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PurposeTo examine whether interpersonal aspects of patient-clinician interactions, such as patient-perceived medical discrimination, clinician mistrust, and treatment decision-making contribute to racial/ethnic/educational disparities in breast cancer care.MethodsA telephone interview was administered to 542 Asian/Pacific Islander (API), Black, Hispanic, and White women identified through the Greater Bay Area Cancer Registry, ages 20 and older diagnosed with a first primary invasive breast cancer. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were calculated from logistic regression models that assessed associations between race/ethnicity/education, medical discrimination, clinician mistrust, and treatment decision-making with concordance to breast cancer treatment guidelines (guideline-concordant treatment) and perceived quality of care (pQoC).ResultsApproximately three-quarters of women received treatment that was guideline-concordant (76.6%) and reported that their breast cancer care was excellent (72.1%). Non-college-educated Black women had lower odds of guideline-concordant care (aOR (CI) = 0.29 (0.12-0.67)) vs. college-educated White women. Odds of excellent pQoC were lower among the following: college-educated Hispanic women (aOR (CI) = 0.09 (0.02-0.47)) and API women regardless of education (aORs ≤ 0.50) vs. college-educated White women, women reporting low and moderate levels of discrimination (aORs ≤ 0.44) vs. none, and women reporting any clinician mistrust (aOR (CI) = 0.50 (0.29-0.88)) vs. none. Disparities in guideline-concordant care and pQoC persisted after controlling for medical discrimination, clinician mistrust, and decision-making.ConclusionsInterpersonal aspects of the patient-clinician interaction had an impact on pQoC but not receipt of guideline-concordant treatment and did not explain disparities in either outcome.Implications for cancer survivorsAlthough breast cancer survivors' interpersonal interactions with clinicians did not influence receipt of appropriate treatment, intervention strategies to improve patient-clinician relations may help attenuate disparities in survivors' pQoC.

USA states have begun legislating mammographic breast density reporting to women, requiring that women undergoing screening mammography who have dense breast tissue (Breast Imaging Reporting and Data System [BI-RADS] density c or d) receive written notification of their breast density; however, the impact that misclassification of breast density will have on this reporting remains unclear. The aim of this study was to assess reproducibility of the four-category BI-RADS density measure and examine its relationship with a continuous measure of percent density. We enrolled 19 radiologists, experienced in breast imaging, from a single integrated health care system. Radiologists interpreted 341 screening mammograms at two points in time 6 months apart. We assessed intra- and interobserver agreement in radiologists'; interpretations of BI-RADS density and explored whether agreement depended upon radiologist characteristics. We examined the relationship between BI-RADS density and percent density in a subset of 282 examinations. Intraradiologist agreement was moderate to substantial, with kappa varying across radiologists from 0.50 to 0.81 (mean = 0.69, 95% CI [0.63, 0.73]). Intraradiologist agreement was higher for radiologists with ≥10 years experience interpreting mammograms (difference in mean kappa = 0.10, 95% CI [0.01, 0.24]). Interradiologist agreement varied widely across radiologist pairs from slight to substantial, with kappa ranging from 0.02 to 0.72 (mean = 0.46, 95% CI [0.36, 0.55]). Of 145 examinations interpreted as "nondense" (BI-RADS density a or b) by the majority of radiologists, 82.8% were interpreted as "dense" (BI-RADS density c or d) by at least one radiologist. Of 187 examinations interpreted as "dense" by the majority of radiologists, 47.1% were interpreted as "nondense" by at least one radiologist. While the examinations of almost half of the women in our study were interpreted clinically as having BI-RADS density c or d, only about 10% of examinations had percent density >50%. Our results suggest that breast density reporting based on a single BI-RADS density interpretation may be misleading due to high interradiologist variability and a lack of correspondence between BI-RADS density and percent density.

BackgroundWomen with elevated mammographic density have an increased risk of developing breast cancer. However, among women diagnosed with breast cancer, it is unclear whether higher density portends reduced survival, independent of other factors.MethodsWe evaluated relationships between mammographic density and risk of death from breast cancer and all causes within the US Breast Cancer Surveillance Consortium. We studied 9232 women diagnosed with primary invasive breast carcinoma during 1996-2005, with a mean follow-up of 6.6 years. Mammographic density was assessed using the Breast Imaging Reporting and Data System (BI-RADS) density classification. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards regression; women with scattered fibroglandular densities (BI-RADS 2) were the referent group. All statistical tests were two-sided.ResultsA total of 1795 women died, of whom 889 died of breast cancer. In multivariable analyses (adjusted for site, age at and year of diagnosis, American Joint Committee on Cancer stage, body mass index, mode of detection, treatment, and income), high density (BI-RADS 4) was not related to risk of death from breast cancer (HR = 0.92, 95% CI = 0.71 to 1.19) or death from all causes (HR = 0.83, 95% CI = 0.68 to 1.02). Analyses stratified by stage and other prognostic factors yielded similar results, except for an increased risk of breast cancer death among women with low density (BI-RADS 1) who were either obese (HR = 2.02, 95% CI = 1.37 to 2.97) or had tumors of at least 2.0 cm (HR = 1.55, 95% CI = 1.14 to 2.09).ConclusionsHigh mammographic breast density was not associated with risk of death from breast cancer or death from any cause after accounting for other patient and tumor characteristics. Thus, risk factors for the development of breast cancer may not necessarily be the same as factors influencing the risk of death after breast cancer has developed.

BackgroundIt 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.MethodsThe 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.ResultsThere 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.ConclusionsBMD 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.

Breast implants may make breast cancer diagnosis by mammography more difficult, according to a study of approximately 1 million women. Among women with breast implants, mammography only identified 45% of the women who had breast cancer. Among women without breast implants, mammography identified 67% of those who had breast cancer. Breast implants do not make breast cancer worse.

The article focuses on a prospective cohort study conducted on several women aged between 40 to 59 years at mammography facilities in the Breast Cancer Surveillance Consortium to determine and compare the effectiveness of the digital screening mammography and film-Screening mammography in the U.S. Community practice. The study found that both the methods yielded similar results in the cancer diagnosis in U.S. INSET: Untitled.

Background: Most breast biopsies will be negative for cancer. Benign breast biopsy can cause changes in the breast tissue, but whether such changes affect the interpretive performance of future screening mammography is not known. [ABSTRACT FROM PUBLISHER]

The article examines whether rates of using mammography to identify breast cancer have decreased in the U.S. Mammography rates from 1987 through 2005 were assessed. The 2000 and 2005 National Health Interview Survey (NHIS) estimates were used to characterize trends and current patterns in mammography use in the country. The researchers discovered that estimates from the 2005 NHIS showed a decline compared with 2000.

Background: Mammography screening may reduce breast cancer mortality by detecting cancers at an earlier stage. However, certain questions remain, including the ideal interval between mammograms. Methods: We conducted an observational study using information collected by seven mammography registries across the United States to investigate whether women diagnosed with breast cancer after having screening mammograms separated by a 2-year interval (n = 2440) are more likely to be diagnosed with late-stage disease (positive lymph nodes or metastases) than women diagnosed with breast cancer after having screening mammograms separated by a 1-year interval (n = 5400). Analyses were stratified by age and breast density to clarify whether groups that have the poorest mammography sensitivity (i.e., women under age 50 years and those with mammographically dense breasts) would benefit most from annual screening. The subjects were women diagnosed with breast cancer between 1996 and 2001 who were 40–89 years old at their index mammographic examination (i.e., the most recent screen at or before breast cancer diagnosis). Data were analyzed by logistic regression, adjusting for race, ethnicity, family history of breast cancer, and mammography registry. Results: Among women age 40–49 years at the index mammogram, those with a 2-year screening interval were more likely to have late-stage disease at diagnosis than those with a 1-year screening interval (28% versus 21%; odds ratio [OR] = 1.35, 95% confidence interval [CI] = 1.01 to 1.81). There was no increase in late-stage disease for women 50 years or older with a 2-year versus a 1-year screening interval (women age 50–59 years at index mammogram: OR = 0.97, 95% CI = 0.75 to 1.25; women age 60–69 years at index mammogram: OR = 0.99, 95% CI = 0.72 to 1.35; women age 70 years or older at index mammogram: OR = 0.88, 95% CI = 0.64 to 1.19). There was no indication that women with dense breasts would benefit more from a 1-year versus 2-year screening interval than women with fatty breasts. Conclusion: These findings may be useful for policy decisions about appropriate screening intervals and for use in statistical models that estimate the costs and benefits of mammography by age and screening interval. [ABSTRACT FROM AUTHOR]

Background: Radiologists differ in their ability to interpret screening mammograms accurately. We investigated the relationship of radiologist characteristics to actual performance from 1996 to 2001. Methods: Screening mammograms (n = 469 512) interpreted by 124 radiologists were linked to cancer outcome data. The radiologists completed a survey that included questions on demographics, malpractice concerns, years of experience interpreting mammograms, and the number of mammograms read annually. We used receiver operating characteristics (ROC) analysis to analyze variables associated with sensitivity, specificity, and the combination of the two, adjusting for patient variables that affect performance. All P values are two-sided. Results: Within 1 year of the mammogram, 2402 breast cancers were identified. Relative to low annual interpretive volume (≤1000 mammograms), greater interpretive volume was associated with higher sensitivity (P = .001; odds ratio [OR] for moderate volume [1001-2000] = 1.68, 95% CI = 1.18 to 2.39; OR for high volume [>2000] = 1.89, 95% CI = 1.36 to 2.63). Specificity decreased with volume (OR for 1001-2000 = 0.65, 95% CI = 0.52 to 0.83; OR for more than 2000 = 0.76, 95% CI = 0.60 to 0.96), compared with 1000 or less (P = .002). Greater number of years of experience interpreting mammograms was associated with lower sensitivity (P = .001), but higher specificity (P = .003). ROC analysis using the ordinal BI-RADS interpretation showed an association between accuracy and both previous mammographic history (P = .012) and breast density (P<.001). No association was observed between accuracy and years interpreting mammograms (P = .34) or mammography volume (P = .94), alter adjusting for variables that affect the threshold for calling a mammogram positive. Conclusions: We found no evidence that greater volume or experience at interpreting mammograms is associated with better performance. However, they may affect sensitivity and specificity, possibly by determining the threshold for calling a mammogram positive. Increasing volume requirements is unlikely to improve overall mammography performance. [ABSTRACT FROM AUTHOR]

Background: Mammography screening increases the detection of early-stage breast cancers. Therefore, implementing screening should reduce the percentage of women who are diagnosed with late-stage disease. However, despite high national mammography screening rates, late-stage breast cancers still occur, possibly because of failures in screening implementation. Methods: Using data from seven health care plans that included 1.5 million women aged 50 years or older, we conducted retrospective reviews of chart and automated data for 3 years before 1995–1999 diagnoses of late-stage (metastatic and/or tumor size ≥3 cm; case subjects, n = 1347) and early-stage breast cancers (control subjects, n = 1347). We categorized the earliest screening mammogram during the period 13–36 months before diagnosis as none (absence of screening), negative (absence of detection), or positive (potential breakdown in follow-up). We compared the proportion of case and control subjects in each category of screening implementation and estimated the likelihood (odds ratio [OR] with 95% confidence intervals [CIs]) of late-stage breast cancer. We also evaluated demographic characteristics associated with absence of screening in women with late-stage disease. All statistical tests were two-sided. Results: Absence of screening, absence of detection, and potential breakdown in follow-up were distributed differently among case (52.1%, 39.5%, and 8.4%, respectively) and control subjects (34.4%, 56.9%, and 8.8%, respectively) (P = .03). Among all women, the odds of having late-stage cancer were higher among women with an absence of screening (OR = 2.17, 95% CI = 1.84 to 2.56; P<.001). Among case patients, women were more likely to be in the absence-of-screening group if they were aged 75 years or older (OR = 2.77, 95% CI = 2.10 to 3.65), unmarried (OR = 1.78, 95% CI = 1.41 to 2.24), or without a family history of breast cancer (OR = 1.84, 95% CI = 1.45 to 2.34). A higher proportion of women from census blocks with less education (58.5% versus 49.4%; P = .003) or lower median annual income (54.4% versus 42.9%; P = .004) were in the absence-of-screening category compared with the proportion for the other two categories combined. Conclusions: To reduce late-stage breast cancer occurrence, reaching unscreened women, including elderly, unmarried, low-income, and less educated women, should be made a top priority for screening implementation. [ABSTRACT FROM AUTHOR]

Background: Younger women (40–49 years) have lower mammographic sensitivity (i.e., greater proportion of cancers detected after a negative mammogram) than older women (≥50 years). We explored the effect of tumor growth rate, breast density, mammographic image quality, and breast cancer risk factors on mammographic sensitivity in younger and older women. Methods: We studied 576 women (n = 73 aged 40–49 years and n = 503 aged 50 years or older) who were diagnosed with invasive breast cancer between 1988 and 1993. Interval cancers were defined as those diagnosed within 12 or 24 months after a negative screening mammogram and before a subsequent mammogram. Tumor growth rate was assessed by mitotic figure count and Ki-67 positivity. The main outcome measures were percentage of women with interval cancer (1 - mammographic sensitivity) by age, odds ratio (OR) of interval cancer by age, and excess odds (i.e., the percentage of the odds ratio for age that was explained by individual covariates). Results: Interval cancers occurred in 27.7% of younger women and 13.9% of older women within 12 months (OR = 2.36, 95% confidence interval [CI] = 1.14 to 4.77) and in 52.1% of younger women and 24.7% of older women within 24 months (OR = 3.58, 95% CI = 2.15 to 5.97). Greater breast density explained 67.6% of the decreased mammographic sensitivity in younger women at 12 months, whereas rapid tumor growth explained 30.6% and breast density explained 37.6% of the decreased sensitivity in younger women at 24 months. Conclusions: Breast density largely explained decreased mammographic sensitivity at 12 months, whereas rapid tumor growth contributed to decreased mammographic sensitivity at 24 months. A 12-month versus a 24-month mammography screening interval may therefore reduce the adverse impact of faster growing tumors on mammographic sensitivity in younger women. [ABSTRACT FROM AUTHOR]

Compares the performance of screening mammography in women with a first-degree family history of breast cancer and women with similar age without the history in the U.S. Risk factors for breast cancer; Positive predictive value and sensitivity of screening mammography; Rate of cancer; Breast biopsies.

The convenience of fast computers and the Internet have encouraged large collaborative research efforts by allowing transfers of data from multiple sites to a single data repository; however, standards for managing data security are needed to protect the confidentiality of participants. Through Dartmouth Medical School, in 1996–1998, the authors conducted a medicolegal analysis of federal laws, state statutes, and institutional policies in eight states and three different types of health care settings, which are part of a breast cancer surveillance consortium contributing data electronically to a centralized data repository. They learned that a variety of state and federal laws are available to protect confidentiality of professional and lay research participants. The strongest protection available is the Federal Certificate of Confidentiality, which supersedes state statutory protection, has been tested in court, and extends protection from forced disclosure (in litigation) to health care providers as well as patients. This paper describes the careful planning necessary to ensure adequate legal protection and data security, which must include a comprehensive understanding of state and federal protections applicable to medical research. Researchers must also develop rules or guidelines to ensure appropriate collection, use, and sharing of data. Finally, systems for the storage of both paper and electronic records must be as secure as possible. Am J Epidemiol 2000;152:371–8. [ABSTRACT FROM PUBLISHER]

Describes the role of medical communities in two counties targeted by the Washington State Community Breast Cancer Screening Project. Role of physician planning groups; Evidence that physicians practicing in medium-sized cities are willing to be active in community disease prevention programs.