8% or more or 5% to 8% and mammographic density of 60% or higher were invited to attend or be telephoned to receive risk counseling; 81.9% of those wishing to know their risk have received risk counseling and 85.7% of these were found to be eligible for a risk-reducing intervention. These results confirm the feasibility of determining breast cancer risk and acting on the information in the context of population-based mammographic screening. Cancer Prev Res; 5(7); 943–51. ©2012 AACR.

[1]  S. Moss,et al.  Interval cancers in the NHS breast cancer screening programme in England, Wales and Northern Ireland , 2011, British Journal of Cancer.

[2]  R. Wilkins Polygenes, risk prediction, and targeted prevention of breast cancer. , 2008, The New England journal of medicine.

[3]  D. Evans,et al.  Assessing women at high risk of breast cancer: a review of risk assessment models. , 2010, Journal of the National Cancer Institute.

[4]  D. Gudbjartsson,et al.  Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor–positive breast cancer , 2007, Nature Genetics.

[5]  M. Gail,et al.  Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. , 1989, Journal of the National Cancer Institute.

[6]  A. Gatrell,et al.  Uptake of screening for breast cancer in south Lancashire. , 1998, Public health.

[7]  S. Cummings,et al.  Critical assessment of new risk factors for breast cancer: considerations for development of an improved risk prediction model. , 2007, Endocrine-related cancer.

[8]  J Benichou,et al.  Validation studies for models projecting the risk of invasive and total breast cancer incidence. , 1999, Journal of the National Cancer Institute.

[9]  S. Astley,et al.  Increasing participant recruitment into large-scale screening trials: experience from the CADET II study , 2009, Journal of medical screening.

[10]  K. Heusinger,et al.  Breast cancer risk assessment in a mammography screening program and participation in the IBIS-II chemoprevention trial , 2010, Breast Cancer Research and Treatment.

[11]  S. Ciatto,et al.  Breast density as a determinant of interval cancer at mammographic screening , 2004, British Journal of Cancer.

[12]  Lester L. Peters,et al.  Genome-wide association study identifies novel breast cancer susceptibility loci , 2007, Nature.

[13]  J. Haines,et al.  Genome-wide association study identifies a novel breast cancer susceptibility locus at 6q25.1 , 2009, Nature Genetics.

[14]  Karla Kerlikowske,et al.  Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model , 2008, Annals of Internal Medicine.

[15]  C. Hudis,et al.  Discriminatory accuracy and potential clinical utility of genomic profiling for breast cancer risk in BRCA-negative women , 2011, Breast Cancer Research and Treatment.

[16]  J. Wardle,et al.  Socioeconomic variation in participation in colorectal cancer screening , 2002, Journal of medical screening.

[17]  Deborah Hughes,et al.  Genome-wide association study identifies five new breast cancer susceptibility loci , 2010, Nature Genetics.

[18]  A. Evans,et al.  NHSBSP type 1 interval cancers: a scientifically valid grouping? , 2007, Clinical radiology.

[19]  Jinbo Chen,et al.  Projecting absolute invasive breast cancer risk in white women with a model that includes mammographic density. , 2006, Journal of the National Cancer Institute.

[20]  A Howell,et al.  Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme , 2003, Journal of medical genetics.

[21]  Mary Wilson,et al.  Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view , 2008, Breast Cancer Research.

[22]  A. Jemal,et al.  Global cancer statistics , 2011, CA: a cancer journal for clinicians.

[23]  Karla Kerlikowske,et al.  Prospective breast cancer risk prediction model for women undergoing screening mammography. , 2006, Journal of the National Cancer Institute.

[24]  S G Thompson,et al.  Screening for abdominal aortic aneurysms: the effects of age and social deprivation on screening uptake, prevalence and attendance at follow-up in the MASS trial. , 2004, Journal of medical screening.

[25]  David A. Hinds,et al.  Assessment of Clinical Validity of a Breast Cancer Risk Model Combining Genetic and Clinical Information , 2010, Journal of the National Cancer Institute.

[26]  David Tritchler,et al.  Heritability of mammographic density, a risk factor for breast cancer. , 2002, The New England journal of medicine.

[27]  P. Boyle,et al.  Screening Uptake in a Well-Established Diabetic Retinopathy Screening Program , 2008, Diabetes Care.

[28]  J. Ferlay,et al.  Global Cancer Statistics, 2002 , 2005, CA: a cancer journal for clinicians.

[29]  Susan M Astley,et al.  Single reading with computer-aided detection and double reading of screening mammograms in the United Kingdom National Breast Screening Program. , 2006, Radiology.

[30]  Mammographic screening in women with a family history of breast cancer: some results from the Swedish two-county trial. , 2000, Revue d'epidemiologie et de sante publique.

[31]  M. Parmar,et al.  Recruitment to multicentre trials—lessons from UKCTOCS: descriptive study , 2008, BMJ : British Medical Journal.

[32]  A. Jemal,et al.  Global Cancer Statistics , 2011 .

[33]  J. Pankow,et al.  Genetic analysis of mammographic breast density in adult women: evidence of a gene effect. , 1997, Journal of the National Cancer Institute.

[34]  P. Porter,et al.  Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. , 2000, Journal of the National Cancer Institute.

[35]  M. Gail Value of adding single-nucleotide polymorphism genotypes to a breast cancer risk model. , 2009, Journal of the National Cancer Institute.

[36]  W. Willett,et al.  A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer , 2007, Nature Genetics.

[37]  Stephen W Duffy,et al.  A breast cancer prediction model incorporating familial and personal risk factors , 2004, Hereditary Cancer in Clinical Practice.