Tumor characteristics and family history in relation to mammographic density and breast cancer: The French E3N cohort

BackgroundMammographic density is a known heritable risk factor for breast cancer, but reports how tumor characteristics and family history may modify this association are inconsistent.MethodsDense and total breast areas were assessed using Cumulus™ from pre-diagnostic mammograms for 820 invasive breast cancer cases and 820 matched controls nested within the French E3N cohort study. To allow comparisons across models, percent mammographic density (PMD) was standardized to the distribution of the controls. Odds ratios (OR) and 95% confidence intervals (CI) of breast cancer risk for mammographic density were estimated by conditional logistic regression while adjusting for age and body mass index. Heterogeneity according to tumor characteristic and family history was assessed using stratified analyses.ResultsOverall, the OR per 1 SD for PMD was 1.50 (95% CI, 1.33–1.69). No evidence for significant heterogeneity by tumor size, lymph node status, grade, and hormone receptor status (estrogen, progesterone, and HER2) was detected. However, the association of PMD was stronger for women reporting a family history of breast cancer (OR_1SD = 2.25; 95% CI, 1.67–3.04) than in women reporting none (OR_1SD = 1.41; 95% CI, 1.24–1.60; p_{heterogeneity} = 0.002). Similarly, effect modification by FHBC was observed using categories of PMD (p_{heterogeneity} = 0.02) with respective ORs of 15.16 (95% CI, 4.23–54.28) vs. 3.14 (95% CI, 1.89–5.22) for ≥50% vs. <10% PMD.ConclusionsThe stronger association between mammographic density and breast cancer risk with a family history supports the hypothesis of shared genetic factors responsible for familial aggregation of breast cancer and the heritable component of mammographic density.     

Agreement of Mammographic Measures of Volumetric Breast Density to MRI

Background

Clinical scores of mammographic breast density are highly subjective. Automated technologies for mammography exist to quantify breast density objectively, but the technique that most accurately measures the quantity of breast fibroglandular tissue is not known.

Purpose

To compare the agreement of three automated mammographic techniques for measuring volumetric breast density with a quantitative volumetric MRI-based technique in a screening population.

Materials and Methods

Women were selected from the UCSF Medical Center screening population that had received both a screening MRI and digital mammogram within one year of each other, had Breast Imaging Reporting and Data System (BI-RADS) assessments of normal or benign finding, and no history of breast cancer or surgery. Agreement was assessed of three mammographic techniques (Single-energy X-ray Absorptiometry [SXA], Quantra, and Volpara) with MRI for percent fibroglandular tissue volume, absolute fibroglandular tissue volume, and total breast volume.

Results

Among 99 women, the automated mammographic density techniques were correlated with MRI measures with R² values ranging from 0.40 (log fibroglandular volume) to 0.91 (total breast volume). Substantial agreement measured by kappa statistic was found between all percent fibroglandular tissue measures (0.72 to 0.63), but only moderate agreement for log fibroglandular volumes. The kappa statistics for all percent density measures were highest in the comparisons of the SXA and MRI results. The largest error source between MRI and the mammography techniques was found to be differences in measures of total breast volume.

Conclusion

Automated volumetric fibroglandular tissue measures from screening digital mammograms were in substantial agreement with MRI and if associated with breast cancer could be used in clinical practice to enhance risk assessment and prevention.     

Mammographic Breast Density and Common Genetic Variants in Breast Cancer Risk Prediction

Introduction

Known prediction models for breast cancer can potentially by improved by the addition of mammographic density and common genetic variants identified in genome-wide associations studies known to be associated with risk of the disease. We evaluated the benefit of including mammographic density and the cumulative effect of genetic variants in breast cancer risk prediction among women in a Singapore population.

Methods

We estimated the risk of breast cancer using a prospective cohort of 24,161 women aged 50 to 64 from Singapore with available mammograms and known risk factors for breast cancer who were recruited between 1994 and 1997. We measured mammographic density using the medio-lateral oblique views of both breasts. Each woman’s genotype for 75 SNPs was simulated based on the genotype frequency obtained from the Breast Cancer Association Consortium data and the cumulative effect was summarized by a genetic risk score (GRS). Any improvement in the performance of our proposed prediction model versus one containing only variables from the Gail model was assessed by changes in receiver-operating characteristic and predictive values.

Results

During 17 years of follow-up, 680 breast cancer cases were diagnosed. The multivariate-adjusted hazard ratios (95% confidence intervals) were 1.60 (1.22–2.10), 2.20 (1.65–2.92), 2.33 (1.71–3.20), 2.12 (1.43–3.14), and 3.27 (2.24–4.76) for the corresponding mammographic density categories: 11-20cm², 21-30cm², 31-40cm², 41-50cm², 51-60cm², and 1.10 (1.03–1.16) for GRS. At the predicted absolute 10-year risk thresholds of 2.5% and 3.0%, a model with mammographic density and GRS could correctly identify 0.9% and 0.5% more women who would develop the disease compared to a model using only the Gail variables, respectively.

Conclusion

Mammographic density and common genetic variants can improve the discriminatory power of an established breast cancer risk prediction model among females in Singapore.     

Comparing Visually Assessed BI-RADS Breast Density and Automated Volumetric Breast Density Software: A Cross-Sectional Study in a Breast Cancer Screening Setting

Introduction

The objective of this study is to compare different methods for measuring breast density, both visual assessments and automated volumetric density, in a breast cancer screening setting. These measures could potentially be implemented in future screening programmes, in the context of personalised screening or screening evaluation.

Materials and Methods

Digital mammographic exams (N = 992) of women participating in the Dutch breast cancer screening programme (age 50–75y) in 2013 were included. Breast density was measured in three different ways: BI-RADS density (5^th edition) and with two commercially available automated software programs (Quantra and Volpara volumetric density). BI-RADS density (ordinal scale) was assessed by three radiologists. Quantra (v1.3) and Volpara (v1.5.0) provide continuous estimates. Different comparison methods were used, including Bland-Altman plots and correlation coefficients (e.g., intraclass correlation coefficient [ICC]).

Results

Based on the BI-RADS classification, 40.8% of the women had ‘heterogeneously or extremely dense’ breasts. The median volumetric percent density was 12.1% (IQR: 9.6–16.5) for Quantra, which was higher than the Volpara estimate (median 6.6%, IQR: 4.4–10.9). The mean difference between Quantra and Volpara was 5.19% (95% CI: 5.04–5.34) (ICC: 0.64). There was a clear increase in volumetric percent dense volume as BI-RADS density increased. The highest accuracy for predicting the presence of BI-RADS c+d (heterogeneously or extremely dense) was observed with a cut-off value of 8.0% for Volpara and 13.8% for Quantra.

Conclusion

Although there was no perfect agreement, there appeared to be a strong association between all three measures. Both volumetric density measures seem to be usable in breast cancer screening programmes, provided that the required data flow can be realized.     

Beyond Breast Cancer: Mammographic Features and Mortality Risk in a Population of Healthy Women

Background

Breast fibroglandular (dense) tissue is a risk factor for breast cancer. Beyond breast cancer, little is known regarding the prognostic significance of mammographic features.

Methods

We evaluated relationships between nondense (fatty) breast area and dense area with all-cause mortality in 4,245 initially healthy women from the Breast Cancer Detection Demonstration Project; 1,361 died during a mean follow-up of 28.2 years. Dense area and total breast area were assessed using planimeter measurements from screening mammograms. Percent density reflects dense area relative to breast area and nondense area was calculated as the difference between total breast area and dense area. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards regression.

Results

In age-adjusted models, greater nondense and total breast area were associated with increased risk of death (HR 1.17, 95% CI 1.10-1.24 and HR 1.13, 95% CI 1.06-1.19, per SD difference) while greater dense area and percent density were associated with lower risk of death (HR 0.91, 95% CI 0.86-0.95 and HR 0.87, 95% CI 0.83-0.92, per SD difference). Associations were not attenuated with adjustment for race, education, mammogram type (x-ray or xerogram), smoking status, diabetes and heart disease. With additional adjustment for body mass index, associations were diminished for all features but remained statistically significant for dense area (HR 0.94, 95% CI 0.89-0.99, per SD difference) and percent density (HR 0.93, 95% CI 0.87-0.98, per SD difference).

Conclusions

These data indicate that dense area and percent density may relate to survival in healthy women and suggest the potential utility of mammograms beyond prediction of breast cancer risk.     

Area and Volumetric Density Estimation in Processed Full-Field Digital Mammograms for Risk Assessment of Breast Cancer

Introduction

Mammographic density, the white radiolucent part of a mammogram, is a marker of breast cancer risk and mammographic sensitivity. There are several means of measuring mammographic density, among which are area-based and volumetric-based approaches. Current volumetric methods use only unprocessed, raw mammograms, which is a problematic restriction since such raw mammograms are normally not stored. We describe fully automated methods for measuring both area and volumetric mammographic density from processed images.

Methods

The data set used in this study comprises raw and processed images of the same view from 1462 women. We developed two algorithms for processed images, an automated area-based approach (CASAM-Area) and a volumetric-based approach (CASAM-Vol). The latter method was based on training a random forest prediction model with image statistical features as predictors, against a volumetric measure, Volpara, for corresponding raw images. We contrast the three methods, CASAM-Area, CASAM-Vol and Volpara directly and in terms of association with breast cancer risk and a known genetic variant for mammographic density and breast cancer, rs10995190 in the gene ZNF365. Associations with breast cancer risk were evaluated using images from 47 breast cancer cases and 1011 control subjects. The genetic association analysis was based on 1011 control subjects.

Results

All three measures of mammographic density were associated with breast cancer risk and rs10995190 (p<0.025 for breast cancer risk and p<1×10⁻⁶ for rs10995190). After adjusting for one of the measures there remained little or no evidence of residual association with the remaining density measures (p>0.10 for risk, p>0.03 for rs10995190).

Conclusions

Our results show that it is possible to obtain reliable automated measures of volumetric and area mammographic density from processed digital images. Area and volumetric measures of density on processed digital images performed similar in terms of risk and genetic association.     

Optical assessment of mammographic breast density by a 12‐wavelength vs a continuous‐spectrum optical spectroscopy device

A 12‐laser‐wavelength, fixed source‐detector position, cup‐based optical breast spectroscopy (OBS) device was developed for use in large‐scale, multicenter trials as a mammographic breast density (MBD) quantification and breast cancer (BC) risk prescreening tool. In this study, the device was evaluated in comparison with a spectrometer‐based device used in previous studies. The devices were compared on their ability to predict mammographic percent density (MPD) and to identify women with high MBD from optical spectra. OBS measurements were made on 60 women, (age 29‐73), using both devices. Recent mammograms were collected for all women and MPD quantified from the mammograms. Principal components (PCs) analysis was performed on both sets of OBS spectra, and multivariate logistic regression analysis of the resulting PC scores was used to identify women with high MBD. Both devices are able to identify high MBD with very high sensitivity and specificity. Partial least‐squares regression of the spectra was used to predict MPD. Both devices show a strong correlation between OBS‐predicted MPD and MPD read from mammograms, however, the correlation is stronger for the continuous‐spectrum device (r = 0.74, P = .001) than for the 12‐wavelength device (r = 0.62, P = .004). Improvements to the cup‐based device to reduce detector saturation should improve the prediction of MPD from the spectra.      

Mammographic density and hormone receptor expression in breast cancer: the Multiethnic Cohort Study

Background: It is unclear whether mammographic breast density, a strong risk factor for breast cancer, predicts subtypes of breast cancer defined by estrogen receptor (ER) and/or progesterone receptor (PR) expression. Methods: In a nested case–control study, we compared the breast density of 667 controls and 607 breast cancer cases among women of Caucasian, Japanese, and Native Hawaiian ancestry in the Hawaii component of the Multiethnic Cohort Study. A reader blinded to disease status performed computer assisted density assessment on prediagnostic mammograms. Receptor status was obtained from the statewide Hawaii Tumor Registry. Tumors were classified into ER+PR+ (n = 341), ER−PR− (n = 50), ER+PR−/ER−PR+ (n = 64), and unstaged/unknown (n = 152). Mean percent density values were computed for women with more than one mammogram. Polytomous logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) while adjusting for confounders. Results: Mean percent density was significantly greater for ER+PR+ but not for ER−PR− tumors compared to controls after adjusting for age: 37.3%, 28.9% versus 29.4%, respectively. The overall OR per 10% increase in percent density were similar for ER+PR+ and ER+PR−/ER−PR+ tumors: 1.26 (95% CI 1.17–1.36) and 1.23 (95% CI 1.07–1.42), respectively. However, percent density was not found to be a predictor for ER−PR− tumors (OR 1.00, 95% CI 0.84–1.18). The results did not differ by ethnicity, nor by menopausal status, parity, or HRT use. Conclusions: Our findings indicate that within a multiethnic population, women with higher breast density have an increased risk for ER+PR+ but not ER−PR− tumors.     

Ethnic Differences in Mammographic Densities: An Asian Cross-Sectional Study

BackgroundMammographic density is a strong risk factor for breast cancer and is highly variable, but, to date, few studies have examined density in Asian women, particularly those in low and middle-income Asian countries where genetic and lifestyle determinants may be significantly different.MethodsA total of 1,240 women who attended an opportunistic mammogram screening programme were eligible for analysis. Mammographic density was estimated using a fully-automated thresholding method and differences across ethnic groups were examined using linear regression in 205 randomly selected Chinese women, 138 Malay and 199 Indian women.ResultsPercent density was significantly higher in Chinese women (28.5%; 95% CI 27.0%, 30.0%) compared to Malay (24.2%; 95% CI 22.5%, 26.0%) and Indian (24.3%; 95% CI 22.8%, 25.7%) women (p<0.001), after adjustment for age, BMI, menopausal status, parity and age at first full term pregnancy. Correspondingly, adjusted nondense area was significantly lower in Chinese (72.2cm²; 95% CI 67.9cm², 76.5cm²) women compared to Malay (92.1cm²; 95% CI 86.9cm², 97.2cm²) and Indian (97.7cm²; 95% CI 93.4cm², 101.9cm²) women (p<0.001), but dense area did not differ across the three ethnic groups.ConclusionsOur study shows that higher percent density and lower nondense area reflect the higher incidence of breast cancer in Chinese compared to Malay and Indian women in Malaysia. Known lifestyle determinants of mammographic density do not fully account for the ethnic variations observed in mammographic density in this Asian cohort.     

MRI Background Parenchymal Enhancement Is Not Associated with Breast Cancer

BackgroundPreviously, a strong positive association between background parenchymal enhancement (BPE) at magnetic resonance imaging (MRI) and breast cancer was reported in high-risk populations. We sought to determine, whether this was also true for non-high-risk patients.Methods540 consecutive patients underwent breast MRI for assessment of breast findings (BI-RADS 0–5, non-high-risk screening (no familial history of breast cancer, no known genetic mutation, no prior chest irradiation, or previous breast cancer diagnosis)) and subsequent histological work-up. For this IRB-approved study, BPE and fibroglandular tissue FGT were retrospectively assessed by two experienced radiologists according to the BI-RADS lexicon. Pearson correlation coefficients were calculated to explore associations between BPE, FGT, age and final diagnosis of breast cancer. Subsequently, multivariate logistic regression analysis, considering covariate colinearities, was performed, using final diagnosis as the target variable and BPE, FGT and age as covariates.ResultsAge showed a moderate negative correlation with FGT (r = -0.43, p<0.001) and a weak negative correlation with BPE (r = -0.28, p<0.001). FGT and BPE correlated moderately (r = 0.35, p<0.001). Final diagnosis of breast cancer displayed very weak negative correlations with FGT (r = -0.09, p = 0.046) and BPE (r = -0.156, p<0.001) and weak positive correlation with age (r = 0.353, p<0.001). On multivariate logistic regression analysis, the only independent covariate for prediction of breast cancer was age (OR 1.032, p<0.001).ConclusionsBased on our data, neither BPE nor FGT independently correlate with breast cancer risk in non-high-risk patients at MRI. Our model retained only age as an independent risk factor for breast cancer in this setting.     

Mammographic screening and mortality from breast cancer: the Malm? mammographic screening trial.

STUDY OBJECTIVE--To determine whether mortality from breast cancer could be reduced by repeated mammographic screening. DESIGN--Birth year cohorts of city population separately randomised into study and control groups. SETTING--Screening clinic outside main hospital. PATIENTS--Women aged over 45; 21,088 invited for screening and 21,195 in control group. INTERVENTIONS--Women in the study group were invited to attend for mammographic screening at intervals of 18-24 months. Five rounds of screening were completed. Breast cancer was treated according to stage at diagnosis. END POINT--Mortality from breast cancer. MEASUREMENTS AND MAIN RESULTS--All women were followed up and classed at end point as alive without breast cancer, alive with breast cancer, dead from breast cancer, or dead from other causes. Cause of death was taken from national mortality registry and for patients with breast cancer was validated independently. Mean follow up was 8.8 years. Altogether 588 cases of breast cancer were diagnosed in the study group and 447 in the control group; 99 v 94 women died of all causes and 63 v 66 women died of breast cancer (no significant difference; relative risk 0.96 (95% confidence interval 0.68 to 1.35)). In the study group 29% more women aged less than 55 died of breast cancer (28 v 22; relative risk 1.29 (0.74 to 2.25)). More women in the study group died from breast cancer in the first seven years; after that the trend reversed, especially in women aged greater than or equal to 55 at entry. Overall, women in the study group aged greater than or equal to 55 had a 20% reduction in mortality from breast cancer (35 v 44; relative risk 0.79 (0.51 to 1.24)). OTHER FINDINGS--In the study group 100 (17%) cancers appeared in intervals between screenings and 107 (18%) in non-attenders; 51 of these women died from breast cancer. Cancers classed as stages II-IV comprised 33% (190/579) of cancers in the study group and 52% (231/443) in the control group. CONCLUSIONS--Invitation to mammographic screening may lead to reduced mortality from breast cancer, at least in women aged 55 or over.     

Breast Tissue Composition and Immunophenotype and Its Relationship with Mammographic Density in Women at High Risk of Breast Cancer

Aim

To investigate the cellular and immunophenotypic basis of mammographic density in women at high risk of breast cancer.

Methods

Mammograms and targeted breast biopsies were accrued from 24 women at high risk of breast cancer. Mammographic density was classified into Wolfe categories and ranked by increasing density. The histological composition and immunophenotypic profile were quantified from digitized haematoxylin and eosin-stained and immunohistochemically-stained (ERα, ERβ, PgR, HER2, Ki-67, and CD31) slides and correlated to mammographic density.

Results

Increasing mammographic density was significantly correlated with increased fibrous stroma proportion (rs (22) = 0.5226, p = 0.0088) and significantly inversely associated with adipose tissue proportion (rs (22) = -0.5409, p = 0.0064). Contrary to previous reports, stromal expression of ERα was common (19/20 cases, 95%). There was significantly higher stromal PgR expression in mammographically-dense breasts (p=0.026).

Conclusions

The proportion of stroma and fat underlies mammographic density in women at high risk of breast cancer. Increased expression of PgR in the stroma of mammographically dense breasts and frequent and unexpected presence of stromal ERα expression raises the possibility that hormone receptor expression in breast stroma may have a role in mediating the effects of exogenous hormonal therapy on mammographic density.     

Higher alcohol intake may modify the association between mammographic density and breast cancer: An analysis of three case-control studies

Alcohol consumption and mammographic density are established risk factors for breast cancer. This study examined whether the association of mammographic density with breast cancer varies by alcohol intake. Mammographic density was assessed in digitized images for 1207 cases and 1663 controls from three populations (Japan, Hawaii, California) using a computer-assisted method. Associations were estimated by logistic regression. When comparing ever to never drinking, mean density was similar and consumption was not associated with breast cancer risk. However, within the Hawaii/Japan subset, women consuming >1 drink/day had a non-significantly elevated relative risk compared to never drinkers. Also in the Hawaii/Japan population, alcohol intake only modified the association between mammographic density and breast cancer in women consuming >1 drink/day (p(interaction)=0.05) with significant risk estimates of 3.65 and 6.58 for the 2nd and 3rd density tertiles as compared to 1.57 and 1.61 for never drinkers in Hawaii/Japan. Although these findings suggest a stronger association between mammographic density and breast cancer risk for alcohol consumers, the small number of cases requires caution in interpreting the results.     

Dépistage du cancer du sein

The purpose of this article is to remind why and how the screening mammographic program has been developed in France, and generalized in 2004, and to explain what is the BI-RADS of ACR. Perspectives on emerging new technologies that may change breast cancer screening will be discussed.     

Effect modification of body mass index on the association between ovarian cysts and endometrial cancer

BackgroundOvarian cysts represent a common condition among women. Epidemiologic studies are inconsistent in determining if women with cysts are more likely to develop endometrial cancer (EC) regardless of overweight/obesity. We investigated the combined role of cysts and body mass index (BMI) on EC risk.MethodsWe pooled data from three case-control studies conducted in Italy and Switzerland on 920 women with EC and 1700 controls. The prevalence of cysts was 5% among both cases and controls, with 63% of cases being overweight/obese. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) using logistic regression models, adjusting for potential confounders. We conducted stratified analyses according to BMI, and estimated the interaction between cysts and BMI; we carried out additional analyses according to age at diagnosis of cysts.ResultsOverall, history of cysts was not associated to EC (OR=1.27, 95% CI=0.82–1.97, P = 0.29). Normal weight women reporting cysts had an increased risk of EC (OR=2.49, 95% CI=1.31–4.74), while no such effect was found among overweight/obese women (OR=0.65, 95% CI=0.36–1.18; P for interaction=0.004). The association was limited to women below 65 years of age and was stronger in those who reported cysts at age 48 or older.ConclusionsCysts appeared to be a risk factor for EC in lean women but not in overweight/obese ones; these results are consistent with an effect of cysts and obesity on EC along common pathways.     

Association between SHBG Asp327Asn (rs6259) polymorphism and breast cancer risk: a meta-analysis of 10,454 cases and 13,111 controls

Sex hormone-binding globulin (SHBG) is a plasma glycoprotein that plays an important role in breast cancer pathophysiology and risk definition, since it regulates the bioavailable fraction of circulating estradiol. Epidemiological studies have evaluated the association between SHBG Asp327Asn polymorphism and breast cancer risk in diverse populations. However, the results remain conflicting rather than conclusive. This meta-analysis of literatures was performed to derive a more precise estimation of the relationship. A total of 10 studies were identified for the meta-analysis, including 10,454 cases and 13,111 controls for SHBG Asp327Asn polymorphism. When all studies were pooled into the meta-analysis, there was no evidence for significant association between SHBG Asp327Asn polymorphism and breast cancer risk (for Asn/Asn vs. Asp/Asp: OR = 1.20, 95 % CI = 0.94-1.55; for Asp/Asn vs. Asp/Asp: OR = 0.94, 95 % CI = 0.87-1.01; for dominant model: OR = 0.95, 95 % CI = 0.90-1.02; for recessive model: OR = 1.22, 95 % CI = 0.95-1.57). In the subgroup analyses by ethnicity, menopausal status, and source of controls, no significant associations were found in all genetic models. Interestingly, further analyses stratified by menopausal status in different ethnicities revealed that this polymorphism might provide protective effects against breast cancer risk in postmenopausal Asian women (for dominant model: OR = 0.83, 95 % CI = 0.70-0.97). Sensitivity analyses were performed by sequential removal of individual studies and cumulative statistics have showed combined ORs were not materially altered by any individual study under all comparisons. In summary, this meta-analysis suggests that SHBG Asp327Asn polymorphism is not associated with breast cancer risk overall, while it might be an important genetic susceptibility factor in postmenopausal Asian women for developing breast cancer. Larger and well-designed studies are warranted to confirm our findings in the future.     

Age as a factor in breast cancer knowledge,attitudes and screening behaviour.

OBJECTIVE: To determine whether there are age-related differences in knowledge, attitudes and behaviour with respect to breast cancer and whether the differences reflect the age-specific Canadian recommendations on breast cancer screening. DESIGN: Telephone survey. SETTING: Two cities and five towns and their surrounding areas in Alberta. PARTICIPANTS: The age-specific, randomly selected sample comprised 1284 women aged 40 to 75 years who did not have breast cancer. Of the 1741 eligible women who were contacted, 1350 (78%) agreed to participate; 66 were excluded because of age ineligibility or a history of breast cancer. MAIN OUTCOME MEASURE: Frequency of knowledge, attitudes and behaviour with respect to breast cancer, by age group. RESULTS: Knowledge of breast cancer risk factors was generally low and decreased with age. Few women were aware of the Canadian recommendations on breast self-examination, physical examination of the breasts by a health care practitioner and mammographic screening. Older women believed they were less susceptible to breast cancer than younger women and were less likely to have positive attitudes toward screening. Self-examination was performed 9 to 15 times per year by 424 women (33%), and 810 (63%) had been examined by a health care professional in the past year. Although 664 (52%) had undergone mammography, the proportion decreased with age after age 59. The main barriers to mammography were lack of physician referral and the woman''s belief that the procedure is unnecessary if she is healthy. CONCLUSIONS: Education is needed to increase breast cancer knowledge, promote the Canadian recommendations for early detection of breast cancer and decrease negative beliefs about the disease. Changes in the behaviour of women and physicians are needed to increase the use of breast self-examination, clinical breast examination by a health care professional and mammographic screening. Reaching women in the upper range (60 to 69 years) of the target group for mammographic screening should be a focus in promoting early detection of breast cancer.     

Predictors of behavioral cancer risk factors and preventive behaviors among Nebraskans

BackgroundThe overall incidence rate of cancer in Nebraska is higher than the national average with cancer being the second leading cause of death in the state. Interventions are required to reduce the cancer burden; however, further research is first needed to identify behavioral cancer risk factors and preventive behaviors among Nebraskans that can be targeted.MethodsA statewide cross-sectional survey of Nebraskans aged 19 and older was conducted in 2019 using an address-based sampling method (n = 1640). Multivariable logistic regression was used to examine factors associated with being up-to-date on cancer screening and with behavioral cancer risk factors and preventive behaviors.Results93.42% of Nebraskans did not meet the daily recommended consumption of fruits and vegetables, and 71.51% did not meet weekly physical activity guidelines. The proportion of adults up to date on cancer screening was 64.57% for breast, 68.83% for cervical, 69.01% for colorectal, and 24.07% for skin cancers. Individuals 65–74 (OR: 3.40, 95% CI: 1.52–7.62) and 75 or older (OR: 3.30, 95% CI: 1.35–8.07) were more likely to be current with their colorectal cancer screening compared to ages 50–64. Hispanics were less likely to be current with mammograms (OR: 0.06, 95% CI: 0.01–0.71) and ever screened for cervical cancer (OR:0.13, 95% CI: 0.02–0.94) compared to Non-Hispanic Whites.ConclusionsDisparities in cancer screening and risk and preventive behaviors exist in Nebraska.ImpactThe study highlights a need for continuing efforts to improve preventive cancer behaviors for the entire population as well as some high-risk populations in Nebraska.     

Parity and risk of developing breast cancer according to tumor subtype: A systematic review and meta-analysis

BackgroundClinical breast cancer subtypes are categorized basing on the expression of hormone receptors and overexpression of the human epidermal growth factor receptor 2 (HER2). It is still unclear whether parity impact the risk of different breast cancer subtypes.MethodsWe searched eight mainstream databases for published epidemiologic studies that assessed the relationship between parity and risk of breast cancer subtypes up to January 12, 2021. Parity number were unified into nulliparity and ever parity. The random-effects or fixed-effect models were used to calculate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) among different subtypes. Restricted cubic spline analysis with four knots was applied to determine the relationship of parity number and risk of breast cancer subtypes.ResultsWe pooled sixteen case-control and four cohort studies, and performed an analysis including 7795 luminal A, 3576 luminal B, 1794 HER2-overexpressing, and 5192 triple-negative breast cancer cases among 1135131 participants. The combined ORs for ever parity versus nulliparity indicated a 34% reduction in luminal A risk (OR=0.66, 95% CI: 0.56–0.78), and a 29% reduction in luminal B risk (OR=0.71, 95% CI: 0.63–0.81), there was no significant association in HER2-overexpressing or TNBC risk. In the dose-response analysis, we observed a potentially non-linear and gradually increasing protective relationship between the number of parity and luminal breast cancer risk.ConclusionsThe effect of parity on breast cancer seems to vary among breast tumor subtypes, and it plays a protective role in luminal breast cancer.