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Background: Breast cancer rates in women with multiple breast symptoms have not been well described., Methods: We examined the association between self-reported symptoms (lump, nipple discharge, pain, other) and breast cancer risk for screening and diagnostic mammograms in 57,681 women. Subanalyses evaluated risk among women with no prior mammograms, new symptoms, and repeated symptoms. One thousand, three hundred and eighty-nine women were diagnosed with cancer within 12 months of their mammograms. We calculated the breast cancer rate for each symptom and odds ratios (OR) with 95% confidence intervals (CI) for breast cancer among symptomatic women compared with asymptomatic women., Results: Women reporting a lump had an increased odds of breast cancer compared with asymptomatic women (OR for diagnostic examination = 2.8, 95% CI = 2.3 to 3.4; OR for screening examination = 3.6, 95% CI = 2.6 to 5.0). No other symptoms were associated with breast cancer after controlling for a reported lump. A new lump at a diagnostic examination was significantly predictive of cancer among women with no prior mammograms (OR = 12.2, 95% CI = 2.8 to 53.5); reporting symptoms at 2 successive exams had little effect on breast cancer risk (OR for lump = 1.2, 95% CI = 0.6 to 2.5)., Conclusions: Having a lump is the most predictive symptom of breast cancer whether it is reported at a screening or diagnostic examination or in conjunction with other symptoms.

Background: It is not well understood whether breast density is a marker of cumulative exposure to estrogen or a marker of recent exposure to estrogen. The authors examined the relationship between bone mineral density (BMD; a marker of lifetime estrogen exposure) and breast density., Methods: The authors conducted a cross-sectional analysis among 1800 postmenopausal women > or = 54 years. BMD data were taken from two population-based studies conducted in 1992-1993 (n = 1055) and in 1998-1999 (n = 753). The authors linked BMD data with breast density information collected as part of a mammography screening program. They used linear regression to evaluate the density relationship, adjusted for age, hormone therapy use, body mass index (BMI), and reproductive covariates., Results: There was a small but significant negative association between BMD and breast density. The negative correlation between density measures was not explained by hormone therapy or age, and BMI was the only covariate that notably influenced the relationship. Stratification by BMI only revealed the negative correlation between bone and breast densities in women with normal BMI. There was no relationship in overweight or obese women. The same relationship was seen for all women who had never used hormone therapy, but it was not significant once stratified by BMI., Conclusions: BMD and breast density were not positively associated although both are independently associated with estrogen exposure. It is likely that unique organ responses obscure the relationship between the two as indicators of cumulative estrogen exposure.

The hypothesis that antibiotic use may increase cancer risk was first proposed several decades ago and some research suggests an increased risk of breast cancer among women with conditions likely to require long-term antibiotic use (e.g., acne, recurrent urinary-tract infections, UTI). However, this hypothesis has not been verified and the possible biological mechanisms are not entirely clear. A recent cohort study in Finland reported an increased risk of breast-cancer associated with antibiotic use for UTI. The effect of antibiotics on the ability of intestinal microflora to metabolise phytochemicals from edible plants into compounds that may protect against cancer was proposed as a potential mechanism. We extend this hypothesis by proposing that antibiotic use may be associated with breast-cancer risk through effects on immune and inflammatory factors, such as cytokines, T lymphocytes, prostaglandins, and matrix metalloproteinases, as well as disruption of phytochemical and oestrogen metabolism by intestinal microflora. We suggest that some mechanisms may increase breast-cancer risk, while others may decrease risk, depending on the antibiotic classification.

Background: To describe when women diagnosed with breast cancer return for their first mammography, and to identify factors predictive of women returning for mammographic surveillance., Methods: Women who underwent mammography at facilities participating in the National Cancer Institute's Breast Cancer Surveillance Consortium (BCSC) during 1996 and who were subsequently diagnosed with ductal carcinoma in situ or invasive breast cancer were included in this study. Data from seven mammography registries were linked to population-based cancer and pathology registries. Kaplan-Meier curves were used to depict the number of months from the breast cancer diagnosis to the first mammogram within the defined follow-up period. Demographic, disease and treatment variables were included in univariate and multivariate analyses to identify factors predictive of women returning for mammography., Results: Of the 2503 women diagnosed with breast cancer, 78.1% returned for mammography examination between 7 and 30 months following the diagnosis. Mammography facilities indicated that 66.8% of mammography examinations were classified as screening. Multivariate analyses found that women were most likely to undergo surveillance mammography if they were diagnosed at ages 60-69 with Stage 0, I or II breast cancer and had received radiation therapy in addition to surgery., Conclusions: While the majority of women return for mammographic surveillance following breast cancer, some important subgroups of women at higher risk for recurrence are less likely to return. Research is needed to determine why some women are not undergoing mammography surveillance after a breast cancer diagnosis and whether surveillance increases the chance of detecting tumors with a good prognosis.

This commentary presents a conceptual framework, Quality in the Continuum of Cancer Care (QCCC), for quality improvement studies and research. Data sources include review of relevant literature (cancer care, quality improvement, organizational behavior, health services evaluation, and research). The Detecting Early Tumors Enables Cancer Therapy (DETECT) project is used to apply the QCCC model to evaluate the quality of secondary prevention. Cancer care includes risk assessment, primary prevention, screening, detection, diagnosis, treatment, recurrence surveillance, and end-of-life care. The QCCC model represents a systematic approach for assessing factors that influence types of cancer care and the transitions between them, the factors at several levels (community, plan and practice setting) that potentially impact access and quality, and the strategies groups and organizations can consider to reduce potential failures. Focusing on the steps and transitions in care where failures can occur can facilitate more organized systems and medical practices that improve care, establish meaningful measures of quality that promote improved outcomes, and enhance interdisciplinary research.

Clinical breast examination (CBE) is one of the most common breast cancer screening modalities, but factors that affect its sensitivity are not well understood. We examined the association between CBE sensitivity and tumor, breast and personal characteristics among members of a managed care organization's Breast Cancer Screening Program (BCSP). The study population was 468 screened women 40 years and older diagnosed with invasive breast cancer between 1988 and 1994 within 1 year of a screening CBE. Logistic regression was used to evaluate the likelihood of a true positive versus a false negative CBE result, after adjustment for age, body weight and tumor size. CBE sensitivity increased with larger tumor size (17% for tumors < or = 0.5 cm and 58% for tumors > or = 2.1 cm, adjusted p for trend < 0.001) and decreased with higher body weight (48 and 23% for the lowest and highest quartiles, adjusted p for trend < 0.001). CBE was more sensitive in Asian women compared to white women (88% v.s. 35%, adjusted p = 0.04) and in current users of estrogen and progesterone combination therapy compared to never/former users (52% v.s. 33%, adjusted p = 0.08). There was an inverted U-shaped association between age and CBE sensitivity (40-49: 26%, 50-59: 48%, 60-69: 36%, 70-79: 33%, 80+: 18%, significant for oldest and youngest groups v.s. age 50-59 years). These findings suggest certain groups of women, for example, obese women and younger women, receive less benefit from CBE.

Objective: We evaluated the association between clinical image quality and breast cancer occurrence within 24 months of a negative mammogram., Materials and Methods: We identified women with breast cancer who were younger than 40 years old and older and screened from January 1, 1988, through December 31, 1993. We retrospectively assigned Breast Imaging Reporting and Data System (BI-RADS) assessments to their screening mammogram. We classified cancers (invasive or ductal in situ) as "screen-detected" when found after positive assessments (BI-RADS codes 3, 4, and 5) and "interval-detected" when found after negative assessments (BI-RADS codes 1 and 2). One reviewer evaluated mediolateral oblique and craniocaudal views for all cancer cases using a 3-point scale (failure, borderline, pass) for each measure of clinical image quality (positioning, breast compression, contrast, exposure, noise, sharpness, artifacts, overall quality). We used separate logistic regression models and evaluated the odds of interval invasive cancer or invasive plus in situ cancer as a function of each measure of quality using "pass" as the referent group., Results: We found 492 screen-detected and 164 interval-detected cancers that met study criteria. Cancer detection (sensitivity) was highest (84%) among patients with proper breast positioning, but when images failed this measure (33.4%), sensitivity fell to 66.3%. After adjustment for age, film date, and breast density, interval-detected invasive cancers were more likely after images failing positioning (odds ratio, 2.57; 95% confidence interval, 1.28-5.52%). Failures in overall quality were also associated with interval cancers when cases of ductal carcinoma in situ (p = 0.037) were included., Conclusion: Invasive breast cancer detection by mammography may be improved through attention to correct positioning.