Estimating the cost of 3 risk prediction strategies for potential use in the United Kingdom National Breast Screening Program

Abstract

Background: Economic evaluations have suggested that risk-stratified breast cancer screening may be cost-effective but have used assumptions to estimate the cost of risk prediction. The aim of this study was to identify and quantify the resource use and associated costs required to introduce a breast cancer risk-stratification approach into the English national breast screening program. Methods: A micro-costing study, conducted alongside a cohort-based prospective trial (BC-PREDICT), identified the resource use and cost per individual (£; 2021 price year) of providing a risk-stratification strategy at a woman's first mammography. Costs were calculated for 3 risk-stratification approaches: Tyrer-Cuzick survey, Tyrer-Cuzick with Volpara breast-density measurement, and Tyrer-Cuzick with Volpara breast-density measurement and testing for 142 single nucleotide polymorphisms (SNP). Costs were determined for the intervention as implemented in the trial and in the health service. Results: The cost of providing the risk-stratification strategy was calculated to be £16.45 for the Tyrer-Cuzick survey approach, £21.82 for the Tyrer-Cuzick with Volpara breast-density measurement, and £102.22 for the Tyrer-Cuzick with Volpara breast-density measurement and SNP testing. Limitations: This study did not use formal expert elicitation methods to synthesize estimates. Conclusion: The costs of risk prediction using a survey and breast density measurement were low, but adding SNP testing substantially increases costs. Implementation issues present in the trial may also significantly increase the cost of risk prediction. Implications: This is the first study to robustly estimate the cost of risk-stratification for breast cancer screening. The cost of risk prediction using questionnaires and automated breast density measurement was low, but full economic evaluations including accurate costs are required to provide evidence of the cost-effectiveness of risk-stratified breast cancer screening.