A systematic review of decision aids for mammography screening: Focus on outcomes and characteristics

Women's health literacy and attendance in breast cancer screening: A Danish population-based study combining survey and register data

AIM

To investigate the association between women's health literacy and attendance in the Danish national breast cancer screening programme.

METHODS

In a population-based cross-sectional study, information on two health literacy subscales, measured using the Health Literacy Questionnaire (HLQ), and sociodemographic factors was obtained from the 'How are you? 2017' survey in the Central Denmark Region. Information on screening attendance was obtained from register data from 2016-2017. Data were linked based on individual civil registration numbers. To account for missing data, multiple imputation by chained equations was implemented to fill in missing values on all variables. Unadjusted and adjusted logistic regression analyses were performed separately for two HLQ subscales to estimate odds ratio (OR) of screening attendance. Both multiple imputation analyses and complete case analyses were performed.

RESULTS

A total of 6012 women were included in multiple imputed statistical analyses. Generally, women had high health literacy levels. In multiple imputed analyses, the unadjusted OR of the primary HLQ subscale, understanding, was 1.32 (95% confidence interval (CI): 1.10-1.59), indicating higher odds for screening attendance with higher health literacy level. However, after adjustment no significant association between the HLQ subscale of understanding and screening attendance was found (OR 1.09 (95% CI: 0.90-1.33)). Similar results were found for the secondary HLQ subscale of engaging (insignificant association in adjusted analysis). No effect modification from sociodemographic characteristics was found. Similar results were found in complete case analyses.

CONCLUSIONS

No significant association was found between health literacy and attendance in the Danish breast cancer screening programme.

Team Science Principles Enhance Cancer Care Delivery Quality Improvement: Interdisciplinary Implementation of Breast Cancer Screening Shared Decision Making

PURPOSE

Implementing shared decision making (SDM), recommended in screening mammography by national guidelines for women age 40-49 years, faces challenges that innovations in quality improvement and team science (TS) are poised to address. We aimed to improve the effectiveness, patient-centeredness, and efficiency of SDM in primary care for breast cancer screening.

METHODS

Our interdisciplinary team included primary and specialty care, psychology, epidemiology, communication science, engineering, and stakeholders (patients and clinicians). Over a 6-year period, we executed two iterative cycles of plan-do-study-act (PDSA) to develop, revise, and implement a SDM tool using TS principles. Patient and physician surveys and retrospective analysis of tool performance informed our first PDSA cycle. Patient and physician surveys, toolkit use, and clinical outcomes in the second PDSA cycle supported SDM implementation. We gathered team member assessments on the importance of individual TS activities.

RESULTS

Our first PDSA cycle successfully generated a SDM tool called Breast Cancer Risk Estimator, deemed valuable by 87% of patients surveyed. Our second PDSA cycle increased Breast Cancer Risk Estimator utilization, from 2,000 sessions in 2017 to 4,097 sessions in 2019 while maintaining early-stage breast cancer diagnoses. Although TS activities such as culture, trust, and communication needed to be sustained throughout the project, shared goals, research/data infrastructure support, and leadership were more important earlier in the project and persisted in the later stages of the project.

CONCLUSION

Combining rigorous quality improvement and TS principles can support the complex, interdependent, and interdisciplinary activities necessary to improve cancer care delivery exemplified by our implementation of a breast cancer screening SDM tool.

Breast cancer: a randomized controlled trial assessing the effect of a decision aid on mammography screening uptake: study protocol

Introduction

Breast cancer (BC) is the primary cancer among women. The World Health Organization recommends a bilateral screening mammogram every 2 years for women aged 50 to 74 years. However, it has been shown that there is an absence of information about the benefits and risks of screening. Shared medical decision-making is important to ensure patients are involved in the decision process. Decision aids can facilitative this decision-making process. This article presents a protocol to evaluate the effect of a decision aid on participation rates in the French organized BC screening program.

Methods and analysis

Design and setting. The design is a 2 arm randomized controlled study, performed in the Pays de la Loire region (French West Coast). Randomization will be based on general medicine practices (Primary Care).

Participants

Women aged between 50 and 74 years, eligible for BC screening. In this region, there are 75000 women, and 2800 general practitioners eligible for recruitment.

Intervention

In the « Decision aid for organized cancer screening » arm, the intervention will distribute invitation letters to eligible women combined with the provision of decision aid to these women and their general practitioners and an incentive to implement shared medical decision-making. In the « Standard organized cancer screening » arm, only the screening invitation will be sent to eligible women.

Primary endpoint

BC screening participation rates will be assessed after an 18-month follow-up period.

Statistical analysis

In this non-inferiority trial, the percentage of women who are up-to-date with their screening at 18 months after the intervention will be compared across arms using a generalized mixed linear model.

Discussion

The research team expect to demonstrate that providing a better explanation of the benefits and risks of BC screening is not at odds with screening participation. The study results should help policy makers thinking about implementing shared medical decision-making within the framework of organized BC screening programs in the future.

Ethics and dissemination

On 6 December 2021, the protocol received a favorable opinion from the French Committee for the Protection of Persons (2021-A01583-38). This study is registered with ClinicalTrials.gov, number NCT05607849. (Version 1, November 7, 2022; https://www.clinicaltrials.gov/ct2/show/NCT05607849). The study findings will be used for publication in peer-reviewed scientific journals and presentations in scientific meetings.

Mammography and Decision Aid Use for Breast Cancer Screening in Older Women

INTRODUCTION

Decision aids for breast cancer screening are increasingly being used by physicians, but the association between physician practice decision-aid use and mammography rates remains uncertain. Using national data, this study examines the association between practice-level decision-aid use and mammography use among older women.

METHODS

Physician practice responses to the 2017/2018 National Survey of Healthcare Organizations and Systems (n=1,236) were linked to 2016 and 2017 Medicare fee-for-service beneficiary data from eligible beneficiaries (n=439,684) aged 65-74 years. In 2021, multivariable generalized linear models estimated the association of practice decision-aid use for breast cancer screening and advanced health information technology functions with mammography use, controlling for practice and beneficiary characteristics.

RESULTS

Overall, 60.1% of eligible beneficiaries had a screening mammogram, and 37.3% of physician practices routinely used decision aids for breast cancer screening. In adjusted analyses, advanced health information technology functions (OR=1.19, p=0.04) were associated with mammography use, but practice use of decision aids was not (OR=0.95, p=0.21). Beneficiary clinical and socioeconomic characteristics, including race, comorbidities, Medicare and Medicaid eligibility, and median household income were more strongly associated with mammography use than practice-level decision-aid use or advanced health information technology functions.

CONCLUSIONS

Health information technology‒enabled automation of mammography reminders and other advanced health information technology functions may support mammography, whereas breast cancer decision aids may reduce patients' propensities to be screened through the alignment of their preferences and screening decision. More resources may be needed for decision aids to be routinely implemented to improve solicitation of patient preferences and targeting of mammography services.

Shape-Based Breast Lesion Classification Using Digital Tomosynthesis Images: The Role of Explainable Artificial Intelligence

Computer-aided diagnosis (CAD) systems can help radiologists in numerous medical tasks including classification and staging of the various diseases. The 3D tomosynthesis imaging technique adds value to the CAD systems in diagnosis and classification of the breast lesions. Several convolutional neural network (CNN) architectures have been proposed to classify the lesion shapes to the respective classes using a similar imaging method. However, not only is the black box nature of these CNN models questionable in the healthcare domain, but so is the morphological-based cancer classification, concerning the clinicians. As a result, this study proposes both a mathematically and visually explainable deep-learning-driven multiclass shape-based classification framework for the tomosynthesis breast lesion images. In this study, authors exploit eight pretrained CNN architectures for the classification task on the previously extracted regions of interests images containing the lesions. Additionally, the study also unleashes the black box nature of the deep learning models using two well-known perceptive explainable artificial intelligence (XAI) algorithms including Grad-CAM and LIME. Moreover, two mathematical-structure-based interpretability techniques, i.e., t-SNE and UMAP, are employed to investigate the pretrained models’ behavior towards multiclass feature clustering. The experimental results of the classification task validate the applicability of the proposed framework by yielding the mean area under the curve of 98.2%. The explanability study validates the applicability of all employed methods, mainly emphasizing the pros and cons of both Grad-CAM and LIME methods that can provide useful insights towards explainable CAD systems.