What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420)

French, David P.; Astley, Susan; Brentnall, Adam R.; Cuzick, Jack; Dobrashian, Richard; Duffy, Stephen W.; Gorman, Louise S.; Harkness, Elaine F.; Harrison, Fiona; Harvie, Michelle; Howell, Anthony; Jerrison, Andrew; Machin, Matthew; Maxwell, Anthony J.; McWilliams, Lorna; Payne, Katherine; Qureshi, Nadeem; Ruane, Helen; Sampson, Sarah; Stavrinos, Paula; Thorpe, Emma; Ulph, Fiona; van Staa, Tjeerd; Woof, Victoria; Evans, D. Gareth

Abstract

Background
In principle, risk-stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) should produce a better balance of benefits and harms. The main benefit is the offer of NICE-approved more frequent screening and/ or chemoprevention for women who are at increased risk, but are unaware of this. We have developed BC-Predict, to be offered to women when invited to NHSBSP which collects information on risk factors (self-reported information on family history and hormone-related factors via questionnaire; mammographic density; and in a sub-sample, Single Nucleotide Polymorphisms). BC-Predict produces risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5 to [less than] 8% 10-year) to have discussion of prevention and early detection options at Family History, Risk and Prevention Clinics. Despite the promise of systems such as BC-Predict, there are still too many uncertainties for a fully-powered definitive trial to be appropriate or ethical. The present research aims to identify these key uncertainties regarding the feasibility of integrating BC-Predict into the NHSBSP. Key objectives of the present research are to quantify important potential benefits and harms, and identify key drivers of the relative cost-effectiveness of embedding BC-Predict into NHSBSP.

Methods
A non-randomised fully counterbalanced study design will be used, to include approximately equal numbers of women offered NHSBSP (n = 18,700) and BC-Predict (n = 18,700) from selected screening sites (n = 7). In the initial 8-month time period, women eligible for NHSBSP will be offered BC-Predict in four screening sites. Three screening sites will offer women usual NHSBSP. In the following 8-months the study sites offering usual NHSBSP switch to BC-Predict and vice versa. Key potential benefits including uptake of risk consultations, chemoprevention and additional screening will be obtained for both groups. Key potential harms such as increased anxiety will be obtained via self-report questionnaires, with embedded qualitative process analysis. A decision-analytic model-based cost-effectiveness analysis will identify the key uncertainties underpinning the relative cost-effectiveness of embedding BC-Predict into NHSBSP.

Discussion
We will assess the feasibility of integrating BC-Predict into the NHSBSP, and identify the main uncertainties for a definitive evaluation of the clinical and cost-effectiveness of BC-Predict.

Citation

French, D. P., Astley, S., Brentnall, A. R., Cuzick, J., Dobrashian, R., Duffy, S. W., Gorman, L. S., Harkness, E. F., Harrison, F., Harvie, M., Howell, A., Jerrison, A., Machin, M., Maxwell, A. J., McWilliams, L., Payne, K., Qureshi, N., Ruane, H., Sampson, S., Stavrinos, P., …Evans, D. G. (2020). What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420). BMC Cancer, 20, Article 570. https://doi.org/10.1186/s12885-020-07054-2

• Journal Article Type: Article
• Acceptance Date: Jun 9, 2020
• Online Publication Date: Jun 18, 2020
• Publication Date: Jun 18, 2020
• Deposit Date: Jun 24, 2020
• Publicly Available Date: Jul 2, 2020
• Journal: BMC Cancer
• Electronic ISSN: 1471-2407
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Article Number: 570
• DOI: https://doi.org/10.1186/s12885-020-07054-2
• Keywords: Genetics; Cancer Research; Oncology
• Public URL: https://nottingham-repository.worktribe.com/output/4706302
• Publisher URL: https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07054-2