False-positive mammography results are common. Biennial screening may decrease the cumulative probability of false-positive results across many years of repeated screening but could also delay cancer ...diagnosis.
To compare the cumulative probability of false-positive results and the stage distribution of incident breast cancer after 10 years of annual or biennial screening mammography.
Prospective cohort study.
7 mammography registries in the National Cancer Institute-funded Breast Cancer Surveillance Consortium.
169,456 women who underwent first screening mammography at age 40 to 59 years between 1994 and 2006 and 4492 women with incident invasive breast cancer diagnosed between 1996 and 2006.
False-positive recalls and biopsy recommendations stage distribution of incident breast cancer.
False-positive recall probability was 16.3% at first and 9.6% at subsequent mammography. Probability of false-positive biopsy recommendation was 2.5% at first and 1.0% at subsequent examinations. Availability of comparison mammograms halved the odds of a false-positive recall (adjusted odds ratio, 0.50 95% CI, 0.45 to 0.56). When screening began at age 40 years, the cumulative probability of a woman receiving at least 1 false-positive recall after 10 years was 61.3% (CI, 59.4% to 63.1%) with annual and 41.6% (CI, 40.6% to 42.5%) with biennial screening. Cumulative probability of false-positive biopsy recommendation was 7.0% (CI, 6.1% to 7.8%) with annual and 4.8% (CI, 4.4% to 5.2%) with biennial screening. Estimates were similar when screening began at age 50 years. A non-statistically significant increase in the proportion of late-stage cancers was observed with biennial compared with annual screening (absolute increases, 3.3 percentage points CI, -1.1 to 7.8 percentage points for women age 40 to 49 years and 2.3 percentage points CI, -1.0 to 5.7 percentage points for women age 50 to 59 years) among women with incident breast cancer.
Few women underwent screening over the entire 10-year period. Radiologist characteristics influence recall rates and were unavailable. Most mammograms were film rather than digital. Incident cancer was analyzed in a small sample of women who developed cancer.
After 10 years of annual screening, more than half of women will receive at least 1 false-positive recall, and 7% to 9% will receive a false-positive biopsy recommendation. Biennial screening appears to reduce the cumulative probability of false-positive results after 10 years but may be associated with a small absolute increase in the probability of late-stage cancer diagnosis.
National Cancer Institute.
The relationships among breast density, age, and use of hormone replacement therapy (HRT) in breast cancer detection have not been fully evaluated.
To determine how breast density, age, and use of ...HRT individually and in combination affect the accuracy of screening mammography.
Prospective cohort study.
7 population-based mammography registries in North Carolina; New Mexico; New Hampshire; Vermont; Colorado; Seattle, Washington; and San Francisco, California.
329 495 women 40 to 89 years of age who had 463 372 screening mammograms from 1996 to 1998; 2223 women received a diagnosis of breast cancer.
Breast density, age, HRT use, rate of breast cancer occurrence, and sensitivity and specificity of screening mammography.
Adjusted sensitivity ranged from 62.9% in women with extremely dense breasts to 87.0% in women with almost entirely fatty breasts; adjusted sensitivity increased with age from 68.6% in women 40 to 44 years of age to 83.3% in women 80 to 89 years of age. Adjusted specificity increased from 89.1% in women with extremely dense breasts to 96.9% in women with almost entirely fatty breasts. In women who did not use HRT, adjusted specificity increased from 91.4% in women 40 to 44 years of age to 94.4% in women 80 to 89 years of age. In women who used HRT, adjusted specificity was about 91.7% for all ages.
Mammographic breast density and age are important predictors of the accuracy of screening mammography. Although HRT use is not an independent predictor of accuracy, it probably affects accuracy by increasing breast density.
Few studies have examined the comparative effectiveness of digital versus film-screen mammography in U.S. community practice.
To determine whether the interpretive performance of digital and ...film-screen mammography differs.
Prospective cohort study.
Mammography facilities in the Breast Cancer Surveillance Consortium.
329,261 women aged 40 to 79 years underwent 869 286 mammograms (231 034 digital; 638 252 film-screen).
Invasive cancer or ductal carcinoma in situ diagnosed within 12 months of a digital or film-screen examination and calculation of mammography sensitivity, specificity, cancer detection rates, and tumor outcomes.
Overall, cancer detection rates and tumor characteristics were similar for digital and film-screen mammography, but the sensitivity and specificity of each modality varied by age, tumor characteristics, breast density, and menopausal status. Compared with film-screen mammography, the sensitivity of digital mammography was significantly higher for women aged 60 to 69 years (89.9% vs. 83.0%; P = 0.014) and those with estrogen receptor-negative cancer (78.5% vs. 65.8%; P = 0.016); borderline significantly higher for women aged 40 to 49 years (82.4% vs. 75.6%; P = 0.071), those with extremely dense breasts (83.6% vs. 68.1%; P = 0.051), and pre- or perimenopausal women (87.1% vs. 81.7%; P = 0.057); and borderline significantly lower for women aged 50 to 59 years (80.5% vs. 85.1%; P = 0.097). The specificity of digital and film-screen mammography was similar by decade of age, except for women aged 40 to 49 years (88.0% vs. 89.7%; P < 0.001).
Statistical power for subgroup analyses was limited.
Overall, cancer detection with digital or film-screen mammography is similar in U.S. women aged 50 to 79 years undergoing screening mammography. Women aged 40 to 49 years are more likely to have extremely dense breasts and estrogen receptor-negative tumors; if they are offered mammography screening, they may choose to undergo digital mammography to optimize cancer detection.
National Cancer Institute.
Background: Risk prediction models for breast cancer can be improved by the addition of recently identified risk factors, including breast density and use of hormone therapy. We used prospective risk ...information to predict a diagnosis of breast cancer in a cohort of 1 million women undergoing screening mammography. Methods: There were 2 392 998 eligible screening mammograms from women without previously diagnosed breast cancer who had had a prior mammogram in the preceding 5 years. Within 1 year of the screening mammogram, 11 638 women were diagnosed with breast cancer. Separate logistic regression risk models were constructed for premenopausal and postmenopausal examinations by use of a stringent (P<.0001) criterion for the inclusion of risk factors. Risk models were constructed with 75% of the data and validated with the remaining 25%. Concordance of the predicted with the observed outcomes was assessed by a concordance (c) statistic after logistic regression model fit. All statistical tests were two-sided. Results: Statistically significant risk factors for breast cancer diagnosis among premenopausal women included age, breast density, family history of breast cancer, and a prior breast procedure. For postmenopausal women, the statistically significant factors included age, breast density, race, ethnicity, family history of breast cancer, a prior breast procedure, body mass index, natural menopause, hormone therapy, and a prior false-positive mammogram. The model may identify high-risk women better than the Gail model, although predictive accuracy was only moderate. The c statistics were 0.631 (95% confidence interval CI = 0.618 to 0.644) for premenopausal women and 0.624 (95% CI = 0.619 to 0.630) for postmenopausal women. Conclusion: Breast density is a strong additional risk factor for breast cancer, although it is unknown whether reduction in breast density would reduce risk. Our risk model may be able to identify women at high risk for breast cancer for preventive interventions or more intensive surveillance.
IMPORTANCE Breast magnetic resonance imaging (MRI) is increasingly used for breast cancer screening, diagnostic evaluation, and surveillance. However, we lack data on national patterns of breast MRI ...use in community practice. OBJECTIVE To describe patterns of breast MRI use in US community practice during the period 2005 through 2009. DESIGN, SETTING, AND PARTICIPANTS Observational cohort study using data collected from 2005 through 2009 on breast MRI and mammography from 5 national Breast Cancer Surveillance Consortium registries. Data included 8931 breast MRI examinations and 1 288 924 screening mammograms from women aged 18 to 79 years. MAIN OUTCOMES AND MEASURES We calculated the rate of breast MRI examinations per 1000 women with breast imaging within the same year and described the clinical indications for the breast MRI examinations by year and age. We compared women screened with breast MRI to women screened with mammography alone for patient characteristics and lifetime breast cancer risk. RESULTS The overall rate of breast MRI from 2005 through 2009 nearly tripled from 4.2 to 11.5 examinations per 1000 women, with the most rapid increase from 2005 to 2007 (P = .02). The most common clinical indication was diagnostic evaluation (40.3%), followed by screening (31.7%). Compared with women who received screening mammography alone, women who underwent screening breast MRI were more likely to be younger than 50 years, white non-Hispanic, and nulliparous and to have a personal history of breast cancer, a family history of breast cancer, and extremely dense breast tissue (all P < .001). The proportion of women screened using breast MRI at high lifetime risk for breast cancer (>20%) increased during the study period from 9% in 2005 to 29% in 2009. CONCLUSIONS AND RELEVANCE Use of breast MRI for screening in high-risk women is increasing. However, our findings suggest that there is a need to improve appropriate use, including among women who may benefit from screening breast MRI.
To retrospectively evaluate the range of performance outcomes of the radiologist in an audit of screening mammography by using a representative sample of U.S. radiologists to allow development of ...performance benchmarks for screening mammography.
Institutional review board approval was obtained, and study was HIPAA compliant. Informed consent was or was not obtained according to institutional review board guidelines. Data from 188 mammographic facilities and 807 radiologists obtained between 1996 and 2002 were analyzed from six registries from the Breast Cancer Surveillance Consortium (BCSC). Contributed data included demographic information, clinical findings, mammographic interpretation, and biopsy results. Measurements calculated were positive predictive values (PPVs) from screening mammography (PPV(1)), biopsy recommendation (PPV(2)), biopsy performed (PPV(3)), recall rate, cancer detection rate, mean cancer size, and cancer stage. Radiologist performance data are presented as 50th (median), 10th, 25th, 75th, and 90th percentiles and as graphic presentations by using smoothed curves.
There were 2 580 151 screening mammographic studies from 1 117 390 women (age range, <30 to >/=80 years). The respective means and ranges of performance outcomes for the middle 50% of radiologists were as follows: recall rate, 9.8% and 6.4%-13.3%; PPV(1), 4.8% and 3.4%-6.2%; and PPV(2), 24.6% and 18.8%-32.0%. Mean cancer detection rate was 4.7 per 1000, and the median corrected mean size of invasive cancers was 13 mm. The range of performance outcomes for the middle 80% of radiologists also was presented.
Community screening mammographic performance measurements of cancer outcomes for the majority of radiologists in the BCSC surpass performance recommendations. Recall rate for almost half of radiologists, however, is higher than the recommended rate.
Mammographic density is a strong risk factor for breast cancer, but limited data are available in African American (AA) women. We examined the association between mammographic density and breast ...cancer risk in AA and white women. Cases (
n
= 491) and controls (
n
= 528) were from the Carolina Breast Cancer Study (CBCS) who also had mammograms recorded in the Carolina Mammography Registry (CMR). Mammographic density was reported to CMR using Breast Imaging Reporting and Data System (BI-RADS) categories. Increasing mammographic density was associated with increased breast cancer risk among all women. After adjusting for potential confounders, a monotonically increasing risk of breast cancer was observed between the highest versus the lowest BI-RADS density categories OR = 2.45, (95 % confidence interval: 0.99, 6.09). The association was stronger in whites, with ~40 % higher risk among those with extremely dense breasts compared to those with scattered fibroglandular densities 1.39, (0.75, 2.55). In AA women, the same comparison suggested lower risk 0.75, (0.30, 1.91). Because age, obesity, and exogenous hormones have strong associations with breast cancer risk, mammographic density, and race in the CBCS, effect measure modification by these factors was considered. Consistent with previous literature, density-associated risk was greatest among those with BMI > 30 and current hormone users (
P
value = 0.02 and 0.01, respectively). In the CBCS, mammographic density is associated with increased breast cancer risk, with some suggestion of effect measure modification by race, although results were not statistically significant. However, exposures such as BMI and hormone therapy may be important modifiers of this association and merit further investigation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
To identify radiologists' characteristics associated with interpretive performance in screening mammography.
The study was approved by institutional review boards of University of Washington ...(Seattle, Wash) and institutions at seven Breast Cancer Surveillance Consortium sites, informed consent was obtained, and procedures were HIPAA compliant. Radiologists who interpreted mammograms in seven U.S. regions completed a self-administered mailed survey; information on demographics, practice type, and experience in and perceptions of general radiology and breast imaging was collected. Survey data were linked to data on screening mammograms the radiologists interpreted between January 1, 1998, and December 31, 2005, and included patient risk factors, Breast Imaging Reporting and Data System assessment, and follow-up breast cancer data. The survey was returned by 71% (257 of 364) of radiologists; in 56% (205 of 364) of the eligible radiologists, complete data on screening mammograms during the study period were provided; these data were used in the final analysis. An evaluation of whether the radiologists' characteristics were associated with recall rate, false-positive rate, sensitivity, or positive predictive value of recall (PPV(1)) of the screening examinations was performed with logistic regression models that were adjusted for patients' characteristics and radiologist-specific random effects.
Study radiologists interpreted 1 036 155 screening mammograms; 4961 breast cancers were detected. Median percentages and interquartile ranges, respectively, were as follows: recall rate, 9.3% and 6.3%-13.2%; false-positive rate, 8.9% and 5.9%-12.8%; sensitivity, 83.8% and 74.5%-92.3%; and PPV(1), 4.0% and 2.6%-5.9%. Wide variability in sensitivity was noted, even among radiologists with similar false-positive rates. In adjusted regression models, female radiologists or fellowship-trained radiologists had significantly higher recall and false-positive rates (P < .05, all). Fellowship training in breast imaging was the only characteristic significantly associated with improved sensitivity (odds ratio, 2.32; 95% confidence interval: 1.42, 3.80; P < .001) and the overall accuracy parameter (odds ratio, 1.61; 95% confidence interval: 1.05, 2.45; P = .028).
Fellowship training in breast imaging may lead to improved cancer detection, but it is associated with higher false-positive rates.
Background: With the large number of women having mammography—an estimated 28.4 million U.S. women aged 40 years and older in 1998—the percentage of cancers detected as ductal carcinoma in situ ...(DCIS), which has an uncertain prognosis, has increased. We pooled data from seven regional mammography registries to determine the percentage of mammographically detected cancers that are DCIS and the rate of DCIS per 1000 mammograms. Methods: We analyzed data on 653 833 mammograms from 540 738 women between 40 and 84 years of age who underwent screening mammography at facilities participating in the National Cancer Institute’s Breast Cancer Surveillance Consortium (BCSC) throughout 1996 and 1997. Mammography results were linked to population-based cancer and pathology registries. We calculated the percentage of screen-detected breast cancers that were DCIS, the rate of screen-detected DCIS per 1000 mammograms by age and by previous mammography status, and the sensitivity of screening mammography. Statistical tests were two-sided. Results: A total of 3266 cases of breast cancer were identified, 591 DCIS and 2675 invasive breast cancer. The percentage of screen-detected breast cancers that were DCIS decreased with age (from 28.2% 95% confidence interval (CI) = 23.9% to 32.5% for women aged 40–49 years to 16.0% 95% CI = 13.3% to 18.7% for women aged 70–84 years). However, the rate of screen-detected DCIS cases per 1000 mammograms increased with age (from 0.56 95% CI = 0.41 to 0.70 for women aged 40–49 years to 1.07 95% CI = 0.87 to 1.27 for women aged 70–84 years). Sensitivity of screening mammography in all age groups combined was higher for detecting DCIS (86.0% 95% CI = 83.2% to 88.8%) than it was for detecting invasive breast cancer (75.1% 95% CI = 73.5% to 76.8%). Conclusions: Overall, approximately 1 in every 1300 screening mammography examinations leads to a diagnosis of DCIS. Given uncertainty about the natural history of DCIS, the clinical significance of screen-detected DCIS needs further investigation.
Detecting and tracking early cystic fibrosis (CF) lung disease are difficult due to lack of sensitive markers of airway dysfunction.
The goals were to detect regional distribution of airway disease ...through high-resolution computed tomography, correlate abnormalities to lower airway inflammation/infection, and compare computed tomography findings before and after intravenous antibiotic therapy in children with CF younger than 4 years experiencing a pulmonary exacerbation.
High-resolution computed tomography was performed in 17 children scheduled for bronchoscopy. The radiologist identified the lobes with the "greatest" and "least" disease based on computed tomography, and bronchoalveolar lavage was performed in these areas. In 13 subjects, imaging was repeated after antibiotic completion. Modified Brody scores were assigned by two radiologists.
The lobe with greatest disease was predominantly localized to the right and had higher modified Brody scores, indicating more severe abnormalities (p < 0.01), compared with the lobe with least disease. The total modified Brody score (p < 0.01), hyperinflation subscore (p < 0.01), and bronchial dilatation/bronchiectasis subscore (p < 0.01) improved after antibiotics and intensified airway clearance. Interleukin-8 levels (p < 0.01) and % neutrophils (p = 0.04) were increased in the lobe with greatest disease compared with the lobe with least disease.
These results indicate that, in young children with CF experiencing a pulmonary exacerbation, computed tomography detects regional differences in airway inflammation, may be a sensitive outcome to evaluate therapeutic interventions, and identifies early lung disease as being more prominent on the right.
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