Trade-Offs Between Harms and Benefits of Different Breast Cancer Screening Intervals Among Low-Risk Women

Risk-Adapted Breast Screening for Women at Low Predicted Risk of Breast Cancer: An Online Discrete Choice Experiment

BACKGROUND

A risk-stratified breast screening program could offer low-risk women less screening than is currently offered by the National Health Service. The acceptability of this approach may be enhanced if it corresponds to UK women's screening preferences and values.

OBJECTIVES

To elicit and quantify preferences for low-risk screening options.

METHODS

Women aged 40 to 70 y with no history of breast cancer took part in an online discrete choice experiment. We generated 32 hypothetical low-risk screening programs defined by 5 attributes (start age, end age, screening interval, risk of dying from breast cancer, and risk of overdiagnosis), the levels of which were systematically varied between the programs. Respondents were presented with 8 choice sets and asked to choose between 2 screening alternatives or no screening. Preference data were analyzed using conditional logit regression models. The relative importance of attributes and the mean predicted probability of choosing each program were estimated.

RESULTS

Participants (N = 502) preferred all screening programs over no screening. An older starting age of screening, younger end age of screening, longer intervals between screening, and increased risk of dying had a negative impact on support for screening programs (P < 0.01). Although the risk of overdiagnosis was of low relative importance, a decreased risk of this harm had a small positive impact on screening choices. The mean predicted probabilities that risk-adapted screening programs would be supported relative to current guidelines were low (range, 0.18 to 0.52).

CONCLUSIONS

A deintensified screening pathway for women at low risk of breast cancer, especially one that recommends a later screening start age, would run counter to women's breast screening preferences. Further research is needed to enhance the acceptability of offering less screening to those at low risk of breast cancer.

HIGHLIGHTS

Risk-based breast screening may involve the deintensification of screening for women at low risk of breast cancer.Low-risk screening pathways run counter to women's screening preferences and values.Longer screening intervals may be preferable to a later start age.Work is needed to enhance the acceptability of a low-risk screening pathway.

Cumulative 6-Year Risk of Screen-Detected Ductal Carcinoma In Situ by Screening Frequency

IMPORTANCE

Detection of ductal carcinoma in situ (DCIS) by mammography screening is a controversial outcome with potential benefits and harms. The association of mammography screening interval and woman's risk factors with the likelihood of DCIS detection after multiple screening rounds is poorly understood.

OBJECTIVE

To develop a 6-year risk prediction model for screen-detected DCIS according to mammography screening interval and women's risk factors.

DESIGN, SETTING, AND PARTICIPANTS

This Breast Cancer Surveillance Consortium cohort study assessed women aged 40 to 74 years undergoing mammography screening (digital mammography or digital breast tomosynthesis) from January 1, 2005, to December 31, 2020, at breast imaging facilities within 6 geographically diverse registries of the consortium. Data were analyzed between February and June 2022.

EXPOSURES

Screening interval (annual, biennial, or triennial), age, menopausal status, race and ethnicity, family history of breast cancer, benign breast biopsy history, breast density, body mass index, age at first birth, and false-positive mammography history.

MAIN OUTCOMES AND MEASURES

Screen-detected DCIS defined as a DCIS diagnosis within 12 months after a positive screening mammography result, with no concurrent invasive disease.

RESULTS

A total of 916 931 women (median [IQR] age at baseline, 54 [46-62] years; 12% Asian, 9% Black, 5% Hispanic/Latina, 69% White, 2% other or multiple races, and 4% missing) met the eligibility criteria, with 3757 screen-detected DCIS diagnoses. Screening round-specific risk estimates from multivariable logistic regression were well calibrated (expected-observed ratio, 1.00; 95% CI, 0.97-1.03) with a cross-validated area under the receiver operating characteristic curve of 0.639 (95% CI, 0.630-0.648). Cumulative 6-year risk of screen-detected DCIS estimated from screening round-specific risk estimates, accounting for competing risks of death and invasive cancer, varied widely by all included risk factors. Cumulative 6-year screen-detected DCIS risk increased with age and shorter screening interval. Among women aged 40 to 49 years, the mean 6-year screen-detected DCIS risk was 0.30% (IQR, 0.21%-0.37%) for annual screening, 0.21% (IQR, 0.14%-0.26%) for biennial screening, and 0.17% (IQR, 0.12%-0.22%) for triennial screening. Among women aged 70 to 74 years, the mean cumulative risks were 0.58% (IQR, 0.41%-0.69%) after 6 annual screens, 0.40% (IQR, 0.28%-0.48%) for 3 biennial screens, and 0.33% (IQR, 0.23%-0.39%) after 2 triennial screens.

CONCLUSIONS AND RELEVANCE

In this cohort study, 6-year screen-detected DCIS risk was higher with annual screening compared with biennial or triennial screening intervals. Estimates from the prediction model, along with risk estimates of other screening benefits and harms, could help inform policy makers' discussions of screening strategies.

A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old

BACKGROUND

Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women's breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women's individualized BC risk and life expectancy.

METHODS

Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses' Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women's Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk.

RESULTS

Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784-0.796) in NHS and 0.768 (0.757-0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538-0.641) in NHS and 0.573 (0.536-0.611) in BWHS.

CONCLUSIONS

We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening.

Perceptions of Breast Cancer Risks Among Women Receiving Mammograph Screening

Importance

Breast density is an independent risk factor for breast cancer. Despite the proliferation of mandated written notifications about breast density following mammography, there is little understanding of how women perceive the relative breast cancer risk associated with breast density.

Objective

To assess women's perception of breast density compared with other breast cancer risks and explore their understanding of risk reduction.

Design, Setting, and Participants

This mixed-methods qualitative study used telephone surveys and semistructured interviews to investigate perceptions about breast cancer risk among a nationally representative, population-based sample of women. Eligible study participants were aged 40 to 76 years, reported having recently undergone mammography, had no history of prior breast cancer, and had heard of breast density. Survey participants who had been informed of their personal breast density were invited for a qualitative interview. Survey administration spanned July 1, 2019, to April 30, 2020, with 2306 women completing the survey. Qualitative interviews were conducted from February 1 to May 30, 2020.

Main Outcomes and Measures

Respondents compared the breast cancer risk associated with breast density with 5 other risk factors. Participants qualitatively described what they thought contributed to breast cancer risk and ways to reduce risk.

Results

Of the 2306 women who completed the survey, 1858 (166 [9%] Asian, 503 [27%] Black, 268 [14%] Hispanic, 792 [43%] White, and 128 [7%] other race or ethnicity; 358 [19%] aged 40-49 years, 906 [49%] aged 50-64 years, and 594 [32%] aged ≥65 years) completed the revised risk perception questions and were included in the analysis. Half of respondents thought breast density to be a greater risk than not having children (957 [52%]), having more than 1 alcoholic drink per day (975 [53%]), or having a prior breast biopsy (867 [48%]). Most respondents felt breast density was a lesser risk than having a first-degree relative with breast cancer (1706 [93%]) or being overweight or obese (1188 [65%]). Of the 61 women who were interviewed, 6 (10%) described breast density as contributing to breast cancer risk, and 43 (70%) emphasized family history as a breast cancer risk factor. Of the interviewed women, 17 (28%) stated they did not know whether it was possible to reduce their breast cancer risk.

Conclusions and Relevance

In this qualitative study of women of breast cancer screening age, family history was perceived as the primary breast cancer risk factor. Most interviewees did not identify breast density as a risk factor and did not feel confident about actions to mitigate breast cancer risk. Comprehensive education about breast cancer risks and prevention strategies is needed.

Study protocol comparing the ethical, psychological and socio-economic impact of personalised breast cancer screening to that of standard screening in the "My Personal Breast Screening" (MyPeBS) randomised clinical trial

Background

The MyPeBS study is an ongoing randomised controlled trial testing whether a risk-stratified breast cancer screening strategy is non-inferior, or eventually superior, to standard age-based screening at reducing incidence of stage 2 or more cancers. This large European Commission-funded initiative aims to include 85,000 women aged 40 to 70 years, without prior breast cancer and not previously identified at high risk in six countries (Belgium, France, Italy, Israel, Spain, UK). A specific work package within MyPeBS examines psychological, socio-economic and ethical aspects of this new screening strategy. It compares women’s reported data and outcomes in both trial arms on the following issues: general anxiety, cancer-related worry, understanding of breast cancer screening strategy and information-seeking behaviour, socio-demographic and economic characteristics, quality of life, risk perception, intention to change health-related behaviours, satisfaction with the trial.

Methods

At inclusion, 3-months, 1-year and 4-years, each woman participating in MyPeBS is asked to fill online questionnaires. Descriptive statistics, bivariate analyses, subgroup comparisons and analysis of variations over time will be performed with appropriate tests to assess differences between arms. Multivariate regression models will allow modelling of different patient reported data and outcomes such as comprehension of the information provided, general anxiety or cancer worry, and information seeking behaviour. In addition, a qualitative study (48 semi-structured interviews conducted in France and in the UK with women randomised in the risk-stratified arm), will help further understand participants’ acceptability and comprehension of the trial, and their experience of risk assessment.

Discussion

Beyond the scientific and medical objectives of this clinical study, it is critical to acknowledge the consequences of such a paradigm shift for women. Indeed, introducing a risk-based screening relying on individual biological differences also implies addressing non-biological differences (e.g. social status or health literacy) from an ethical perspective, to ensure equal access to healthcare. The results of the present study will facilitate making recommendations on implementation at the end of the trial to accompany any potential change in screening strategy.

Trial registration

Study sponsor: UNICANCER. My personalised breast screening (MyPeBS). Clinicaltrials.gov (2018) available at: https://clinicaltrials.gov/ct2/show/NCT03672331

Contact: Cécile VISSAC SABATIER, PhD, + 33 (0)1 73 79 77 58 ext + 330,142,114,293, contact@mypebs.eu.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09484-6.

Navigating Breast Cancer Screening in Rural Missouri: From Patient Navigation to Social Navigation

The National Cancer Institute recently identified rural cancer disparities as a priority issue, dedicating resources to rural cancer prevention, presenting opportunities and also risks. We bring an anthropological concept, social navigation, to bear on a popular public health intervention, patient navigation, increasingly proposed as an "evidence-based" approach to reducing health disparities. Our study of mammography in the Missouri Bootheel demonstrates how such interventions elide the shifting terrain and slow violence of rural health care where people must improvise care through trying out or sticking with providers, negotiating self-advocacy and deference, or changing screening timelines amidst structural constraints and rural stereotypes.

Systematic Review of Cost-Effectiveness Models in Prostate Cancer: Exploring New Developments in Testing and Diagnosis

OBJECTIVES

Recent innovations in prostate cancer diagnosis include new biomarkers and more accurate biopsy methods. This study assesses the evidence base on cost-effectiveness of these developments (eg, Prostate Health Index and magnetic resonance imaging [MRI]-guided biopsy) and identifies areas of improvement for future cost-effectiveness models.

METHODS

A systematic review using the National Health Service Economic Evaluation Database, MEDLINE, Embase, Health Technology Assessment databases, National Institute for Health and Care Excellence guidelines, and United Kingdom National Screening Committee guidance was performed, between 2009 and 2021. Relevant data were extracted on study type, model inputs, modeling methods and cost-effectiveness conclusions, and results narratively synthesized.

RESULTS

A total of 22 model-based economic evaluations were included. A total of 11 compared the cost-effectiveness of new biomarkers to prostate-specific antigen testing alone and all found biomarkers to be cost saving. A total of 8 compared MRI-guided biopsy methods to transrectal ultrasound-guided methods and found MRI-guided methods to be most cost-effective. Newer detection methods showed a reduction in unnecessary biopsies and overtreatment. The most cost-effective follow-up strategy in men with a negative initial biopsy was uncertain. Many studies did not model for stage or grade of cancer, cancer progression, or the entire testing and treatment pathway. Few fully accounted for uncertainty.

CONCLUSIONS

This review brings together the cost-effectiveness literature for novel diagnostic methods in prostate cancer, showing that most studies have found new methods to be more cost-effective than standard of care. Several limitations of the models were identified, however, limiting the reliability of the results. Areas for further development include accurately modeling the impact of early diagnostic tests on long-term outcomes of prostate cancer and fully accounting for uncertainty.