Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality

PURPOSE

To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mammograms taken at approximately 1/10th of the usual dose. We investigate the quality and reliability of the density scores produced on low dose mammograms focussing on how image resolution and levels of training affect the low dose predictions. Methods: Deep learning models are developed and tested, with two feature extraction methods and an end-to-end trained method, on five different resolutions of 15,290 standard dose and simulated low dose mammograms with known labels. The models are further tested on a dataset with 296 matching standard and real low dose images allowing performance on the low dose images to be ascertained. Results: Prediction quality on standard and simulated low dose images compared to labels is similar for all equivalent model training and image resolution versions. Increasing resolution results in improved performance of both feature extraction methods for standard and simulated low dose images, while the trained models show high performance across the resolutions. For the trained models the Spearman rank correlation coefficient between predictions of standard and low dose images at low resolution is 0.951 (0.937 to 0.960) and at the highest resolution 0.956 (0.942 to 0.965). If pairs of model predictions are averaged, similarity increases. Conclusions: Deep learning mammographic density predictions on low dose mammograms are highly correlated with standard dose equivalents for feature extraction and end-to-end approaches across multiple image resolutions. Deep learning models can reliably make high quality mammographic density predictions on low dose mammograms. .

Germline testing of BRCA1, BRCA2, PALB2 and CHEK2 c.1100delC in 1514 triple negative familial and isolated breast cancers from a single centre, with extended testing of ATM, RAD51C and RAD51D in over 400

BACKGROUND

The identification of germline pathogenic gene variants (PGVs) in triple negative breast cancer (TNBC) is important to inform further primary cancer risk reduction and TNBC treatment strategies. We therefore investigated the contribution of breast cancer associated PGVs to familial and isolated invasive TNBC.

METHODS

Outcomes of germline BRCA1, BRCA2 and CHEK2_c.1100delC testing were recorded in 1514 women (743-isolated, 771-familial), and for PALB2 in 846 women (541-isolated, 305-familial), with TNBC and smaller numbers for additional genes. Breast cancer free controls were identified from Predicting Risk Of Cancer At Screening and BRIDGES (Breast cancer RIsk after Diagnostic GEne Sequencing) studies.

RESULTS

BRCA1_PGVs were detected in 52 isolated (7.0%) and 195 (25.3%) familial cases (isolated-OR=58.9, 95% CI: 16.6 to 247.0), BRCA2_PGVs in 21 (2.8%) isolated and 67 (8.7%) familial cases (isolated-OR=5.0, 95% CI: 2.3 to 11.2), PALB2_PGVs in 9 (1.7%) isolated and 12 (3.9%) familial cases (isolated-OR=8.8, 95% CI: 2.5 to 30.4) and CHEK2_c.1100delC in 0 isolated and 3 (0.45%) familial cases (isolated-OR=0.0, 95% CI: 0.00 to 2.11). BRCA1_PGV detection rate was >10% for all familial TNBC age groups and significantly higher for younger diagnoses (familial: <50 years, n=165/538 (30.7%); ≥50 years, n=30/233 (12.9%); p<0.0001). Women with a G3_TNBC were more likely to have a BRCA1_PGV as compared with a BRCA2 or PALB2_PGV (p<0.0001). 0/743 isolated TNBC had the CHEK2_c.1100delC PGV and 0/305 any ATM_PGV, but 2/240 (0.83%) had a RAD51D_PGV.

CONCLUSION

PGVs in BRCA1 are associated with G3_TNBCs. Familial TNBCs and isolated TNBCs <30 years have a >10% likelihood of a PGV in BRCA1. BRCA1_PGVs are associated with younger age of familial TNBC. There was no evidence for any increased risk of TNBC with CHEK2 or ATM PGVs.

TP53 c.455C>T p.(Pro152Leu) pathogenic variant is a lower risk allele with attenuated risks of breast cancer and sarcoma

Germline (likely) pathogenic TP53 variants cause Li-Fraumeni syndrome (LFS), typically associated with sarcoma, brain, breast and adrenal tumours. Although classical LFS is highly penetrant, the p.R337H variant, common in Brazil, is typically associated with childhood adrenal tumours and an older onset age of other LFS tumours. Previously, we reported the finding of p.P152L in 6 children from 5 families with adrenal tumours. We have now assessed cancer risks over the subsequent 23 years, and in one further family with p.P152L. Cancer risks were compared with those in the 11 families known to our service with classical dominant negative mutations affecting neighbouring codons 245 and 248 (codon 245/248).Compared with codon 245/248 families, we found lower age-related risks for all non-adrenal tumours in codon 152 families (p<0.0001) with an absence of breast cancer as compared with 100% penetrance by age 36 years in codon 245/248 families (p<0.0001), and lower rates of sarcoma in non-irradiated individuals (p=0.0001). Although there were more adrenal tumours in codon 152 families (6/26 individuals, 1/27 for codon 245/248), this was not significant (p=0.05).Understanding codon-specific cancer risks in LFS is important for accurate personalised cancer risk assessment, and subsequent prevention and early detection strategies.

Detection of pathogenic variants in breast cancer susceptibility genes in bilateral breast cancer

PURPOSE

To investigate the frequency of germline pathogenic variants (PVs) in women with bilateral breast cancer.

METHODS

We undertook BRCA1/2 and CHEK2 c.1100delC molecular analysis in 764 samples and a multigene panel in 156. Detection rates were assessed by age at first primary, Manchester Score, and breast pathology. Oestrogen receptor (ER) status of the contralateral versus first breast cancer was compared on 1081 patients with breast cancer with BRCA1/BRCA2 PVs.

RESULTS

764 women with bilateral breast cancer have undergone testing of BRCA1/2 and CHEK2; 407 were also tested for PALB2 and 177 for ATM. Detection rates were BRCA1 11.6%, BRCA2 14.0%, CHEK2 2.4%, PALB2 1.0%, ATM 1.1% and, for a subset of mainly very early onset tumours, TP53 4.6% (9 of 195). The highest PV detection rates were for triple negative cancers for BRCA1 (26.4%), grade 3 ER+HER2 for BRCA2 (27.9%) and HER2+ for CHEK2 (8.9%). ER status of the first primary in BRCA1 and BRCA2 PV heterozygotes was strongly predictive of the ER status of the second contralateral tumour since ~90% of second tumours were ER- in BRCA1 heterozygotes, and 50% were ER- in BRCA2 heterozygotes if the first was ER-.

CONCLUSION

We have shown a high rate of detection of BRCA1 and BRCA2 PVs in triple negative and grade 3 ER+HER2- first primary diagnoses, respectively. High rates of HER2+ were associated with CHEK2 PVs, and women ≤30 years were associated with TP53 PVs. First primary ER status in BRCA1/2 strongly predicts the second tumour will be the same ER status even if unusual for PVs in that gene.

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: application to BRCA1 and BRCA2

A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

Breast cancer polygenic risk scores derived in White European populations are not calibrated for women of Ashkenazi Jewish descent

PURPOSE

Polygenic risk scores (PRSs) are a major component of accurate breast cancer (BC) risk prediction but require ethnicity-specific calibration. Ashkenazi Jewish (AJ) population is assumed to be of White European (WE) origin in some commercially available PRSs despite differing effect allele frequencies (EAFs). We conducted a case-control study of WE and AJ women from the Predicting Risk of Cancer at Screening Study. The Breast Cancer in Northern Israel Study provided a separate AJ population-based case-control validation series.

METHODS

All women underwent Illumina OncoArray single-nucleotide variation (SNV; formerly single-nucleotide polymorphism [SNP]) analysis. Two PRSs were assessed, SNV142 and SNV78. A total of 221 of 2243 WE women (discovery: cases = 111; controls = 110; validation: cases = 651; controls = 1772) and 221 AJ women (cases = 121; controls = 110) were included from the UK study; the Israeli series consisted of 2045 AJ women (cases = 1331; controls = 714). EAFs were obtained from the Genome Aggregation Database.

RESULTS

In the UK study, the mean SNV142 PRS demonstrated good calibration and discrimination in WE population, with mean PRS of 1.33 (95% CI 1.18-1.48) in cases and 1.01 (95% CI 0.89-1.13) in controls. In AJ women from Manchester, the mean PRS of 1.54 (1.38-1.70) in cases and 1.20 (1.08-1.32) in controls demonstrated good discrimination but overestimation of BC relative risk. After adjusting for EAFs for the AJ population, mean risk was corrected (mean SNV142 PRS cases = 1.30 [95% CI 1.16-1.44] and controls = 1.02 [95% CI 0.92-1.12]). This was recapitulated in the larger Israeli data set with good discrimination (area under the curve = 0.632 [95% CI 0.607-0.657] for SNV142).

CONCLUSION

AJ women should not be given BC relative risk predictions based on PRSs calibrated to EAFs from the WE population. PRSs need to be recalibrated using AJ-derived EAFs. A simple recalibration using the mean PRS adjustment ratio likely performs well.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

BACKGROUND

Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.

METHODS

Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.

RESULTS

Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).

CONCLUSIONS

Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Differential involvement of germline pathogenic variants in breast cancer genes between DCIS and low-grade invasive cancers

PURPOSE

To investigate frequency of germline pathogenic variants (PVs) in women with ductal carcinoma in situ (DCIS) and grade 1 invasive breast cancer (G1BC).

METHODS

We undertook BRCA1/2 analysis in 311 women with DCIS and 392 with G1BC and extended panel testing (non-BRCA1/2) in 176/311 with DCIS and 156/392 with G1BC. We investigated PV detection by age at diagnosis, Manchester Score (MS), DCIS grade and receptor status.

RESULTS

30/311 (9.6%) with DCIS and 16/392 with G1BC (4.1%) had a BRCA1/2 PV (p=0.003), and 24/176-(13.6%) and 7/156-(4.5%), respectively, a non-BRCA1/2 PV (p=0.004). Increasing MS was associated with increased likelihood of BRCA1/2 PV in both DCIS and G1BC, although the 10% threshold was not predictive for G1GB. 13/32 (40.6%) DCIS and 0/17 with G1BC <40 years had a non-BRCA1/2 PV (p<0.001). 0/16 DCIS G1 had a PV. For G2 and G3 DCIS, PV rates were 10/98 (BRCA1/2) and 9/90 (non-BRCA1/2), and 8/47 (BRCA1/2) and 8/45 (non-BRCA1/2), respectively. 6/9 BRCA1 and 3/26 BRCA2-associated DCIS were oestrogen receptor negative-(p=0.003). G1BC population testing showed no increased PV rate (OR=1.16, 95% CI 0.28 to 4.80).

CONCLUSION

DCIS is more likely to be associated with both BRCA1/2 and non-BRCA1/2 PVs than G1BC. Extended panel testing ought to be offered in young-onset DCIS where PV detection rates are highest.

The effect of variable labels on deep learning models trained to predict breast density

Purpose. High breast density is associated with reduced efficacy of mammographic screening and increased risk of developing breast cancer. Accurate and reliable automated density estimates can be used for direct risk prediction and passing density related information to further predictive models. Expert reader assessments of density show a strong relationship to cancer risk but also inter-reader variation. The effect of label variability on model performance is important when considering how to utilise automated methods for both research and clinical purposes.Methods. We utilise subsets of images with density labels from the same 13 readers and 12 reader pairs, and train a deep transfer learning model which is used to assess how label variability affects the mapping from representation to prediction. We then create two end-to-end models: one that is trained on averaged labels across the reader pairs and the second that is trained using individual reader scores, with a novel alteration to the objective function. The combination of these two end-to-end models allows us to investigate the effect of label variability on the model representation formed.Results. We show that the trained mappings from representations to labels are altered considerably by the variability of reader scores. Training on labels with distribution variation removed causes the Spearman rank correlation coefficients to rise from 0.751 ± 0.002 to either 0.815 ± 0.026 when averaging across readers or 0.844 ± 0.002 when averaging across images. However, when we train different models to investigate the representation effect we see little difference, with Spearman rank correlation coefficients of 0.846 ± 0.006 and 0.850 ± 0.006 showing no statistically significant difference in the quality of the model representation with regard to density prediction.Conclusions. We show that the mapping between representation and mammographic density prediction is significantly affected by label variability. However, the effect of the label variability on the model representation is limited.

Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420)

BACKGROUND

Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS).

METHODS

Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer-Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5-<8% 10-year) to have appointments to discuss prevention and additional screening.

RESULTS

Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication.

DISCUSSION

We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification.

TRIAL REGISTRATION

Retrospectively registered with clinicaltrials.gov (NCT04359420).

Radiation treatment of benign tumours in NF2-related-schwannomatosis: a national study of 266 irradiated patients showing a significant increase in malignancy/malignant progression

Background

Radiation treatment of benign tumours in tumour-predisposition syndromes is controversial, but short-term studies from treatment centres suggests safety despite apparent radiation associated malignancy being reported. We determined whether radiation treatment in NF2-related-schwannomatosis patients is associated with increased rates of subsequent malignancy-(M)/malignant progression-(MP).

Methods

All UK patients with NF2 were eligible if they had a clinical/molecular diagnosis. Cases were NF2 patients treated with radiation for benign tumours. Controls were matched for treatment location with surgical/medical treatments based on age and year of treatment. Prospective data collection began in 1990 with addition of retrospective cases to 1969. Kaplan-Meier analysis was performed for malignancy incidence and survival. Outcomes were CNS M/MP (2cm annualised diameter growth) and survival from index tumour treatment.

Results

1345 NF2 patients, 266 (133-Male) underwent radiation treatments between 1969-2021 with median first radiotherapy aged 32.9-(IQR=22.4-46.0). Nine subsequent CNS malignancies/malignant progressions were identified in cases with only four in 1079 untreated-(p&lt;0.001). Lifetime and 20-year CNS M/MP was ~6% in all irradiated patients-(4.9% for VS radiotherapy) versus &lt;1% in the non-irradiated population-(p&lt;0.001/0.01). Controls were well-matched for age at NF2 diagnosis and treatment-(Males=133-50%) and had no M/MP in the CNS post index-tumour treatment-(p=0.0016). Thirty-year survival from index tumour treatment was 45.62%-(95%CI=34.0–56.5) for cases and 66.4%-(57.3–74.0) for controls-(p=0.02), but was non-significantly worse for VS radiotherapy.

Conclusion

-NF2 patients should not be offered radiotherapy as first line treatment of benign tumours and should be given a frank discussion of the potential 5% excess absolute risk of M/MP.

Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

BACKGROUND

Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.

METHODS

We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.

RESULTS

In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10-6) and AC058822.1 (P = 1.47 × 10-4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.

CONCLUSIONS

Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10-5), demonstrating the importance of diversifying study cohorts.

Obesity at age 20 and weight gain during adulthood increase risk of total and premature all-cause mortality: findings from women attending breast screening in Manchester

BACKGROUND

Obesity in early adulthood is associated with lower breast cancer rates in later life. This could be interpreted as a positive reinforcement of excess weight amongst younger women however, the wider implications of higher weights are less well known. This study examined the association between both obesity in early adulthood and body mass index (BMI) change through adulthood, and all-cause mortality.

METHODS

The Predicting Risk of Cancer At Screening (PROCAS) study recruited 57,902 women aged 46-73 years (median age 57.2, IQR 51.8-63.7 years) from the Greater Manchester National Health Service breast screening programme in North West England between 2009 and 2015. It was used to assess associations between BMI at 20 years and cohort entry with all-cause mortality ascertained via deaths recorded on the National Breast Screening System to June 2020. Hazard ratios were estimated using proportional hazards (Cox) regression adjusted for factors at entry to the cohort: age, deprivation, bilateral oophorectomy, hormone-replacement therapy, menopausal status, ethnicity, alcohol intake, physical activity, and BMI.

RESULTS

The prevalence of overweight (25-30 kg/m²) and obesity (> 30 kg/m²) were 10.4% and 2.5% respectively at 20 years, increasing to 35.2% and 25.9% respectively at cohort entry. After a mean 8.7 years follow-up we observed that overweight (HR = 1.27, 95%CI = 1.10-1.47) and obesity (HR = 2.11, 95%CI = 1.67-2.66) at 20 years had a higher mortality rate compared with healthy weight. Women who were underweight/healthy weight at 20 years and gained weight to obesity at entry had a slightly increased mortality rate compared with women who were underweight/healthy weight at both time points (HR 1.16, 95%CI = 1.02-1.32). Women with overweight (HR = 1.36, 95%CI = 1.06-1.75) or obesity (HR = 1.90, 95%CI = 1.45-2.48) at both 20 years and entry had a higher mortality rate than women who were underweight/healthy weight at both points.

CONCLUSIONS

Women who self-reported overweight and obesity at 20 years had a shorter life expectancy in this cohort of women attending breast cancer screening. Weight gain from 20 years was common in this group. Girls and women should be supported to maintain a healthy weight throughout the lifespan to help increase life expectancy. Trial registration number NCT04359420, retrospectively registered 24/04/2020.

Magnitude and attributed reasons for adult weight gain amongst women at increased risk of breast cancer

BACKGROUND

Excess weight (BMI ≥25.0 kg/m2) and weight gain during adult life increase the risk of postmenopausal breast cancer in women who are already at increased risk of the disease. Reasons for weight gain in this population can inform strategies for weight gain prevention.

METHODS

Baseline data from six weight loss studies for women at increased risk of breast cancer (age 31-74 years) were collated. Self-reported patterns of adult weight gain and attributed reasons for weight gain before joining the weight loss study were reported for the whole population and secondary analyses reported the different reasons given by women with/without children, pre-/peri- or postmenopausal, and moderate/high risk of breast cancer.

RESULTS

Five hundred and one women with a mean age of 47.6 (SD 8.4) years and median BMI of 29.9 (IQR 27.0-34.7) kg/m2 were included in the analyses. The median weight gain since young adulthood (18-20 years) was 20.5 (IQR 14.0-29.7) kg or 33.7 (23.4-50.2) % and median annual weight gain was 0.73 (IQR 0.51-1.08) kg. Four hundred and one women were included in analysis of weight gain reasons. The main five self-reported reasons for weight gain were children / childcare / pregnancy (stated by 55.9% of participants), followed by inactivity (41.9%), comfort or boredom eating (38.2%), portion size (32.4%), and stress (27.4%). Reasons appeared broadly similar between the different groups in the secondary analyses.

CONCLUSIONS

We have highlighted common reasons for weight gain in women at increased risk of breast cancer. This will inform future interventions to support women to avoid weight gain in adulthood which would reduce the burden of breast cancer.

TRIAL REGISTRATION

NIHR NRR N0226132725, ISRCTN52913838, ISRCTN77916487, ISRCTN91372184, ISRCTN10803394 and ISRCTN16431108.

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

BACKGROUND

Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).

METHOD

The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.

RESULTS

Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.

CONCLUSION

The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Mammographic breast density and breast cancer risk in the Saudi population: a case-control study using visual and automated methods

OBJECTIVE

This study aims to establish risk of breast cancer based on breast density among Saudi women and to compare cancer prediction using different breast density methods.

METHODS

1140 pseudonymised screening mammograms from Saudi females were retrospectively collected. Breast density was assessed using Breast Imaging Reporting and Data System (BI-RADS) density categories and visual analogue scale (VAS) of 285 cases and 855 controls matched on age and body mass index. In a subset of 160 cases and 480 controls density was estimated by two automated methods, Volpara Density™ and predicted VAS (pVAS). Odds ratios (ORs) between the highest and second categories in BI-RADS and Volpara density grades, and highest vs lowest quartiles in VAS, pVAS and Volpara Density™, were estimated using conditional logistic regression.

RESULTS

For BI-RADS, the OR was 6.69 (95% CI 2.79-16.06) in the highest vs second category and OR = 4.78 (95% CI 3.01-7.58) in the highest vs lowest quartile for VAS. In the subset, VAS was the strongest predictor OR = 7.54 (95% CI 3.86-14.74), followed by pVAS using raw images OR = 5.38 (95% CI 2.68-10.77) and Volpara Density ™ OR = 3.55, (95% CI 1.86-6.75) for highest vs lowest quartiles. The matched concordance index for VAS was 0.70 (95% CI 0.65-0.75) demonstrating better discrimination between cases and controls than all other methods.

CONCLUSION

Increased mammographic density was strongly associated with risk of breast cancer among Saudi women. Radiologists' visual assessment of breast density is superior to automated methods. However, pVAS and Volpara Density ™ also significantly predicted breast cancer risk based on breast density.

ADVANCES IN KNOWLEDGE

Our study established an association between breast density and breast cancer in a Saudi population and compared the performance of automated methods. This provides a stepping-stone towards personalised screening using automated breast density methods.

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

BACKGROUND

Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.

METHODS

We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.

RESULTS

The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.

CONCLUSIONS

These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

Breast cancer risk stratification in women of screening age: Incremental effects of adding mammographic density, polygenic risk, and a gene panel

PURPOSE

There is great promise in breast cancer risk stratification to target screening and prevention. It is unclear whether adding gene panels to other risk tools improves breast cancer risk stratification and adds discriminatory benefit on a population basis.

METHODS

In total, 10,025 of 57,902 women aged 46 to 73 years in the Predicting Risk of Cancer at Screening study provided DNA samples. A case-control study was used to evaluate breast cancer risk assessment using polygenic risk scores (PRSs), cancer gene panel (n = 33), mammographic density (density residual [DR]), and risk factors collected using a self-completed 2-page questionnaire (Tyrer-Cuzick [TC] model version 8). In total, 525 cases and 1410 controls underwent gene panel testing and PRS calculation (18, 143, and/or 313 single-nucleotide polymorphisms [SNPs]).

RESULTS

Actionable pathogenic variants (PGVs) in BRCA1/2 were found in 1.7% of cases and 0.55% of controls, and overall PGVs were found in 6.1% of cases and 1.3% of controls. A combined assessment of TC8-DR-SNP313 and gene panel provided the best risk stratification with 26.1% of controls and 9.7% of cases identified at <1.4% 10-year risk and 9.01% of controls and 23.3% of cases at ≥8% 10-year risk. Because actionable PGVs were uncommon, discrimination was identical with/without gene panel (with/without: area under the curve = 0.67, 95% CI = 0.64-0.70). Only 7 of 17 PGVs in cases resulted in actionable risk category change. Extended case (n = 644)-control (n = 1779) series with TC8-DR-SNP143 identified 18.9% of controls and only 6.4% of stage 2+ cases at <1.4% 10-year risk and 20.7% of controls and 47.9% of stage 2+ cases at ≥5% 10-year risk.

CONCLUSION

Further studies and economic analysis will determine whether adding panels to PRS is a cost-effective strategy for risk stratification.

Common variants in breast cancer risk loci predispose to distinct tumor subtypes

BACKGROUND

Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

METHODS

Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

RESULTS

Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

CONCLUSION

This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

The importance of ethnicity: Are breast cancer polygenic risk scores ready for women who are not of White European origin?

Polygenic risk scores (PRS) for disease risk stratification show great promise for application in general populations, but most are based on data from individuals of White European origin. We assessed two well validated PRS (SNP18, SNP143) in the Predicting-Risk-of-Cancer-At-Screening (PROCAS) study in North-West England for breast cancer prediction based on ethnicity. Overall, 9475 women without breast cancer at study entry, including 645 who subsequently developed invasive breast cancer or ductal carcinoma in situ provided DNA. All were genotyped for SNP18 and a subset of 1868 controls were genotyped for SNP143. For White Europeans both PRS discriminated well between individuals with and without cancer. For n = 395 Black (n = 112), Asian (n = 119), mixed (n = 44) or Jewish (n = 120) women without cancer both PRS overestimated breast cancer risk, being most marked for women of Black and Jewish origin (P < .001). SNP143 resulted in a potential mean 40% breast cancer risk overestimation in the combined group of non-White/non-European origin. SNP-PRS that has been normalized based on White European ethnicity for breast cancer should not be used to predict risk in women of other ethnicities. There is an urgent need to develop PRS specific for other ethnicities, in order to widen access of this technology.

Validation of a new fully automated software for 2D digital mammographic breast density evaluation in predicting breast cancer risk

We compared accuracy for breast cancer (BC) risk stratification of a new fully automated system (DenSeeMammo-DSM) for breast density (BD) assessment to a non-inferiority threshold based on radiologists' visual assessment. Pooled analysis was performed on 14,267 2D mammograms collected from women aged 48-55 years who underwent BC screening within three studies: RETomo, Florence study and PROCAS. BD was expressed through clinical Breast Imaging Reporting and Data System (BI-RADS) density classification. Women in BI-RADS D category had a 2.6 (95% CI 1.5-4.4) and a 3.6 (95% CI 1.4-9.3) times higher risk of incident and interval cancer, respectively, than women in the two lowest BD categories. The ability of DSM to predict risk of incident cancer was non-inferior to radiologists' visual assessment as both point estimate and lower bound of 95% CI (AUC 0.589; 95% CI 0.580-0.597) were above the predefined visual assessment threshold (AUC 0.571). AUC for interval (AUC 0.631; 95% CI 0.623-0.639) cancers was even higher. BD assessed with new fully automated method is positively associated with BC risk and is not inferior to radiologists' visual assessment. It is an even stronger marker of interval cancer, confirming an appreciable masking effect of BD that reduces mammography sensitivity.

Mendelian randomisation study of smoking exposure in relation to breast cancer risk

BACKGROUND

Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk.

METHODS

We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy.

RESULTS

Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect.

CONCLUSION

Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Disease course of neurofibromatosis type 2: a 30-year follow-up study of 353 patients seen at a single institution

BACKGROUND

Limited data exist on the disease course of neurofibromatosis type 2 (NF2) to guide clinical trial design.

METHODS

A prospective database of patients meeting NF2 diagnostic criteria, reviewed between 1990 and 2020, was evaluated. Follow-up to first vestibular schwannoma (VS) intervention and death was assessed by univariate analysis and stratified by age at onset, era referred, and inheritance type. Interventions for NF2-related tumors were assessed. Cox regression was performed to determine the relationship between individual factors from time of diagnosis to NF2-related death.

RESULTS

Three hundred and fifty-three patients were evaluated. During 4643.1 follow-up years from diagnosis to censoring, 60 patients (17.0%) died. The annual mean number of patients undergoing VS surgery or radiotherapy declined, from 4.66 and 1.65, respectively, per 100 NF2 patients in 1990-1999 to 2.11 and 1.01 in 2010-2020, as the number receiving bevacizumab increased (2.51 per 100 NF2 patients in 2010-2020). Five patients stopped bevacizumab to remove growing meningioma or spinal schwannoma. 153/353 (43.3%) had at least one neurosurgical intervention/radiation treatment within 5 years of diagnosis. Patients asymptomatic at diagnosis had longer time to intervention and better survival compared to those presenting with symptoms. Those symptomatically presenting <16 and >40 years had poorer overall survival than those presenting at 26-39 years (P = .03 and P = .02, respectively) but those presenting between 16 and 39 had shorter time to VS intervention. Individuals with de novo constitutional variants had worse survival than those with de novo mosaic or inherited disease (P = .004).

CONCLUSION

Understanding disease course improves prognostication, allowing for better-informed decisions about care.

High likelihood of actionable pathogenic variant detection in breast cancer genes in women with very early onset breast cancer

Background

While the likelihood of identifying constitutional breast cancer-associated BRCA1, BRCA2 and TP53 pathogenic variants (PVs) increases with earlier diagnosis age, little is known about the correlation with age at diagnosis in other predisposition genes. Here, we assessed the contribution of known breast cancer-associated genes to very early onset disease.

Methods

Sequencing of BRCA1, BRCA2, TP53 and CHEK2 c.1100delC was undertaken in women with breast cancer diagnosed ≤30 years. Those testing negative were screened for PVs in a minimum of eight additional breast cancer-associated genes. Rates of PVs were compared with cases ≤30 years from the Prospective study of Outcomes in Sporadic vs Hereditary breast cancer (POSH) study.

Results

Testing 379 women with breast cancer aged ≤30 years identified 75 PVs (19.7%) in BRCA1, 35 (9.2%) in BRCA2, 22 (5.8%) in TP53 and 2 (0.5%) CHEK2 c.1100delC. Extended screening of 184 PV negative women only identified eight additional actionable PVs. BRCA1/2 PVs were more common in women aged 26–30 years than in younger women (p=0.0083) although the younger age group had rates more similar to those in the POSH cohort. Out of 26 women with ductal carcinoma in situ (DCIS) alone, most were high-grade and 11/26 (42.3%) had a PV (TP53=6, BRCA2=2, BRCA1=2, PALB2=1). This PV yield is similar to the 61 (48.8%) BRCA1/2 PVs identified in 125 women with triple-negative breast cancer. The POSH cohort specifically excluded pure DCIS which may explain lower TP53 PV rates in this group (1.7%).

Conclusion

The rates of BRCA1, BRCA2 and TP53 PVs are high in very early onset breast cancer, with limited benefit from testing of additional breast cancer-associated genes.

Uptake and efficacy of bilateral risk reducing surgery in unaffected female BRCA1 and BRCA2 carriers

BACKGROUND

Women testing positive for BRCA1/2 pathogenic variants have high lifetime risks of breast cancer (BC) and ovarian cancer. The effectiveness of risk reducing surgery (RRS) has been demonstrated in numerous previous studies. We evaluated long-term uptake, timing and effectiveness of risk reducing mastectomy (RRM) and bilateral salpingo-oophorectomy (RRSO) in healthy BRCA1/2 carriers.

METHODS

Women were prospectively followed up from positive genetic test (GT) result to censor date. χ² testing compared categorical variables; Cox regression model estimated HRs and 95% CI for BC/ovarian cancer cases associated with RRS, and impact on all-cause mortality; Kaplan-Meier curves estimated cumulative RRS uptake. The annual cancer incidence was estimated by women-years at risk.

RESULTS

In total, 887 women were included in this analysis. Mean follow-up was 6.26 years (range=0.01-24.3; total=4685.4 women-years). RRS was performed in 512 women, 73 before GT. Overall RRM uptake was 57.9% and RRSO uptake was 78.6%. The median time from GT to RRM was 18.4 months, and from GT to RRSO-10.0 months. Annual BC incidence in the study population was 1.28%. Relative BC risk reduction (RRM versus non-RRM) was 94%. Risk reduction of ovarian cancer (RRSO versus non-RRSO) was 100%.

CONCLUSION

Over a 24-year period, we observed an increasing number of women opting for RRS. We showed that the timing of RRS remains suboptimal, especially in women undergoing RRSO. Both RRM and RRSO showed a significant effect on relevant cancer risk reduction. However, there was no statistically significant RRSO protective effect on BC.

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

BACKGROUND

Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

METHODS

We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

RESULTS

Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

CONCLUSIONS

The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Breast cancer incidence and early diagnosis in a family history risk and prevention clinic: 33-year experience in 14,311 women

PURPOSE

Women at increased familial breast cancer risk have been offered screening starting at an earlier age and increased frequency than national Screening Programmes for over 30 years. There are limited data on longer-term largescale implementation of this approach on cancer diagnosis.

METHODS

Women at our institution at ≥ 17% lifetime breast cancer risk have been offered enhanced screening with annual mammography starting at age 35 or 5-years younger than youngest affected relative, with upper age limit 50 for moderate and 60 for high-risk. Breast cancer pathology, stage and receptor status were assessed as well as survival from cancer diagnosis by Kaplan-Meier analysis.

RESULTS

Overall 14,311 women were seen and assessed for breast cancer risk, with 649 breast cancers occurring in 129,119 years follow up (post-prevalent annual incidence = 4.55/1000). Of 323/394 invasive breast cancers occurring whilst on enhanced screening, most were lymph-node negative (72.9%), T1 (≤ 20 mm, 73.2%) and stage-1 (61.4%), 126/394 stage2-4 (32%). 10-year breast cancer specific survival was 91.3% (95% CI 87.4-94.0) better than the 75.9% (95% CI 74.9-77.0) published for England in 2013-2017. As expected, survival was significantly better for women with screen detected cancers (p < 0.001). Ten-year survival was particularly good for those diagnosed ≤ 40 at 93.8% (n = 75; 95% CI 84.2-97.6). Women with lobular breast cancers had worse 10-year survival at 85.9% (95% CI 66.7-94.5). Breast cancer specific survival was good for 119 BRCA1/2 carriers with 20-year survival in BRCA1:91.2% (95% CI 77.8-96.6) and 83.8% (62.6-93.5) for BRCA2.

CONCLUSIONS

Targeted breast screening in women aged 30-60 years at increased familial risk is associated with good long-term survival that is substantially better than expected from population data.

Specialist oncological surgery for removal of the ovaries and fallopian tubes in BRCA1 and BRCA2 pathogenic variant carriers may reduce primary peritoneal cancer risk to very low levels

Risk‐reducing bilateral salpingo‐oophorectomy (RRBSO) is highly effective for the prevention of high‐grade serous ovarian cancer (HGSOC) in BRCA1/2 pathogenic variant carriers (PVCs), but does not completely eliminate future risk of primary peritoneal cancer (PPC). The requirement to completely remove fallopian tubes at RRBSO and carefully exclude occult cancer/serous tubal intraepithelial carcinoma (STIC) lesions may not have been appreciated historically. We calculated rates of HGSOC and PPC in confirmed BRCA1/2 PVCs registered on the regional database in those who did (cases) and did not (controls) undergo RRBSO after genetic testing. Expected annual rates of ovarian/peritoneal cancer were 1% for BRCA1 ≥ 35 years and 0.5% for BRCA2 ≥ 45 years. Follow‐up before 35/45 years was “risk free” and lead time excluded RRBSO <35 years and <45 years for BRCA1 and BRCA2, respectively. Women were followed from personal mutation report (controls) or RRBSO (cases) to death, ovarian/peritoneal cancer or last follow‐up, whichever was sooner. In total, 891 cases (BRCA1 = 468, BRCA2 = 423) and 1302 controls had follow‐up ≥35 years (BRCA1 = 736) and ≥45 years (BRCA2 = 566), respectively, over a total of 7261.1 risk eligible years (mean = 8.15 years). Twenty‐one occult ovarian cancers were found at RRBSO (2.4%), 16 at stage 1. Post RRBSO, 56.97 ovarian/peritoneal cancers were expected but only 3 were observed (HR = 0.053; 95% CI = 0.013‐0.14), with combined Kaplan‐Meier analysis HR = 0.029 (95% CI = 0.009‐0.100, P < .001). Risk reduction was greater in specialist (HR = 0.03; 95% CI = 0.001‐0.13) compared to non‐specialist centres (HR = 0.11; 95% CI = 0.02‐0.37) (P = .07). In controls, 23.35 ovarian/peritoneal cancers were expected with 32 observed (HR = 1.37; 95% CI = 0.95‐1.91). RRBSO <35/<45 years reduces the risk of ovarian/peritoneal cancer by 95% in BRCA1/2 PVCs and may be greater in specialist centres.

What's new?

Women who carry genetic variants in BRCA1/2 that are linked to high‐grade serous ovarian cancer are advised to undergo risk‐reducing prophylactic bilateral salpingo‐oophorectomy (RRBSO). RRBSO, however, is associated with a significant residual risk of primary peritoneal cancer (PPC). Here, the rate of PPC following prophylactic surgery for high‐grade serous ovarian cancer was investigated among 2,193 BRCA1/2 mutation carriers who had undergone RRBSO. Estimates indicate that prophylactic surgery reduced the overall risk of PPC by 95 percent, a far greater reduction than previously described. Residual risk was lowest when RRBSO was carried out at specialist centers compared to non‐specialist centers.

Mainstreaming germline BRCA1/2 testing in non-mucinous epithelial ovarian cancer in the North West of England

Poly(ADP-ribose) polymerase (PARP) inhibitors improve survival in BRCA-mutant high-grade serous ovarian carcinoma. As a result, germline and somatic BRCA1/2 testing has become standard practice in women diagnosed with ovarian cancer. We outline changes in testing and detection rates of germline BRCA1/2 pathogenic variants (PVs) in cases of non-mucinous epithelial ovarian cancer diagnosed during three eras, spanning 12 years, within the North West of England, and compare the uptake of cascade testing in families identified by oncology-led mainstreaming versus regional genetics clinics. Eras included: Period 1 (20% risk threshold for testing): between January 2007 and May 2013; Period 2 (10% risk threshold for testing): between June 2013 and October 2017 and; Period 3 (mainstream testing): between November 2017 and November 2019. A total of 1081 women underwent germline BRCA1/2 testing between January 2007 and November 2019 and 222 (20.5%) were found to have a PV. The monthly testing rate increased by 3.3-fold and 2.5-fold between Periods 1-2 and Periods 2-3, respectively. A similar incidence of germline BRCA1/2 PVs were detected in Period 2 (17.2%) and Period 3 (18.5%). Uptake of cascade testing from first-degree relatives was significantly lower in those women undergoing mainstream testing compared with those tested in regional genetics clinics (31.6% versus 47.3%, P = 0.038). Mainstream testing allows timely detection of germline BRCA1/2 status to select patients for PARP inhibitors, but shortfalls in the uptake of cascade testing in first-degree relatives requires optimisation to broaden benefits within families.

Mammographic density change in a cohort of premenopausal women receiving tamoxifen for breast cancer prevention over 5 years

Background

A decrease in breast density due to tamoxifen preventive therapy might indicate greater benefit from the drug. It is not known whether mammographic density continues to decline after 1 year of therapy, or whether measures of breast density change are sufficiently stable for personalised recommendations.

Methods

Mammographic density was measured annually over up to 5 years in premenopausal women with no previous diagnosis of breast cancer but at increased risk of breast cancer attending a family-history clinic in Manchester, UK (baseline 2010-2013). Tamoxifen (20 mg/day) for prevention was prescribed for up to 5 years in one group; the other group did not receive tamoxifen and were matched by age. Fully automatic methods were used on mammograms over the 5-year follow-up: three area-based measures (NN-VAS, Stratus, Densitas) and one volumetric (Volpara). Additionally, percentage breast density at baseline and first follow-up mammograms was measured visually. The size of density declines at the first follow-up mammogram and thereafter was estimated using a linear mixed model adjusted for age and body mass index. The stability of density change at 1 year was assessed by evaluating mean squared error loss from predictions based on individual or mean density change at 1 year.

Results

Analysis used mammograms from 126 healthy premenopausal women before and as they received tamoxifen for prevention (median age 42 years) and 172 matched controls (median age 41 years), with median 3 years follow-up. There was a strong correlation between percentage density measures used on the same mammogram in both the tamoxifen and no tamoxifen groups (all correlation coeficients > 0.8). Tamoxifen reduced mean breast density in year 1 by approximately 17–25% of the inter-quartile range of four automated percentage density measures at baseline, and from year 2, it decreased further by approximately 2–7% per year. Predicting change at 2 years using individual change at 1 year was approximately 60–300% worse than using mean change at 1year.

Conclusions

All measures showed a consistent and large average tamoxifen-induced change in density over the first year, and a continued decline thereafter. However, these measures of density change at 1 year were not stable on an individual basis.

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).

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Uptake of pre-symptomatic testing for BRCA1 and BRCA2 is age, gender, offspring and time-dependent

BACKGROUND

Genetic testing for BRCA1 and BRCA2 pathogenic variants (PVs) has been available in North West England since 1995. We assessed uptake of pre-symptomatic testing in 1564 families with PVs over a 24.5year follow-up (FU) period.

METHODS

First-degree relatives (FDRs) in families with BRCA1 or BRCA2 PVs were eligible from date of index family report if unaffected by a relevant cancer and alive at report date. FDRs were censored as not having undergone a pre-symptomatic test at diagnosis of a relevant cancer, date of death, age 93 or 30/03/2019. Time to uptake of pre-symptomatic testing was assessed by Kaplan-Meier curves, by gender and children.

RESULTS

2554 male and 3115 female FDRs were eligible. Overall uptake was 775 (30.3%) in men and 1935 (62.1%) in women. This increased at 15 years to 33.6% and 67.9%, and continued to rise until 24 years (p<0.001). For women, the 29-year to 39-year age group had the highest uptake at 10 years FU (72.5%; p<0.01), whereas the 50-year to 59-year age group was highest in men (37.2%; p<0.01). Women <18 years at the time of familial variant identification had lower initial uptake, but this rose to >80% by 15 years. Uptake was higher in parous women (p<0.001) and in men with daughters (p<0.0001).

CONCLUSION

Uptake of BRCA1/2 pre-symptomatic testing is age, gender and time-dependent, and higher in women with children and men with daughters.

A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density

Panels of single nucleotide polymorphisms (SNPs) stratify risk for breast cancer in women from the general population, but studies are needed assess their use in a fully comprehensive model including classical risk factors, mammographic density and more than 100 SNPs associated with breast cancer. A case-control study was designed (1,668 controls, 405 cases) in women aged 47-73 years attending routine screening in Manchester UK, and enrolled in a wider study to assess methods for risk assessment. Risk from classical questionnaire risk factors was assessed using the Tyrer-Cuzick model; mean percentage visual mammographic density was scored by two independent readers. DNA extracted from saliva was genotyped at selected SNPs using the OncoArray. A predefined polygenic risk score based on 143 SNPs was calculated (SNP143). The odds ratio (OR, and 95% confidence interval, CI) per interquartile range (IQ-OR) of SNP143 was estimated unadjusted and adjusted for Tyrer-Cuzick and breast density. Secondary analysis assessed risk by oestrogen receptor (ER) status. The primary polygenic risk score was well calibrated (O/E OR 1.10, 95% CI 0.86-1.34) and accuracy was retained after adjustment for Tyrer-Cuzick risk and mammographic density (IQ-OR unadjusted 2.12, 95% CI% 1.75-2.42; adjusted 2.06, 95% CI 1.75-2.42). SNP143 was a risk factor for ER+ and ER- breast cancer (adjusted IQ-OR, ER+ 2.11, 95% CI 1.78-2.51; ER- 1.81, 95% CI 1.16-2.84). In conclusion, polygenic risk scores based on a large number of SNPs improve risk stratification in combination with classical risk factors and mammographic density, and SNP143 was similarly predictive for ER-positive and ER-negative disease.

Risk of Contralateral Breast Cancer in Women with and without Pathogenic Variants in BRCA1, BRCA2, and TP53 Genes in Women with Very Early-Onset (<36 Years) Breast Cancer

Early age at diagnosis of breast cancer is a known risk factor for hereditary predisposition and some studies show a high risk of contralateral breast cancer in BRCA1 carriers diagnosed at very young ages. However, little is published on the risk of TP53 carriers. 397 women with breast cancer diagnosed <36 years of age were obtained from three sources: (i) a population-based study of 283 women diagnosed sequentially from 1980-1997 in North-West England, (ii) referrals to the Genomic Medicine Department at St Mary's Hospital from 1990-2018, and (iii) individuals from (i) and the Family History Clinic at Wythenshawe Hospital South Manchester who tested negative for pathogenic variants (PV) in all three genes. Sequencing of BRCA1, BRCA2, and TP53 genes was carried out alongside tests for copy number for PV on all referred women. Rates of contralateral breast cancer were censored at death, last assessment, or risk-reducing mastectomy. In total, 47 TP53, 218 BRCA1, and 132 BRCA2 PV carriers were identified with breast cancer diagnosed aged 35 years and under, as well as a representative sample of 261 not known to carry a PV in BRCA1, BRCA2, and TP53. Annual rates of contralateral breast cancer (and percentage of synchronous breast cancers) were TP53: 7.03% (4.3%), BRCA1: 3.57% (1.8%), and BRCA2: 2.63% (1.5%). In non-PV carriers, contralateral rates in isolated presumed/tested non-carrier cases with no family history were 0.56%, and for those with a family history, 0.69%. Contralateral breast cancer rates are substantial in TP53, BRCA1, and BRCA2 PV carriers diagnosed with breast cancer aged 35 and under. Women need to be advised to help make informed decisions on contralateral mastectomy, guided by life expectancy from their index tumor.

Incidence of mosaicism in 1055 de novo NF2 cases: much higher than previous estimates with high utility of next-generation sequencing

PURPOSE

To evaluate the incidence of mosaicism in de novo neurofibromatosis 2 (NF2).

METHODS

Patients fulfilling NF2 criteria, but with no known affected family member from a previous generation (n = 1055), were tested for NF2 variants in lymphocyte DNA and where available tumor DNA. The proportion of individuals with a proven or presumed mosaic NF2 variant was assessed and allele frequencies of identified variants evaluated using next-generation sequencing.

RESULTS

The rate of proven/presumed mosaicism was 232/1055 (22.0%). However, nonmosaic heterozygous pathogenic variants were only identified in 387/1055 (36.7%). When variant detection rates in second generation nonmosaics were applied to de novo cases, we assessed the overall probable mosaicism rate to be 59.7%. This rate differed by age from 21.7% in those presenting with bilateral vestibular schwannoma <20 years to 80.7% in those aged ≥60 years. A mosaic variant was detected in all parents of affected children with a single-nucleotide pathogenic NF2 variant.

CONCLUSION

This study has identified a very high probable mosaicism rate in de novo NF2, probably making NF2 the condition with the highest expressed rate of mosaicism in de novo dominant disease that is nonlethal in heterozygote form. Risks to offspring are small and probably correlate with variant allele frequency detected in blood.

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.

Electronic supplementary material

The online version of this article (10.1007/s10549-019-05210-2) contains supplementary material, which is available to authorized users.

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND

We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.

METHODS

Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).

RESULTS

We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster.

CONCLUSIONS

We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

Prediction of reader estimates of mammographic density using convolutional neural networks

Mammographic density is an important risk factor for breast cancer. In recent research, percentage density assessed visually using visual analogue scales (VAS) showed stronger risk prediction than existing automated density measures, suggesting readers may recognize relevant image features not yet captured by hand-crafted algorithms. With deep learning, it may be possible to encapsulate this knowledge in an automatic method. We have built convolutional neural networks (CNN) to predict density VAS scores from full-field digital mammograms. The CNNs are trained using whole-image mammograms, each labeled with the average VAS score of two independent readers. Each CNN learns a mapping between mammographic appearance and VAS score so that at test time, they can predict VAS score for an unseen image. Networks were trained using 67,520 mammographic images from 16,968 women and for model selection we used a dataset of 73,128 images. Two case-control sets of contralateral mammograms of screen detected cancers and prior images of women with cancers detected subsequently, matched to controls on age, menopausal status, parity, HRT and BMI, were used for evaluating performance on breast cancer prediction. In the case-control sets, odd ratios of cancer in the highest versus lowest quintile of percentage density were 2.49 (95% CI: 1.59 to 3.96) for screen-detected cancers and 4.16 (2.53 to 6.82) for priors, with matched concordance indices of 0.587 (0.542 to 0.627) and 0.616 (0.578 to 0.655), respectively. There was no significant difference between reader VAS and predicted VAS for the prior test set (likelihood ratio chi square, p = 0.134 ). Our fully automated method shows promising results for cancer risk prediction and is comparable with human performance.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Schwannomatosis: a genetic and epidemiological study

OBJECTIVES

Schwannomatosis is a dominantly inherited condition predisposing to schwannomas of mainly spinal and peripheral nerves with some diagnostic overlap with neurofibromatosis-2 (NF2), but the underlying epidemiology is poorly understood. We present the birth incidence and prevalence allowing for overlap with NF2.

METHODS

Schwannomatosis and NF2 cases were ascertained from the Manchester region of England (population=4.8 million) and from across the UK. Point prevalence and birth incidence were calculated from regional birth statistics. Genetic analysis was also performed on NF2, LZTR1 and SMARCB1 on blood and tumour DNA samples when available.

RESULTS

Regional prevalence for schwannomatosis and NF2 were 1 in 126 315 and 50 500, respectively, with calculated birth incidences of 1 in 68 956 and 1 in 27 956. Mosaic NF2 causes a substantial overlap with schwannomatosis resulting in the misdiagnosis of at least 9% of schwannomatosis cases. LZTR1-associated schwannomatosis also causes a small number of cases that are misdiagnosed with NF2 (1%-2%), due to the occurrence of a unilateral vestibular schwannoma. Patients with schwannomatosis had lower numbers of non-vestibular cranial schwannomas, but more peripheral and spinal nerve schwannomas with pain as a predominant presenting symptom. Life expectancy was significantly better in schwannomatosis (mean age at death 76.9) compared with NF2 (mean age at death 66.2; p=0.004).

CONCLUSIONS

Within the highly ascertained North-West England population, schwannomatosis has less than half the birth incidence and prevalence of NF2.

Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds

BACKGROUND

The percentage of mammographic dense tissue (PD) defined by pixel value threshold is a well-established risk factor for breast cancer. Recently there has been some evidence to suggest that an increased threshold based on visual assessment could improve risk prediction. It is unknown, however, whether this also applies to volumetric density using digital raw mammograms.

METHOD

Two case-control studies nested within a screening cohort (ages of participants 46-73 years) from Manchester UK were used. In the first study (317 cases and 947 controls) cases were detected at the first screen; whereas in the second study (318 cases and 935 controls), cases were diagnosed after the initial mammogram. Volpara software was used to estimate dense tissue height at each pixel point, and from these, volumetric and area-based PD were computed at a range of thresholds. Volumetric and area-based PDs were evaluated using conditional logistic regression, and their predictive ability was assessed using the Akaike information criterion (AIC) and matched concordance index (mC).

RESULTS

The best performing volumetric PD was based on a threshold of 5 mm of dense tissue height (which we refer to as VPD5), and the best areal PD was at a threshold level of 6 mm (which we refer to as APD6), using pooled data and in both studies separately. VPD5 showed a modest improvement in prediction performance compared to the original volumetric PD by Volpara with ΔAIC = 5.90 for the pooled data. APD6, on the other hand, shows much stronger evidence for better prediction performance, with ΔAIC = 14.52 for the pooled data, and mC increased slightly from 0.567 to 0.577.

CONCLUSION

These results suggest that imposing a 5 mm threshold on dense tissue height for volumetric PD could result in better prediction of cancer risk. There is stronger evidence that area-based density with a 6 mm threshold gives better prediction than the original volumetric density metric.

Use of Single-Nucleotide Polymorphisms and Mammographic Density Plus Classic Risk Factors for Breast Cancer Risk Prediction

IMPORTANCE

Single-nucleotide polymorphisms (SNPs) have demonstrated an association with breast cancer susceptibility, but there is limited evidence on how to incorporate them into current breast cancer risk prediction models.

OBJECTIVE

To determine whether a panel of 18 SNPs (SNP18) may be used to predict breast cancer in combination with classic risk factors and mammographic density.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study enrolled a subcohort of 9363 women, aged 46 to 73 years, without a previous breast cancer diagnosis from the larger prospective cohort of the PROCAS study (Predicting Risk of Cancer at Screening) specifically to evaluate breast cancer risk-assessment methods. Enrollment took place from October 2009 through June 2015 from multiple population-based screening centers in Greater Manchester, England. Follow-up continued through January 5, 2017.

EXPOSURES

Genotyping of 18 SNPs, visual-assessment percentage mammographic density, and classic risk assessed by the Tyrer-Cuzick risk model from a self-completed questionnaire at cohort entry.

MAIN OUTCOMES AND MEASURES

The predictive ability of SNP18 for breast cancer diagnosis (invasive and ductal carcinoma in situ) was assessed using logistic regression odds ratios per interquartile range of the predicted risk.

RESULTS

A total of 9363 women were enrolled in this study (mean [range] age, 59 [46-73] years). Of these, 466 were found to have breast cancer (271 prevalent; 195 incident). SNP18 was similarly predictive when unadjusted or adjusted for mammographic density and classic factors (odds ratios per interquartile range, respectively, 1.56; 95% CI, 1.38-1.77 and 1.53; 95% CI, 1.35-1.74), with observed risks being very close to expected (adjusted observed-to-expected odds ratio, 0.98; 95% CI, 0.69-1.28). A combined risk assessment indicated 18% of the subcohort to be at 5% or greater 10-year risk, compared with 30% of all cancers, 35% of interval-detected cancers, and 42% of stage 2+ cancers. In contrast, 33% of the subcohort were at less than 2% risk but accounted for only 18%, 17%, and 15% of the total, interval, and stage 2+ breast cancers, respectively.

CONCLUSIONS AND RELEVANCE

SNP18 added substantial information to risk assessment based on the Tyrer-Cuzick model and mammographic density. A combined risk is likely to aid risk-stratified screening and prevention strategies.

Penetrance estimates for BRCA1, BRCA2 (also applied to Lynch syndrome) based on presymptomatic testing: a new unbiased method to assess risk?

PURPOSE

The identification of BRCA1, BRCA2 or mismatch repair (MMR) pathogenic gene variants in familial breast/ovarian/colorectal cancer families facilitates predictive genetic testing of at-risk relatives. However, controversy still exists regarding overall lifetime risks of cancer in individuals testing positive.

METHODS

We assessed the penetrance of BRCA1, BRCA2, MLH1 and MSH2 mutations in men and women using Bayesian calculations based on ratios of positive to negative presymptomatic testing by 10-year age cohorts. Mutation position was also assessed for BRCA1/BRCA2. RESULTS: Using results from 2264 presymptomatic tests in first-degree relatives (FDRs) of mutation carriers in BRCA1 and BRCA2 and 646 FDRs of patients with MMR mutations, we assessed overall associated cancer penetrance to age of 68 years as 73% (95% CI 61% to 82%) for BRCA1, 60% (95% CI 49% to 71%) for BRCA2, 95% (95% CI 76% to 99%) for MLH1% and 61% (95% CI 49% to 76%) for MSH2. There was no evidence for significant penetrance for males in BRCA1 or BRCA2 families and males had equivalent penetrance to females with Lynch syndrome. Mutation position and degree of family history influenced penetrance in BRCA2 but not BRCA1. CONCLUSION: We describe a new method for assessing penetrance in cancer-prone syndromes. Results are in keeping with published prospective series and present modern-day estimates for overall disease penetrance that bypasses retrospective series biases.

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.