An Open Systematic Review on Methodology and Quality of Economic Evaluations of Breast Cancer Screening Strategies

OBJECTIVES: This systematic review aims to evaluate the methodological approaches and quality of health-economic evaluations of breast cancer screening strategies and to make the findings openly accessible for future research.

METHODS: A literature search was performed in MEDLINE, EMBASE, Web of Science, Econlit, and HTA database. Health-economic evaluations of breast cancer screening strategies using imaging modalities were included and screened independently by two reviewers. Data on study design, screening strategies, outcomes, and sensitivity analyses methods were extracted and synthesized. Methodological and reporting quality was assessed using ISPOR checklist for model-based studies and CHEC-extended checklist for empirical-data-based studies. All results were made publicly accessible via a Shiny web-app.

RESULTS: The review included 100 studies: 73 model-based, 24 empirical-data-based, and 3 with unclear methods. Microsimulation and cohort-simulation were employed in 38 and 39 studies, respectively, with 12 studies not clearly reporting their approaches. The state-transition model was most prevalent (41 studies), followed by decision tree (16 studies), discrete-event simulation (16 studies) and natural history model (14 studies), used either independently or in combination. Mammography was evaluated in 95 studies, either alone or combined with MRI, ultrasound, tomosynthesis, clinical breast examination, and contrast-enhanced mammography. The quality of model-based and empirical-data-based studies were reflected by average scores of 5.18 out of 10 and 11.89 out of 20, respectively. Microsimulation studies scored higher than cohort-simulation studies (5.85 versus 4.83) especially in design, validation, and result interpretation. However, despite this, both approaches scored low in data, validation, and reporting.

CONCLUSIONS: Mammography is the most commonly evaluated modality in economic evaluations of breast cancer screening. While being equally utilized, microsimulations showed higher quality than cohort-simulation studies. Future studies should prioritize enhancing overall quality, particularly in data, validation and reporting. This work marks as the first open systematic review, providing a transparent and openly accessible foundation for future evidence generation.