Assessing Multimodality Breast Cancer Screening Strategies for BRCA1/2 Gene Mutation Carriers and Other High-Risk Populations

High-risk women with BRCA1/2 gene mutations and a familial history of breast or ovarian cancer require intensified screening, potentially incorporating ultrasound (US) and magnetic resonance imaging (MRI) alongside mammography. However, concerns arise regarding the cost and false-positive rates of MRI and the operator dependency of US. Current guidelines lack rigorous evidence-based support, fueling debate over the optimal utilization of US and MRI in conjunction with or instead of mammography in high-risk populations. In this paper, our objective is to study the multimodality breast cancer screening problem in high-risk populations and identify optimal cost-effective population screening strategies. We develop a Markov model to capture the disease dynamics in high-risk women and formulate a mixed integer linear program to identify the optimal structured strategies that are practical for implementation. We parameterize and solve this model using real data and evidence synthesized from clinical studies. Furthermore, studying the structural properties of the optimal strategies, we establish sufficient conditions under which a strategy with more frequent screens yields higher health benefits than a strategy utilizing a more sensitive modality. Our main findings are as follows: (i) for young women (women aged 25–44 years), annual screening with ultrasound alone, despite its high operator dependency, is affordable with moderate budgets, optimal over a wide range of budget levels, and cost-effective; (ii) for middle-aged women (women 45–74 years old), annual mammography screening is robustly optimal and cost-effective; and (iii) the use of MRI alone or combined with mammogram, a recommended strategy by the current guidelines, leads to outcomes that are not cost-effective. We also discuss the impact of patient adherence and operator dependency of US on these results. We find that the optimal strategy significantly shifts when adherence is less than perfect, underscoring the complex interplay between adherence and screening outcomes. This emphasizes the need to account for patient behavior to optimize health benefits particularly at the individual level. Our findings can be helpful in designing future trials, developing evidence-based guidelines and informing insurance coverage decisions.

History: Accepted by J. Paul Brooks, Area Editor for Applications in Biology, Medicine, & Healthcare.

Funding: This research was supported in part by the National Science Foundation [Award 1601084].

Supplemental Material: The software and data that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0373) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0373). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/.