What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420).

BACKGROUND: In principle, risk-stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) should produce a better balance of benefits and harms. The main benefit is the offer of NICE-approved more frequent screening and/ or chemoprevention for women who are at increased risk, but are unaware of this. We have developed BC-Predict, to be offered to women when invited to NHSBSP which collects information on risk factors (self-reported information on family history and hormone-related factors via questionnaire; mammographic density; and in a sub-sample, Single Nucleotide Polymorphisms). BC-Predict produces risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5 to < 8% 10-year) to have discussion of prevention and early detection options at Family History, Risk and Prevention Clinics. Despite the promise of systems such as BC-Predict, there are still too many uncertainties for a fully-powered definitive trial to be appropriate or ethical. The present research aims to identify these key uncertainties regarding the feasibility of integrating BC-Predict into the NHSBSP. Key objectives of the present research are to quantify important potential benefits and harms, and identify key drivers of the relative cost-effectiveness of embedding BC-Predict into NHSBSP. METHODS: A non-randomised fully counterbalanced study design will be used, to include approximately equal numbers of women offered NHSBSP (n = 18,700) and BC-Predict (n = 18,700) from selected screening sites (n = 7). In the initial 8-month time period, women eligible for NHSBSP will be offered BC-Predict in four screening sites. Three screening sites will offer women usual NHSBSP. In the following 8-months the study sites offering usual NHSBSP switch to BC-Predict and vice versa. Key potential benefits including uptake of risk consultations, chemoprevention and additional screening will be obtained for both groups. Key potential harms such as increased anxiety will be obtained via self-report questionnaires, with embedded qualitative process analysis. A decision-analytic model-based cost-effectiveness analysis will identify the key uncertainties underpinning the relative cost-effectiveness of embedding BC-Predict into NHSBSP. DISCUSSION: We will assess the feasibility of integrating BC-Predict into the NHSBSP, and identify the main uncertainties for a definitive evaluation of the clinical and cost-effectiveness of BC-Predict. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420).

Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants.

PURPOSE: To improve breast cancer risk stratification to enable more targeted early detection/prevention strategies that will better balance risks and benefits of population screening programmes. METHODS: 9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology. RESULTS: 195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall [IQ-OR 2.25 (95% CI 1.89-2.68)] with excellent calibration-(0.99). The model performed particularly well in predicting higher stage stage 2+ IQ-OR 2.69 (95% CI 2.02-3.60) and ER + BCs (IQ-OR 2.36 (95% CI 1.93-2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast, PRS gave the highest OR for incident stage 2+ cancers, [IQR-OR 1.79 (95% CI 1.30-2.46)]. CONCLUSIONS: A combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.

Psychological impact of providing women with personalised 10-year breast cancer risk estimates.

BACKGROUND: The Predicting Risk of Cancer at Screening (PROCAS) study estimated 10-year breast cancer risk for 53,596 women attending NHS Breast Screening Programme. The present study, nested within the PROCAS study, aimed to assess the psychological impact of receiving breast cancer risk estimates, based on: (a) the Tyrer-Cuzick (T-C) algorithm including breast density or (b) T-C including breast density plus single-nucleotide polymorphisms (SNPs), versus (c) comparison women awaiting results. METHODS: A sample of 2138 women from the PROCAS study was stratified by testing groups: T-C only, T-C(+SNPs) and comparison women; and by 10-year risk estimates received: 'moderate' (5-7.99%), 'average' (2-4.99%) or 'below average' (<1.99%) risk. Postal questionnaires were returned by 765 (36%) women. RESULTS: Overall state anxiety and cancer worry were low, and similar for women in T-C only and T-C(+SNPs) groups. Women in both T-C only and T-C(+SNPs) groups showed lower-state anxiety but slightly higher cancer worry than comparison women awaiting results. Risk information had no consistent effects on intentions to change behaviour. Most women were satisfied with information provided. There was considerable variation in understanding. CONCLUSIONS: No major harms of providing women with 10-year breast cancer risk estimates were detected. Research to establish the feasibility of risk-stratified breast screening is warranted.

A comparison of five methods of measuring mammographic density: a case-control study.

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.

Breast cancer risk in a screening cohort of Asian and white British/Irish women from Manchester UK.

BACKGROUND: The differences between breast cancer risk factors in white British/Irish and Asian women attending screening in the UK are not well documented. METHODS: Between 2009-15 ethnicity and traditional breast cancer risk factors were self-identified by a screening cohort from Greater Manchester, with follow up to 2016. Risk factors and incidence rates were compared using age-standardised statistics (European standard population). RESULTS: Eight hundred and seventy-nine Asian women and 51,779 unaffected white British/Irish women aged 46-73 years were recruited. Asian women were at lower predicted breast cancer risk from hormonal and reproductive risk factors than white British/Irish women (mean 10 year risk 2.6% vs 3.1%, difference 0.4%, 95%CI 0.3-0.5%). White British/Irish women were more likely to have had a younger age at menarche, be overweight or obese, taller, used hormone replacement therapy and not to have had children.. However, despite being less overweight Asian women had gained more weight from age 20 years and were less likely to undertake moderate physical activity. Asian women also had a slightly higher mammographic density. Asian age-standardised incidence was 3.2 (95%CI 1.6-5.2, 18 cancers) per thousand women/year vs 4.5 (95%CI 4.2-4.8, 1076 cancers) for white British/Irish women. CONCLUSIONS: Asian women attending screening in Greater Manchester are likely to have a lower risk of breast cancer than white British/Irish women, but they undertake less physical activity and have more adult weight gain.

The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case-control study.

BACKGROUND: Breast cancer familial risk clinics offer screening and preventive strategies. While BRCA1/BRCA2 genetic testing provides important risk information for some women, panels of more common breast cancer risk genetic variants may have relevance to greater numbers of women with familial risk. METHODS: Three polygenic risk scores (PRS) based on 18 SNPs were investigated in a case-control study of women attending a familial risk clinic. PRS were derived from published general European population allele ORs and frequencies (18-SNPs (SNP18)). In women with BRCA1/BRCA2 mutations, 3 SNPs/13 SNPs, respectively, generated the PRS estimates. In total, 364 incident breast cancer cases (112 with BRCA1/2 mutations) were matched with 1605 controls (691 BRCA1/2) by age last mammogram and BRCA1/2 genetic test result. 87 women with cancer before attendance were also considered. Logistic regression was used to measure PRS performance through ORs per IQR and calibration of the observed to expected (O/E) logarithm relative risk when unadjusted and adjusted for phenotypic risk factors assessed by the Tyrer-Cuzick (TC) model. RESULTS: SNP18 was predictive for non-carriers of BRCA1/2 mutations (IQR OR 1.55, 95% CI 1.29 to 1.87, O/E 96%). Findings were unaffected by adjustment from TC (IQR OR 1.56, 95% CI 1.29 to 1.89) or when prior cancers were included (IQR OR 1.55, 95% CI 1.30 to 1.87). There was some evidence to support polygenic scores with weights for individuals with BRCA1/2 mutations (BRCA1 IQR OR 1.44, 95% CI 1.17 to 1.76; BRCA2 IQ OR 1.44, 95% CI 0.90 to 2.31). CONCLUSIONS: PRS may be used to refine risk assessment for women at increased familial risk who test negative/have low likelihood of BRCA1/2 mutations. They may alter the recommended prevention strategy for many women attending family history clinics.

Breast cancer risk feedback to women in the UK NHS breast screening population.

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 (<1%) were invited for face-to-face or telephone risk feedback and counselling. 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%) (P<0.001). Women at high risk were significantly more likely to perceive their risk as high (P<0.001) and to attend their subsequent mammogram (94.4%) compared with low-risk women (84.2%; P=0.04) and all attendees (84.3%; ⩽0.0001). CONCLUSIONS: 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 adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort.

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.

Tumour characteristics and survival in familial breast cancer prospectively diagnosed by annual mammography.

Women from breast cancer families without a demonstrable BRCA1/2 mutation were subjected to annual mammography from age 30 years onwards. One-hundred and ninety-eight patients were diagnosed prospectively with invasive breast cancer and followed for a total of 1513 years. Overall 10-year survival was 88 %. Together with our previous report that women in such kindreds had about twice the population risk of breast cancer, the combined conclusion was that the overall chances of developing breast cancer causing death within 10 years before 50 years of age was 1 % or less when subjected to annual mammography and current treatment. These are empirical prospective observations which may be used for genetic counselling. The majority (160/194 = 84 %) of patients had ER+ and/or low grade tumours with 92 % 10-year survival. One minor group of the patients had ER- tumours, another small group had high grade tumours with nodal spread, both groups were associated with worse prognosis, but the two groups were not mutually associated.

Breast cancer risk in young women in the national breast screening programme: implications for applying NICE guidelines for additional screening and chemoprevention.

In the United Kingdom, women at moderate and high risk of breast cancer between the ages of 40 and 49 years are eligible for annual mammographic screening and preventive therapy with tamoxifen. Here, we estimate the numbers of women in a population eligible for this service and the proportion of breast cancers detected in this group compared with the whole population. Women <50 attending for mammographic screening in the National Health Service Breast Screening Programme (NHSBSP) completed a risk questionnaire. The proportion at moderate and high risk according to National Institute of Health Care Excellence (NICE) guidelines was estimated. An estimate was also made using a different model of risk estimation (Tyrer-Cuzick). The numbers of cancers detected in the moderate/high risk groups were compared with numbers detected in the whole population. Completed questionnaires were available for 4,360 women between ages 46 and 49 years. Thirty women [0.7%; 95% confidence interval (CI), 0.5-1.0%] were at high risk and 130 (3.0%, 2.5-3.5%) were at moderate risk according to NICE guidelines. Thirty-seven cancers were detected by mammography in the whole group. Five of these were found in the moderate-/high-risk group giving a 3.2-fold increase in detection compared with the standard risk group. More women were assigned to the moderate- or high-risk group using the Tyrer-Cuzick model (N = 384), but the numbers of cancers in this group were not appreciably increased (N = 8). Systematic assessment of family history in primary care or through population-based screening will identify appreciable numbers of women in their forties, eligible for additional surveillance and chemoprevention.

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.