Overdiagnosis In Breast Cancer Screening Research Articles

USPSTF Recommendations and Overdiagnosis.

Overdiagnosis is the concept that some cancers detected at screening would never have become clinically apparent during a woman's lifetime in the absence of screening. This could occur if a woman dies of a cause other than breast cancer in the interval between mammographic detection and clinical detection (obligate overdiagnosis) or if a mammographically detected breast cancer fails to progress to clinical presentation. Overdiagnosis cannot be measured directly. Indirect methods of estimating overdiagnosis include use of data from randomized controlled trials (RCTs) designed to evaluate breast cancer mortality, population-based screening studies, or modeling. In each case, estimates of overdiagnosis must consider lead time, breast cancer incidence trends in the absence of screening, and accurate and predictable rates of tumor progression. Failure to do so has led to widely varying estimates of overdiagnosis. The U.S. Preventive Services Task Force (USPSTF) considers overdiagnosis a major harm of mammography screening. Their 2024 report estimated overdiagnosis using summary evaluations of 3 RCTs that did not provide screening to their control groups at the end of the screening period, along with Cancer Intervention and Surveillance Network modeling. However, there are major flaws in their evidence sources and modeling estimates, limiting the USPSTF assessment. The most plausible estimates remain those based on observational studies that suggest overdiagnosis in breast cancer screening is 10% or less and can be attributed primarily to obligate overdiagnosis and nonprogressive ductal carcinoma in situ.

Breast cancer screening and overdiagnosis.

Overdiagnosis is a harmful consequence of screening which is particularly challenging to estimate. An unbiased setting to measure overdiagnosis in breast cancer screening requires comparative data from a screened and an unscreened cohort for at least 30 years. Such randomised data will not become available, leaving us with observational data over shorter time periods and outcomes of modelling. This collaborative effort of the International Cancer Screening Network quantified the variation in estimated breast cancer overdiagnosis in organised programmes with evaluation of both observed and simulated data, and presented examples of how modelling can provide additional insights. Reliable observational data, analysed with study design accounting for methodological pitfalls, and modelling studies with different approaches, indicate that overdiagnosis accounts for less than 10% of invasive breast cancer cases in a screening target population of women aged 50 to 69. Estimates above this level are likely to derive from inaccuracies in study design. The widely discrepant estimates of overdiagnosis reported from observational data could substantially be reduced by use of a cohort study design with at least 10 years of follow-up after screening stops. In contexts where concomitant opportunistic screening or gradual implementation of screening occurs, and data on valid comparison groups are not readily available, modelling of screening intervention becomes an advantageous option to obtain reliable estimates of breast cancer overdiagnosis.

Ductal Carcinoma In Situ Biology, Language, and Active Surveillance: A Survey of Breast Radiologists' Knowledge and Opinions.

To understand how breast radiologists perceive ductal carcinoma in situ (DCIS). A 19-item survey was developed by the Society of Breast Imaging Patient Care and Delivery Committee and distributed to all Society of Breast Imaging members. The survey queried respondents' demographics, knowledge of DCIS biology, language used to discuss a new diagnosis of DCIS, and perspectives on active surveillance for DCIS. Five-point Likert scales (1= strongly disagree, 3= neutral, 5= strongly agree) were used. There were 536 responses for a response rate of 41%. There was agreement that DCIS is the primary driver of overdiagnosis in breast cancer screening (median 4), and respondents provided mean and median overdiagnosis estimates of 29.7% and 25% for low-grade DCIS as well as 4.2% and 0% for high-grade DCIS, respectively. Responses varied in how to describe DCIS but most often used the word "cancer" with a qualifier such as "early" (32%) or "pre-invasive" (25%). Respondents disagreed (median 2) with removing the word "carcinoma" from DCIS. Finally, there was agreement that current standard of care therapy for some forms of DCIS is overtreatment (median 4) and that active surveillance as an alternative management strategy should be studied (mean 4), but felt that ultrasound (median 4) and MRI (median 4) should be used to exclude women with occult invasive disease before active surveillance. Breast radiologists' opinions about DCIS biology, language, and active surveillance are not homogenous, but general trends exist that can be used to guide research, education, and advocacy efforts.

Lack of association between screening interval and cancer stage in Lynch syndrome may be accounted for by over-diagnosis; a prospective Lynch syndrome database report

BackgroundRecent epidemiological evidence shows that colorectal cancer (CRC) continues to occur in carriers of pathogenic mismatch repair (path_MMR) variants despite frequent colonoscopy surveillance in expert centres. This observation conflicts with the paradigm that removal of all visible polyps should prevent the vast majority of CRC in path_MMR carriers, provided the screening interval is sufficiently short and colonoscopic practice is optimal.MethodsTo inform the debate, we examined, in the Prospective Lynch Syndrome Database (PLSD), whether the time since last colonoscopy was associated with the pathological stage at which CRC was diagnosed during prospective surveillance. Path_MMR carriers were recruited for prospective surveillance by colonoscopy. Only variants scored by the InSiGHT Variant Interpretation Committee as class 4 and 5 (clinically actionable) were included. CRCs detected at the first planned colonoscopy, or within one year of this, were excluded as prevalent cancers.ResultsStage at diagnosis and interval between last prospective surveillance colonoscopy and diagnosis were available for 209 patients with 218 CRCs, including 162 path_MLH1, 45 path_MSH2, 10 path_MSH6 and 1 path_PMS2 carriers. The numbers of cancers detected within < 1.5, 1.5–2.5, 2.5–3.5 and at > 3.5 years since last colonoscopy were 36, 93, 56 and 33, respectively. Among these, 16.7, 19.4, 9.9 and 15.1% were stage III–IV, respectively (p = 0.34). The cancers detected more than 2.5 years after the last colonoscopy were not more advanced than those diagnosed earlier (p = 0.14).ConclusionsThe CRC stage and interval since last colonoscopy were not correlated, which is in conflict with the accelerated adenoma-carcinoma paradigm. We have previously reported that more frequent colonoscopy is not associated with lower incidence of CRC in path_MMR carriers as was expected. In contrast, point estimates showed a higher incidence with shorter intervals between examinations, a situation that may parallel to over-diagnosis in breast cancer screening. Our findings raise the possibility that some CRCs in path_MMR carriers may spontaneously disappear: the host immune response may not only remove CRC precursor lesions in path_MMR carriers, but may remove infiltrating cancers as well. If confirmed, our suggested interpretation will have a bearing on surveillance policy for path_MMR carriers.

Overdiagnosis in breast cancer screening

The purpose of breast cancer screening is to reduce breast cancer mortality. In order to achieve this purpose, an X-ray search—a mammography examination—is made of the breast tissue of healthy women to detect potential cancers that have not given rise to symptoms. With early detection, a woman with breast cancer can be offered a more efficient treatment than it would otherwise had been possible. If screening works, women with screen-detected breast cancer will have a better prognosis than women diagnosed with symptoms of breast cancer.

Is an indistinct picture "exactly what we need"? Objectivity, accuracy, and harm in imaging for cancer.

Assumptions about the epistemic ideal of objectivity, closely related to ontological assumptions about the nature of disease as pathophysiological abnormality, lead us into oversimplified ways of thinking about medical imaging. This is illustrated by current controversies in the early detection of cancer. Improvements in the technical quality of imaging failed to address the problem of overdiagnosis in breast cancer screening and exacerbate the problem in thyroid cancer diagnosis. Drawing on Douglas and on Daston and Galison, I distinguish 3 dimensions of objectivity (accuracy, reliability, and precision) and demonstrate ways they may be at odds, as illustrated in the early detection of cancer. Guidelines for evaluating the efficacy of diagnostic imaging are insufficiently sensitive to this complexity. Improving imaging quality may raise epistemic issues, place disease definitions in question, and lead to overall harm or to changes in the distribution of harms and benefits among population subgroups. With a nod to Wittgenstein, I argue that we cannot take for granted that "an indistinct picture" is not "exactly what we need."

As you like it: How the same data can support manifold views of overdiagnosis in breast cancer screening

Overdiagnosis estimates have varied substantially, causing confusion. The discussions have been complicated by the fact that population and study design have varied substantially between studies. To help assess the impact of study design choices on the estimates, we compared them on a single population. A cohort study from Funen County, Denmark, recently suggested little (∼1%) overdiagnosis. It followed previously screened women for up to 14 years after screening had ended. Using publically available data from Funen, we recreated the designs from five high-estimate, highly cited studies from various countries. Selected studies estimated overdiagnosis to be 25-54%. Their designs were adapted only to the extent that they reflect the start of screening in Funen in 1993. The reanalysis of the Funen data resulted in overdiagnosis estimates that were remarkably similar to those from the original high-estimate age-period studies, 21-55%. In additional analyses, undertaken to elucidate the effect of the individual components of the study designs, overdiagnosis estimates were more than halved after the most likely changes in the background risk were accounted for and decreased additionally when never-screened birth cohorts were excluded from the analysis. The same data give both low and high estimates of overdiagnosis, it all depends on the study design. This stresses the need for a careful scrutiny of the validity of the assumptions underpinning the estimates. Age-period analyses of breast cancer overdiagnosis suggesting very high frequencies of overdiagnosis rested on unmet assumptions. This study showed that overdiagnosis estimates should in the future be requested to adequately control for the background risk and include an informative selection of the studied population to achieve valid and comparable estimates of overdiagnosis.

Estimation of overdiagnosis in breast cancer screening using a non-homogeneous multi-state model: A simulation study

Overdiagnosis is regarded as a harm of screening. We aimed to develop a non-homogeneous multi-state model to consider the age-specific transition rates for estimation of overdiagnosis, to validate the model by a simulation study where the true frequency of overdiagnosis can be calculated, and to compare our estimate with the cumulative incidence method. We constructed a four-state model to describe the natural history of breast cancer. The latent disease progression and the observed states for each individual were simulated in a trial with biennial screening of women aged 51-69 and a control group of the same size without screening. We performed 100 repetitions of the simulation with one million women to evaluate the performance of estimates. A sensitivity analysis with reduced number of controls was performed to imitate the data from the service screening programme. Based on the 100 repetitions, the mean value of the true frequency of overdiagnosis was 12.5% and the average estimates by the cumulative incidence method and the multi-state model were 12.9% (interquartile range: 2.46%) and 13.4% (interquartile range: 2.16%), respectively. The multi-state model had a greater bias of overdiagnosis than the cumulative incidence method, but the variation in the estimates was smaller. When the number of unscreened group was reduced, the variation of multi-state model estimates increased. The multi-state model produces a proper estimate of overdiagnosis and the results are comparable with the cumulative incidence method. The multi-state model can be used in the estimation of overdiagnosis, and might be useful for the ongoing service screening programmes.

Overdiagnosis in mammography screening for breast cancer

Screening has been always considered as a double-edged sword. Cancer screening could save lives in some cases, however, in other cases, it might also turn people into overdiagnosis. Overdiagnosis is the diagnosis of cancer that will never cause symptoms or death during a patient's lifetime. Therefore, overdiagnosis might lead to unnecessary treatments and lifetime surveillance, and then increase economic burden and psychological burden. In this review, we focus on how to correctly evaluate the overdiagnosis rate, and how to avoid or reduce the harms caused by overdiagnosis in the future according to the reasons associated with overdiagnosis. After systematically reviewing the previous studies, we will try to identify the potential reasons associated with overdiagnosis in breast cancer screening with mammography, address how to correctly evaluate the overdiagnosis rate, and finally provide some suggestions to reduce the overdiagnosis.

Quantifying Overdiagnosis in Cancer Screening: A Systematic Review to Evaluate the Methodology.

Overdiagnosis is the main harm of cancer screening programs but is difficult to quantify. This review aims to evaluate existing approaches to estimate the magnitude of overdiagnosis in cancer screening in order to gain insight into the strengths and limitations of these approaches and to provide researchers with guidance to obtain reliable estimates of overdiagnosis in cancer screening. A systematic review was done of primary research studies in PubMed that were published before January 1, 2016, and quantified overdiagnosis in breast cancer screening. The studies meeting inclusion criteria were then categorized by their methods to adjust for lead time and to obtain an unscreened reference population. For each approach, we provide an overview of the data required, assumptions made, limitations, and strengths. A total of 442 studies were identified in the initial search. Forty studies met the inclusion criteria for the qualitative review. We grouped the approaches to adjust for lead time in two main categories: the lead time approach and the excess incidence approach. The lead time approach was further subdivided into the mean lead time approach, lead time distribution approach, and natural history modeling. The excess incidence approach was subdivided into the cumulative incidence approach and early vs late-stage cancer approach. The approaches used to obtain an unscreened reference population were grouped into the following categories: control group of a randomized controlled trial, nonattenders, control region, extrapolation of a prescreening trend, uninvited groups, adjustment for the effect of screening, and natural history modeling. Each approach to adjust for lead time and obtain an unscreened reference population has its own strengths and limitations, which should be taken into consideration when estimating overdiagnosis.

Overdiagnosis in breast cancer screening: The impact of study design and calculations

Overdiagnosis in breast cancer screening is an important issue. A recent study from Denmark concluded that one in three breast cancers diagnosed in screening areas in women aged 50–69 years were overdiagnosed. The purpose of this short communication was to disentangle the study's methodology in order to evaluate the soundness of this conclusion. We found that both the use of absolute differences as opposed to ratios; the sole focus on non-advanced tumours and the crude allocation of tumours and person-years by screening history for women aged 70–84 years, all contributed to the very high estimate of overdiagnosis. Screening affects cohorts of screened women. Danish registers allow very accurate mapping of the fate of every woman. We should be past the phase where studies of overdiagnosis are based on the fixed age groups from routine statistics.

Abstract P5-02-04: Study on over-diagnosis of high-precision breast cancer screening ∼ Consideration from epidemiological point of view

Abstract &amp;lt;Introduction&amp;gt; In breast cancer screening, it has been attempted to combine US with MMG. For relatively small breasts and dense breasts, there is the opinion that this combination is useful. On the other hand, the problem of over-diagnosis of breast cancer screening has been raised. We've been breast cancer screening with US/MMG combination method since 2005. The results were examined from the epidemiological point of view. &amp;lt;Subjects and Methods &amp;gt; Breast cancer discovery rate through US/MMG screening at our facility from 2005 to 2014 was considered. The medical examination was performed on 35,353 women. Kagawa Prefecture, in which our facility is located has had 100 percent breast cancer registration for more than 10 years. We have compared the breast cancer registration of 2013 with our examination results. &amp;lt;Results&amp;gt; Asymptomatic breast cancer detection rate in our breast cancer screening was 0.6%. ４６% of the detected cancer was DCIS. Low-grade DCIS (Van Nuys 1 and 2) accounted for three-quarters of DCIS. In invasive carcinoma, 10 mm or less of luminal A type was 17%, other luminal types 19%, non-luminal types 5% and unclassified 6%. If our facility's highly precise breast cancer medical examination were performed throughout Kagawa Prefecture, DCIS would be found in 860 cases, 10 mm or less of luminal A type found in 276, other luminal type found in 320 and non-luminal type found in 70 cases per year.Compared to the Kagawa Prefecture breast cancer registered in 2013, DCIS was 6.6 times larger than the registered data, 10 mm or less of luminal A 2.9 times larger, other luminal types 1.1 times larger, and non-luminal types 1.2 times larger. The differences between the registered data and our findings for DCIS and 10mm or less of luminal A type are remarkable. &amp;lt;Conclusion&amp;gt; With the US/MMG combination method, the detection rate of DCIS and 10 mm or less of luminal A type have been excessive. Many type of DCIS and tiny luminal A type must exist latently. When performing a high-precision breast cancer screening, it is necessary to note such over-diagnosis. Furthermore, it is also necessary to re-examine the pathology diagnostic criteria of DCIS. Citation Format: Takebe K, Arai T. Study on over-diagnosis of high-precision breast cancer screening ∼ Consideration from epidemiological point of view [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-02-04.

The distribution of ductal carcinoma in situ (DCIS) grade in 4232 women and its impact on overdiagnosis in breast cancer screening.

BackgroundThe incidence of ductal carcinoma in situ (DCIS) has rapidly increased over time. The malignant potential of DCIS is dependent on its differentiation grade.MethodsOur aim is to determine the distribution of different grades of DCIS among women screened in the mass screening programme, and women not screened in the mass screening programme, and to estimate the amount of overdiagnosis by grade of DCIS. We retrospectively included a population-based sample of 4232 women with a diagnosis of DCIS in the years 2007–2009 from the Nationwide network and registry of histopathology and cytopathology in the Netherlands. Excluded were women with concurrent invasive breast cancer, lobular carcinoma in situ and no DCIS, women recently treated for invasive breast cancer, no grade mentioned in the record, inconclusive record on invasion, and prevalent DCIS. The screening status was obtained via the screening organisations. The distribution of grades was incorporated in the well-established and validated microsimulation model MISCAN.ResultsOverall, 17.7 % of DCIS were low grade, 31.4 % intermediate grade, and 50.9 % high grade. This distribution did not differ by screening status, but did vary by age. Older women were more likely to have low-grade DCIS than younger women. Overdiagnosis as a proportion of all cancers in women of the screening age was 61 % for low-grade, 57 % for intermediate-grade, 45 % for high-grade DCIS. For women age 50–60 years with a high-grade DCIS this overdiagnosis rate was 21–29 %, compared to 50–66 % in women age 60–75 years with high-grade DCIS.ConclusionsAmongst the rapidly increasing numbers of DCIS diagnosed each year is a significant number of overdiagnosed cases. Tailoring treatment to the probability of progression is the next step to preventing overtreatment. The basis of this tailoring could be DCIS grade and age.

Basic Concept of Overdiagnosis in Breast Cancer Screening

Basic Concept of Overdiagnosis in Breast Cancer Screening

Overdiagnosis in Breast Cancer Screening : With Special Reference to the Predictable Relative Risk and Numbers of Lifesaved

マンモグラフィを用いる乳癌検診においては，過剰診断（overdiagnosis: OD）の存在が不可避である。まず，OD がどの程度，検診発見乳癌中に含まれるのかを知ることが重要である。 本研究では，もしOD が早期乳癌にある割合で存在すると仮定した場合に，その割合によって乳癌死亡減少を示す相対リスク（RR）がどのように変化するかを定量的に明らかにすることを試みた。日本のデータを利用して計算すると，OD が０％の場合，RR は０．７５４であるのに対し，２０％ではRRは０．８０７と低下し，６１％では１．０と有効性がなくなることが示された。今後，日本の乳癌検診において，どの程度のOD が含まれるかを調べることが必要である。

Breast cancer: The importance of overdiagnosis in breast-cancer screening.

The results of three recent studies demand that more attention be placed on defining the most-appropriate approach to population-based breast-cancer screening, in particular regarding the potential harms of increasing overdiagnosis. Two of these studies report that more-sensitive detection of breast neoplasms is possible by 3D tomography and by MRI, but the third paper raises the question of whether this increased sensitivity is desirable.

Framing overdiagnosis in breast screening: a qualitative study with Australian experts.

BackgroundThe purpose of this study was to identify how the topic of overdiagnosis in breast cancer screening is framed by experts and to clarify differences and similarities within these frames in terms of problems, causes, values and solutions.MethodsWe used a qualitative methodology using interviews with breast screening experts across Australia and applying framing theory to map and analyse their views about overdiagnosis. We interviewed 33 breast screening experts who influence the public and/or policy makers via one or more of: public or academic commentary; senior service management; government advisory bodies; professional committees; non-government/consumer organisations. Experts were currently or previously working in breast screening in a variety of roles including clinical practice, research, service provision and policy, consumer representation and advocacy.ResultsEach expert used one or more of six frames to conceptualise overdiagnosis in breast screening. Frames are described as: Overdiagnosis is harming women; Stop squabbling in public; Don’t hide the problem from women; We need to know the overdiagnosis rate; Balancing harms and benefits is a personal matter; and The problem is overtreatment. Each frame contains a different but internally coherent account of what the problem is, the causes and solutions, and a moral evaluation. Some of the frames are at least partly commensurable with each other; others are strongly incommensurable.ConclusionsExperts have very different ways of framing overdiagnosis in breast screening. This variation may contribute to the ongoing controversy in this topic. The concept of experts using different frames when thinking and talking about overdiagnosis might be a useful tool for those who are trying to negotiate the complexity of expert disagreement in order to participate in decisions about screening.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1603-4) contains supplementary material, which is available to authorized users.

A survey study of women's responses to information about overdiagnosis in breast cancer screening in Britain.

Background:There is concern about public understanding of overdiagnosis in breast cancer screening, and uncertainty about the likely impact on screening participation.Methods:In a population-based survey of 2272 women, we assessed understanding of overdiagnosis and screening intentions before and after exposure to an explanation of overdiagnosis, and one of the three information formats providing an estimate of the rate of overdiagnosis based on the findings of the UK Independent Review.Results:Subjective and objective comprehension of overdiagnosis was moderate across information formats (64% and 57%, respectively). Following overdiagnosis information, 7% of women showed a decrease in screening intention, with a stronger effect among women below screening age (<47 years), and receiving the estimate of the rate of overdiagnosis in a simple ratio format (one life saved to three overdiagnoses).Conclusions:Brief written information on overdiagnosis was incompletely understood, but reduced breast screening intentions in a proportion of women, regardless of comprehension. Subjective comprehension was lower among women who had not yet reached screening age but the deterrent effect was higher.

Counterpoint: Overdiagnosis in Breast Cancer Screening

INTRODUCTION In the ongoing debate over the balance of benefits and harms associated with breast cancer screening, overdiagnosis has become the dommage du jour. Dr Berlin [1] is right to be concerned about overdiagnosis. There can be no argument that treatment of a nonprogressive, mammographically detected lesion is the greatest possible harm associated with breast cancer screening, and to the extent that overdiagnosis exists, women need to be informed of that possibility. However, the magnitude of overdiagnosis in breast cancer screening is uncertain, with a wide range of estimates (0% to >50%) deriving from a wide range of study methodologies [2]. Estimating the magnitude of overdiagnosis in breast cancer screening is exceedingly complex, although we can say with confidence that the most credible estimates are considerably smaller than thoseBerlin cites. Thus, he overpromises when he asserts that his commentary on overdiagnosis is “the truth vs. whole truth, vs. nothing but the truth.”

Trends in aggregate cancer incidence rates in relation to screening and possible overdiagnosis: A word of caution

Overdiagnosis in breast cancer screening is a topic of debate. Researchers often estimate trends in incidence prior to screening and project these to predict incidence during the screening epoch. Data was obtained from the Cancer Registry of Norway and the Norwegian Breast Cancer Screening Programme. Using breast cancer incidence prior to screening in Norway (1976-1995), incidence trends were estimated from age-period and age-cohort models. These estimates were used to predict the incidence of breast cancer in five-year age and period groups in the screening epoch (1996-2009). Excess numbers of cancers in the screening age range (6,876 cancers), and deficits in women above and below the screening age range (1,947 cancers) were observed. However, only part of the observed differences between the observed and the expected incidence can be explained by screening, as evidenced by numbers of excess cancers greater than the numbers of screen-detected cancers in some age groups and time periods. There are potential errors in estimation of overdiagnosis from screening if individual data on screening exposure and detection mode are not taken into account. For reliable estimates of overdiagnosis, it is necessary to compare excess incidence in the screening period in those actually screened with the corresponding excess in those not screened. This is the subject of ongoing research.