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Background High mammographic density is associated with both risk of cancers being missed at mammography, and increased risk of developing breast cancer. Stratification of breast cancer prevention and screening requires mammographic density measures predictive of cancer. This study compares five mammographic density measures to determine the association with subsequent diagnosis of breast cancer and the presence of breast cancer at screening. Methods Women participating in the “Predicting Risk Of Cancer At Screening” (PROCAS) study, a study of cancer risk, completed questionnaires to provide personal information to enable computation of the Tyrer-Cuzick risk score. Mammographic density was assessed by visual analogue scale (VAS), thresholding (Cumulus) and fully-automated methods (Densitas, Quantra, Volpara) in contralateral breasts of 366 women with unilateral breast cancer (cases) detected at screening on entry to the study (Cumulus 311/366) and in 338 women with cancer detected subsequently. Three controls per case were matched using age, body mass index category, hormone replacement therapy use and menopausal status. Odds ratios (OR) between the highest and lowest quintile, based on the density distribution in controls, for each density measure were estimated by conditional logistic regression, adjusting for classic risk factors. Results The strongest predictor of screen-detected cancer at study entry was VAS, OR 4.37 (95% CI 2.72–7.03) in the highest vs lowest quintile of percent density after adjustment for classical risk factors. Volpara, Densitas and Cumulus gave ORs for the highest vs lowest quintile of 2.42 (95% CI 1.56–3.78), 2.17 (95% CI 1.41–3.33) and 2.12 (95% CI 1.30–3.45), respectively. Quantra was not significantly associated with breast cancer (OR 1.02, 95% CI 0.67–1.54). Similar results were found for subsequent cancers, with ORs of 4.48 (95% CI 2.79–7.18), 2.87 (95% CI 1.77–4.64) and 2.34 (95% CI 1.50–3.68) in highest vs lowest quintiles of VAS, Volpara and Densitas, respectively. Quantra gave an OR in the highest vs lowest quintile of 1.32 (95% CI 0.85–2.05). Conclusions Visual density assessment demonstrated a strong relationship with cancer, despite known inter-observer variability; however, it is impractical for population-based screening. Percentage density measured by Volpara and Densitas also had a strong association with breast cancer risk, amongst the automated measures evaluated, providing practical automated methods for risk stratification. Electronic supplementary material The online version of this article (10.1186/s13058-018-0932-z) contains supplementary material, which is available to authorized users.

Purpose To assess whether individual reader performance with digital breast tomosynthesis (DBT) and two-dimensional (2D) mammography varies with number of years of experience or volume of 2D mammograms read. Materials and Methods After written informed consent was obtained, 8869 women (age range, 29–85 years; mean age, 56 years) were recruited into the TOMMY trial (A Comparison of Tomosynthesis with Digital Mammography in the UK National Health Service Breast Screening Program), an ethically approved, multicenter, multireader, retrospective reading study, between July 2011 and March 2013. Each case was read prospectively for clinical assessment and to establish ground truth. A retrospective reading data set of 7060 cases was created and randomly allocated for independent blinded review of (a) 2D mammograms, (b) DBT images and 2D mammograms, and (c) synthetic 2D mammograms and DBT images, without access to previous examinations. Readers (19 radiologists, three advanced practitioner radiographers, and two breast clinicians) who had 3–25 (median, 10) years of experience in the U.K. National Health Service Breast Screening Program and read 5000–13 000 (median, 8000) cases per annum were included in this study. Specificity was analyzed according to reader type and years and volume of experience, and then both specificity and sensitivity were analyzed by matched inference. The median duration of experience (10 years) was used as the cutoff point for comparison of reader performance. Results Specificity improved with the addition of DBT for all readers. This was significant for all staff groups (56% vs 68% and 49% vs 67% [P < .0001] for radiologists and advanced practitioner radiographers, respectively; 46% vs 55% [P = .02] for breast clinicians). Sensitivity was improved for 19 of 24 (79%) readers and was significantly higher for those with less than 10 years of experience (91% vs 86%; P = .03) and those with total mammographic experience of fewer than 80 000 cases (88% vs 86%; P = .03). Conclusion The addition of DBT to conventional 2D screening mammography improved specificity for all readers, but the gain in sensitivity was greater for readers with less than 10 years of experience.

Body: Introduction In the IBIS I Prevention Trial we demonstrated that tamoxifen prevented breast cancer in women with greater than 9 % absolute reduction in visually assessed mammographic density over a 12-18 month period as assessed by an expert radiologist, RW (1). In this study we investigated: whether RW obtained similar results in a different group of women treated with tamoxifen; how other expert mammographic film readers with experience of density assessment (radiologists, advanced practitioner radiographers and a breast physician) estimated mammographic change; how visual change relates to change in automated measures of volumetric density; and whether we can predict change by serum markers or SNPs. Methods 105 women aged 33 to 46 at greater than 1 in 6 lifetime breast cancer risk completed one year’s treatment with tamoxifen. RW assessed mammographic percentage density in increments of 5% for baseline and one year mammograms. Two or three of a pool of eight readers estimated % density using a visual analogue scale (VAS). Percent change was also estimated using a computer-assisted thresholding technique (Cumulus). Change in volume of dense tissue (Quantra™ & Volpara™) was measured. Changes in lipids, IGF1, insulin and relevant SNPs were measured to determine whether they predicted density change. Results. Estimates of change obtained by RW were broadly consistent with those from our previous study, as were those from Cumulus, but could not be replicated using estimates from the pooled results of VAS readers. Tamoxifen was associated with marked reductions of dense volume of the breast (Table 1) However the different methods were at best only moderately correlated with RW (r less than 0.6). Change in serum triglycerides significantly predicted density change as measured by RW but none of the other serum measures or SNPs did. Table 1 Numbers of women and percentage change in density measures after one year of tamoxifen% Density changeRW %changeOther radiologists %changeCumulus %change_____% Dense volume change^Quantra %changeVolpara %change40+001 40+15930+503 30+141020+12013 20+202010+35630 10+17260+498143 0+16190-4188 0-1615Number10510598 9899RW = Ruth Warren. CUMULUS was measured by JS, a trained operator of the software. * Percentage point change eg if density changed from 40% to 30% this was regarded as a 10% change.^ Reduction in dense volume expressed as a percentage of baseline dense volume. We used Quantra version 2.0 and Volpara version 1.4.5 Conclusions Whilst RW remained consistent with previous density estimation it was not possible to use a pool of other expert readers to predict change. Cumulus gave similar results to RW but is difficult to use in practice. There was good agreement between the two objective volumetric measures used (r=0.5) and since these are automated they may be suitable for clinical practice. However their relationship to the long term breast cancer preventative effect of tamoxifen needs to be established. Reference 1 Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case-control study. Cuzick J, Warwick J, Pinney E, Duffy JW, Cawthorn S, Howell A, Forbes JF, Warren RM. J Natl Cancer Inst. 2011 May 4; 103 (9): 744-52. Citation Format: Anthony Howell, Sue Astley, Elaine Harkness, Julia Wiseman, Jill Fox, Paula Stavrinos, Mary Wilson, Yit Lim, Valerie Reece, Ursula Beetles, Anil Jain, Jamie Sergeant, Jack Cuzick, Ruth Warren, Gareth Evans. Predicting the effect of tamoxifen on the breast: Change in measures of breast density, serum markers and SNPs [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P5-12-01.

This study compared mammographic density over time between women who developed breast cancer cases and women who did not controls. Cases had an initial negative mammographic screen and another three years later when cancer was diagnosed. Cases were matched to three controls with two successive negative screens by age, year of mammogram, BMI, parity, menopausal status and HRT use. Mammographic density was measured by VolparaTM. There was a significant reduction in percentage density in the affected breast for cases 5.2 to 4.8i?ź%, pi?ź

This study aimed to determine whether correcting for observer variability alters estimations of breast cancer risk associated with mammographic density. A case control design examined the relationship between mammographic density, measured by visual analogue scales VAS, and the risk of breast cancer after correcting for observer variability. Mammographic density was assessed by two observers and average scores V2 were adjusted to correct for observer variability V2ad. Two case-control sets were identified: i breast cancer detected during screening at entry and ii breast cancer detected subsequently. Cases were matched to three controls. In the first case-control set the odds ratio for breast cancer was 4.6 95i?ź%CI 2.8---7.5 for the highest compared to the lowest quintile of V2, and was attenuated for V2ad OR 3.1, 95i?ź%CI 1.9---4.8. Similar findings were observed for the second case-control set. Not adjusting for observer variability may lead to an overestimate of the risk of breast cancer.

Breast cancer is not only increasing in the west but also particularly rapidly in eastern countries where traditionally the incidence has been low. The rise in incidence is mainly related to changes in reproductive patterns and lifestyle. These trends could potentially be reversed by defining women at greatest risk and offering appropriate preventive measures. A model for this approach was the establishment of Family History Clinics (FHCs), which have resulted in improved survival in younger women at high risk. New predictive models of risk that include reproductive and lifestyle factors, mammographic density and measurement of risk-associated single nucleotide polymorphisms (SNPs) may give more precise information concerning risk and enable better targeting for mammographic screening programmes and of preventive measures. Endocrine prevention using anti-oestrogens and aromatase inhibitors is effective, and observational studies suggest lifestyle modification may also be effective. However, referral to FHCs is opportunistic and predominantly includes younger women. A better approach for identifying older women at risk may be to use national breast screening programmes. Here were described pilot studies to assess whether the routine assessment of breast cancer risk is feasible within a population-based screening programme, whether the feedback and advice on risk-reducing interventions would be welcomed and taken up, and to consider whether the screening interval should be modified according to breast cancer risk.

Background: Currently there are no real attempts internationally to tailor breast screening programmes to individual risk Methods: We have assessed the feasibility of collecting breast cancer risk information during routine mammographic screening in the National Health Service Breast Screening Programme (NHSBSP) in England, in order to consider, ultimately, adapting the screening interval to risk of breast cancer and introducing preventive strategies in women at high risk. The study Predicting Risk Of Cancer At Screening (PROCAS) aims to recruit 60,000 women over 3 years. Results: 26,000 women (June 8th 2011) have so far given consent to join the study. Thirty six percent of the first 20,000 women in nineteen screening sites in Manchester consented to enter the study and completed a risk factor questionnaire. The median 10 year breast cancer risk was 2.65%, with 926 (9.26%) of the first 10,000 women having a 10 year risk of ≥5% and 92 (0.92%) having a 10 year risk of ≥8% (Tyrer-Cuzick), IQR:1.35. 832 (8.32%) women had a mammographic density of 60% or greater (Visual Analogue Scale). We collected saliva samples from 1019 women for genetic analysis and will extend this to 18% of participants. Of those who agreed to participate in the study, 94% indicated that they wished to know their breast cancer risk. Women with a 10-year risk of ≥8%, and women with a 10-year risk of ≥5% and mammographic density ≥60% were invited to attend or be telephoned to be counselled. To date 138 have accepted with 135, so far, having received risk counselling. Nineteen percent of the high-risk women identified subsequently decided to enter a randomised breast cancer prevention study with either a dietary or drug intervention (IBIS2, anastrazole vs placebo). Results from the first 1,000 women who provided DNA samples suggest that the risk information from the 18 validated SNPS may enhance existing risk models. Conclusion: This study demonstrates that it is feasible to determine individual breast cancer risk and offer women appropriate risk-reducing interventions within the context of a population-based mammographic screening programme. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-11-07.

INTRODUCTION: There are widespread moves to develop risk-stratified approaches to population-based breast screening. The public needs to favour receiving breast cancer risk information, which ideally should produce no detrimental effects. This study investigates risk perception, the proportion wishing to know their 10-year risk and whether subsequent screening attendance is affected.METHODS: Fifty thousand women attending the NHS Breast Screening Programme completed a risk assessment questionnaire. Ten-year breast cancer risks were estimated using a validated algorithm (Tyrer-Cuzick) adjusted for visually assessed mammographic density. Women at high risk (⩾8%) and low risk (RESULTS: Of those invited to receive risk feedback, more high-risk women, 500 out of 673 (74.3%), opted to receive a consultation than low-risk women, 106 out of 193 (54.9%) (PCONCLUSIONS: Population-based assessment of breast cancer risk is feasible. The majority of women wished to receive risk information. Perception of general population breast cancer risk is poor. There were no apparent adverse effects on screening attendance for high-risk women whose subsequent screening attendance was increased.

Mammographic density in digital mammograms can be assessed visually or using automated volumetric methods; the aim in both cases is to identify women at greater risk of developing breast cancer, and those for whom mammography is less sensitive. Ideally all methods should identify the same women as having high density, but this is not the case in practice. 6422 women were ranked from the highest to lowest density by three methods: QuantraTM, VolparaTM and visual assessment recorded on Visual Analogue Scales. For each pair of methods the 20 cases with the greatest agreement in rank were compared with the 20 with the least agreement. The presence of microcalcifications, skin folds, suboptimally positioned inframammary folds, and whether or not the nipple was in profile were found to affect agreement between methods (p

High breast density, where there is a relatively large proportion of fibroglandular tissue in the breast, is associated with increased risk of developing cancer. There are several methods of assessing breast density from mammograms, and as these sometimes disagree about whether density is high (or low), we have investigated potential causes of disagreement.

The proportion of radio-opaque fibroglandular tissue in a mammographic image of the breast is a strong and modifiable risk factor for breast cancer. Subjective, area-based estimates made by expert observers provide a simple and efficient way of measuring breast density within a screening programme, but the degree of variability may render the reliable identification of women at increased risk impossible. This study examines the repeatability of visual assessment of percent breast density by expert observers. Five consultant radiologists and two breast physicians, all with at least two years’ experience in mammographic density assessment, were presented with 100 digital mammogram cases for which they had estimated density at least 12 months previously. Estimates of percent density were made for each mammographic view and recorded on a printed visual analogue scale. The level of agreement between the two sets of estimates was assessed graphically using Bland-Altman plots. All but one observer had a mean difference of less than 6 percentage points, while the largest mean difference was 14.66 percentage points. The narrowest 95% limits of agreement for the differences were -11.15 to 17.35 and the widest were -13.95 to 40.43. Coefficients of repeatability ranged from 14.40 to 38.60. Although visual assessment of breast density has been shown to be strongly associated with cancer risk, the lack of agreement shown here between repeat assessments of the same images by the same observers questions the reliability of using visual assessment to identify women at high risk or to detect moderate changes in breast density over time.

Digital Breast Tomosynthesis (DBT) provides three-dimensional images of the breast that enable radiologists to discern whether densities are due to overlapping structures or lesions. To aid assessment of the cost-effectiveness of DBT for screening, we have compared the time taken to interpret DBT images and the corresponding two-dimensional Full Field Digital Mammography (FFDM) images. Four Consultant Radiologists experienced in reading FFDM images (4 years 8 months to 8 years) with training in DBT interpretation but more limited experience (137-407 cases in the past 6 months) were timed reading between 24 and 32 two view FFDM and DBT cases. The images were of women recalled from screening for further assessment and women under surveillance because of a family history of breast cancer. FFDM images were read before DBT, according to local practice. The median time for readers to interpret FFDM images was 17.0 seconds, with an interquartile range of 12.3-23.6 seconds. For DBT, the median time was 66.0 seconds, and the interquartile range was 51.1-80.5 seconds. The difference was statistically significant (p

Currently, breast screening is implemented with X-ray mammography, but new technology such as digital breast tomosynthesis (DBT) may provide significant advantages because it produces three-dimensional breast images with high spatial resolution. To aid assessment of the cost-effectiveness of DBT, we have compared reading times for DBT images and full-field digital mammograms (FFDM) of the same women.

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.

OBJECTIVE:The current recommendation from the UK National Health Service Breast Screening Programme is that digital breast tomosynthesis (DBT) can be used for further assessment of possible screen-detected soft-tissue abnormalities in place of spot compression views and when used should be performed in two projections. The aim of the study was to assess whether two-view DBT is necessary if the abnormality is seen only in one view on initial full-field digital mammography (FFDM).METHODS:617 cases with possible masses, distortions and asymmetrical densities visualized only in one view on screening FFDM were included. All of these females underwent two-view DBT, clinical examination and ultrasound. The FFDM and DBT findings on each view were compared and correlated with the histological diagnosis.RESULTS:586 of 617 cases had normal or benign findings on further assessment, and no additional information was obtained on the other DBT view. There were 31 confirmed cancers. In 26 cases (84%), the cancer was seen on the corresponding DBT view. No cancer was seen on the other DBT view alone. Five cancers (16%) were not seen on either view on DBT owing to technical reasons. No cancers would have been missed if only the corresponding DBT view was performed.CONCLUSION:Two-view DBT may not be necessary when used for further assessment of possible screen-detected soft-tissue abnormalities. Larger studies should be undertaken to investigate this further.ADVANCES IN KNOWLEDGE:One-view DBT may be adequate in assessing soft-tissue abnormalities seen only on one FFDM view.

Computer-aided detection (CAD) systems place prompts in digital images to attract readers' attention to potential malignancies. A reader must then decide whether or not prompted regions correspond to genuine abnormalities and has the option of disregarding falsely prompted regions. In this paper we investigate different readers' performance with CAD in the context of breast screening. In a retrospective study, eight consultant radiologists each read over 1000 screening mammograms comprising normal cases, screen detected cancer cases and cases that were detected as cancers subsequently. We present their results in terms of cancer detection and recall rates, and relate this to their previous experience of film reading. Our results show that the detection of cancers did not differ significantly between readers, although more experienced film readers were less likely to recommend that normal cases should be recalled.

Two-view mammography is known to be more effective than one-view in increasing breast cancer detection and reducing recall rates. In addition, there is evidence that computer aided detection (CAD) systems are able to prompt malignant abnormalities that have been overlooked by a human reader. Using data from the UK NHS Breast Screening Programme (NHSBSP) we compared double reading with single reading using a CAD system, to assess the relationship between CAD and number of views in terms of the sensitivity of the screening regime to cancer detection and the recall rate of normal cases. CAD appeared to contribute to an increased cancer detection rate with single-view mammography without significantly increasing the recall rate. For two-view mammography, there was no significant change in sensitivity using CAD but a significantly higher recall rate. However, single-view mammography was used in incident rounds in which previous mammograms were available whereas two-view mammography was used in the prevalent round where no previous mammograms were available.

The National Health Service Breast Screening Programme is an intensive consumer of radiology time. In principle, screening mammograms must be double read, and this puts considerable strain on human resources. The possibility of using single reading assisted by computer-aided detection rather than double reading is therefore an important research issue. Before expending considerable resources on a prospective randomised trial, we design a retrospective study involving re-reading of previously double-read mammograms (Computer Aided Detection Evaluation Trial). This was an equivalence, powered to assess whether the sensitivity of a single human reader with the R2 system of computer-aided detection was at least no worse than 10% less sensitive than the previous two human readers. Various complications had to be taken account of in the design: • power calculations suggested we needed 15,000 mammograms to give the required number of cancers, but funding was only available to re-read 10,000; • the ethical problem of potential de novo discovery of previously missed cancer; • a limited period of free availability of the R2 system; and • a need to avoid previous readers re-reading the same mammograms. Design strategies to cope with these are described in this poster.

Breast density is an important risk factor for breast cancer. Assessment of density at screening could help identify women at increased risk of cancer, who may benefit from screening with shorter intervals or different modalities. Visual analogue scale (VAS) assessment of percentage density by observers is straightforward to implement and strongly associated with cancer risk. However, using VAS assessment for stratification would require reproducibility between observers. We examine agreement between observers assessing VAS density.

Breast density, measured as the proportion of the breast occupied by fibroglandular tissue in a mammogram, is a strong and modifiable risk factor for breast cancer. Area-based estimates made by expert observers are a practical approach, but are subjective. Here we investigate repeatability of visual assessment of percentage breast density.

Introduction:\ud 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 labour-intensive process for large-scale studies.\ud \ud Methods:\ud Our aim was to determine the performance of visually assessed percent breast density as an indicator of breast cancer risk. We compared the effect on risk of density as measured with the mediolateral oblique view only versus that estimated as the average density from the mediolateral oblique view and the craniocaudal view. Density was assessed using a visual analogue scale in 10,048 screening mammograms, including 311 breast cancer cases diagnosed at that screening episode or within the following 6 years.\ud \ud Results:\ud Where only the mediolateral oblique view was available, there was a modest effect of breast density on risk with an odds ratio for the 76% to 100% density relative to 0% to 25% of 1.51 (95% confidence interval 0.71 to 3.18). When two views were available, there was a considerably stronger association, with the corresponding odds ratio being 6.77 (95% confidence interval 2.75 to 16.67).\ud \ud Conclusion:\ud This indicates that a substantial amount of information on risk from percentage breast density is contained in the second view. It also suggests that visually assessed breast density has predictive potential for breast cancer risk comparable to that of density measured using the interactive threshold software when two views are available. This observation needs to be confirmed by studies applying the different measurement methods to the same individuals.

Introduction The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Methods Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. Results There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). Conclusions For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision.

Introduction The Predicting Risk of Cancer at Screening study in Manchester, UK, is a prospective study of breast cancer risk estimation. It was designed to assess whether mammographic density may help in refinement of breast cancer risk estimation using either the Gail model (Breast Cancer Risk Assessment Tool) or the Tyrer-Cuzick model (International Breast Intervention Study model). Methods Mammographic density was measured at entry as a percentage visual assessment, adjusted for age and body mass index. Tyrer-Cuzick and Gail 10-year risks were based on a questionnaire completed contemporaneously. Breast cancers were identified at the entry screen or shortly thereafter. The contribution of density to risk models was assessed using odds ratios (ORs) with profile likelihood confidence intervals (CIs) and area under the receiver operating characteristic curve (AUC). The calibration of predicted ORs was estimated as a percentage [(observed vs expected (O/E)] from logistic regression. Results The analysis included 50,628 women aged 47–73 years who were recruited between October 2009 and September 2013. Of these, 697 had breast cancer diagnosed after enrolment. Median follow-up was 3.2 years. Breast density [interquartile range odds ratio (IQR-OR) 1.48, 95 % CI 1.34–1.63, AUC 0.59] was a slightly stronger univariate risk factor than the Tyrer-Cuzick model [IQR-OR 1.36 (95 % CI 1.25–1.48), O/E 60 % (95 % CI 44–74), AUC 0.57] or the Gail model [IQR-OR 1.22 (95 % CI 1.12–1.33), O/E 46 % (95 % CI 26–65 %), AUC 0.55]. It continued to add information after allowing for Tyrer-Cuzick [IQR-OR 1.47 (95 % CI 1.33–1.62), combined AUC 0.61] or Gail [IQR-OR 1.45 (95 % CI 1.32–1.60), combined AUC 0.59]. Conclusions Breast density may be usefully combined with the Tyrer-Cuzick model or the Gail model. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0653-5) contains supplementary material, which is available to authorized users.