Overdiagnosis of breast cancer after 14 years of mammography screening

Women's conceptual knowledge about breast cancer screening and overdiagnosis in Norway: a cross-sectional study

OBJECTIVE

To investigate conceptual knowledge about mammographic screening among Norwegian women.

DESIGN

We administered a cross-sectional, web-based survey. We used multiple-choice questions and a grading rubric published by a research group from Australia.

SETTING

Our Norwegian-language survey was open from April to June 2020 and targeted women aged 45-74 years.

PARTICIPANTS

2033 women completed our questionnaire. We excluded 13 women outside the target age range and 128 women with incomplete data. Responses from 1892 women were included in the final study sample.

PRIMARY AND SECONDARY OUTCOME MEASURES

The questionnaire focused on women's knowledge about the breast cancer mortality reduction, false positive results and overdiagnosis associated with mammographic screening. The primary outcome was the mean number of marks assigned in each of the three themes and overall. There were three potential marks for questions about breast cancer mortality, one for false positives and six for overdiagnosis.

RESULTS

Most women (91.7%) correctly reported that screened women are less likely to die of breast cancer than non-screened women. 39.7% of women reported having heard of a 'false positive screening result' and 86.2% identified the term's definition; 51.3% of women had heard of 'overdiagnosis' and 14.8% identified the term's definition. The mean score was 2.59 of 3 for questions about breast cancer mortality benefit and 0.93 of 1 for the question about false positive screening results. It was 2.23 of 6 for questions about overdiagnosis.

CONCLUSIONS

Most participants correctly answered questions about the breast cancer mortality benefit and false positive results associated with screening. The proportion of correct responses to questions about overdiagnosis was modest, indicating that conceptual knowledge about overdiagnosis was lower. Qualitative studies that can obtain in-depth information about women's understanding of overdiagnosis may help improve Norwegian-language information about this challenging topic.

Estimations of overdiagnosis in breast cancer screening vary between 0% and over 50%: why?

BACKGROUND

Published estimations of the extent of breast cancer overdiagnosis vary widely, and there have been heated debates around these estimations. Some high estimates have even been the basis of campaigns against national breast cancer screening programmes. Identifying some of the sources of heterogeneity between different estimates would help to clarify the issue.

METHODS

The simple case of neuroblastoma-a childhood cancer-screening is used to describe the basic principle of overdiagnosis estimation. The more complicated mechanism of breast cancer overdiagnosis is described based on data from Denmark, taking into account the type of data used, individual or aggregated.

FINDINGS

The type of data used in overdiagnosis studies has a meaningful effect on the estimation: no study based on individual data provides an estimate higher than 17%, while studies based on aggregated data often provide estimates higher than 40%. This is too systematic to be random. The analysis of two Danish studies, one of each kind, highlights the biases that come with the use of aggregated data and shows how they can lead to overdiagnosis.

INTERPRETATION

Many estimates of overdiagnosis associated with breast cancer screening programmes are serious overestimations.

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.

Quality-of-life effects of screening mammography in Norway

Mammography screening may save women from dying of breast cancer, although it has not been shown to reduce all-cause mortality. Screening also leads to overdiagnosis and many false positive mammograms aggravating women's quality-of-life. Quality adjusted life years (QALY) analyses of mammography screening have so far, calculated life years gained assuming that all prevented breast cancer deaths translate into a reduction in all-cause mortality. We calculated net QALYs in two hypothesized cohorts of 100,000 Norwegian women; one screened biennially from age 50 to 69 years and one not screened. We followed both cohorts to age 85 years. We used EQ-5D and an alternative equity weighted QALY instrument to estimate utility losses. In the screening cohort, we assumed 20% false positive tests during screening, different levels of overdiagnosis (20-75%) and different levels of breast cancer mortality reduction (10-30%). We assumed that reductions in breast cancer mortality only to a limited extent (20, 50 or 80%), resulted in reductions in all-cause mortality. We calculated both undiscounted and discounted (4%) QALYs. Assuming that 50% of the reduction in breast cancer mortality translated to a reduction in all-cause mortality and using estimated levels of benefits and harms in modern screening programs (50-75% overdiagnosis and 10% reduction in breast cancer mortality), undiscounted equity weighted QALY loss varied from 437 to 875 per 100,000 women. Using the levels of benefit and harms as reported in 30-40 years old randomized trials (30% overdiagnosis and 15% reduction in breast cancer mortality), undiscounted equity weighted QALY gain was 535 per 100,000. Net QALY in modern mammography screening in Norway is negative. Results could also be representative for Sweden, Denmark, UK and the US.

[Discrepancies and overdiagnosis in breast cancer organized screening. A "methodology" systematic review]

BACKGROUND

The risk-benefit ratio of breast cancer organized screening is the focus of much scientific controversy, especially about overdiagnosis. The aim of this study was to relate methodological discrepancies to variations in rates of overdiagnosis to help build future decision aids and to better communicate with patients.

METHODS

A systematic review of methodology was conducted by two investigators who searched Medline and Cochrane databases from 01/01/2004 to 12/31/2016. Results were restricted to randomized controlled trials (RCTs) and observational studies in French or English that examined the question of the overdiagnosis computation.

RESULTS

Twenty-three observational studies and four RCTs were analyzed. The methods used comparisons of annual or cumulative incidence rates (age-cohort model) in populations invited to screen versus non-invited populations. Lead time and ductal carcinoma in situ (DCIS) were often taken into account. Some studies used statistical modeling based on the natural history of breast cancer and gradual screening implementation. Adjustments for lead time lowered the rate of overdiagnosis. Rate discrepancies, ranging from 1 to 15 % for some authors and around 30 % for others, could be explained by the hypotheses accepted concerning very slow growing tumors or tumors that regress spontaneously.

CONCLUSION

Apparently, research has to be centered on the natural history of breast cancer in order to provide responses concerning the questions raised by the overdiagnosis controversy.

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.

Breast cancer incidence trends in Norway and estimates of overdiagnosis

Objective

Fluctuations in the incidence of breast cancer in Norway in the last three decades are partly explained by the use of hormone replacement therapy and mammography screening, but overdiagnosis has also been suggested as a cause. We assessed the trends in breast cancer incidence and overdiagnosis in Norway.

Methods

We calibrated our microsimulation model to Norwegian Cancer Registration data. The model takes into account the use of mammography (both within and outside the Norwegian Breast Cancer Screening Programme) and of hormone replacement therapy. We obtained a proper fit of breast cancer incidence in recent years, when assuming an increase in the background risk for breast cancer, and estimated overdiagnosis.

Results

We estimated a 2% overdiagnosis rate as a fraction of all cancers diagnosed in women aged 50–100, and a 3% overdiagnosis rate as a fraction of all cancers diagnosed in women aged 50–70 (i.e. screening age). If all of the increased incidence would be the result of the detection of slow growing tumours, these estimates were 7% and 11%, respectively.

Conclusion

Besides mammography and hormone replacement therapy use, additional risk factors contributed to the sudden increase in breast cancer incidence in Norway. Overdiagnosis estimates due to screening were within the range of international plausible estimates.

Balancing the benefits and detriments among women targeted by the Norwegian Breast Cancer Screening Program

Objective

To compute a ratio between the estimated numbers of lives saved from breast cancer death and the number of women diagnosed with a breast cancer that never would have been diagnosed during the woman’s lifetime had she not attended screening (epidemiologic over-diagnosis) in the Norwegian Breast Cancer Screening Program.

Methods

The Norwegian Breast Cancer Screening Program invites women aged 50–69 to biennial mammographic screening. Results from published studies using individual level data from the programme for estimating breast cancer mortality and epidemiologic over-diagnosis comprised the basis for the ratio. The mortality reduction varied from 36.8% to 43% among screened women, while estimates on epidemiologic over-diagnosis ranged from 7% to 19.6%. We computed the average estimates for both values. The benefit–detriment ratio, number of lives saved, and number of women over-diagnosed were computed for different scenarios of reduction in breast cancer mortality and epidemiologic over-diagnosis.

Results

For every 10,000 biennially screened women, followed until age 79, we estimated that 53–61 (average 57) women were saved from breast cancer death, and 45–126 (average 82) were over-diagnosed. The benefit–detriment ratio using average estimates was 1:1.4, indicating that the programme saved about one life per 1–2 women with epidemiologic over-diagnosis.

Conclusion

The benefit–detriment ratio estimates of the Norwegian Breast Cancer Screening Program, expressed as lives saved from breast cancer death and epidemiologic over-diagnosis, should be interpreted with care due to substantial uncertainties in the estimates, and the differences in the scale of values of the events compared.

Overdiagnosis in Mammographic Screening because of Competing Risk of Death

BACKGROUND

Different definitions and estimates of overdiagnosis in mammographic screening reflect a substantial need to investigate and understand the complexity of the issue. This modeling study aims to estimate the number of overdiagnosed women, defined as those diagnosed with breast cancer who die from any cause within the lead-time period.

METHODS

We used numbers from incidence and death statistics available online and published estimates of lead-time. Postulated cohorts of screened and not screened women ages 50 to 51 were followed for a period corresponding to 10 biennial screening exams during 20 years, and a further 10 years, to ages 78 to 79. The increase in breast cancer incidence because of screening was estimated based on lead-time. The proportion of women diagnosed with breast cancer who died within the lead-time period was assessed based on the differences in the cumulative number of breast cancer diagnosed in a nonscreened and screened cohort.

RESULTS

The proportion of inevitable overdiagnosed women in a screened versus nonscreened cohort was 1.9% for England and Wales and 1.8% for Norway. Sensitivity analyses using various assumptions increased the estimates up to a maximum of 4%.

CONCLUSION

The proportion of women with breast cancer diagnosed after participation in a screening program who died within the estimated lead-time period was less than 4%. This inevitable proportion of overdiagnosis should be emphasized in the definition and communication of the issue.

IMPACT

The issue of overdiagnosis is complex and estimates should be interpreted with substantial care. Cancer Epidemiol Biomarkers Prev; 25(5); 759-65. ©2016 AACR.

Harms of Breast Cancer Screening: Systematic Review to Update the 2009 U.S. Preventive Services Task Force Recommendation

BACKGROUND

In 2009, the U.S. Preventive Services Task Force recommended biennial mammography screening for women aged 50 to 74 years and selective screening for those aged 40 to 49 years.

PURPOSE

To review studies of screening in average-risk women with mammography, magnetic resonance imaging, or ultrasonography that reported on false-positive results, overdiagnosis, anxiety, pain, and radiation exposure.

DATA SOURCES

MEDLINE and Cochrane databases through December 2014.

STUDY SELECTION

English-language systematic reviews, randomized trials, and observational studies of screening.

DATA EXTRACTION

Investigators extracted and confirmed data from studies and dual-rated study quality. Discrepancies were resolved through consensus.

DATA SYNTHESIS

Based on 2 studies of U.S. data, 10-year cumulative rates of false-positive mammography results and biopsies were higher with annual than biennial screening (61% vs. 42% and 7% vs. 5%, respectively) and for women aged 40 to 49 years, those with dense breasts, and those using combination hormone therapy. Twenty-nine studies using different methods reported overdiagnosis rates of 0% to 54%; rates from randomized trials were 11% to 22%. Women with false-positive results reported more anxiety, distress, and breast cancer-specific worry, although results varied across 80 observational studies. Thirty-nine observational studies indicated that some women reported pain during mammography (1% to 77%); of these, 11% to 46% declined future screening. Models estimated 2 to 11 screening-related deaths from radiation-induced cancer per 100,000 women using digital mammography, depending on age and screening interval. Five observational studies of tomosynthesis and mammography indicated increased biopsies but reduced recalls compared with mammography alone.

LIMITATIONS

Studies of overdiagnosis were highly heterogeneous, and estimates varied depending on the analytic approach. Studies of anxiety and pain used different outcome measures. Radiation exposure was based on models.

CONCLUSION

False-positive results are common and are higher for annual screening, younger women, and women with dense breasts. Although overdiagnosis, anxiety, pain, and radiation exposure may cause harm, their effects on individual women are difficult to estimate and vary widely.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality.

Estimates of over-diagnosis of breast cancer due to population-based mammography screening in South Australia after adjustment for lead time effects

OBJECTIVE

To estimate over-diagnosis due to population-based mammography screening using a lead time adjustment approach, with lead time measures based on symptomatic cancers only.

SUBJECTS

Women aged 40-84 in 1989-2009 in South Australia eligible for mammography screening.

METHODS

Numbers of observed and expected breast cancer cases were compared, after adjustment for lead time. Lead time effects were modelled using age-specific estimates of lead time (derived from interval cancer rates and predicted background incidence, using maximum likelihood methods) and screening sensitivity, projected background breast cancer incidence rates (in the absence of screening), and proportions screened, by age and calendar year.

RESULTS

Lead time estimates were 12, 26, 43 and 53 months, for women aged 40-49, 50-59, 60-69 and 70-79 respectively. Background incidence rates were estimated to have increased by 0.9% and 1.2% per year for invasive and all breast cancer. Over-diagnosis among women aged 40-84 was estimated at 7.9% (0.1-12.0%) for invasive cases and 12.0% (5.7-15.4%) when including ductal carcinoma in-situ (DCIS).

CONCLUSIONS

We estimated 8% over-diagnosis for invasive breast cancer and 12% inclusive of DCIS cancers due to mammography screening among women aged 40-84. These estimates may overstate the extent of over-diagnosis if the increasing prevalence of breast cancer risk factors has led to higher background incidence than projected.

Invasive Breast Cancer Incidence in 2,305,427 Screened Asymptomatic Women: Estimated Long Term Outcomes during Menopause Using a Systematic Review

BACKGROUND

Earlier studies of breast cancer, screening mammography, and mortality reduction may have inflated lifetime and long-term risk estimates for invasive breast cancer due to limitations in their data collection methods and interpretation.

OBJECTIVE

To estimate the percentage of asymptomatic peri/postmenopausal women who will be diagnosed with a first invasive breast cancer over their next 25 years of life.

METHODS

A systematic review identified peer-reviewed published studies that: 1) enrolled no study participants with a history of invasive breast cancer; 2) specified the number of women enrolled; 3) reported the number of women diagnosed with a first invasive breast cancer; 4) did not overcount [count a woman multiple times]; and, 5) defined the length of follow-up. Data sources included PubMed, Cochrane Library, and an annotated library of 4,409 full-text menopause-related papers collected and reviewed by the first author from 1974 through 2008. Linear regression predicted incidence of first invasive breast cancer, based on follow-up duration in all studies that met the our inclusion criteria, and in a subset of these studies that included only women who were 1) at least 50 years old and 2) either at least 50 or less than 50 but surgically menopausal at enrollment.

RESULTS

Nineteen studies met the inclusion criteria. They included a total of 2,305,427 peri/postmenopasual women. The mean cumulative incidence rate of first invasive breast cancer increased by 0.20% for each year of age (95% CI: 0.17, 0.23; p < 0.01; R2 = 0.90). Over 25 years of follow-up, an estimated 94.55% of women will remain breast cancer-free (95% CI: 93.97, 95.13). In the 12 studies (n = 1,711,178) that enrolled only postmenopausal women, an estimated 0.23% of women will be diagnosed with a first invasive breast cancer each year (95% CI: 0.18, 0.28; p < 0.01, R2 = 0.88).

CONCLUSION

The vast majority (99.75%) of screened asymptomatic peri/postmenopasual women will not be diagnosed with invasive breast cancer each year. Approximately 95% will not be diagnosed with invasive breast cancer during 25 years of follow-up. Women who receive clinical examinations, but do not have mammograms, will have higher cancer-free rates because innocuous positives (comprising 30-50% of mammography diagnoses) will remain undetected. Informed consent to asymptomatic women should include these results and consideration of the benefits of avoiding mammograms.

Bias in Observational Studies of the Association between Menopausal Hormone Therapy and Breast Cancer

Background

During the period 1985-2000 the breast cancer incidence rates increased 50% in the age group invited to mammography screening in Norway and Sweden. Simultaneously, use of hormone replacement treatment therapy (HT) increased 5 times. Several influential observational studies showed that HT was associated with 50% to 100% increased risk of breast cancer and most for those using combined (estrogen plus progestin) hormone replacement therapy (CHT). In contrast, the randomized WHI trial reported that CHT increased the risk by 10% for those not having previously used hormones and 24% when including previous users in the analyses. In another randomized trial, estrogen use only was not associated with any increased risk at all. After the WHI trial was published in 2003, use of HT dropped 70% within 5 years in Norway and Sweden while breast cancer rates were essentially unchanged. After 2008, HT use has dropped further and breast cancer incidence rates have started increasing again. The study objective is to calculate and to explain potential bias in the observational study design.

Methods and Findings

Here we use data from the randomized WHI trial and analyze these data as done in the observational studies to calculate the magnitude of the potential biases in the observational study design. Time varying effect of hormones and categorization of the follow-up time may increase the hazard ratio for long-term users from 1.10 to 1.48. Selective retrospective reporting of hormone use may further increase the hazard ratio to 1.68.

Conclusions

We suggest that the mechanism causing higher hazard ratio of breast cancer (compared to the observational studies) is the time-varying effect of CHT on the breast cancer risk and selective retrospective reporting of hormone use. Other risk factors for the increase in breast cancer risk in the age group 50-69 years should be considered, for example, overdiagnosis.

Overdiagnosis: epidemiologic concepts and estimation

Overdiagnosis of thyroid cancer was propounded regarding the rapidly increasing incidence in South Korea. Overdiagnosis is defined as 'the detection of cancers that would never have been found were it not for the screening test', and may be an extreme form of lead bias due to indolent cancers, as is inevitable when conducting a cancer screening programme. Because it is solely an epidemiological concept, it can be estimated indirectly by phenomena such as a lack of compensatory drop in post-screening periods, or discrepancies between incidence and mortality. The erstwhile trials for quantifying the overdiagnosis in screening mammography were reviewed in order to secure the data needed to establish its prevalence in South Korea.

Quantifying and monitoring overdiagnosis in cancer screening: a systematic review of methods

OBJECTIVE

To determine the optimal method for quantifying and monitoring overdiagnosis in cancer screening over time.

DESIGN

Systematic review of primary research studies of any design that quantified overdiagnosis from screening for nine types of cancer. We used explicit criteria to critically appraise individual studies and assess strength of the body of evidence for each study design (double blinded review), and assessed the potential for each study design to accurately quantify and monitor overdiagnosis over time.

DATA SOURCES

PubMed and Embase up to 28 February 2014; hand searching of systematic reviews.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

English language studies of any design that quantified overdiagnosis for any of nine common cancers (prostate, breast, lung, colorectal, melanoma, bladder, renal, thyroid, and uterine); excluded case series, case reports, and reviews that only reported results of other studies.

RESULTS

52 studies met the inclusion criteria. We grouped studies into four methodological categories: (1) follow-up of a well designed randomized controlled trial (n=3), which has low risk of bias but may not be generalizable and is not suitable for monitoring; (2) pathological or imaging studies (n=8), drawing conclusions about overdiagnosis by examining biological characteristics of cancers, a simple design limited by the uncertain assumption that the measured characteristics are highly correlated with disease progression; (3) modeling studies (n=21), which can be done in a shorter time frame but require complex mathematical equations simulating the natural course of screen detected cancer, the fundamental unknown question; and (4) ecological and cohort studies (n=20), which are suitable for monitoring over time but are limited by a lack of agreed standards, by variable data quality, by inadequate follow-up time, and by the potential for population level confounders. Some ecological and cohort studies, however, have addressed these potential weaknesses in reasonable ways.

CONCLUSIONS

Well conducted ecological and cohort studies in multiple settings are the most appropriate approach for quantifying and monitoring overdiagnosis in cancer screening programs. To support this work, we need internationally agreed standards for ecological and cohort studies and a multinational team of unbiased researchers to perform ongoing analysis.

Lead-time models should not be used to estimate overdiagnosis in cancer screening

Lead-time can mean two different things: Clinical lead-time is the lead-time for clinically relevant tumors; that is, those that are not overdiagnosed. Model-based lead-time is a theoretical construct where the time when the tumor would have caused symptoms is not limited by the person's death. It is the average time at which the diagnosis is brought forward for both clinically relevant and overdiagnosed cancers. When screening for breast cancer, clinical lead-time is about 1 year, while model-based lead-time varies from 2 to 7 years. There are two different methods to calculate overdiagnosis in cancer screening--the excess-incidence approach and the lead-time approach--that rely on two different lead-time definitions. Overdiagnosis when screening with mammography has varied from 0 to 75 %. We have explained that these differences are mainly caused by using different definitions and methods and not by variations in data. High levels of overdiagnosis of cancer have usually been explained by detection of many slow-growing tumors with long lead-times. This theory can be tested by studying if slow-growing tumors accumulate in the absence of screening, which they don't. Thus, it is likely that the natural history of many subclinical cancers is spontaneous regression.

Overestimated lead times in cancer screening has led to substantial underestimation of overdiagnosis

Background:

Published lead time estimates in breast cancer screening vary from 1 to 7 years and the percentages of overdiagnosis vary from 0 to 75%. The differences are usually explained as random variations. We study how much can be explained by using different definitions and methods.

Methods:

We estimated the clinically relevant lead time based on the observed incidence reduction after attending the last screening round in the Norwegian mammography screening programme. We compared this estimate with estimates based on models that do not take overdiagnosis into account (model-based lead times), for varying levels of overdiagnosis. Finally, we calculated overdiagnosis adjusted for clinical and model-based lead times and compared results.

Results:

Clinical lead time was about one year based on the reduction in incidence in women previously offered screening. When overdiagnosed tumours were included, the estimates increased to 4–9 years, depending on the age at which screening begins and the level of overdiagnosis. Including all breast cancers detected in women long after the end of the screening programme dilutes the level of overdiagnosis by a factor of 2–3.

Conclusion:

When overdiagnosis is not taken into account, lead time is substantially overestimated. Overdiagnosis adjusted for model-based lead time is a function tending to zero, with no simple interpretation. Furthermore, the estimates are not in general comparable, because they depend on both the duration of screening and duration of follow-up. In contrast, overdiagnosis adjusted for clinically relevant tumours is a point estimate (and interpreted as percentage), which we find is the most reasonable method.

Breast cancer screening implementation and reassurance

BACKGROUND

Women not offered screening mammography reported higher levels of negative psychosocial aspects than women offered screening. This was demonstrated in a questionnaire survey where 1000 women were included: 500 women living in areas where the public authorities had never offered screening mammography and 500 women living in areas where women had been invited to screening mammography for >10 years. After this baseline survey, nationwide screening mammography was implemented. The aim of this follow-up study was to resurvey the 1000 women and to investigate if the identified difference in reported psychosocial aspects had disappeared or been reduced because of the nationwide screening implementation.

METHODS

The 1000 women included in the previous survey were posted part I of the questionnaire Consequences of Screening in Breast Cancer (COS-BC1) in August 2011, nearly 5 years after they received the COS-BC1 the first time.

RESULTS

A total of 677 women returned the questionnaire. There was no statistically significant difference between the two groups in reported psychosocial aspects. Women new to screening reported less negative psychosocial aspects compared with the previous survey.

CONCLUSION

An implementation of a screening mammography programme provides reassurance for those women invited to the screening. This reassurance is in contrast to the unbalanced proportion between the intended benefits and the unintended harms of the screening programme.