Re-attendance in supplemental breast MRI screening rounds of the DENSE trial for women with extremely dense breasts.

OBJECTIVES: Supplemental MRI screening improves early breast cancer detection and reduces interval cancers in women with extremely dense breasts in a cost-effective way. Recently, the European Society of Breast Imaging recommended offering MRI screening to women with extremely dense breasts, but the debate on whether to implement it in breast cancer screening programs is ongoing. Insight into the participant experience and willingness to re-attend is important for this discussion. METHODS: We calculated the re-attendance rates of the second and third MRI screening rounds of the DENSE trial. Moreover, we calculated age-adjusted odds ratios (ORs) to study the association between characteristics and re-attendance. Women who discontinued MRI screening were asked to provide one or more reasons for this. RESULTS: The re-attendance rates were 81.3% (3458/4252) and 85.2% (2693/3160) in the second and third MRI screening round, respectively. A high age (> 65 years), a very low BMI, lower education, not being employed, smoking, and no alcohol consumption were correlated with lower re-attendance rates. Moderate or high levels of pain, discomfort, or anxiety experienced during the previous MRI screening round were correlated with lower re-attendance rates. Finally, a plurality of women mentioned an examination-related inconvenience as a reason to discontinue screening (39.1% and 34.8% in the second and third screening round, respectively). CONCLUSIONS: The willingness of women with dense breasts to re-attend an ongoing MRI screening study is high. However, emphasis should be placed on improving the MRI experience to increase the re-attendance rate if widespread supplemental MRI screening is implemented. CLINICAL RELEVANCE STATEMENT: For many women, MRI is an acceptable screening method, as re-attendance rates were high - even for screening in a clinical trial setting. To further enhance the (re-)attendance rate, one possible approach could be improving the overall MRI experience. KEY POINTS: • The willingness to re-attend in an ongoing MRI screening study is high. • Pain, discomfort, and anxiety in the previous MRI screening round were related to lower re-attendance rates. • Emphasis should be placed on improving MRI experience to increase the re-attendance rate in supplemental MRI screening.

Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts.

Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. MRI was performed in eight hospitals between December 2011 and January 2016. After segmentation of fibroglandular tissue, quantitative features (including volumetric density, volumetric morphology, and enhancement characteristics) of the parenchyma were extracted from baseline MRI scans. Principal component analysis was used to identify parenchymal measures with the greatest variance. Multivariable Cox proportional hazards regression was applied to assess the association between breast cancer occurrence and quantitative parenchymal features, followed by stratification of significant features into tertiles. Results A total of 4553 women (mean age, 55.7 years ± 6 [SD]) with extremely dense breasts were included; of these women, 122 (3%) were diagnosed with breast cancer. Five principal components representing 96% of the variance were identified, and the component explaining the greatest independent variance (42%) consisted of MRI features relating to volume of enhancing parenchyma. Multivariable analysis showed that volume of enhancing parenchyma was associated with breast cancer occurrence (hazard ratio [HR], 1.09; 95% CI: 1.01, 1.18; P = .02). Additionally, women in the high tertile of volume of enhancing parenchyma showed a breast cancer occurrence twice that of women in the low tertile (HR, 2.09; 95% CI: 1.25, 3.61; P = .005). Conclusion In women with extremely dense breasts, a high volume of enhancing parenchyma on baseline DCE MRI scans was associated with increased occurrence of breast cancer as compared with a low volume of enhancing parenchyma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grimm in this issue.

Supplemental MRI Screening for Women with Extremely Dense Breast Tissue.

BACKGROUND: Extremely dense breast tissue is a risk factor for breast cancer and limits the detection of cancer with mammography. Data are needed on the use of supplemental magnetic resonance imaging (MRI) to improve early detection and reduce interval breast cancers in such patients. METHODS: In this multicenter, randomized, controlled trial in the Netherlands, we assigned 40,373 women between the ages of 50 and 75 years with extremely dense breast tissue and normal results on screening mammography to a group that was invited to undergo supplemental MRI or to a group that received mammography screening only. The groups were assigned in a 1:4 ratio, with 8061 in the MRI-invitation group and 32,312 in the mammography-only group. The primary outcome was the between-group difference in the incidence of interval cancers during a 2-year screening period. RESULTS: The interval-cancer rate was 2.5 per 1000 screenings in the MRI-invitation group and 5.0 per 1000 screenings in the mammography-only group, for a difference of 2.5 per 1000 screenings (95% confidence interval [CI], 1.0 to 3.7; P<0.001). Of the women who were invited to undergo MRI, 59% accepted the invitation. Of the 20 interval cancers that were diagnosed in the MRI-invitation group, 4 were diagnosed in the women who actually underwent MRI (0.8 per 1000 screenings) and 16 in those who did not accept the invitation (4.9 per 1000 screenings). The MRI cancer-detection rate among the women who actually underwent MRI screening was 16.5 per 1000 screenings (95% CI, 13.3 to 20.5). The positive predictive value was 17.4% (95% CI, 14.2 to 21.2) for recall for additional testing and 26.3% (95% CI, 21.7 to 31.6) for biopsy. The false positive rate was 79.8 per 1000 screenings. Among the women who underwent MRI, 0.1% had either an adverse event or a serious adverse event during or immediately after the screening. CONCLUSIONS: The use of supplemental MRI screening in women with extremely dense breast tissue and normal results on mammography resulted in the diagnosis of significantly fewer interval cancers than mammography alone during a 2-year screening period. (Funded by the University Medical Center Utrecht and others; DENSE ClinicalTrials.gov number, NCT01315015.).

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI examinations to reduce radiologist workload are needed. Purpose To determine the feasibility of an automated triaging method using deep learning (DL) to dismiss the highest number of MRI examinations without lesions while still identifying malignant disease. Materials and Methods This secondary analysis of data from the Dense Tissue and Early Breast Neoplasm Screening, or DENSE, trial evaluated breast MRI examinations from the first screening round performed in eight hospitals between December 2011 and January 2016. A DL model was developed to differentiate between breasts with lesions and breasts without lesions. The model was trained to dismiss breasts with normal phenotypical variation and to triage lesions (Breast Imaging Reporting and Data System [BI-RADS] categories 2-5) using eightfold internal-external validation. The model was trained on data from seven hospitals and tested on data from the eighth hospital, alternating such that each hospital was used once as an external test set. Performance was assessed using receiver operating characteristic analysis. At 100% sensitivity for malignant disease, the fraction of examinations dismissed from radiologic review was estimated. Results A total of 4581 MRI examinations of extremely dense breasts from 4581women (mean age, 54.3 years; interquartile range, 51.5-59.8 years) were included. Of the 9162 breasts, 838 had at least one lesion (BI-RADS category 2-5, of which 77 were malignant) and 8324 had no lesions. At 100% sensitivity for malignant lesions, the DL model considered 90.7% (95% CI: 86.7, 94.7) of the MRI examinations with lesions to be nonnormal and triaged them to radiologic review. The DL model dismissed 39.7% (95% CI: 30.0, 49.4) of the MRI examinations without lesions. The DL model had an average area under the receiver operating characteristic curve of 0.83 (95% CI: 0.80, 0.85) in the differentiation between normal breast MRI examinations and MRI examinations with lesions. Conclusion Automated analysis of breast MRI examinations in women with dense breasts dismissed nearly 40% of MRI scans without lesions while not missing any cancers. ClinicalTrials.gov: NCT01315015 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Joe in this issue.

Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial.

Background High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive screenings. Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed. Purpose To build prediction models based on clinical characteristics and MRI findings to reduce the rate of false-positive screening MRI findings in women with extremely dense breasts. Materials and Methods Clinical characteristics and MRI findings in Dutch breast cancer screening participants (age range, 50-75 years) with positive first-round MRI screening results (Breast Imaging Reporting and Data System 3, 4, or 5) after a normal screening mammography with extremely dense breasts (Volpara density category 4) were prospectively collected within the randomized controlled Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial from December 2011 through November 2015. In this secondary analysis, prediction models were built using multivariable logistic regression analysis to distinguish true-positive MRI screening findings from false-positive ones. Results Among 454 women (median age, 52 years; interquartile range, 50-57 years) with a positive MRI result in a first supplemental MRI screening round, 79 were diagnosed with breast cancer (true-positive findings), and 375 had false-positive MRI results. The full prediction model (area under the receiver operating characteristics curve [AUC], 0.88; 95% CI: 0.84, 0.92), based on all collected clinical characteristics and MRI findings, could have prevented 45.5% (95% CI: 39.6, 51.5) of false-positive recalls and 21.3% (95% CI: 15.7, 28.3) of benign biopsies without missing any cancers. The model solely based on readily available MRI findings and age had a comparable performance (AUC, 0.84; 95% CI: 0.79, 0.88; P = .15) and could have prevented 35.5% (95% CI: 30.4, 41.1) of false-positive MRI screening results and 13.0% (95% CI: 8.8, 18.6) of benign biopsies. Conclusion Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive first-round screening MRI rate and benign biopsy rate in women with extremely dense breasts. Clinical trial registration no. NCT01315015 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Imbriaco in this issue.

Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial.

Background In the first (prevalent) supplemental MRI screening round of the Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial, a considerable number of breast cancers were found at the cost of an increased false-positive rate (FPR). In incident screening rounds, a lower cancer detection rate (CDR) is expected due to a smaller pool of prevalent cancers, and a reduced FPR, due to the availability of prior MRI examinations. Purpose To investigate screening performance indicators of the second round (incidence round) of the DENSE trial. Materials and Methods The DENSE trial (ClinicalTrials.gov: NCT01315015) is embedded within the Dutch population-based biennial mammography screening program for women aged 50-75 years. MRI examinations were performed between December 2011 and January 2016. Women were eligible for the second round when they again had a negative screening mammogram 2 years after their first MRI. The recall rate, biopsy rate, CDR, FPR, positive predictive values, and distributions of tumor characteristics were calculated and compared with results of the first round using 95% CIs and χ2 tests. Results A total of 3436 women (median age, 56 years; interquartile range, 48-64 years) underwent a second MRI screening. The CDR was 5.8 per 1000 screening examinations (95% CI: 3.8, 9.0) compared with 16.5 per 1000 screening examinations (95% CI: 13.3, 20.5) in the first round. The FPR was 26.3 per 1000 screening examinations (95% CI: 21.5, 32.3) in the second round versus 79.8 per 1000 screening examinations (95% CI: 72.4, 87.9) in the first round. The positive predictive value for recall was 18% (20 of 110 participants recalled; 95% CI: 12.1, 26.4), and the positive predictive value for biopsy was 24% (20 of 84 participants who underwent biopsy; 95% CI: 16.0, 33.9), both comparable to that of the first round. All tumors in the second round were stage 0-I and node negative. Conclusion The incremental cancer detection rate in the second round was 5.8 per 1000 screening examinations-compared with 16.5 per 1000 screening examinations in the first round. This was accompanied by a strong reduction in the number of false-positive results. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Moy and Gao in this issue.

Nutrient-wide association study of 92 foods and nutrients and breast cancer risk.

BACKGROUND: Several dietary factors have been reported to be associated with risk of breast cancer, but to date, unequivocal evidence only exists for alcohol consumption. We sought to systematically assess the association between intake of 92 foods and nutrients and breast cancer risk using a nutrient-wide association study. METHODS: Using data from 272,098 women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we assessed dietary intake of 92 foods and nutrients estimated by dietary questionnaires. Cox regression was used to quantify the association between each food/nutrient and risk of breast cancer. A false discovery rate (FDR) of 0.05 was used to select the set of foods and nutrients to be replicated in the independent Netherlands Cohort Study (NLCS). RESULTS: Six foods and nutrients were identified as associated with risk of breast cancer in the EPIC study (10,979 cases). Higher intake of alcohol overall was associated with a higher risk of breast cancer (hazard ratio (HR) for a 1 SD increment in intake = 1.05, 95% CI 1.03-1.07), as was beer/cider intake and wine intake (HRs per 1 SD increment = 1.05, 95% CI 1.03-1.06 and 1.04, 95% CI 1.02-1.06, respectively), whereas higher intakes of fibre, apple/pear, and carbohydrates were associated with a lower risk of breast cancer (HRs per 1 SD increment = 0.96, 95% CI 0.94-0.98; 0.96, 95% CI 0.94-0.99; and 0.96, 95% CI 0.95-0.98, respectively). When evaluated in the NLCS (2368 cases), estimates for each of these foods and nutrients were similar in magnitude and direction, with the exception of beer/cider intake, which was not associated with risk in the NLCS. CONCLUSIONS: Our findings confirm a positive association of alcohol consumption and suggest an inverse association of dietary fibre and possibly fruit intake with breast cancer risk.

Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study.

BACKGROUND: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. METHODS: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. RESULTS: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. CONCLUSION: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.

The Physiological MicroRNA Landscape in Nipple Aspirate Fluid: Differences and Similarities with Breast Tissue, Breast Milk, Plasma and Serum.

BACKGROUND: MicroRNAs (miRNAs) target 60% of human messenger RNAs and can be detected in tissues and biofluids without loss of stability during sample processing, making them highly appraised upcoming biomarkers for evaluation of disease. However, reporting of the abundantly expressed miRNAs in healthy samples is often surpassed. Here, we characterized for the first time the physiological miRNA landscape in a biofluid of the healthy breast: nipple aspirate fluid (NAF), and compared NAF miRNA expression patterns with publically available miRNA expression profiles of healthy breast tissue, breast milk, plasma and serum. METHODS: MiRNA RT-qPCR profiling of NAF (n = 41) and serum (n = 23) samples from two healthy female cohorts was performed using the TaqMan OpenArray Human Advanced MicroRNA 754-Panel. MiRNA quantification data based on non-targeted or multi-targeted profiling techniques for breast tissue, breast milk, plasma and serum were retrieved from the literature by means of a systematic search. MiRNAs from each individual study were orderly ranked between 1 and 50, combined into an overall ranking per sample type and compared. RESULTS: NAF expressed 11 unique miRNAs and shared 21/50 miRNAs with breast tissue. Seven miRNAs were shared between the five sample types. Overlap between sample types varied between 42% and 62%. Highly ranked NAF miRNAs have established roles in breast carcinogenesis. CONCLUSION: This is the first study to characterize and compare the unique physiological NAF-derived miRNA landscape with the physiological expression pattern in breast tissue, breast milk, plasma and serum. Breast-specific sources did not mutually overlap more than with systemic sources. Given their established role in carcinogenesis, NAF miRNA assessment could be a valuable tool in breast tumor diagnostics.

Adherence to the World Cancer Research Fund/American Institute for Cancer Research cancer prevention recommendations and risk of in situ breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

BACKGROUND: Even though in situ breast cancer (BCIS) accounts for a large proportion of the breast cancers diagnosed, few studies have investigated potential risk factors for BCIS. Their results suggest that some established risk factors for invasive breast cancer have a similar impact on BCIS risk, but large population-based studies on lifestyle factors and BCIS risk are lacking. Thus, we investigated the association between lifestyle and BCIS risk within the European Prospective Investigation into Cancer and Nutrition cohort. METHODS: Lifestyle was operationalized by a score reflecting the adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations. The recommendations utilized in these analyses were the ones pertinent to healthy body weight, physical activity, consumption of plant-based foods, energy-dense foods, red and processed meat, and sugary drinks and alcohol, as well as the recommendation on breastfeeding. Cox proportional hazards regression was used to assess the association between lifestyle score and BCIS risk. The results were presented as hazard ratios (HR) and corresponding 95% confidence intervals (CI). RESULTS: After an overall median follow-up time of 14.9 years, 1277 BCIS cases were diagnosed. Greater adherence to the WCRF/AICR cancer prevention recommendations was not associated with BCIS risk (HR = 0.98, 95% CI 0.93-1.03; per one unit of increase; multivariable model). An inverse association between the lifestyle score and BCIS risk was observed in study centers, where participants were recruited mainly via mammographic screening and attended additional screening throughout follow-up (HR = 0.85, 95% CI 0.73-0.99), but not in the remaining ones (HR = 0.99, 95% CI 0.94-1.05). CONCLUSIONS: While we did not observe an overall association between lifestyle and BCIS risk, our results indicate that lifestyle is associated with BCIS risk among women recruited via screening programs and with regular screening participation. This suggests that a true inverse association between lifestyle habits and BCIS risk in the overall cohort may have been masked by a lack of information on screening attendance. The potential inverse association between lifestyle and BCIS risk in our analyses is consistent with the inverse associations between lifestyle scores and breast cancer risk reported from previous studies.

Non-occupational physical activity levels of shift workers compared with non-shift workers.

OBJECTIVES: Lack of physical activity (PA) has been hypothesised as an underlying mechanism in the adverse health effects of shift work. Therefore, our aim was to compare non-occupational PA levels between shift workers and non-shift workers. Furthermore, exposure-response relationships for frequency of night shifts and years of shift work regarding non-occupational PA levels were studied. METHODS: Data of 5980 non-shift workers and 532 shift workers from the European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL) were used in these cross-sectional analyses. Time spent (hours/week) in different PA types (walking/cycling/exercise/chores) and intensities (moderate/vigorous) were calculated based on self-reported PA. Furthermore, sports were operationalised as: playing sports (no/yes), individual versus non-individual sports, and non-vigorous-intensity versus vigorous-intensity sports. PA levels were compared between shift workers and non-shift workers using Generalized Estimating Equations and logistic regression. RESULTS: Shift workers reported spending more time walking than non-shift workers (B=2.3 (95% CI 1.2 to 3.4)), but shift work was not associated with other PA types and any of the sports activities. Shift workers who worked 1-4 night shifts/month (B=2.4 (95% CI 0.6 to 4.3)) and ≥5 night shifts/month (B=3.7 (95% CI 1.8 to 5.6)) spent more time walking than non-shift workers. No exposure-response relationships were found between years of shift work and PA levels. CONCLUSIONS: Shift workers spent more time walking than non-shift workers, but we observed no differences in other non-occupational PA levels. To better understand if and how PA plays a role in the negative health consequences of shift work, our findings need to be confirmed in future studies.

A treelet transform analysis to relate nutrient patterns to the risk of hormonal receptor-defined breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

OBJECTIVE: Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology. DESIGN: Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison. SETTING: The European Prospective Investigation into Cancer and Nutrition (EPIC). SUBJECTS: Women (n 334 850) from the EPIC study. RESULTS: The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in ß-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, P trend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, P trend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, P trend<0·01). CONCLUSIONS: TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.

The effect of weight change on changes in breast density measures over menopause in a breast cancer screening cohort.

INTRODUCTION: High weight and high percentage mammographic breast density are both breast cancer risk factors but are negatively correlated. Therefore, we wanted to obtain more insight into this apparent paradox. METHODS: We investigated in a longitudinal study how weight change over menopause is related to changes in mammographic breast features. Five hundred ninety-one participants of the EPIC-NL cohort were divided into three groups according to their prospectively measured weight change over menopause: (1) weight loss (more than -3.0 %), (2) stable weight (between -3.0 % and +3.0 %), and (3) weight gain (more than 3.0 %). SPSS GLM univariate analysis was used to determine both the mean breast measure changes in, and the trend over, the weight change groups. RESULTS: Over a median period of 5 years, the mean changes in percent density in these groups were -5.0 % (95 % confidence interval (CI) -8.0; -2.1), -6.8 % (95 % CI -9.0; -4.5), and -10.2 % (95 % CI -12.5; -7.9), respectively (P-trend = 0.001). The mean changes in dense area were -16.7 cm(2) (95 % CI -20.1; -13.4), -16.4 cm(2) (95 % CI -18.9; -13.9), and -18.1 cm(2) (95 % CI -20.6; -15.5), respectively (P-trend = 0.437). Finally, the mean changes in nondense area were -6.1 cm(2) (95 % CI -11.9; -0.4), -0.6 cm(2) (95 % CI -4.9; 3.8), and 5.3 cm(2) (95 % CI 0.9; 9.8), respectively (P-trend < 0.001). CONCLUSIONS: Going through menopause is associated with a decrease in both percent density and dense area. Owing to an increase in the nondense tissue, the decrease in percent density is largest in women who gain weight. The decrease in dense area is not related to weight change. So the fact that both high percent density and high weight or weight gain are associated with high postmenopausal breast cancer risk can probably not be explained by an increase (or slower decrease) of dense area in women gaining weight compared with women losing weight or maintaining a stable weight. These results suggest that weight and dense area are presumably two independent postmenopausal breast cancer risk factors.

Plasma carotenoids, vitamin C, retinol and tocopherols levels and pancreatic cancer risk within the European Prospective Investigation into Cancer and Nutrition: a nested case-control study: plasma micronutrients and pancreatic cancer risk.

Evidence of a protective effect of several antioxidants and other nutrients on pancreatic cancer risk is inconsistent. The aim of this study was to investigate the association for prediagnostic plasma levels of carotenoids, vitamin C, retinol and tocopherols with risk of pancreatic cancer in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). 446 incident exocrine pancreatic cancer cases were matched to 446 controls by age at blood collection, study center, sex, date and time of blood collection, fasting status and hormone use. Plasma carotenoids (α- and ß-carotene, lycopene, ß-cryptoxanthin, canthaxanthin, zeaxanthin and lutein), α- and γ-tocopherol and retinol were measured by reverse phase high-performance liquid chromatography and plasma vitamin C by a colorimetric assay. Incidence rate ratios (IRRs) with 95% confidence intervals (95%CIs) for pancreatic cancer risk were estimated using a conditional logistic regression analysis, adjusted for smoking status, smoking duration and intensity, waist circumference, cotinine levels and diabetes status. Inverse associations with pancreatic cancer risk were found for plasma ß-carotene (IRR highest vs. lowest quartile 0.52, 95%CI 0.31-0.88, p for trend = 0.02), zeaxanthin (IRR highest vs. lowest quartile 0.53, 95%CI 0.30-0.94, p for trend = 0.06) and α-tocopherol (IRR highest vs. lowest quartile 0.62, 95%CI 0.39-0.99, p for trend = 0.08. For α- and ß-carotene, lutein, sum of carotenoids and γ-tocopherol, heterogeneity between geographical regions was observed. In conclusion, our results show that higher plasma concentrations of ß-carotene, zeaxanthin and α-tocopherol may be inversely associated with risk of pancreatic cancer, but further studies are warranted.

MR Imaging as an Additional Screening Modality for the Detection of Breast Cancer in Women Aged 50-75 Years with Extremely Dense Breasts: The DENSE Trial Study Design.

Women with extremely dense breasts have an increased risk of breast cancer and lower mammographic tumor detectability. Nevertheless, in most countries, these women are currently screened with mammography only. Magnetic resonance (MR) imaging has the potential to improve breast cancer detection at an early stage because of its higher sensitivity. However, MR imaging is more expensive and is expected to be accompanied by an increase in the number of false-positive results and, possibly, an increase in overdiagnosis. To study the additional value of MR imaging, a randomized controlled trial (RCT) design is needed in which one group undergoes mammography and the other group undergoes mammography and MR imaging. With this design, it is possible to determine the proportion of interval cancers within each study arm. For this to be an effective screening strategy, the additional cancers detected at MR imaging screening must be accompanied by a subsequent reduction in interval cancers. The Dense Tissue and Early Breast Neoplasm Screening, or DENSE, trial is a multicenter RCT performed in the Dutch biennial population-based screening program (subject age range, 50-75 years). The study was approved by the Dutch Minister of Health, Welfare and Sport. In this study, mammographic density is measured by using a fully automated volumetric method. Participants with extremely dense breasts (American College of Radiology breast density category 4) and a negative result at mammography (Breast Imaging Recording and Data System category 1 or 2) are randomly assigned to undergo additional MR imaging (n = 7237) or to be treated according to current practice (n = 28 948). Participants provide written informed consent before the MR imaging examination, which consists of dynamic breast MR imaging with gadolinium-based contrast medium and is intended to be performed for three consecutive screening rounds. The primary outcome is the difference in the proportions of interval cancers between the study arms. Secondary outcomes are the number of MR imaging screening-detected cancers, proportions of false-positive results, diagnostic yield of MR imaging, tumor characteristics, quality of life, and cost effectiveness.

Geographic variation in volumetric breast density between screening regions in the Netherlands.

OBJECTIVES: Differences in breast density between populations may explain part of the variation in regional breast cancer screening performance. This study aimed to determine whether regional differences in breast density distribution are present in the Dutch screening population. METHODS: As part of the DENSE trial, mammographic density was measured using a fully-automated volumetric method. The regions in our study were based on the geographic coverage of 14 reading units representing a large part of the Netherlands. General linear models were used. RESULTS: Four hundred eighty-five thousand and twenty-one screening participants with a median age of 60 years were included (2013-2014). The proportion of women with heterogeneously or extremely dense breasts ranged from 32.5% to 45.7% between regions. Mean percent dense volume varied between 6.51% (95% confidence interval [CI]: 6.46-6.55) and 7.68% (95% CI: 7.66-7.71). Age differences could not explain the variation. Socio-economic status (SES) was positively associated with volumetric density in all analyses (low SES: 6.95% vs. high SES: 7.63%; p trend < 0.0001), whereas a potential association between urbanisation and breast density only became apparent after SES adjustment. CONCLUSION: There appears to be geographic variation in mammographic density in the Netherlands, emphasizing the importance of including breast density as parameter in the evaluation of screening performance. KEY POINTS: • Mammographic density may affect regional breast cancer screening performance. • Volumetric breast density varies across screening areas. • SES is positively associated with breast density. • Implications of volumetric breast density differences need to be studied further.

Plasma and dietary carotenoids and vitamins A, C and E and risk of colon and rectal cancer in the European Prospective Investigation into Cancer and Nutrition.

Carotenoids and vitamins A, C and E are possibly associated with a reduced colorectal cancer (CRC) risk through antioxidative properties. The association of prediagnostic plasma concentrations and dietary consumption of carotenoids and vitamins A, C and E with the risk of colon and rectal cancer was examined in this case-control study, nested within the European Prospective Investigation into Cancer and Nutrition study. Plasma concentrations of carotenoids (α- and ß-carotene, canthaxanthin, ß-cryptoxanthin, lutein, lycopene, zeaxanthin) and vitamins A (retinol), C and E (α-, ß- and γ- and δ-tocopherol) and dietary consumption of ß-carotene and vitamins A, C and E were determined in 898 colon cancer cases, 501 rectal cancer cases and 1,399 matched controls. Multivariable conditional logistic regression models were performed to estimate incidence rate ratios (IRR) and corresponding 95% confidence intervals (CIs). An association was observed between higher prediagnostic plasma retinol concentration and a lower risk of colon cancer (IRR for highest quartile = 0.63, 95% CI: 0.46, 0.87, p for trend = 0.01), most notably proximal colon cancer (IRR for highest quartile = 0.46, 95% CI: 0.27, 0.77, p for trend = 0.01). Additionally, inverse associations for dietary ß-carotene and dietary vitamins C and E with (distal) colon cancer were observed. Although other associations were suggested, there seems little evidence for a role of these selected compounds in preventing CRC through their antioxidative properties.

Weight change in middle adulthood and breast cancer risk in the EPIC-PANACEA study.

Long-term weight gain (i.e., weight gain since age 20) has been related to higher risk of postmenopausal breast cancer, but a lower risk of premenopausal breast cancer. The effect of weight change in middle adulthood is unclear. We investigated the association between weight change in middle adulthood (i.e., women aged 40-50 years) and the risk of breast cancer before and after the age of 50. We included female participants of the European Prospective Investigation into Cancer and Nutrition cohort, with information on anthropometric measures at recruitment and after a median follow-up of 4.3 years. Annual weight change was categorized using quintiles taking quintile 2 and 3 as the reference category (-0.44 to 0.36 kg/year). Multivariable Cox proportional hazards regression analysis was used to examine the association. 205,723 women were included and 4,663 incident breast cancer cases were diagnosed during a median follow-up of 7.5 years (from second weight assessment onward). High weight gain (Q5: 0.83-4.98 kg/year) was related to a slightly, but significantly higher breast cancer risk (HRQ5_versus_Q2/3 : 1.09, 95% CI: 1.01-1.18). The association was more pronounced for breast cancer diagnosed before or at age 50 (HRQ5_versus_Q2/3 : 1.37, 95% CI: 1.02-1.85). Weight loss was not associated with breast cancer risk. There was no evidence for heterogeneity by hormone receptor status. In conclusion, high weight gain in middle adulthood increases the risk of breast cancer. The association seems to be more pronounced for breast cancer diagnosed before or at age 50. Our results illustrate the importance of avoiding weight gain in middle adulthood.

Degree of urbanization and mammographic density in Dutch breast cancer screening participants: results from the EPIC-NL cohort.

It has been observed that women living in urban areas have a higher mammographic density (MD) compared to women living in rural areas. This association might be explained by regional differences in reproductive and lifestyle factors or perhaps by variation in exposure to ambient air pollution as air pollution particles have been described to show estrogenic activity. We investigated the association between degree of urbanization and MD, and aimed to unravel the underlying etiology. 2,543 EPIC-NL participants were studied, and general linear models were used. Urbanization was categorized into five categories according to the number of addresses/km(2). Information on reproductive and lifestyle factors was obtained from the recruitment questionnaire. Air pollution exposure was estimated using land-use regression models. MD was expressed as percent density (PD) and dense area (DA), and was quantified using Cumulus. Women living in extremely urbanized areas had a higher PD (21.4%, 95% confidence interval (CI) 20.5-22.3%) compared to women living in not urbanized areas (16.1, 95% CI 14.5-17.8%, P trend < 0.01).The association persisted after adjustment for reproductive and lifestyle factors as well as for individual exposure to air pollution (adjusted PDextremely_urbanized = 22.1%, 95% CI 18.0-26.5% versus adjusted PDnot_urbanized = 16.9%, 95% CI 13.0-21.2, P trend < 0.01).The results for DA showed close similarity to the results for PD. We found evidence that degree of urbanization is associated with MD. The association could not be explained by differences in reproductive and lifestyle factors or by variation in air pollution exposure.