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Methods We used data from the Surveillance, Epidemiology, and End Results (SEER) program, 1975 through 2012, to calculate the tumor-size distribution and size-specific incidence of breast cancer among women 40 years of age or older. We then calculated the size-specific cancer case fatality rate for two time periods: a baseline period before the implementation of widespread screening mammography (1975 through 1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002). Results After the advent of screening mammography, the proportion of detected breast tumors that were small (invasive tumors measuring. Conclusions Although the rate of detection of large tumors fell after the introduction of screening mammography, the more favorable size distribution was primarily the result of the additional detection of small tumors. Women were more likely to have breast cancer that was overdiagnosed than to have earlier detection of a tumor that was destined to become large.

The reduction in breast cancer mortality after the implementation of screening mammography was predominantly the result of improved systemic therapy. Figure 1 Temporal Relationship between the Introduction of Screening Mammography and Increased Incidence of Invasive Breast Cancer. Shown are the incidences of overall invasive breast cancer and metastatic breast cancer among women 40 years of age or older at nine sites of the Surveillance, Epidemiology, and End Results (SEER) program, during the period from 1975 through 2012. The use of screening mammography was rare before 1980 (as evidenced by the rarity of ductal carcinoma in situ — an abnormality that is nearly always detected by mammography rather than by breast self-examination, physical examination, or the development of symptoms), yet its use had disseminated to over half of women 40 years of age or older by 1990 (as determined by responses to a National Health Interview Survey question in which women were asked if they had had a mammogram in either 1988 or 1989 ). Figure 2 Breast-Cancer Tumor-Size Distribution and Size-Specific Incidence among Women 40 Years of Age or Older in the United States, 1975–2012.

Panel A shows the shift in the size distribution of breast tumors over time. The percentages along the left side of the panel represent the size distribution during the period from 1975 through 1979 (before the widespread use of mammography screening) and those along the right side represent the period from 2008 through 2012. Larger tumors are shown in shades of red, and smaller tumors in shades of blue. Percentages may not sum to 100 because of rounding. Panel B shows the size-specific incidence of breast cancer per 100,000 women.

Although it may be possible to show the efficacy of screening mammography in reducing cancer-specific mortality in the relatively controlled setting of randomized trials, those trials may not accurately reflect the actual effectiveness of screening when it is used in clinical practice. Differences between efficacy and effectiveness with respect to the benefit of screening may be particularly stark when the treatments administered in practice have markedly changed from those administered in the trials that led to the implementation of widespread screening.

Furthermore, although trial data may provide an assessment of some negative consequences of screening, such as false positive results and associated diagnostic procedures, such assessments may understate what actually occurs when screening is implemented in the general community. The collection of data regarding other harms, such as overdiagnosis (i.e., tumors detected on screening that never would have led to clinical symptoms), requires additional long-term follow-up of trial participants, and those data are often either not available or they reflect patient follow-up and testing practices from decades earlier. One response to these challenges in the assessment of the population effects of screening mammography has been microsimulation modeling. The output of statistical models has the appeal of quantitative precision, but the precision may be more apparent than real. Modeling is only as good as its data inputs and underlying assumptions, particularly those regarding the (unobserved) natural history of tumors detected with the use of screening mammography. Not surprisingly, different models elicit a wide range of results; in the models used by the Cancer Intervention and Surveillance Modeling Network, for example, the estimates of the contribution of screening to the observed reduction in breast-cancer mortality ranged from as little as 28% to as much as 65%.. Furthermore, the complexity of modeling limits the ability of peer reviewers and journal readers to assess the validity of the approach.

To assess the potential mortality benefit and the potential harm of overdiagnosis associated with breast-cancer screening, we used a transparent approach in which the objective was to approximate the magnitude of these effects rather than to attempt precise estimation. We used population data on tumor size, a variable that has been collected for decades and is a direct proximate indicator of screening effect. Although the biologic characteristics of a tumor are now recognized to be more relevant to breast-cancer prognosis than the size of the tumor, tumor size is more relevant to the assessment of the proximate effect of screening. Screening mammography is not an assessment of functional gene expression; rather, it is an anatomy-based search for small structural abnormalities that are too small to be felt. Thus, the ultimate goal of reduced cancer-specific mortality must be mediated through tumor size at diagnosis. In this analysis, we used trends in malignant breast-tumor size to approximate the contribution of screening mammography to the reduction in breast-cancer mortality and to estimate the magnitude of overdiagnosis. Overview To assess the effectiveness of screening mammography, we examined trends in breast-tumor size at diagnosis.

We started with the assumption that the underlying probability that clinically meaningful breast cancer would develop was stable, an assumption we believe was warranted given the stable incidence of metastatic breast cancer for more than three decades, despite spanning the era of increasing prevalence of screening-mediated breast cancer and changing patterns of hormone therapy ( Figure 1 Temporal Relationship between the Introduction of Screening Mammography and Increased Incidence of Invasive Breast Cancer. Shown are the incidences of overall invasive breast cancer and metastatic breast cancer among women 40 years of age or older at nine sites of the Surveillance, Epidemiology, and End Results (SEER) program, during the period from 1975 through 2012. The use of screening mammography was rare before 1980 (as evidenced by the rarity of ductal carcinoma in situ — an abnormality that is nearly always detected by mammography rather than by breast self-examination, physical examination, or the development of symptoms), yet its use had disseminated to over half of women 40 years of age or older by 1990 (as determined by responses to a National Health Interview Survey question in which women were asked if they had had a mammogram in either 1988 or 1989 ).

All the analyses were performed in the same study population: women 40 years of age or older at nine long-standing sites of the Surveillance, Epidemiology, and End Results (SEER) program, which represents approximately 10% of the population of the United States. The SEER program is the population-based registry for incident cancers in the United States. It is broadly representative of the nation as a whole; SEER-based estimates of breast-cancer mortality are virtually identical to those ascertained from U.S. Mortality data, and the SEER program has had virtually complete case ascertainment and reporting for decades. The study period, 1975 through 2012, spans the time periods before and after the widespread dissemination of screening mammography. All population rates are age-adjusted to the standard population of the United States in 2000.

Tumor-Size Distribution and Size-Specific Incidence We classified the recorded size of invasive breast tumors in five categories (details regarding these categories are provided in Section 1 in the, available with the full text of this article at NEJM.org). In situ carcinomas were included as a separate category.

The denominator for the determination of tumor-size distribution was the number of women with a diagnosis of breast cancer; the denominator for the determination of size-specific incidence was the number of women in the study population. In both cases, the numerator was the number of women with breast cancer within each size category. Missing data with respect to tumor size decreased with time; missing data were common in the early years (33% of tumors were of unknown size in the period from 1975 through 1979), then became less common (5% of tumors were of unknown size in the period from 2008 through 2012).

If we had directly calculated size-specific incidence by excluding tumors of unknown size, this decreasing frequency of missing data on size would have produced a spuriously low baseline incidence followed by a spuriously large increase, which would have led us to overestimate overdiagnosis and underestimate the contribution of screening to lowering mortality. To avoid this bias, we used inverse-probability weighting to calculate the tumor-size distribution. The data for each woman with a known tumor size were weighted by the reciprocal of the probability that similar women — those with identical values of observed characteristics — had tumors that were of a known size (details of this analysis are provided in Section 2 in the ). Size-specific incidence was then calculated by multiplying the proportion of tumors in the specific size category by the overall incidence of invasive breast cancer. Ten-Year Risk of Death from Breast Cancer We calculated the 10-year risk of death from breast cancer (case fatality rate) for two time periods: a baseline period before the advent of widespread screening mammography (1975 through 1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002). The denominator for the determination of case fatality rate was the number of women who received a diagnosis of breast cancer at the beginning of a 10-year period, and the numerator was the number of deaths from breast cancer within 10 years after diagnosis.

Magnitude of Overdiagnosis An increased incidence of small tumors is an early indicator of screening effect that could be the result of either effective screening or overdiagnosis. Assuming a stable underlying incidence of disease burden and no overdiagnosis of tumors, the additional detection of small tumors should be accompanied by a corresponding decrease in large tumors over time. In other words, the potential benefit of screening is to identify women in whom larger tumors are destined to develop and to make the diagnosis of the cancer earlier, when their tumors are still small. Dompdf Install New Fonts Vista. A decrease in the incidence of larger tumors suggests that earlier detection is occurring — a necessary, but not sufficient, condition for screening to result in lower mortality (with the second condition being that earlier treatment of these tumors must be more effective than treatment after clinical presentation). The extent to which diagnosis of additional smaller tumors exceeds the decrease in the incidence of larger tumors approximates the magnitude of overdiagnosis in the population. Relative Contribution of Improved Cancer Treatment versus Screening Analyses of the relative contribution of improved treatment of breast cancer versus screening to lowering breast-cancer mortality were limited to the larger tumors (invasive tumors measuring ≥2 cm). This restriction was established for two reasons: the potential benefit of screening in lowering mortality should be mediated largely through the reduction in the incidence of the larger tumors, and the case fatality rate is a relatively unbiased estimate of the treatment effect in larger tumors because those tumors are detected predominantly clinically, which minimizes biases associated with lead time, length, and overdiagnosis.

Lead-time bias refers to the overestimation of the duration of survival among women with screening-detected tumors (relative to tumors detected by signs and symptoms) when survival is measured from diagnosis. Length bias refers to the overestimation of the duration of survival among women with screening-detected tumors, with the overestimation caused by the relative excess of cases that progress slowly; these cases are disproportionately identified by screening because the probability of detection is directly proportional to the length of time during which they are detectable. Overdiagnosis bias refers to the overestimation of the duration of survival among women with screening-detected tumors, with the overestimation caused by the inclusion of “pseudodisease” — subclinical disease that would not become overt before the patient dies of other causes.

(Further details regarding these biases can be found at.) The contribution of improved treatment to lowering breast-cancer mortality in the absence of screening was approximated by holding size-specific incidence constant at prescreening levels and applying the reduction in size-specific case fatality rate over time periods of increasingly effective systemic therapy. The contribution of screening was approximated by applying the reduction of size-specific incidence to a constant size-specific case fatality rate. To explore the effect of screening both before and after improvement in therapy, we performed the latter calculation twice, according to the case fatality rate associated with older therapy (1975 through 1979) and the rate associated with more recent therapy (2000 through 2002). Tumor-Size Distribution and Size-Specific Incidence The shift in the size distribution of breast tumors associated with the widespread use of screening mammography is shown in Figure 2 Breast-Cancer Tumor-Size Distribution and Size-Specific Incidence among Women 40 Years of Age or Older in the United States, 1975–2012. Panel A shows the shift in the size distribution of breast tumors over time.

The percentages along the left side of the panel represent the size distribution during the period from 1975 through 1979 (before the widespread use of mammography screening) and those along the right side represent the period from 2008 through 2012. Larger tumors are shown in shades of red, and smaller tumors in shades of blue. Percentages may not sum to 100 because of rounding. Panel B shows the size-specific incidence of breast cancer per 100,000 women.. Although large tumors predominated in the period before the advent of screening, small tumors predominated after its implementation. From 1975 to 2012, the proportion of breast tumors that were small (invasive tumors measuring.

Size-Specific Case Fatality Rate The size-specific case fatality rates during the baseline period before the introduction of screening mammography and the period encompassing the most recent years for which 10 years of follow-up data were available are shown in Figure 3 Change in Size-Specific Case Fatality Rate. Data are shown for the size-specific 10-year risk of death from breast cancer (case fatality rate) among women 40 years of age or older with breast cancer that was treated before the introduction of screening mammography (diagnosis during the period from 1975 through 1979) and during the most recent years for which 10 years of follow-up were available (diagnosis during the period from 2000 through 2002). The relative risk is for the risk in 2000 through 2002 versus 1975 through 1979. In the period from 2000 through 2002, women with tumors less than 1 cm in size were more than 4 times as likely to die from causes other than breast cancer than from breast cancer.

In that same period, women with in situ carcinoma were more than 10 times as likely to die from causes other than breast cancer than from breast cancer. Details of this analysis are provided in Section 3 in the.. For large tumors, the declining case fatality rate predominantly reflected improved treatment. For small tumors, however, the declining case fatality rate was biased by the combined effect of lead time, length, and overdiagnosis. In fact, during the period from 2000 through 2002, women with in situ carcinomas or those with invasive tumors measuring less than 1 cm had 10-year relative survival rates that exceeded 100% — meaning that they were more likely than age-matched women in the general population to survive. Relative survival refers to the ratio of the proportion of survivors in a cohort of patients with cancer to the proportion of survivors in a comparable set of persons free from cancer. Details of this analysis are provided in Section 3 in the.

The approximate effect of improved treatment of breast cancer on mortality had screening mammography not occurred is shown in Table 2 Approximations of the Effects of Improved Breast-Cancer Treatment and Screening Mammography on Breast-Cancer Mortality among Women 40 Years of Age or Older.. The estimated reduction in mortality owing to treatment alone was approximately 17 deaths per 100,000 women. Effects of Screening Mammography on Mortality The effect of screening mammography on mortality given previously available therapies and more recent available therapies is also shown in. In this analysis, the reduction in the incidence of large tumors was attributed to screening, and this reduction was assumed to translate directly to a reduction in mortality. During the period of previously available therapy, the reduction in mortality as a result of screening mammography was approximately 12 deaths per 100,000 women. As treatment improved, the benefit of early detection of tumors necessarily diminished: the reduction in mortality as a result of screening during the period of more recent therapy was approximately 8 deaths per 100,000 women. Thus, improved treatment was responsible for at least two thirds (i.e., 17 divided by the sum of 17 and 8) of the reduction in breast cancer mortality.

Discussion Decisions about cancer prognosis and therapy have historically been guided by anatomy — the size of the tumor and the extent of disease. However, it has become increasingly clear that the biologic characteristics of the tumor are more relevant to breast-cancer prognosis than the size of the tumor. Tumor size is, at best, a very crude manifestation of underlying biologic characteristics. A recent prospective trial involving women with breast cancer showed that the prognoses of those whose tumors had favorable molecular features were similar regardless of whether their tumors measured greater than or less than 2 cm.

Although few clinicians would question that nodal status is a far better indicator of metastatic potential and biologic aggressiveness than tumor size, some even question whether advances in tumor biology will supplant the need to determine lymph-node status. However, while clinicians have moved on to focus on tumor biology, breast-cancer screening has remained rooted in anatomy. The immediate focus of screening continues to be the detection of small lesions; in fact, the detection rate of so-called “minimal tumors” (i.e., invasive tumors measuring. Source Information From the Dartmouth Institute for Health Policy and Clinical Practice, Lebanon (H.G.W., A.J.O.), and the Departments of Medicine (H.G.W.) and Biomedical Data Science (A.J.O.), Geisel School of Medicine, Hanover — both in New Hampshire; and the Division of Cancer Prevention, National Cancer Institute, Bethesda, MD (P.C.P., B.S.K.).

Address reprint requests to Dr. Welch at the Dartmouth Institute for Health Policy and Clinical Practice, 35 Centerra Pkwy., HB 7251, Lebanon, NH 03766,.