Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view

Duffy, Stephen W.; Nagtegaal, Irıs D.; Astley, Susan M.; Gillan, Maureen Gc; McGee, Magnus A.; Boggis, Caroline; Wilson, Mary; Beetles, Ursula; Griffiths, Miriam A.; Jain, Anil K.; Johnson, Jill; Roberts, Rita M.; Deans, Heather; Duncan, Karen A.; Iyengar, Geeta S.; Griffiths, Pamela M.; Warwick, Jane; Cuzick, Jack; Gilbert, Fiona J.

doi:10.1186/bcr2123

Cited by 46 publications

(32 citation statements)

References 16 publications

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“…However, the evaluation of a larger set of images is required; previous research has demonstrated the ability of visual and computer-assisted density assessment to predict later cancers in more extensive data sets. 167,204 Longitudinal assessment (such as that employed by Kerlikowske et al, 205 but using continuous objective density assessment) may also be important.…”

Section: Discussionmentioning

confidence: 99%

“…166 In the UK, the use of BI-RADS is not common, and other techniques such as estimation of percentage density using a VAS have been successfully related to risk of cancer. 167 Subjective visual estimates of MD and thresholding methods suffer from the limitation that the assessment is in two dimensions, as the mammogram is a projection image of the three-dimensional structure of the breast. The same volume of dense tissue could, therefore, give rise to different density estimates, depending on compression and imaging.…”

Section: Mammographic Densitymentioning

confidence: 99%

“…Assessment using VASs had previously been employed by mammographic film readers in Manchester in CADET (Computer-Aided Detection Evaluation Trial), 191 and a significant association with cancer risk was found. 167 Cumulus thresholding has been widely used in research studies and the relationship with risk of developing cancer is well established. 26,87 However, the research that underpins these relationships was based on analysis of film mammograms, and the NHSBSP was in the process of a transition to FFDM at the time the PROCAS study commenced.…”

Section: Measurement Of Mammographic Density In Procasmentioning

confidence: 99%

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Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Evans

Astley

Stavrinos³

et al. 2016

Programme Grants Appl Res

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112

126

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BackgroundIn the UK, women are invited for 3-yearly mammography screening, through the NHS Breast Screening Programme (NHSBSP), from the ages of 47–50 years to the ages of 69–73 years. Women with family histories of breast cancer can, from the age of 40 years, obtain enhanced surveillance and, in exceptionally high-risk cases, magnetic resonance imaging. However, no NHSBSP risk assessment is undertaken. Risk prediction models are able to categorise women by risk using known risk factors, although accurate individual risk prediction remains elusive. The identification of mammographic breast density (MD) and common genetic risk variants [single nucleotide polymorphisms (SNPs)] has presaged the improved precision of risk models.ObjectivesTo (1) identify the best performing model to assess breast cancer risk in family history clinic (FHC) and population settings; (2) use information from MD/SNPs to improve risk prediction; (3) assess the acceptability and feasibility of offering risk assessment in the NHSBSP; and (4) identify the incremental costs and benefits of risk stratified screening in a preliminary cost-effectiveness analysis.DesignTwo cohort studies assessing breast cancer incidence.SettingHigh-risk FHC and the NHSBSP Greater Manchester, UK.ParticipantsA total of 10,000 women aged 20–79 years [Family History Risk Study (FH-Risk); UK Clinical Research Network identification number (UKCRN-ID) 8611] and 53,000 women from the NHSBSP [aged 46–73 years; Predicting the Risk of Cancer At Screening (PROCAS) study; UKCRN-ID 8080].InterventionsQuestionnaires collected standard risk information, and mammograms were assessed for breast density by a number of techniques. All FH-Risk and 10,000 PROCAS participants participated in deoxyribonucleic acid (DNA) studies. The risk prediction models Manual method, Tyrer–Cuzick (TC), BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) and Gail were used to assess risk, with modelling based on MD and SNPs. A preliminary model-based cost-effectiveness analysis of risk stratified screening was conducted.Main outcome measuresBreast cancer incidence.Data sourcesThe NHSBSP; cancer registration.ResultsA total of 446 women developed incident breast cancers in FH-Risk in 97,958 years of follow-up. All risk models accurately stratified women into risk categories. TC had better risk precision than Gail, and BOADICEA accurately predicted risk in the 6268 single probands. The Manual model was also accurate in the whole cohort. In PROCAS, TC had better risk precision than Gail [area under the curve (AUC) 0.58 vs. 0.54], identifying 547 prospective breast cancers. The addition of SNPs in the FH-Risk case–control study improved risk precision but was not useful inBRCA1(breast cancer 1 gene) families. Risk modelling of SNPs in PROCAS showed an incremental improvement from using SNP18 used in PROCAS to SNP67. MD measured by visual assessment score provided better risk stratification than automatic measures, despite wide intra- and inter-reader variability. Using a MD-adjusted TC model in PROCAS improved risk stratification (AUC = 0.6) and identified significantly higher rates (4.7 per 10,000 vs. 1.3 per 10,000;p < 0.001) of high-stage cancers in women with above-average breast cancer risks. It is not possible to provide estimates of the incremental costs and benefits of risk stratified screening because of lack of data inputs for key parameters in the model-based cost-effectiveness analysis.ConclusionsRisk precision can be improved by using DNA and MD, and can potentially be used to stratify NHSBSP screening. It may also identify those at greater risk of high-stage cancers for enhanced screening. The cost-effectiveness of risk stratified screening is currently associated with extensive uncertainty. Additional research is needed to identify data needed for key inputs into model-based cost-effectiveness analyses to identify the impact on health-care resource use and patient benefits.Future workA pilot of real-time NHSBSP risk prediction to identify women for chemoprevention and enhanced screening is required.FundingThe National Institute for Health Research Programme Grants for Applied Research programme. The DNA saliva collection for SNP analysis for PROCAS was funded by the Genesis Breast Cancer Prevention Appeal.

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Section: Discussionmentioning

confidence: 99%

Section: Mammographic Densitymentioning

confidence: 99%

Section: Measurement Of Mammographic Density In Procasmentioning

confidence: 99%

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Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Evans

Astley

Stavrinos³

et al. 2016

Programme Grants Appl Res

Self Cite

112

126

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“…Here overall density score was taken to be the average. The radiologists at our center were trained in this method during the CADET-1 trial (22) and their performance was shown to be comparable with interactive thresholding software (Cumulus), with regard to predicting breast cancer risk when the assessment was based on both the mediolateral and craniocaudal views (23), and the process incorporated into usual practice.…”

Section: Assessment Of Mammographic Densitymentioning

confidence: 99%

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

Evans

Warwick

Astley

et al. 2012

Cancer Prevention Research

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107

121

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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);

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“…4 Dense breast tissue has been shown to offer more opportunities for breast cancer to develop, especially in younger women. 3,[6][7][8] Additionally, there is a genetic predisposition to breast density, 9,10 and other established risk factors for breast cancer such as hormonal agents, 11,12 lifestyle, and reproductive characteristics are associated with high breast density. [13][14][15][16] Importantly, breast density is a potentially modifiable risk factor for breast cancer, 17,18 and lower density has been shown to be a prognostic factor for the effect of interventions on breast cancer risk.…”

Section: Introductionmentioning

confidence: 99%

Breast composition: Measurement and clinical use

Ekpo¹,

Hogg²,

Highnam³

et al. 2015

Radiography

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Breast density is a measure of the extent of radiodense fibroglandular tissue in the breast. The risk of developing breast cancer and the risk of missing cancer at screening rise with higher breast density. In this paper, the historical background to breast density measurement is outlined and current evidence based practice is explained. The relevance of breast density knowledge to mammographic practice and image interpretation is considered in the light of clinical assessment and notification of mammographic breast density (MBD). The current work also discusses risk stratification for decisionmaking regarding screening frequency and better modalities for earlier detection of breast cancer in the dense breast. Automated volumetric approaches are explained while ultrasound, digital breast tomosynthesis, molecular breast imaging, and magnetic resonance imaging are introduced as valuable adjuncts to digital mammography for imaging the dense breast. The work concludes on the important note that screened women should be notified of their breast density, and such notification should be accompanied with clear and adequate information about breast density and cancer risk, strategies associated with lower MBD, as well as best screening intervals and pathways for women with dense breasts. Adoption of these strategies may be crucial to early detection and treatment of cancer and improving survival from the disease.

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Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view

Abstract: Introduction Mammographic density is known to be a strong risk factor for breast cancer. A particularly strong association with risk has been observed when density is measured using interactive threshold software. This, however, is a labourintensive process for large-scale studies.

Cited by 46 publications

References 16 publications

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

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

Breast composition: Measurement and clinical use

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