Cost effectiveness of breast cancer screening and prevention: a systematic review with a focus on risk-adapted strategies

[The possible benefit of artificial intelligence in an organized population-related screening program : Initial results and perspective]

BACKGROUND

Mammography screening programs (MSP) have shown that breast cancer can be detected at an earlier stage enabling less invasive treatment and leading to a better survival rate. The considerable numbers of interval breast cancer (IBC) and the additional examinations required, the majority of which turn out not to be cancer, are critically assessed.

OBJECTIVE

In recent years companies and universities have used machine learning (ML) to develop powerful algorithms that demonstrate astonishing abilities to read mammograms. Can such algorithms be used to improve the quality of MSP?

METHOD

The original screening mammographies of 251 cases with IBC were retrospectively analyzed using the software ProFound AI® (iCAD) and the results were compared (case score, risk score) with a control group. The relevant current literature was also studied.

RESULTS

The distributions of the case scores and the risk scores were markedly shifted to higher risks compared to the control group, comparable to the results of other studies.

CONCLUSION

Retrospective studies as well as our own data show that artificial intelligence (AI) could change our approach to MSP in the future in the direction of personalized screening and could enable a significant reduction in the workload of radiologists, fewer additional examinations and a reduced number of IBCs; however, the results of prospective studies are needed before implementation.

ESR Essentials: screening for breast cancer - general recommendations by EUSOBI

Breast cancer is the most frequently diagnosed cancer in women accounting for about 30% of all new cancer cases and the incidence is constantly increasing. Implementation of mammographic screening has contributed to a reduction in breast cancer mortality of at least 20% over the last 30 years. Screening programs usually include all women irrespective of their risk of developing breast cancer and with age being the only determining factor. This approach has some recognized limitations, including underdiagnosis, false positive cases, and overdiagnosis. Indeed, breast cancer remains a major cause of cancer-related deaths in women undergoing cancer screening. Supplemental imaging modalities, including digital breast tomosynthesis, ultrasound, breast MRI, and, more recently, contrast-enhanced mammography, are available and have already shown potential to further increase the diagnostic performances. Use of breast MRI is recommended in high-risk women and women with extremely dense breasts. Artificial intelligence has also shown promising results to support risk categorization and interval cancer reduction. The implementation of a risk-stratified approach instead of a "one-size-fits-all" approach may help to improve the benefit-to-harm ratio as well as the cost-effectiveness of breast cancer screening. KEY POINTS: Regular mammography should still be considered the mainstay of the breast cancer screening. High-risk women and women with extremely dense breast tissue should use MRI for supplemental screening or US if MRI is not available. Women need to participate actively in the decision to undergo personalized screening. KEY RECOMMENDATIONS: Mammography is an effective imaging tool to diagnose breast cancer in an early stage and to reduce breast cancer mortality (evidence level I). Until more evidence is available to move to a personalized approach, regular mammography should be considered the mainstay of the breast cancer screening. High-risk women should start screening earlier; first with yearly breast MRI which can be supplemented by yearly or biennial mammography starting at 35-40 years old (evidence level I). Breast MRI screening should be also offered to women with extremely dense breasts (evidence level I). If MRI is not available, ultrasound can be performed as an alternative, although the added value of supplemental ultrasound regarding cancer detection remains limited. Individual screening recommendations should be made through a shared decision-making process between women and physicians.

Repeated measures of mammographic density and texture to evaluate prediction and risk of breast cancer: a systematic review of the methods used in the literature

PURPOSE

It may be important for women to have mammograms at different points in time to track changes in breast density, as fluctuations in breast density can affect breast cancer risk. This systematic review aimed to assess methods used to relate repeated mammographic images to breast cancer risk.

METHODS

The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021. Eligibility criteria included published articles in English describing the relationship of change in mammographic features with risk of breast cancer. Risk of bias was assessed using the Quality in Prognostic Studies tool.

RESULTS

Twenty articles were included. The Breast Imaging Reporting and Data System and Cumulus were most commonly used for classifying mammographic density and automated assessment was used on more recent digital mammograms. Time between mammograms varied from 1 year to a median of 4.1, and only nine of the studies used more than two mammograms. Several studies showed that adding change of density or mammographic features improved model performance. Variation in risk of bias of studies was highest in prognostic factor measurement and study confounding.

CONCLUSION

This review provided an updated overview and revealed research gaps in assessment of the use of texture features, risk prediction, and AUC. We provide recommendations for future studies using repeated measure methods for mammogram images to improve risk classification and risk prediction for women to tailor screening and prevention strategies to level of risk.

Expanding mammography screening for women aged 40-80 years: evidence from a modeling approach using real-world data

If a mammography screening program (MS) is to be expanded, the benefit must be demonstrated for each additional age cohort. For the age interval between 40 and 80 years, the association between tumor-related and tumor-independent mortality of 21 2-year cohorts is modeled using up-to-date, valid data to determine MS outcome. Disease trajectories with and without biennial MS are extrapolated for each age cohort using the available data and knowledge on MS. The competing mortality is randomly generated for each age cohort with and without MS for a follow-up period of 20 years. Analyses of the modeled cohorts describe incremental change for each year, quantifying the changing benefits of MS. With increasing age, the proportion of tumor-independent mortality before and with metastatic disease increases and the benefit decreases. The simulations with 21 studies on the age interval 40-80 years provide four parameters to determine the benefits and costs of MS: The number of prevented deaths, required mammography screening exams (MSE) and their costs, life-years gained, and the required MSEs. If one additional MSE is offered for age groups 48/70 years, this will result in 311/320 prevented breast cancer (BC) deaths with 1742/1494 required MSEs or 8784/4168 life-years gained with 64/140 required MSEs. A rational cutoff cannot be quantified. The mortality effect of MS between 40 and 80 years is quantified in 21 steps using two metrics, number of MSEs per tumor-related mortality prevented and per life-year gained. This provides a decision support for stepwise expansions. Given this real-world evidence no rational age cutoffs for MS becomes evident. A society has to decide which MS costs, including side effects of MS for women who remain BC-free, it is willing and able to accept in order to reduce breast cancer mortality.

The "Breast-4Y" web app for breast cancer prevention at young age: Development, evaluation, and validation

BACKGROUND

Improving knowledge of risk factors, signs and symptoms positively influence an individual's intention to acquire healthy lifestyle behaviors to prevent breast cancer, to identify breast cancer risk early and seek health advice early. The aim of the present study was to develop and to assess the usability and quality of a web-app (Breast-4Y) designed specifically for younger women to improve their knowledge about breast cancer risk factors and symptoms as well as protective behaviors to reduce their risk.

METHODS

The development of the Breast-4Y web-app, based on Health Belief Model and the Behaviour Change Wheel, comprised four steps: i) analysis of scientific literature regarding breast cancer risk factors, symptoms and preventive lifestyle behaviors; ii) design of web-app; iii) content review by experts; iv) quality and usability assessment by the end-users (n = 20). Web-app usability was evaluated using the Spanish version of the System Usability Scale for the Assessment of Electronic Tools and the quality using the Spanish version of uMARS.

RESULTS

The contents were rated 4.25 or above, indicating high content quality. The mean usability score was 84.9 (SD 12.4), the mean rating for objective quality and subjective quality dimensions mean were 4.2 (SD 0.4) and 3.4 (0.777) respectively, indicating excellent usability and quality. Positive associations (p < .05) were observed between numbers of app used and attitudes to change (r = 0.479), and intention to change (r = 0.539). Strong positive associations (p < .001) were also observed between usability satisfaction and attitudes to change (r = 0.584), intention to change (r = 0.656), and help-seeking (r = 0.656).

CONCLUSIONS

This study provided evidence that Breast-4Y has adequate contents, high quality, and usability. Breast-4Y can be tested in pragmatic trials to assess their effectiveness to reduce the risk of breast cancer, raise women's awareness of breast cancer risk factors, increase women's knowledge of breast cancer symptoms, and adopt protective lifestyle behaviors.

How to create value with constrained budgets in oncological care? A narrative review

INTRODUCTION

As a result of an increasing focus on patient-centered care within oncology and more pressure on the sustainability of health-care systems, the discussion on what exactly constitutes value re-appears. Policymakers seek to improve patient values; however, funding all values is not sustainable.

AREAS COVERED

We collect available evidence from scientific literature and reflect on the concept of value, the possible incorporation of a wide spectrum of values in reimbursement decisions, and alternative strategies to increase value in oncological care.

EXPERT OPINION

We state that value holds many different aspects. For reimbursement decisions, we argue that it is simply not feasible to incorporate all patient values because of the need for efficient resource allocation. We argue that we should shift the value debate from the individual perspective of patients to creating value for the cancer population at large. The different strategies we address are as follows: (1) shared decision-making; (2) biomarkers and molecular diagnostics; (3) appropriate evaluation, payment and use of drugs; (4) supportive care; (5) cancer prevention and screening; (6) monitoring late effect; (7) concentration of care and oncological networking; and (8) management of comorbidities. Important preconditions to support these strategies are strategic planning, consistent cancer policies and data availability.

Canadian Healthcare Professionals' Views and Attitudes toward Risk-Stratified Breast Cancer Screening

Given the controversy over the effectiveness of age-based breast cancer (BC) screening, offering risk-stratified screening to women may be a way to improve patient outcomes with detection of earlier-stage disease. While this approach seems promising, its integration requires the buy-in of many stakeholders. In this cross-sectional study, we surveyed Canadian healthcare professionals about their views and attitudes toward a risk-stratified BC screening approach. An anonymous online questionnaire was disseminated through Canadian healthcare professional associations between November 2020 and May 2021. Information collected included attitudes toward BC screening recommendations based on individual risk, comfort and perceived readiness related to the possible implementation of this approach. Close to 90% of the 593 respondents agreed with increased frequency and earlier initiation of BC screening for women at high risk. However, only 9% agreed with the idea of not offering BC screening to women at very low risk. Respondents indicated that primary care physicians and nurse practitioners should play a leading role in the risk-stratified BC screening approach. This survey identifies health services and policy enhancements that would be needed to support future implementation of a risk-stratified BC screening approach in healthcare systems in Canada and other countries.

Return on investment of workplace-based prevention interventions: a systematic review

BACKGROUND

Occupational Safety and Health is an important public health topic. Many employers may regard health promotion or prevention initiatives as an additional cost with few benefits. The aim of this systematic review is to identify the studies conducted on the return on investment (ROI) of preventive health interventions conducted within workplaces, and to describe their designs, topics and calculation methods.

METHODS

We searched PubMed, Web of Science, Science Direct, National Institute for Occupational Safety and Health, International Labour Organization and Occupational Safety and Health Administration from 2013 to 2021. We included studies that evaluated prevention interventions in the workplace setting and reported an economic outcome or company-related benefits. We report the findings according to PRISMA reporting guidelines.

RESULTS

We included 141 articles reporting 138 interventions. Of them, 62 (44.9%) had an experimental design, 29 (21.0%) had a quasi-experimental design, 37 (26.8%) were observational studies and 10 (7.2%) were modelling studies. The interventions' objectives were mostly related to psychosocial risks (N = 42; 30.4%), absenteeism (N = 40; 29.0%), general health (N = 35; 25.4%), specific diseases (N = 31; 22.5%), nutrition (N = 24; 17.4%), sedentarism (N = 21; 15.2%) musculoskeletal disorders (N = 17; 12.3%) and accidents (N = 14; 10.1%). The ROI calculation was positive for 78 interventions (56.5%), negative for 12 (8.7%), neutral for 13 (9.4%) and undetermined for 35 (25.4%).

CONCLUSION

There were many different ROI calculations. Most studies have a positive result but randomized controlled trials have fewer positive results than other designs. It is important to conduct more high-quality studies so that results can inform employers and policy-makers.

An Assessment of the Predictive Performance of Current Machine Learning-Based Breast Cancer Risk Prediction Models: Systematic Review

BACKGROUND

Several studies have explored the predictive performance of machine learning-based breast cancer risk prediction models and have shown controversial conclusions. Thus, the performance of the current machine learning-based breast cancer risk prediction models and their benefits and weakness need to be evaluated for the future development of feasible and efficient risk prediction models.

OBJECTIVE

The aim of this review was to assess the performance and the clinical feasibility of the currently available machine learning-based breast cancer risk prediction models.

METHODS

We searched for papers published until June 9, 2021, on machine learning-based breast cancer risk prediction models in PubMed, Embase, and Web of Science. Studies describing the development or validation models for predicting future breast cancer risk were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias and the clinical applicability of the included studies. The pooled area under the curve (AUC) was calculated using the DerSimonian and Laird random-effects model.

RESULTS

A total of 8 studies with 10 data sets were included. Neural network was the most common machine learning method for the development of breast cancer risk prediction models. The pooled AUC of the machine learning-based optimal risk prediction model reported in each study was 0.73 (95% CI 0.66-0.80; approximate 95% prediction interval 0.56-0.96), with a high level of heterogeneity between studies (Q=576.07, I²=98.44%; P<.001). The results of head-to-head comparison of the performance difference between the 2 types of models trained by the same data set showed that machine learning models had a slightly higher advantage than traditional risk factor-based models in predicting future breast cancer risk. The pooled AUC of the neural network-based risk prediction model was higher than that of the nonneural network-based optimal risk prediction model (0.71 vs 0.68, respectively). Subgroup analysis showed that the incorporation of imaging features in risk models resulted in a higher pooled AUC than the nonincorporation of imaging features in risk models (0.73 vs 0.61; P_{heterogeneity}=.001, respectively). The PROBAST analysis indicated that many machine learning models had high risk of bias and poorly reported calibration analysis.

CONCLUSIONS

Our review shows that the current machine learning-based breast cancer risk prediction models have some technical pitfalls and that their clinical feasibility and reliability are unsatisfactory.

Feasibility and Acceptability of Personalized Breast Cancer Screening (DECIDO Study): A Single-Arm Proof-of-Concept Trial

The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40-50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.

Inherited genetics of adult diffuse glioma and polygenic risk scores-a review

Knowledge about inherited and acquired genetics of adult diffuse glioma has expanded significantly over the past decade. Genomewide association studies (GWAS) stratified by histologic subtype identified six germline variants that were associated specifically with glioblastoma (GBM) and 12 that were associated with lower grade glioma. A GWAS performed using the 2016 WHO criteria, stratifying patients by IDH mutation and 1p/19q codeletion (as well as TERT promoter mutation), discovered that many of the known variants are associated with specific WHO glioma subtypes. In addition, the GWAS stratified by molecular group identified two additional novel regions: variants in D2HGDH that were associated with tumors that had an IDH mutation and a variant near FAM20C that was associated with tumors that had both IDH mutation and 1p/19q codeletion. The results of these germline associations have been used to calculate polygenic risk scores, from which to estimate relative and absolute risk of overall glioma and risk of specific glioma subtypes. We will review the concept of polygenic risk models and their potential clinical utility, as well as discuss the published adult diffuse glioma polygenic risk models. To date, these prior genetic studies have been done on European populations. Using the published glioma polygenic risk model, we show that the genetic associations published to date do not generalize across genetic ancestries, demonstrating that genetic studies need to be done on more diverse populations.

Finding the optimal mammography screening strategy: a cost‐effectiveness analysis of 920 modelled strategies

Breast cancer screening policies have been designed decades ago, but current screening strategies may not be optimal anymore. Next to that, screening capacity issues may restrict feasibility. This cost‐effectiveness study evaluates an extensive set of breast cancer screening strategies in the Netherlands. Using the Microsimulation Screening Analysis‐Breast (MISCAN‐Breast) model, the cost‐effectiveness of 920 breast cancer screening strategies with varying starting ages (40‐60), stopping ages (64‐84) and intervals (1‐4 years) were simulated. The number of quality adjusted life years (QALYs) gained and additional net costs (in €) per 1000 women were predicted (3.5% discounted) and incremental cost‐effectiveness ratios (ICERs) were calculated to compare screening scenarios. Sensitivity analyses were performed using different assumptions. In total, 26 strategies covering all four intervals were on the efficiency frontier. Using a willingness‐to‐pay threshold of €20 000/QALY gained, the biennial 40 to 76 screening strategy was optimal. However, this strategy resulted in more overdiagnoses and false positives, and required a high screening capacity. The current strategy in the Netherlands, biennial 50 to 74 years, was dominated. Triennial screening in the age range 44 to 71 (ICER 9364) or 44 to 74 (ICER 11144) resulted in slightly more QALYs gained and lower costs than the current Dutch strategy. Furthermore, these strategies were estimated to require a lower screening capacity. Findings were robust when varying attendance and effectiveness of treatment. In conclusion, switching from biennial to triennial screening while simultaneously lowering the starting age to 44 can increase benefits at lower costs and with a minor increase in harms compared to the current strategy.

Current Resources for Evidence-Based Practice, March 2022

An extensive review of new resources to support the provision of evidence-based care for women and infants. The current column includes a discussion of systemic racism and its effect on maternal health in the United States and commentaries on reviews focused on barriers and facilitators to HPV vaccination and delayed cord clamping in preterm infants.

UK Women's Views of the Concepts of Personalised Breast Cancer Risk Assessment and Risk-Stratified Breast Screening: A Qualitative Interview Study

Simple Summary

Risk-based breast screening will involve tailoring the amount of screening to women’s level of risk. Therefore, women at high-risk may be offered more frequent screening and over a longer period of time than those at low risk for whom less screening may be recommended. As this will involve considerable changes to the NHS Breast Screening Programme, it is important to explore what women in the UK think and feel about this approach. Analysis of in-depth interviews revealed that some women would find both high and low-risk screening options acceptable whereas others were resistant to the prospect of reduced screening if they were assessed as low-risk. We also found that the idea of risk-based screening had little influence on the attitudes of women who were already sceptical about breast screening. These findings highlight the communication challenges that will be faced by those introducing risk-based screening and suggest a need for tailored support and advice.

Abstract

Any introduction of risk-stratification within the NHS Breast Screening Programme needs to be considered acceptable by women. We conducted interviews to explore women’s attitudes to personalised risk assessment and risk-stratified breast screening. Twenty-five UK women were purposively sampled by screening experience and socioeconomic background. Interview transcripts were qualitatively analysed using Framework Analysis. Women expressed positive intentions for personal risk assessment and willingness to receive risk feedback to provide reassurance and certainty. Women responded to risk-stratified screening scenarios in three ways: ‘Overall acceptors’ considered both high- and low-risk options acceptable as a reasonable allocation of resources to clinical need, yet acceptability was subject to specified conditions including accuracy of risk estimates and availability of support throughout the screening pathway. Others who thought ‘more is better’ only supported high-risk scenarios where increased screening was proposed. ‘Screening sceptics’ found low-risk scenarios more aligned to their screening values than high-risk screening options. Consideration of screening recommendations for other risk groups had more influence on women’s responses than screening-related harms. These findings demonstrate high, but not universal, acceptability. Support and guidance, tailored to screening values and preferences, may be required by women at all levels of risk.