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Following the introduction of mammography, women were considerably more likely to have tumors that were overdiagnosed than to have earlier detection of a tumor that was destined to become large, according to an analysis of trends from the Surveillance, Epidemiology, and End Results (SEER) database.
To assess the effectiveness of screening mammography in the real-world clinical and community setting, H. Gilbert Welch, MD, of the Dartmouth Institute for Health Policy and Clinical Practice and his associates examined trends in breast tumor size between the years of 1975 and 2012, a span of time that can be broken down into two distinct periods: a baseline period that predated the widespread use of screening mammography (1975-1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002).
Retrospective analysis of the SEER database revealed a shift in the size distribution of breast tumors: Large tumors, defined as invasive tumors measuring two centimeters or more, predominated in the period before widespread screening mammography, and small tumors, defined as in situ carcinomas or invasive tumors measuring less than two centimeters, predominated after.
This shift, the researchers noted, can, in part, be attributed to the use of screening mammography.
Overall, from 1975 to 2012, the proportion of breast tumors that were small increased from 36% to 68%. In that same time period, the proportion of large tumors decreased from 64% to 32%.
“This shift in size distribution was less the result of a substantial decrease in the incidence of large tumors and more the result of substantial increases in the detection of small tumors,” Dr. Welch and his associates wrote.
Put another way, the incidence of small tumors increased by 162 cases of cancer per 100,000 women, from 82 to 244 cases, while the incidence of large tumors decreased by 30 cases of cancer per 100,000 women, from 145 to 115 cases. “Assuming that the underlying burden of clinically meaningful breast cancer was unchanged, these data suggest that 30 cases of cancer per 100,000 women were destined to become large but were detected earlier, and the remaining 132 cases of cancer per 100,000 women were overdiagnosed,” the researchers wrote.
“The magnitude of the imbalance indicates that women were considerably more likely to have tumors that were overdiagnosed than to have earlier detection of a tumor that was destined to become large,” the researchers continued. “Our analysis of size-specific incidence highlights the fact that the introduction of screening mammography has produced a mixture of effects,” Dr. Welch and his associates added.
The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth’s Geisel School of Medicine, and the National Cancer Institute supported this study. The investigators had no relevant disclosures.
Overdiagnosis of breast cancer has been suggested on the basis of multiple studies that used different designs and approaches and is acknowledged by national organizations such as the American Cancer Society and the U.S. Preventive Services Task Force. Although Dr. Welch and his associates present powerful data on a large number of women in a very clear fashion, they also rely on data with extensive missing values, make assumptions about underlying disease burden that cannot be verified, and acknowledge that their estimates are imprecise.
Rather than focusing on statistical issues and study design, we should move forward by agreeing that overdiagnosis does occur, even though the exact percentage of overdiagnosed cases remains unknown. Some consider overdiagnosis to be an intractable problem. No single approach will adequately address the issue. Instead, a multilevel approach ranging from research and education at the population level to intensified focus at the patient level is needed. One way to reduce overdiagnosis is targeted, precision screening of persons who have a higher risk of breast cancer rather than screening large populations in which the majority of persons are at a lower risk for harmful disease.
At the provider level, we need better tools to evaluate medical data and classify findings on the basis of clinical judgment. Previous research has documented extensive diagnostic variability among radiologists in their interpretation of mammograms and among pathologists in their interpretation of breast biopsy specimens. We are using archaic disease-classification systems with inadequate vetting and defective nosologic boundaries. Diagnostic thresholds for “abnormality” need to be revised because the middle and lower boundaries of these classification systems have expanded without a clear benefit to patients.
Rigorous analytic methods are required for the development of disease nosologies, and physicians need more sophisticated tools to improve diagnostic precision and accuracy. At the patient level, we need better methods of distinguishing biologically self-limited tumors from harmful tumors that progress. We must also improve communication regarding overdiagnosis at all levels, from dissemination of scientific findings at a population level to education of patients before they undergo screening.
Clinicians face time constraints and lack experience in communicating screening nuances. Better training may help. Building trust in science and medicine starts by taking ownership of all aspects of the screening cascade, including the collateral damage of our well-intentioned efforts.
Dr. Elmore is a professor of medicine and adjunct professor of epidemiology at the University of Washington. Dr. Elmore reported having no relevant disclosures related to this commentary but did report receiving financial compensation from UpToDate and Healthwise/Informed Medical Decisions Foundation. These comments are excerpted from an accompanying editorial (N Engl J Med. 2016 Oct 12;375[15]:1483-6).
Overdiagnosis of breast cancer has been suggested on the basis of multiple studies that used different designs and approaches and is acknowledged by national organizations such as the American Cancer Society and the U.S. Preventive Services Task Force. Although Dr. Welch and his associates present powerful data on a large number of women in a very clear fashion, they also rely on data with extensive missing values, make assumptions about underlying disease burden that cannot be verified, and acknowledge that their estimates are imprecise.
Rather than focusing on statistical issues and study design, we should move forward by agreeing that overdiagnosis does occur, even though the exact percentage of overdiagnosed cases remains unknown. Some consider overdiagnosis to be an intractable problem. No single approach will adequately address the issue. Instead, a multilevel approach ranging from research and education at the population level to intensified focus at the patient level is needed. One way to reduce overdiagnosis is targeted, precision screening of persons who have a higher risk of breast cancer rather than screening large populations in which the majority of persons are at a lower risk for harmful disease.
At the provider level, we need better tools to evaluate medical data and classify findings on the basis of clinical judgment. Previous research has documented extensive diagnostic variability among radiologists in their interpretation of mammograms and among pathologists in their interpretation of breast biopsy specimens. We are using archaic disease-classification systems with inadequate vetting and defective nosologic boundaries. Diagnostic thresholds for “abnormality” need to be revised because the middle and lower boundaries of these classification systems have expanded without a clear benefit to patients.
Rigorous analytic methods are required for the development of disease nosologies, and physicians need more sophisticated tools to improve diagnostic precision and accuracy. At the patient level, we need better methods of distinguishing biologically self-limited tumors from harmful tumors that progress. We must also improve communication regarding overdiagnosis at all levels, from dissemination of scientific findings at a population level to education of patients before they undergo screening.
Clinicians face time constraints and lack experience in communicating screening nuances. Better training may help. Building trust in science and medicine starts by taking ownership of all aspects of the screening cascade, including the collateral damage of our well-intentioned efforts.
Dr. Elmore is a professor of medicine and adjunct professor of epidemiology at the University of Washington. Dr. Elmore reported having no relevant disclosures related to this commentary but did report receiving financial compensation from UpToDate and Healthwise/Informed Medical Decisions Foundation. These comments are excerpted from an accompanying editorial (N Engl J Med. 2016 Oct 12;375[15]:1483-6).
Overdiagnosis of breast cancer has been suggested on the basis of multiple studies that used different designs and approaches and is acknowledged by national organizations such as the American Cancer Society and the U.S. Preventive Services Task Force. Although Dr. Welch and his associates present powerful data on a large number of women in a very clear fashion, they also rely on data with extensive missing values, make assumptions about underlying disease burden that cannot be verified, and acknowledge that their estimates are imprecise.
Rather than focusing on statistical issues and study design, we should move forward by agreeing that overdiagnosis does occur, even though the exact percentage of overdiagnosed cases remains unknown. Some consider overdiagnosis to be an intractable problem. No single approach will adequately address the issue. Instead, a multilevel approach ranging from research and education at the population level to intensified focus at the patient level is needed. One way to reduce overdiagnosis is targeted, precision screening of persons who have a higher risk of breast cancer rather than screening large populations in which the majority of persons are at a lower risk for harmful disease.
At the provider level, we need better tools to evaluate medical data and classify findings on the basis of clinical judgment. Previous research has documented extensive diagnostic variability among radiologists in their interpretation of mammograms and among pathologists in their interpretation of breast biopsy specimens. We are using archaic disease-classification systems with inadequate vetting and defective nosologic boundaries. Diagnostic thresholds for “abnormality” need to be revised because the middle and lower boundaries of these classification systems have expanded without a clear benefit to patients.
Rigorous analytic methods are required for the development of disease nosologies, and physicians need more sophisticated tools to improve diagnostic precision and accuracy. At the patient level, we need better methods of distinguishing biologically self-limited tumors from harmful tumors that progress. We must also improve communication regarding overdiagnosis at all levels, from dissemination of scientific findings at a population level to education of patients before they undergo screening.
Clinicians face time constraints and lack experience in communicating screening nuances. Better training may help. Building trust in science and medicine starts by taking ownership of all aspects of the screening cascade, including the collateral damage of our well-intentioned efforts.
Dr. Elmore is a professor of medicine and adjunct professor of epidemiology at the University of Washington. Dr. Elmore reported having no relevant disclosures related to this commentary but did report receiving financial compensation from UpToDate and Healthwise/Informed Medical Decisions Foundation. These comments are excerpted from an accompanying editorial (N Engl J Med. 2016 Oct 12;375[15]:1483-6).
Following the introduction of mammography, women were considerably more likely to have tumors that were overdiagnosed than to have earlier detection of a tumor that was destined to become large, according to an analysis of trends from the Surveillance, Epidemiology, and End Results (SEER) database.
To assess the effectiveness of screening mammography in the real-world clinical and community setting, H. Gilbert Welch, MD, of the Dartmouth Institute for Health Policy and Clinical Practice and his associates examined trends in breast tumor size between the years of 1975 and 2012, a span of time that can be broken down into two distinct periods: a baseline period that predated the widespread use of screening mammography (1975-1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002).
Retrospective analysis of the SEER database revealed a shift in the size distribution of breast tumors: Large tumors, defined as invasive tumors measuring two centimeters or more, predominated in the period before widespread screening mammography, and small tumors, defined as in situ carcinomas or invasive tumors measuring less than two centimeters, predominated after.
This shift, the researchers noted, can, in part, be attributed to the use of screening mammography.
Overall, from 1975 to 2012, the proportion of breast tumors that were small increased from 36% to 68%. In that same time period, the proportion of large tumors decreased from 64% to 32%.
“This shift in size distribution was less the result of a substantial decrease in the incidence of large tumors and more the result of substantial increases in the detection of small tumors,” Dr. Welch and his associates wrote.
Put another way, the incidence of small tumors increased by 162 cases of cancer per 100,000 women, from 82 to 244 cases, while the incidence of large tumors decreased by 30 cases of cancer per 100,000 women, from 145 to 115 cases. “Assuming that the underlying burden of clinically meaningful breast cancer was unchanged, these data suggest that 30 cases of cancer per 100,000 women were destined to become large but were detected earlier, and the remaining 132 cases of cancer per 100,000 women were overdiagnosed,” the researchers wrote.
“The magnitude of the imbalance indicates that women were considerably more likely to have tumors that were overdiagnosed than to have earlier detection of a tumor that was destined to become large,” the researchers continued. “Our analysis of size-specific incidence highlights the fact that the introduction of screening mammography has produced a mixture of effects,” Dr. Welch and his associates added.
The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth’s Geisel School of Medicine, and the National Cancer Institute supported this study. The investigators had no relevant disclosures.
Following the introduction of mammography, women were considerably more likely to have tumors that were overdiagnosed than to have earlier detection of a tumor that was destined to become large, according to an analysis of trends from the Surveillance, Epidemiology, and End Results (SEER) database.
To assess the effectiveness of screening mammography in the real-world clinical and community setting, H. Gilbert Welch, MD, of the Dartmouth Institute for Health Policy and Clinical Practice and his associates examined trends in breast tumor size between the years of 1975 and 2012, a span of time that can be broken down into two distinct periods: a baseline period that predated the widespread use of screening mammography (1975-1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002).
Retrospective analysis of the SEER database revealed a shift in the size distribution of breast tumors: Large tumors, defined as invasive tumors measuring two centimeters or more, predominated in the period before widespread screening mammography, and small tumors, defined as in situ carcinomas or invasive tumors measuring less than two centimeters, predominated after.
This shift, the researchers noted, can, in part, be attributed to the use of screening mammography.
Overall, from 1975 to 2012, the proportion of breast tumors that were small increased from 36% to 68%. In that same time period, the proportion of large tumors decreased from 64% to 32%.
“This shift in size distribution was less the result of a substantial decrease in the incidence of large tumors and more the result of substantial increases in the detection of small tumors,” Dr. Welch and his associates wrote.
Put another way, the incidence of small tumors increased by 162 cases of cancer per 100,000 women, from 82 to 244 cases, while the incidence of large tumors decreased by 30 cases of cancer per 100,000 women, from 145 to 115 cases. “Assuming that the underlying burden of clinically meaningful breast cancer was unchanged, these data suggest that 30 cases of cancer per 100,000 women were destined to become large but were detected earlier, and the remaining 132 cases of cancer per 100,000 women were overdiagnosed,” the researchers wrote.
“The magnitude of the imbalance indicates that women were considerably more likely to have tumors that were overdiagnosed than to have earlier detection of a tumor that was destined to become large,” the researchers continued. “Our analysis of size-specific incidence highlights the fact that the introduction of screening mammography has produced a mixture of effects,” Dr. Welch and his associates added.
The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth’s Geisel School of Medicine, and the National Cancer Institute supported this study. The investigators had no relevant disclosures.
Key clinical point:
Major finding: Of a population of 100,000 women, mammography detected 30 small tumors that were destined to become large but were detected earlier, while 132 cases of cancer were overdiagnosed.
Data source: Retrospective analysis of SEER data from 1975 to 2012.
Disclosures: The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth’s Geisel School of Medicine, and the National Cancer Institute supported this study. The investigators had no relevant disclosures.