viernes, 27 de diciembre de 2019

Breast Cancer Screening (PDQ®)–Health Professional Version - National Cancer Institute

Breast Cancer Screening (PDQ®)–Health Professional Version - National Cancer Institute

National Cancer Institute

Breast Cancer Screening (PDQ®)–Health Professional Version

Mammography

Description and Background

Mammography utilizes ionizing radiation to image breast tissue. The examination is performed by compressing the breast firmly between two plates, which spreads out overlapping tissues and reduces the amount of radiation needed for the image. For routine screening in the United States, examinations are taken in both mediolateral oblique and craniocaudal projections.[1] Both views will include breast tissue from the nipple to the pectoral muscle. Radiation exposure is 4 to 24 mSv per standard two-view screening examination. Two-view examinations have a lower recall rate than single-view examinations because they reduce concern about abnormalities caused by superimposition of normal breast structures.[2] Two-view exams have lower interval cancer rates than single-view exams.[3]
Under the Mammography Quality Standards Act (MQSA) enacted by Congress in 1992, all U.S. facilities that perform mammography must be certified by the U.S. Food and Drug Administration (FDA) to ensure the use of standardized training for personnel and a standardized mammography technique utilizing a low radiation dose.[4] (Refer to the FDA's web page on Mammography Facility Surveys, Mammography Equipment Evaluations, and Medical Physicist Qualification Requirement under MQSA.) The 1998 MQSA Reauthorization Act requires that patients receive a written lay-language summary of mammography results.
The following Breast Imaging Reporting and Data System (BI-RADS) categories are used for reporting mammographic results:[5]
  • 0: Incomplete—needs additional image evaluation and/or prior mammograms for comparison.
  • 1: Negative; the risk of cancer diagnosis within 1 year is 1%.
  • 2: Benign; the risk of cancer diagnosis within 1 year is 1%.
  • 3: Probably benign; the risk of cancer diagnosis within 1 year is 2%.
  • 4: Suspicious; the risk of cancer diagnosis within 1 year is 2%–95%.
    • 4a: 2%–10%.
    • 4b: 10%–50%.
    • 4c: 50%–95%.
  • 5: Highly suggestive of malignancy; the risk of cancer diagnosis within 1 year is 95%.
  • 6: Known biopsy—proven malignancy.
Most screening mammograms are interpreted as negative or benign (BI-RADS 1 or 2, respectively); about 10% of women in the United States are asked to return for additional evaluation.[6] The percentage of women asked to return for additional evaluation varies not only by the inherent characteristics of each woman but also by the mammography facility and radiologist.[7]

Digital Mammography and Computer-Aided Detection

Digital mammography is more expensive than screen-film mammography (SFM) but is more amenable to data storage and sharing. Performance of both SFM and digital mammography for cancer detection rate, sensitivity, specificity, and positive predictive value (PPV) has been compared directly in several trials, with similar results in most patient groups.
The Digital Mammographic Imaging Screening Trial (DMIST) compared the findings of digital and film mammograms in 42,760 women at 33 U.S. centers. Although digital mammography detected more cancers in women younger than 50 years (area under the curve [AUC] of 0.84 +/- 0.03 for digital; AUC of 0.69 +/- 0.05 for film; P = .002), there was no difference in breast cancer detection overall.[8] A second DMIST report found a trend toward higher AUC for film mammography than for digital mammography in women aged 65 years and older.[9]
Another large U.S. cohort study [10] also found slightly better sensitivity for film mammography for women younger than 50 years with similar specificity.
A Dutch study compared the findings of 1.5 million digital versus 4.5 million screen-film screening mammograms performed between 2004 and 2010. A higher recall and cancer detection rate was observed for the digital screens.[11] A meta-analysis [12] of 10 studies, including the DMIST [8,9] and the U.S. cohort study,[10] compared digital mammography and film mammography in 82,573 women who underwent both types of the exam. In a random-effects model, there was no statistically significant difference in cancer detection between the two types of mammography (AUC of 0.92 for film and AUC of 0.91 for digital). For women younger than 50 years, all studies found that sensitivity was higher for digital mammography, but specificity was either the same or higher for film mammography.
Computer-aided detection (CAD) systems highlight suspicious regions, such as clustered microcalcifications and masses,[13] generally increasing sensitivity, decreasing specificity,[14] and increasing detection of ductal carcinoma in situ (DCIS).[15] Several CAD systems are in use. One large population-based study that compared recall rates and breast cancer detection rates before and after the introduction of CAD systems, found no change in either rate.[13,16] Another large study noted an increase in recall rate and increased DCIS detection but no improvement in invasive cancer detection rate.[15,17] Another study, using a large database and digital mammography in women aged 40 to 89 years, found that CAD did not improve sensitivity, specificity, or detection of interval cancers, but it did detect more DCIS.[18]
The use of new screening mammography modalities by more than 270,000 women aged 65 years and older in two time periods, 2001 to 2002 and 2008 to 2009, was examined, relying on a Surveillance, Epidemiology, and End Results (SEER)–Medicare-linked database. Digital mammography increased from 2% to 30%, CAD increased from 3% to 33%, and spending increased from $660 million to $962 million. CAD was used in 74% of screening mammograms paid for by Medicare in 2008, almost twice as many screening mammograms as in 2004. There was no difference in detection rates of early-stage (DCIS or stage I) or late-stage (stage IV) tumors.[19]

Tomosynthesis

Tomosynthesis, or 3-dimensional (3-D) mammography, like standard 2-D mammography, compresses the breast and uses x-rays to create the image. Multiple short-exposure x-rays are obtained at different angles. Some cancers are better seen with this method than on mammography or ultrasound. The radiation dose is double that of 2-D mammography.
Observational data from eight screening facilities in Vermont allowed the comparison of findings from 86,379 digital breast tomosynthesis (DBT) and 97,378 full-field digital mammography (FFDM) screening examinations performed between 2012 and 2016. Women were included if they had no history of breast cancer or breast implants and if they had not chosen to opt out of clinical research projects. Demographic and risk factor information was obtained by questionnaire, and pathology for all biopsies was obtained through the Vermont Breast Cancer Surveillance System. Recall rate was lower with DBT than with FFDM (7.9% vs. 10.9%; 95% confidence interval [CI], 0.77–0.85), but there was no difference in the rates of biopsy or the detection of benign or malignant disease.[20]

Characteristics of Cancers Detected by Breast Imaging

Regardless of stage, nodal status, and tumor size, screen-detected cancers have a better prognosis than those diagnosed outside of screening.[2] This suggests that they are biologically less lethal (perhaps slower growing and less likely to invade locally and metastasize). This is consistent with the length bias effect associated with screening. That is, screening is more likely to detect indolent (i.e., slow-growing) breast cancers, while the more aggressive cancers are detected in the intervals between screening sessions.
A 10-year follow-up study of 1,983 Finnish women with invasive breast cancer demonstrated that the method of cancer detection is an independent prognostic variable. When controlled for age, nodal status, and tumor size, screen-detected cancers had a lower risk of relapse and better overall survival. For women whose cancers were detected outside of screening, the hazard ratio (HR) for death was 1.90 (95% CI, 1.15–3.11), even though they were more likely to receive adjuvant systemic therapy.[21]
Similarly, an examination of the breast cancers found in three randomized screening trials (Health Insurance Plan, National Breast Screening Study [NBSS]-1, and NBSS-2) accounted for stage, nodal status, and tumor size and determined that patients whose cancer was found via screening had a more favorable prognosis. The relative risks (RR) for death were 1.53 (95% CI, 1.17–2.00) for interval and incident cancers, compared with screen-detected cancers; and 1.36 (95% CI, 1.10–1.68) for cancers in the control group, compared with screen-detected cancers.[22]
A third study compared the outcomes of 5,604 English women with screen-detected cancers to those with symptomatic breast cancers diagnosed between 1998 and 2003. After controlling for tumor size, nodal status, grade, and patient age, researchers found that the women with screen-detected cancers fared better. The HR for survival of the symptomatic women was 0.79 (95% CI, 0.63–0.99).[21,23]
The findings of these studies are also consistent with the evidence that some screen-detected cancers are low risk and represent overdiagnosis.

Screening biases–concepts

Numerous uncontrolled trials and retrospective series have documented the ability of mammography to diagnose small, early-stage breast cancers, which have a favorable clinical course.[24] Individuals whose cancer is detected by screening show a higher survival rate than those whose cancers are not detected by screening even when screening has not prolonged any lives. This concept is explained by the following four types of statistical bias:
  1. Lead-time bias: Cancer detected by screening earlier than the cancer would have been detected based on symptoms does nothing but advance the date of diagnosis. Earlier detection and treatment does not alter the natural disease progression. The 5-year survival rate from the time of diagnosis is longer for a cancer caught early even when the screening has made no difference in how long the person lives.
  2. Length bias: Screening mammography detects slowly growing cancers that have a better prognosis than cancers presenting clinically (detected by the doctor or the person when he or she gets ill). Adding these nonprogressive cancers to the life-threatening cancers (whose outcome is not affected by earlier treatment) increases the 5-year survival rate, even though screening has made no difference in how many lives are saved.
  3. Overdiagnosis bias: Screening detects cancers that would never cause symptoms or death and will increase survival rates without changing length of life.
  4. Healthy volunteer bias: Those who volunteer to participate in screening may be the healthiest, and the most health-conscious women in the general population. Therefore, their outcomes will be better than those of women who are neither healthy nor health-conscious, regardless of possible benefits of early diagnosis.
The impact of these biases is not known. A new randomized controlled trial (RCT) with cause-specific mortality as the endpoint is needed to determine both survival benefit and impact of overdiagnosis, lead time, length time, and healthy volunteer biases. This is not achievable; randomizing patients to screen and nonscreen groups would be unethical, and at least three decades of follow-up would be needed, during which time changes in treatment and imaging technology would invalidate the results. Decisions must therefore be based on available RCTs, despite their limitations, and on ecologic or cohort studies with adequate control groups and adjustment for confounding. (Refer to the PDQ summary on Cancer Screening Overview for more information.)

Assessment of performance and accuracy

Performance benchmarks for screening mammography in the United States are described on the Breast Cancer Surveillance Consortium (BCSC) websiteExit Disclaimer. (Refer to the PDQ summary on Cancer Screening Overview for more information.)

Sensitivity

The sensitivity of mammography is the percentage of women with breast cancers detected by mammographic screening. Sensitivity depends on tumor size, conspicuity, hormone sensitivity, breast tissue density, patient age, timing within the menstrual cycle, overall image quality, and interpretive skill of the radiologist. Overall sensitivity is approximately 79% but is lower in younger women and in those with dense breast tissue (see the BCSC websiteExit Disclaimer).[25-27] Sensitivity is not the same as benefit because some woman with possible breast cancer are harmed by overdiagnosis. According to the Physician's Insurance Association of America (PIAA), delay in diagnosis of breast cancer and errors in diagnosis are common causes of medical malpractice litigation. PIAA data from 2002 through 2011 note that the largest total indemnity payments for breast cancer claims are for errors in diagnosis, with an average indemnity payment of $444,557.[28]

Specificity and false-positive rate

The specificity of mammography is the percentage of all women without breast cancer whose mammograms are negative. The false-positive rate is the likelihood of a positive test in women without breast cancer. Low specificity and high rate of false positives result in unnecessary follow-up examinations and procedures. Because specificity includes all women without cancer in the denominator, even a small percentage of false positives turns out to be a large number in absolute terms. Thus—in screening—a good specificity must be very high. Even 95% specificity is quite low for a screening test.

Interval cancers

Interval cancers are cancers that are diagnosed in the interval between a normal screening examination and the anticipated date of the next screening mammogram. One study found interval cancers occurred more often in women younger than 50 years, and had mucinous or lobular histology, high histologic grade, high proliferative activity with relatively benign mammographic features, and no calcifications. Conversely, screen-detected cancers often had tubular histology, small size, low stage, hormone sensitivity, and a major component of DCIS.[29] Overall, interval cancers have characteristics of rapid growth,[29,30] are diagnosed at an advanced stage, and carry a poor prognosis.[31]
The Nova Scotia Breast Screening Program defined missed cancers as those that were false negatives on the previous screening exam, occurring less often than 1 per 1,000 women. It concluded that interval cancers occurred in approximately 1 per 1,000 women aged 40 to 49 years, and 3 per 1,000 women aged 50 to 59 years.[32]
Conversely, a larger trial found that interval cancers were more prevalent in women aged 40 to 49 years. Those appearing within 12 months of a negative screening mammogram were usually attributable to greater breast density. Those appearing within a 24-month interval were related to decreased mammographic sensitivity caused by greater breast density or to rapid tumor growth.[33]

Variables Associated with Accuracy

Patient characteristics

The accuracy of mammography has been noted to vary with patient characteristics, such as a woman's age, breast density, whether it is her first or subsequent exam, and the time since her last mammogram. Younger women have lower sensitivity and higher false-positive rates than do older women.
The Million Women Study in the United Kingdom found decreased sensitivity and specificity in women aged 50 to 64 years if they used postmenopausal hormone therapy, had prior breast surgery, or had a body mass index below 25.[34] Increased time since the last mammogram increases sensitivity, recall rate, and cancer-detection rate and decreases specificity.[35]
Sensitivity may be improved by scheduling the exam after the initiation of menses or during an interruption from hormone therapy.[36] Obese women have more than a 20% increased risk of having false-positive mammography, although sensitivity is unchanged.[37]
Dense breasts may obscure the detection of small masses on mammography, thereby reducing the sensitivity of mammography.[10] For women of all ages, high breast density is associated with 10% to 29% lower sensitivity.[26] High breast density is an inherent trait, which can be inherited [38,39] or affected by age; endogenous [40] and exogenous [41,42] hormones;[43] selective estrogen receptor modulators, such as tamoxifen;[44] and diet.[45] Hormone therapy is associated with increased breast density, lower mammographic sensitivity, and an increased rate of interval cancers.[46]
Digital mammography is more accurate than film mammography in examining dense breasts.[8] Most U.S. states have enacted laws mandating that mammography facilities report breast density, but inconsistent guidelines have generated confusion and anxiety among patients and health care providers.[47]
Dense breast tissue is not abnormal. Breast density is a description of the proportion of dense versus fatty tissue in a mammographic image.[48] The American College of Radiology’s BI-RADS classifies breast density as follows:
  1. Almost entirely fatty.
  2. Scattered fibroglandular densities.
  3. Heterogeneously dense.
  4. Extremely dense.
The latter two categories are considered dense breast tissue, a description affecting 43% of women aged 40 to 74 years.[49] A radiologist's assignment of breast density is subjective, and in any woman, it may vary over time.[49,50]
While breast density is associated with an increased risk of breast cancer,[51] density is only a modest risk factor for breast cancer and does not confer a higher risk for breast cancer death. The fourfold elevated risk for breast cancer incidence according to breast density is a comparison of density category d versus density category a.
Supplemental imaging with ultrasonography or breast magnetic resonance imaging (MRI) has been suggested by some groups for screening women with dense breasts, but there are no data showing that this strategy results in lower breast cancer mortality. The potential harm of adding these supplemental screening tests is the likelihood of producing more false positives, leading to additional imaging and breast biopsies, with resultant anxiety and cost.[51] Supplemental screening may also increase overdiagnosis of breast cancer with resultant overtreatment.

Tumor characteristics

Mucinous and lobular cancers are more easily detected by mammography. Rapidly growing cancers can sometimes be mistaken for normal breast tissue (e.g., medullary carcinomas, an uncommon type of invasive ductal breast cancer that is often associated with the BRCA1 mutation and aggressive characteristics, but that may demonstrate comparatively favorable responses to treatment).[29,52] Some other cancers associated with BRCA1/2 mutations, which may appear indolent, can also be missed.[53,54]

Physician characteristics

Radiologists’ performance is variable, affected by levels of experience and the volume of mammograms they interpret.[55] Biopsy recommendations of radiologists in academic settings have a higher positive PPV than do community radiologists.[56] Fellowship training in breast imaging may improve detection.[8]
Performance also varies by facility. Mammographic screening accuracy was higher at facilities offering only screening examinations than at those also performing diagnostic tests. Accuracy was also better at facilities with a breast imaging specialist on staff, performing single rather than double readings, and reviewing performance audits two or more times each year.[57]
False-positive rates are higher at facilities where concern about malpractice is high and at facilities serving vulnerable women (racial or ethnic minorities and women with less education, limited household income, or rural residence).[58] These populations may have a higher cancer prevalence and a lack of follow-up.[59]

International comparisons

International comparisons of screening mammography have found higher specificity in countries with more highly centralized screening systems and national quality assurance programs.[60,61]
The recall rate in the United States is twice that of the United Kingdom, with no difference in the rate of cancer detection.[60]

Prevalent versus subsequent examination and the interval between exams

The likelihood of diagnosing cancer is highest with the prevalent (first) screening examination, ranging from 9 to 26 cancers per 1,000 screens, depending on the woman’s age. The likelihood decreases for follow-up examinations, ranging from 1 to 3 cancers per 1,000 screens.[62]
The optimal interval between screening mammograms is unknown; there is little variability across the trials despite differences in protocols and screening intervals. A prospective U.K. trial randomly assigned women aged 50 to 62 years to receive mammograms annually or triennially. Although tumor grade and nodal status were similar in the two groups, more cancers of slightly smaller size were detected in the annual screening group than in the triennial screening group.[63]
A large observational study found a slightly increased risk of late-stage disease at diagnosis for women in their 40s who were adhering to a 2-year versus a 1-year schedule (28% vs. 21%; odds ratio [OR], 1.35; 95% CI, 1.01–1.81), but no difference was seen for women in their 50s or 60s based on schedule difference.[64,65]
A Finnish study of 14,765 women aged 40 to 49 years randomly assigned women to receive either annual screens or triennial screens. There were 18 deaths from breast cancer in 100,738 life-years in the triennial screening group and 18 deaths from breast cancer in 88,780 life-years in the annual screening group (HR, 0.88; 95% CI, 0.59–1.27).[66]

Benefit of Mammographic Screening on Breast Cancer Mortality

Randomized controlled trials (RCTs)

RCTs that studied the effect of screening mammography on breast cancer mortality were performed between 1963 and 2015, with participation by over half-a-million women in four countries. One trial, the Canadian NBSS-2, compared mammography plus clinical breast examination (CBE) to CBE alone; the other trials compared screening mammography with or without CBE to usual care. Refer to the Appendix of Randomized Controlled Trials section of this summary for a detailed description of the trials.
The trials differed in design, recruitment of participants, interventions (both screening and treatment), management of the control group, compliance with assignment to screening and control groups, and analysis of outcomes. Some trials used individual randomization, while others used cluster randomization in which cohorts were identified and then offered screening; one trial used nonrandomized allocation by day of birth in any given month. Cluster randomization sometimes led to imbalances between the intervention and control groups. Age differences have been identified in several trials, although the differences had no major effect on the trial outcome.[67] In the Edinburgh Trial, socioeconomic status, which correlates with the risk of breast cancer mortality, differed markedly between the intervention and control groups, rendering the results uninterpretable.
Breast cancer mortality was the major outcome parameter for each of these trials, so the attribution of cause of death required scrupulous attention. The use of a blinded monitoring committee (New York) and a linkage to independent data sources, such as national mortality registries (Swedish trials), were incorporated but could not ensure impartial attributions of cancer death for women in the screening or control arms. Possible misclassification of breast cancer deaths in the Two-County Trial biasing the results in favor of screening has been suggested.[68]
There were also differences in the methodology used to analyze the results of these trials. Four of the five Swedish trials were designed to include a single screening mammogram in the control group and were timed to correspond with the end of the series of screening mammograms in the study group. The initial analysis of these trials used an evaluation analysis, tallying only the breast cancer deaths that occurred in women whose cancer was discovered at or before the last study mammogram. In some of the trials, a delay occurred in the performance of the end-of-study mammogram, resulting in more time for members of the control group to develop or be diagnosed with breast cancer. Other trials used a follow-up analysis, which counts all deaths attributed to breast cancer, regardless of the time of diagnosis. This type of analysis was used in a meta-analysis of four of the five Swedish trials as a response to concerns about the evaluation analyses.[68]
The accessibility of the data for international audits and verification also varied, with a formal audit having been undertaken only in the Canadian trials. Other trials have been audited to varying degrees, but with less rigor.[69]
All of these studies were designed to study breast cancer mortality rather than all-cause mortality because breast cancer deaths contribute only a small proportion of total mortality in any given population. When all-cause mortality in these trials was examined retrospectively, only the Edinburgh Trial showed a difference attributable to the previously noted socioeconomic differences in the study groups. The meta-analysis (follow-up methods) of the four Swedish trials also showed a small improvement in all-cause mortality.
The relative improvement in breast cancer mortality attributable to screening is approximately 15% to 20%, and the absolute improvement at the individual level is much less. The potential benefit of breast cancer screening can be expressed as the number of lives extended because of early breast cancer detection.[70,71]
The RCT results represent experiences in a defined period of regular examinations, but in practice, women undergo 20 to 30 years of screening throughout their lifetimes.[65,72]
There are several problems with using these RCTs that were performed up to 50 years ago to estimate the current benefits of screening on breast cancer mortality. These problems include the following:
  1. Improvements in mammography technology, with the ability to identify increasingly subtle abnormalities.
  2. Enhanced breast cancer awareness in the general population, with women seeking evaluation and treatment earlier.
  3. Changes in the risk factors for breast cancer in the population (including age at menarche, age at first pregnancy, obesity, and use of postmenopausal hormone treatment).
  4. Improvements in breast cancer treatment, such that larger, more advanced cancers have higher cure rates than in the past.
  5. Applying results of short-term RCTs (e.g., 5 to 10 years) to make estimates of lifetime effects of breast cancer screening.
For these reasons, estimates of the breast cancer mortality reduction resulting from current screening are based on well-conducted cohort and ecologic studies in addition to the RCTs.

Effectiveness of population-based screening programs

An estimate of screening effectiveness can be obtained from nonrandomized controlled studies of screened versus nonscreened populations, case-control studies of screening in real communities, and modeling studies that examine the impact of screening on large populations. These studies must be designed to minimize or exclude the effects of unrelated trends influencing breast cancer mortality such as improved treatment and heightened awareness of breast cancer in the community.
Three population-based, observational studies from Sweden compared breast cancer mortality in the presence and absence of screening mammography programs. One study compared two adjacent time periods in 7 of the 25 counties in Sweden and found a statistically significant breast cancer mortality reduction of 18% to 32% attributable to screening.[73] The most important bias in this study is that the advent of screening in these counties occurred over a period during which dramatic improvements in the effectiveness of adjuvant breast cancer therapy were being made, changes that were not addressed by the study authors. The second study considered an 11-year period comparing seven counties with screening programs with five counties without them.[74] There was a trend in favor of screening, but again, the authors did not consider the effect of adjuvant therapy or differences in geography (urban vs. rural) that might affect treatment practices.
The third study attempted to account for the effects of treatment by using a detailed analysis by county. It found screening had little impact, a conclusion weakened by several flaws in design and analysis.[75]
In Nijmegen, the Netherlands, where a population-based screening program was undertaken in 1975, a case-cohort study found that screened women had decreased mortality compared with unscreened women (OR, 0.48).[76] However, a subsequent study comparing Nijmegen breast cancer mortality rates with neighboring Arnhem in the Netherlands, which had no screening program, showed no difference in breast cancer mortality.[77]
A community-based case-control study of screening in high-quality U.S. health care systems between 1983 and 1998 found no association between previous screening and reduced breast cancer mortality, but the mammography screening rates were generally low.[78]
A well-conducted ecologic study compared three pairs of neighboring European countries that were matched on similarity in health care systems and population structure, one of which had started a national screening program some years earlier than the others. The investigators found that each country had experienced a reduction in breast cancer mortality, with no difference between matched pairs that could be attributed to screening. The authors suggested that improvements in breast cancer treatment and/or health care organizations were more likely responsible for the reduction in mortality than was screening.[79]
A systematic review of ecologic and large cohort studies published through March 2011 compared breast cancer mortality in large populations of women, aged 50 to 69 years, who started breast cancer screening at different times. Seventeen studies met inclusion criteria, but all studies had methodological problems, including control group dissimilarities, insufficient adjustment for differences between areas in breast cancer risk and breast cancer treatment, and problems with similarity of measurement of breast cancer mortality between compared areas. There was great variation in results among the studies, with four studies finding a relative reduction in breast cancer mortality of 33% or more (with wide CIs) and five studies finding no reduction in breast cancer mortality. Because only a part of the overall reduction in breast cancer mortality could possibly be attributed to screening, the review concluded that any relative reduction in breast cancer mortality resulting from screening would likely be no more than 10%.[80]
A U.S. ecologic analysis conducted between 1976 and 2008 examined the incidence of early-stage versus late-stage breast cancer for women aged 40 years and older. To assess a screening effect, the authors compared the magnitude of increase in early-stage cancer with the magnitude of an expected decrease in late-stage cancer. Over the study, the absolute increase in the incidence of early-stage cancer was 122 cancers per 100,000 women, while the absolute decrease in late-stage cancers was 8 cases per 100,000 women. After adjusting for changes in incidence resulting from hormone therapy and other undefined causes, the authors concluded (1) the benefit of screening on breast cancer mortality was small, (2) between 22% and 31% of diagnosed breast cancers represented overdiagnosis, and (3) the observed improvement in breast cancer mortality was probably attributable to improved treatment rather than screening.[81]
An analytic approach was used to approximate the contributions of screening versus treatment to breast cancer mortality reduction and the magnitude of overdiagnosis.[82] The shift in the size distribution of breast cancers in the United States (before the introduction of mammography) to 2012 (after its widespread dissemination), was investigated using SEER data in women aged 40 years and older. The rate of clinically meaningful breast cancer was assumed to be stable during this time. The authors documented a lower incidence of larger (≥2 cm) tumors as well as a reduction in breast cancer case fatality. The lower mortality for women with larger tumors was attributed to improvements in therapy. Two-thirds of the decline in size-specific case fatality was ascribed to improved treatment.
ENLARGEChart showing the temporal relationship between the introduction of screening mammography and increased incidence of invasive breast cancer.
Figure 2. 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. From New England Journal of Medicine, Welch HG, Prorok PC, O'Malley AJ, Kramer BS, Breast-Cancer Tumor Size, Overdiagnosis, and Mammography Screening Effectiveness, Volume 375, Issue 15, Pages 1438-47, Copyright © 2016 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.
A prospective cohort study of community-based screening programs in the United States found that annual compared with biennial screening mammography did not reduce the proportion of unfavorable breast cancers detected in women aged 50 to 74 years or in women aged 40 to 49 years without extremely dense breasts. Women aged 40 to 49 years with extremely dense breasts did have a reduction in cancers larger than 2.0 cm with annual screening (OR, 2.39; 95% CI, 1.37–4.18).[83]
An observational study of women aged 40 to 74 years conducted in 7 of 12 Canadian screening programs compared breast cancer mortality in those participants screened at least once between 1990 and 2009 (85% of the population) with those not screened (15% of the population). The abstract reported a 40% average breast cancer mortality among participants; however, it was likely intended to report a 40% reduction in breast cancer mortality on the basis of language utilized in the Discussion section.[84]
Limitations of this study included the lack of all-cause mortality data, the extent of screening, screening outside of the study, screening prior to the study, the method used for calculating expected mortality and the referent rates of nonparticipants, nonparticipant survival, province-specific population differences, the extent to which limitations of the database prevented correcting for age and other differences between participants, the generalizability of the substudy data of a single province (British Columbia), and the potentially large impact of selection bias. Overall, the study lacked important data and had limitations in methodology and data analysis.

Statistical modeling of breast cancer incidence and mortality in the United States

The optimal screening interval has been addressed by modelers. Modeling makes assumptions that may not be correct; however, the credibility of modeling is greater when the model produces overall results that are consistent with randomized trials and when the model is used to interpolate or extrapolate. For example, if a model’s output agrees with RCT outcomes for annual screening, it has greater credibility to compare the relative effectiveness of biennial versus annual screening.
In 2000, the National Cancer Institute formed a consortium of modeling groups (Cancer Intervention and Surveillance Modeling Network [CISNET]) to address the relative contribution of screening and adjuvant therapy to the observed decline in breast cancer mortality in the United States.[85] These models predicted reductions in breast cancer mortality similar to those expected in the circumstances of the RCTs but updated to the use of modern adjuvant therapy. In 2009, CISNET modelers addressed several questions related to the harms and benefits of mammography, including comparing annual versus biennial screening.[65] Women aged 50 to 74 years received most of the mortality benefit of annual screening by having a mammogram every 2 years. The reduction in breast cancer deaths that was maintained because of the move from annual to biennial screening ranged across the six models from 72% to 95%, with a median of 80%.
Data are limited as to how much of the reduction in mortality, seen over time from 1990 onward, is attributable to advances in imaging techniques for screening and as to how much is the result of the improved effectiveness of therapy. In one CISNET study of six simulation models, about one-third of the decrease in breast cancer mortality in 2012 was attributable to screening, with the balance attributed to treatment.[86] In this CISNET study, the mean estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%–58%), relative to the estimated baseline rate in 2012 if there was no screening or treatment; 37% (model range, 26%–51%) of this reduction was associated with screening, and 63% (model range, 49%–74%) of this reduction was associated with treatment.

Harms of Mammographic Screening

The negative effects of screening mammography are overdiagnosis (true positives that will not become clinically significant), false positives (related to the specificity of the test), false negatives (related to the sensitivity of the test), discomfort associated with the test, radiation risk, psychological harm, financial stress, and opportunity costs.
Table 1 provides an overview of the estimated benefits and harms of screening mammography for 10,000 women who underwent annual screening mammography over a 10-year period.[87]
Table 1. Estimated Benefits and Harms of Mammography Screening for 10,000 Women Who Underwent Annual Screening Mammography During a 10-Year Perioda
Age, yNo. of Breast Cancer Deaths Averted With Mammography Screening During the Next 15 ybNo. (95% CI) With ≥1 False-Positive Result During the 10 ycNo. (95% CI) With ≥1 False Positive Resulting in a Biopsy During the 10 ycNo. of Breast Cancers or DCIS Diagnosed During the 10 y That Would Never Become Clinically Important (Overdiagnosis)d
No. = number; CI = confidence interval; DCIS = ductal carcinoma in situ.
aAdapted from Pace and Keating.[87]
bNumber of deaths averted are from Welch and Passow.[88] The lower bound represents breast cancer mortality reduction if the breast cancer mortality relative risk were 0.95 (based on minimal benefit from the Canadian trials [89,90]), and the upper bound represents the breast cancer mortality reduction if the relative risk were 0.64 (based on the Swedish 2-County Trial [91]).
cFalse positive and biopsy estimates and 95% confidence intervals are 10-year cumulative risks reported in Hubbard et al. [92] and Braithwaite et al.[93]
dThe number of overdiagnosed cases are calculated by Welch and Passow.[88] The lower bound represents overdiagnosis based on results from the Malmö trial,[94] whereas the upper bound represents the estimate from Bleyer and Welch.[81]
eThe lower-bound estimate for overdiagnosis reported by Welch and Passow [88] came from the Malmö study.[94] The study did not enroll women younger than 50 years.
401–166,130 (5,940–6,310)700 (610–780)?–104e
503–326,130 (5,800–6,470)940 (740–1,150)30–137
605–494,970 (4,780–5,150)980 (840–1,130)64–194

Overdiagnosis

Overdiagnosis occurs when screening procedures detect cancers that would never become clinically apparent in the absence of screening. The magnitude of overdiagnosis is debated, particularly regarding DCIS, a cancer precursor whose natural history is unknown. By reason of this inability to predict confidently the tumor behavior at time of diagnosis, standard treatment for invasive cancers and DCIS can cause overtreatment. The related harms include treatment-related side effects and the number of harms associated with a cancer diagnosis, which are immediate. Conversely, a mortality benefit would occur at an uncertain point in the future.
One approach to understanding overdiagnosis is to examine the prevalence of occult cancer in women who died of noncancer causes. In an overview of seven autopsy studies, the median prevalence of occult invasive breast cancer was 1.3% (range, 0%–1.8%) and of DCIS was 8.9% (range, 0%–14.7%).[95,96]
Overdiagnosis can be indirectly measured by comparing breast cancer incidence in screened versus unscreened populations. These comparisons can be confounded by differences in the populations, such as time, geography, health behaviors, and hormone usage. The calculations of overdiagnosis can vary in their adjustment for lead-time bias.[97,98] An overview of 29 studies found calculated rates of overdiagnosis to be 0%–54%, with rates from randomized studies between 11% and 22%.[99] In Denmark, where screened and unscreened populations existed concurrently, the rate of overdiagnosis of invasive cancer was calculated to be 14% and 39%, using two different methodologies. If DCIS cases were included, the overdiagnosis rates were 24% and 48%. The second methodology accounts for regional differences in women younger than the screening age and is likely more accurate.[100]
Theoretically, in a given population, the detection of more breast cancers at an early stage would result in a subsequent reduction in the incidence of advanced-stage cancers. This has not occurred in any of the populations studied to date. Thus, the detection of more early stage cancers likely represents overdiagnosis. A population-based study in the Netherlands showed that about one-half of all screen-detected breast cancers, including DCIS, would represent overdiagnosis and is consistent with other studies, which showed substantial rates of overdiagnosis associated with screening.[101]
A cohort study in Norway compared the increase in cancer incidence in women who were eligible for screening with the cancer incidence in younger women who were not eligible for screening, eligibility was based on age and residence. Eligible women experienced a 60% increase in incidence of localized cancers (RR, 1.60; 95% CI, 1.42–1.79), while the incidence of advanced cancers remained similar in the two groups (RR, 1.08; 95% CI, 0.86–1.35).[102]
A population study that compared different counties in the United States showed that higher rates of screening mammography use were associated with higher rates of breast cancer diagnoses, yet there was no corresponding decrease in 10-year breast cancer mortality.[103] The strengths of this study include its very large size (16 million women) and the strength and consistency of correlation observed across counties. The limitations of this study include the self-reporting of mammograms, the use of a 2-year window to estimate screening prevalence, and the period of analysis (when menopausal hormone use was present).[103]
The extent of overdiagnosis has been estimated in the Canadian NBSS, a randomized clinical trial. At the end of the five screening rounds, 142 more invasive breast cancer cases were diagnosed in the mammography arm, compared with the control arm.[104] At 15 years, the excess number of cancer cases in the mammography arm versus the control arm was 106, representing an overdiagnosis rate of 22% for the 484 screen-detected invasive cancers.[104]
As a consequence of screening mammography, greater numbers of breast cancers with indolent behavior are now identified, resulting in potential overtreatment. In a secondary analysis of a randomized trial of tamoxifen versus no systemic therapy in patients with early breast cancer, the authors utilized the 70-gene MammaPrint assay and identified 15% of patients at ultra-low risk, with 20-year disease-specific survival rates of 97% in the tamoxifen group and 94% in the control group. Thus, these patients would likely have extremely good outcomes with surgery alone. The frequency of such ultra-low risk cancers in the screened population is likely around 25%. Tools such as the 70-gene MammaPrint assay might be utilized in the future to identify these cancers, and thereby, reduce the risk of overtreatment. However, additional studies are needed to confirm these findings.[105]
In 2016, the Canadian NBSS, a randomized screening trial with 25-year follow-up, re-estimated overdiagnosis of breast cancer from mammography screening by age group and concluded that approximately 30% of invasive screen-detected cancers in women aged 40 to 49 years and up to 20% of those detected in women aged 50 to 59 years were overdiagnosed. When in situ cancers are included, the estimated risks of overdiagnosis are 40% aged 40 to 49 years and 30% in women aged 50 to 59 years. Overdiagnosis was calculated as the persistent excess incidence in the screened arm versus the control arm divided by the number of screen-detected cases (excess incidence method). Requirements for adequate estimation of overdiagnosis utilizing this method included the following:
  1. Cessation of screening among participants in the screened arm when the trial screening protocol is completed.
  2. Follow-up after screening ceases needs to be as long as the longest lead time (the time between the identification of a screen-detected cancer until symptomatic diagnosis of that cancer in the absence of screening) among the screen-detected cases.
  3. The comparison population for the cancer incidence during screening and after screening cessation in the screened arm needs to comprise individuals with comparable cancer risk in the absence of screening, as in a randomized control arm.
  4. Compliance with screening is high in the screened arm during the trial protocol screening phase, and contamination (nonprotocol screening) in the control arm is low.
These conditions were largely met in the CNBSS because population-based screening did not become available throughout Canada until a minimum of 2 years later and in most instances 5 to 10 years later (thereby, allowing for cessation of screening after the trial screening period and follow-up longer than most estimates of lead time), because contamination is documented to have been minimal, and because individual randomization resulted in 44 almost identically distributed demographic factors and risk factors between the two trial arms.
Since the conclusion of the trial screening period in 1988, differences in screening quality, intensity, invited age range, and biopsy thresholds decrease the generalizability of these results. These factors and improved imaging technique/quality and low threshold for biopsy, likely contribute to lower estimates of overdiagnosis of in situ cancer than that of invasive cancer.[106]
Table 1, above, shows results from a 10-year period of screening 10,000 women, estimating the number of women with breast cancer or DCIS that would never become clinically important (overdiagnosis). There was likely no overdiagnosis in the Health Insurance Plan study, which used old-technology mammography and CBE. Overdiagnosis has become more prominent in the era of improved-technology mammography. The improved technology has not, however, been shown to make further reductions in mortality than the original technology. In summary, breast cancer overdiagnosis is a complex topic. Studies that used many different methods reported a wide range of estimates, and there is currently no way to assess whether new cancer cases are overdiagnosed or are of real harm to patients.[87]

False positives leading to additional interventions

Because fewer than 5 per 1,000 women screened have breast cancer, most abnormal mammograms are false positives, even given the 90% specificity of mammography (i.e., 90% of all women without breast cancer will have a negative mammogram).[62]
This high false positive rate of mammography is underestimated and can seem counterintuitive because of a statistically based cognitive bias known as the base rate fallacy. Because the base rate of breast cancer is low, (5/1000), the false-positive rate vastly exceeds the true-positive rate, even when utilizing a very accurate test.
Mammography’s true-positive rate of approximately 90% means that, of women with breast cancer, approximately 90% will test positive. The true-negative rate of 90% means that, of women without breast cancer, 90% will test negative. A 10% false-positive rate over 1,000 people means that there will be 100 false positives in 1,000 people. If 5 in 1,000 women have breast cancer, then 4.5 women with breast cancer will have a positive test. In other words, there will approximately 100 false positive for every 4.5 true positives.
Further, abnormal results from screening mammograms prompt additional tests and procedures, such as mammographic views of the region of concern, ultrasound, MRI, and tissue sampling (by fine-needle aspiration, core biopsy, or excisional biopsy). Overall, the harm from unnecessary tests and treatments must be weighed against the benefit of early detection.
A study of breast cancer screening in 2,400 women enrolled in a health maintenance organization found that over a decade, 88 cancers were diagnosed, 58 of which were identified by mammography. One-third of the women had an abnormal mammogram result that required additional testing: 539 additional mammograms, 186 ultrasound examinations, and 188 biopsies. The cumulative biopsy rate (the rate of true positives) resulting from mammographic findings was approximately 1 in 4 (23.6%). The PPV of an abnormal screening mammogram in this population was 6.3% for women aged 40 to 49 years, 6.6% for women aged 50 to 59 years, and 7.8% for women aged 60 to 69 years.[107] A subsequent analysis and modeling of data from the same cohort of women, estimated that the risk of having at least one false-positive mammogram was 7.4% (95% CI, 6.4%–8.5%) at the first mammogram, 26.0% (95% CI, 24.0%–28.2%) by the fifth mammogram, and 43.1% (95% CI, 36.6%–53.6%) by the ninth mammogram.[108] Cumulative risk of at least one false-positive result depended on four patient variables (younger age, higher number of previous breast biopsies, family history of breast cancer, and current estrogen use) and three radiologic variables (longer time between screenings, failure to compare the current and previous mammograms, and the individual radiologist’s tendency to interpret mammograms as abnormal). Overall, the factor most responsible for a false-positive mammogram was the individual radiologist’s tendency to read mammograms as abnormal.
A prospective cohort study of community-based screening found that a greater proportion of women undergoing annual screening had at least one false-positive screen after 10 years than did women undergoing biennial screening, regardless of breast density. For women with scattered fibroglandular densities, the difference was 68.9% (annual) versus 46.3% (biennial) for women in their 40s. For women aged 50 to 74 years, the difference for this density group was 49.8% (annual) versus 30.7% (biennial).[83]
As shown in Table 1, the estimated number of women out of 10,000 who underwent annual screening mammography during a 10-year period with at least one false-positive test result is 6,130 for women aged 40 to 50 years and 4,970 for women aged 60 years. The number of women with a false-positive test that results in a biopsy is estimated to range from 700 to 980, depending on age.[87]

False negatives leading to a false sense of security

The sensitivity of mammography ranges from 70% to 90%, depending on characteristics of the interpreting radiologist (level of experience) and characteristics of the woman (age, breast density, hormone status, and diet). Assuming an average sensitivity of 80%, mammograms will miss approximately 20% of the breast cancers that are present at the time of screening (false negatives). Many of these missed cancers are high risk, with adverse biologic characteristics. If a normal mammogram dissuades or postpones a woman or her doctor from evaluating breast symptoms, she may suffer adverse consequences. Thus, a negative mammogram should never dissuade a woman or her physician from additional evaluation of breast symptoms.

Discomfort

Positioning of the woman and breast compression reduce motion artifact and improve mammogram image quality. Pain and/or discomfort was reported by 90% of women undergoing mammography, with 12% of women rating the sensation as intense or intolerable.[109] A systematic review of 22 studies investigating mammography-associated pain and discomfort found wide variations, some of which were associated with menstrual cycle stage, anxiety, and premammography anticipation of pain.[110]

Radiation exposure

The major risk factors for radiation-associated breast cancer are young age at exposure and dose; however, rarely there are women with an inherited susceptibility to radiation-induced damage who must avoid radiation exposure at any age.[111,112] For many women older than 40 years, the likely benefits of screening mammography outweigh the risks.[113,111,114] Standard two-view screening mammography exposes the breasts to a mean dose of 4 mSv, and the whole body to 0.29 mSv.[112,115] Thus, up to one breast cancer may be induced per 1,000 women undergoing annual mammograms from ages 40 to 80 years. Such risk is doubled in women with large breasts who require increased radiation doses and in women with breast augmentation who require additional views. Radiation-induced breast cancers may be reduced fivefold for women who begin biennial screening at age 50 years rather than annually at age 40 years.[116]

Psychological harms of false positives

A telephone survey of 308 women performed 3 months after screening mammography revealed that about one-fourth of the 68 women recalled for additional testing were still experiencing worry that affected their mood or functioning, even though that testing had ruled out cancer.[117] Research into whether the psychological impact of a false-positive test is long-standing yields mixed results. A cohort study in Spain in 2002 found immediate psychological impact to a woman after receiving a false-positive mammogram, but these results dissipated within a few months.[118] A cohort study in Denmark in 2013 that measured the psychological effects of a false-positive test result several years after the event found long-term negative psychological consequences.[119] Several studies have shown that the anxiety after evaluation of a false-positive test leads to increased participation in future screening examinations.[120-123]

Financial strain and opportunity costs

These potential harms of screening have not been well researched, but it is clear that they exist.
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