Performance of First Mammography Examination in Women Younger Than 40 Years
Bonnie C. Yankaskas, Sebastien Haneuse, Julie M. Kapp, Karla Kerlikowske, Berta Geller, Diana S. M. Buist, for the Breast Cancer Surveillance Consortium
J. Natl. Cancer Inst. 2010 102: 692-701
Link to Journal
Few data have been published on mammography performance in women who are younger than 40 years.
Results: For screening mammograms, no cancers were detected in 637 mammograms for women aged 18–24 years. For women aged 35–39 years who had the largest number of screening mammograms (n = 73 335) in this study, the recall rate was 12.7% (95% confidence interval [CI] = 12.4% to 12.9%), sensitivity was 76.1% (95% CI = 69.2% to 82.6%), specificity was 87.5% (95% CI = 87.2% to 87.7%), positive predictive value was 1.3% (95% CI = 1.1% to 1.5%), and cancer detection rate was 1.6 cancers per 1000 mammograms (95% CI = 1.3 to 1.9 cancers per 1000 mammograms). Most (67 468 [77.7%]) of the 86 871 women screened reported no family history of breast cancer. For diagnostic mammograms, the age-adjusted rates across all age groups were: sensitivity of 85.7% (95% CI = 82.7% to 88.7%), specificity of 88.8% (95% CI = 88.4% to 89.1%), positive predictive value of 14.6% (95% CI = 13.3% to 15.8%), and cancer detection rate of 14.3 cancers per 1000 mammograms (95% CI = 13.0 to 15.7 cancers per 1000 mammograms).
Mammography performance, except for specificity, improved in the presence of a breast lump.
Conclusions: Younger women have very low breast cancer rates but after mammography experience high recall rates, high rates of additional imaging, and low cancer detection rates. We found no cancers in women younger than 25 years and poor performance for the large group of women aged 35–39 years. In a theoretical population of 10 000 women aged 35–39 years, 1266 women who are screened will receive further workup, with 16 cancers detected and 1250 women receiving a false-positive result
EDITORIAL: Mammography in Younger Women: The Dilemma of Diminishing Returns
Ned Calonge
J. Natl. Cancer Inst. 2010 102: 668-669
Link to Journal
There are a number of breast cancer screening guidelines for younger women that have been published by prominent health and medical groups including the American Cancer Society (2) and the American College of Radiology (3) that advocate screening starting at approximately age 30 years (or 10 years before the premenopausal diagnosis of breast cancer in their relevant relative) for women with BRCA1 and/or BRCA2 mutations or who are otherwise at increased risk for breast cancer.
The American Cancer Society recommendation also states that "because the evidence is limited regarding the best age at which to start screening, this decision should be based on shared decision-making between patients and their health care providers, taking into account personal circumstances and preferences."
The BCSC analysis provides a retrospective insight on the benefits and harms that might accompany such screening. It is, however, critical to point out that this article investigates mammography only and not the use of magnetic resonance imaging or ultrasound in combination with mammography in screening younger high-risk women.
On the basis of this study alone, it is difficult to extend this recommendation to women with BRCA1 and/or BRCA2 mutations or to other screening modalities, but this same information should be useful in all screening discussions with younger women. If other modalities (such as magnetic resonance imaging) only improve detection rates without improving important health outcomes, recommendations for the use of these modalities may not be warranted, especially if there is a disproportionate increase in false positives (hopefully decreased by modalities such as ultrasound)
Tuesday, 20 July 2010
A review of breast cancer risk assessment models
EDITORIAL: Comparing Breast Cancer Risk Assessment Models
Mitchell H. Gail and Phuong L. Mai
J. Natl. Cancer Inst. 2010 102: 665-668
Link to Journal
Many practitioners counsel women who have few risk factors for breast cancer as well as women with strong family histories. We believe that good calibration is the key requirement for using a particular risk assessment model to weigh the risks and benefits of an intervention and to design intervention trials.
Some applications, such as deciding who should receive screening mammography or allocating prevention resources to women at highest risk, require a risk assessment model with good discriminatory power. None of the models discussed by Amir et al has good discriminatory power, and the authors indicate possible ways to improve it. Promising directions include incorporating mammographic density, information on genotypes or regulation of gene expression [although initial studies have found only modest improvements in discriminatory accuracy from adding single-nucleotide polymorphisms to models and more refined use of pathology data and biomarker data from biopsy samples. Thus, continuing efforts are needed to improve and assess risk models so that they can play a useful role, in concert with preventive interventions, in reducing the burden of breast cancer.
Assessing Women at High Risk of Breast Cancer: A Review of Risk Assessment Models
Eitan Amir, Orit C. Freedman, Bostjan Seruga, and D. Gareth Evans
J. Natl. Cancer Inst. 2010 102: 680-691
Link to Journal
It is well established that the greatest benefit from breast cancer prevention strategies comes from treating women who are at high risk of the disease. Among high-risk women, such prevention strategies have been shown to potentially reduce the incidence of breast cancer by up to 1500 cases per 100 000, whereas among low-risk women, the reduction is at best 25 cases per 100 000.
Consequently, it is imperative that accurate and individualized risk assessment can be carried out so that appropriate women are selected for prevention strategies. A number of models are available to assess both breast cancer risk and the chances of identifying a BRCA1 or BRCA2 mutation.
Some models perform both tasks, but to date, none are totally able to discriminate between families that do and do not have mutations or between women who will and will not develop breast cancer. Steady and incremental improvements in the models are being made, but these changes require revalidation.
The discovery of alleles that are associated with breast cancer risk will add a new layer of complexity to all of these models
Mitchell H. Gail and Phuong L. Mai
J. Natl. Cancer Inst. 2010 102: 665-668
Link to Journal
Many practitioners counsel women who have few risk factors for breast cancer as well as women with strong family histories. We believe that good calibration is the key requirement for using a particular risk assessment model to weigh the risks and benefits of an intervention and to design intervention trials.
Some applications, such as deciding who should receive screening mammography or allocating prevention resources to women at highest risk, require a risk assessment model with good discriminatory power. None of the models discussed by Amir et al has good discriminatory power, and the authors indicate possible ways to improve it. Promising directions include incorporating mammographic density, information on genotypes or regulation of gene expression [although initial studies have found only modest improvements in discriminatory accuracy from adding single-nucleotide polymorphisms to models and more refined use of pathology data and biomarker data from biopsy samples. Thus, continuing efforts are needed to improve and assess risk models so that they can play a useful role, in concert with preventive interventions, in reducing the burden of breast cancer.
Assessing Women at High Risk of Breast Cancer: A Review of Risk Assessment Models
Eitan Amir, Orit C. Freedman, Bostjan Seruga, and D. Gareth Evans
J. Natl. Cancer Inst. 2010 102: 680-691
Link to Journal
It is well established that the greatest benefit from breast cancer prevention strategies comes from treating women who are at high risk of the disease. Among high-risk women, such prevention strategies have been shown to potentially reduce the incidence of breast cancer by up to 1500 cases per 100 000, whereas among low-risk women, the reduction is at best 25 cases per 100 000.
Consequently, it is imperative that accurate and individualized risk assessment can be carried out so that appropriate women are selected for prevention strategies. A number of models are available to assess both breast cancer risk and the chances of identifying a BRCA1 or BRCA2 mutation.
Some models perform both tasks, but to date, none are totally able to discriminate between families that do and do not have mutations or between women who will and will not develop breast cancer. Steady and incremental improvements in the models are being made, but these changes require revalidation.
The discovery of alleles that are associated with breast cancer risk will add a new layer of complexity to all of these models
Thursday, 8 July 2010
Effect of Previous Benign Breast Biopsy on the Interpretive Performance of Subsequent Screening Mammography
Effect of Previous Benign Breast Biopsy on the Interpretive Performance of Subsequent Screening Mammography
Stephen H. Taplin, L. Abraham, B. M. Geller, B. C. Yankaskas, D. S. M. Buist, R. Smith-Bindman, C. Lehman, D. Weaver, P. A. Carney, and W. E. Barlow
JNCI 2010 102;14:1-12
Link to Journal
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
The reduced accuracy reported in this study is clinically important, regardless of whether the biopsy caused the differences, because this will help clinicians inform women about the potential adverse effects of benign biopsy. Our results showed that the unadjusted specificity was reduced by 2.3 percentage points. After adjustment for women's characteristics, evidence of reduced specificity and reduced PPV2 was statistically significant. These differences in specificity mean additional imaging evaluations and potentially more biopsies among women with a benign biopsy history, but our findings regarding sensitivity make it seem unlikely that more cancers were subsequently missed.
Thus, our results could be used to prepare women with a history of a previous benign biopsy when they are being referred for their next mammogram. Although a woman with a previous benign biopsy is more likely to have cancer than someone without such a history, it can also be noted that she has a higher risk of a false-positive screening mammogram. The message before the next mammogram for a woman with a benign biopsy history should be that a positive test must be taken seriously, but there is also a good chance of a false-positive test. Furthermore, it is not likely to affect subsequent cancer detection. Whether this mitigates anxiety at the time of a referral should be studied further because persistent anxiety is the principal long-term consequence of a false-positive mammogram
Stephen H. Taplin, L. Abraham, B. M. Geller, B. C. Yankaskas, D. S. M. Buist, R. Smith-Bindman, C. Lehman, D. Weaver, P. A. Carney, and W. E. Barlow
JNCI 2010 102;14:1-12
Link to Journal
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
The reduced accuracy reported in this study is clinically important, regardless of whether the biopsy caused the differences, because this will help clinicians inform women about the potential adverse effects of benign biopsy. Our results showed that the unadjusted specificity was reduced by 2.3 percentage points. After adjustment for women's characteristics, evidence of reduced specificity and reduced PPV2 was statistically significant. These differences in specificity mean additional imaging evaluations and potentially more biopsies among women with a benign biopsy history, but our findings regarding sensitivity make it seem unlikely that more cancers were subsequently missed.
Thus, our results could be used to prepare women with a history of a previous benign biopsy when they are being referred for their next mammogram. Although a woman with a previous benign biopsy is more likely to have cancer than someone without such a history, it can also be noted that she has a higher risk of a false-positive screening mammogram. The message before the next mammogram for a woman with a benign biopsy history should be that a positive test must be taken seriously, but there is also a good chance of a false-positive test. Furthermore, it is not likely to affect subsequent cancer detection. Whether this mitigates anxiety at the time of a referral should be studied further because persistent anxiety is the principal long-term consequence of a false-positive mammogram
Breast Tissue Composition and Susceptibility to Breast Cancer
Breast Tissue Composition and Susceptibility to Breast Cancer
Norman F. Boyd, Lisa J. Martin, Michael Bronskill, Martin J. Yaffe, Neb Duric, and Salomon Minkin
JNCI 2010 102;16:1-14
Link to Journal
There is now a substantial body of evidence showing that the variations in breast tissue composition that are reflected by mammographic density have the characteristics of a highly heritable quantitative trait and are associated with differences in risk of breast cancer
Characterization of breast density by mammography has several limitations, and the uses of breast density in risk prediction and breast cancer prevention may be improved by other methods of imaging, such as magnetic resonance or ultrasound tomography
Norman F. Boyd, Lisa J. Martin, Michael Bronskill, Martin J. Yaffe, Neb Duric, and Salomon Minkin
JNCI 2010 102;16:1-14
Link to Journal
There is now a substantial body of evidence showing that the variations in breast tissue composition that are reflected by mammographic density have the characteristics of a highly heritable quantitative trait and are associated with differences in risk of breast cancer
Characterization of breast density by mammography has several limitations, and the uses of breast density in risk prediction and breast cancer prevention may be improved by other methods of imaging, such as magnetic resonance or ultrasound tomography
The Elusive Goal of Maintaining Population Cancer Screening: It Is Time for a New Paradigm
The Elusive Goal of Maintaining Population Cancer Screening: It Is Time for a New Paradigm
Jeanne Mandelblatt and Diana Buist
JNCI 2010 102;14:998-999
Link to Journal
EDITORIAL on paper by Vernon.
(Vernon SW, McQueen A, Tiro JA, del Junco DJ. Interventions to promote repeat breast cancer screening with mammography: a systematic review and meta-analysis. J Natl Cancer Inst (2010) 102(14):1023–1039)
Behavioral interventions only increase rates by a small to moderate amount, and there is insufficient evidence to know which approaches are the most effective (2). These results are all the more discouraging because the reviewed studies focused on getting women to undergo only one to two repeat screening examinations and not the 12–13 biennial screenings presently recommended for average risk women aged 50–74 years (3). Even intensive counseling approaches, which included patient navigation (patient education and assistance), showed only a modest return for their high resource intensity. The most effective approaches reported by studies in this analysis appear to be reminder systems, but those studies were too heterogeneous to provide definitive evidence of superiority
From a public health perspective, there are several different potential actions in response to these results: 1) invest in more research to test additional interventions to improve repeat mammography rates,
2) use risk status to match interventions and technology and target communications rather than a "one size fits all" approach,
3) invest in research to understand how to change the structure of care to promote repeat screening,
4) devote more resources to developing better screening tests, and/or
5) use modeling to evaluate which combinations of approaches would have the greatest potential impact on reducing breast cancer mortality and use these data to guide future directions
Jeanne Mandelblatt and Diana Buist
JNCI 2010 102;14:998-999
Link to Journal
EDITORIAL on paper by Vernon.
(Vernon SW, McQueen A, Tiro JA, del Junco DJ. Interventions to promote repeat breast cancer screening with mammography: a systematic review and meta-analysis. J Natl Cancer Inst (2010) 102(14):1023–1039)
Behavioral interventions only increase rates by a small to moderate amount, and there is insufficient evidence to know which approaches are the most effective (2). These results are all the more discouraging because the reviewed studies focused on getting women to undergo only one to two repeat screening examinations and not the 12–13 biennial screenings presently recommended for average risk women aged 50–74 years (3). Even intensive counseling approaches, which included patient navigation (patient education and assistance), showed only a modest return for their high resource intensity. The most effective approaches reported by studies in this analysis appear to be reminder systems, but those studies were too heterogeneous to provide definitive evidence of superiority
From a public health perspective, there are several different potential actions in response to these results: 1) invest in more research to test additional interventions to improve repeat mammography rates,
2) use risk status to match interventions and technology and target communications rather than a "one size fits all" approach,
3) invest in research to understand how to change the structure of care to promote repeat screening,
4) devote more resources to developing better screening tests, and/or
5) use modeling to evaluate which combinations of approaches would have the greatest potential impact on reducing breast cancer mortality and use these data to guide future directions
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