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dc.contributor.authorFrench, David P.; orcid: 0000-0002-7663-7804; email: David.French@manchester.ac.uk
dc.contributor.authorAstley, Susan
dc.contributor.authorBrentnall, Adam R.
dc.contributor.authorCuzick, Jack
dc.contributor.authorDobrashian, Richard
dc.contributor.authorDuffy, Stephen W.
dc.contributor.authorGorman, Louise S.
dc.contributor.authorHarkness, Elaine F.
dc.contributor.authorHarrison, Fiona
dc.contributor.authorHarvie, Michelle
dc.contributor.authorHowell, Anthony
dc.contributor.authorJerrison, Andrew
dc.contributor.authorMachin, Matthew
dc.contributor.authorMaxwell, Anthony J.
dc.contributor.authorMcWilliams, Lorna
dc.contributor.authorPayne, Katherine
dc.contributor.authorQureshi, Nadeem
dc.contributor.authorRuane, Helen
dc.contributor.authorSampson, Sarah
dc.contributor.authorStavrinos, Paula
dc.contributor.authorThorpe, Emma
dc.contributor.authorUlph, Fiona
dc.contributor.authorvan Staa, Tjeerd
dc.contributor.authorWoof, Victoria
dc.contributor.authorEvans, D. Gareth
dc.date.accessioned2021-06-18T15:40:16Z
dc.date.available2021-06-18T15:40:16Z
dc.date.issued2020-06-18
dc.date.submitted2020-05-01
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/624985/12885_2020_Article_7054_nlm.xml?sequence=2
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/624985/12885_2020_Article_7054.pdf?sequence=3
dc.identifier.citationBMC Cancer, volume 20, issue 1, page 570
dc.identifier.urihttp://hdl.handle.net/10034/624985
dc.descriptionFrom Springer Nature via Jisc Publications Router
dc.descriptionHistory: received 2020-05-01, accepted 2020-06-09, registration 2020-06-09, pub-electronic 2020-06-18, online 2020-06-18, collection 2020-12
dc.descriptionPublication status: Published
dc.descriptionFunder: Programme Grants for Applied Research; doi: http://dx.doi.org/10.13039/501100007602; Grant(s): RP-PG-1214-20016
dc.descriptionFunder: Manchester Biomedical Research Centre; doi: http://dx.doi.org/10.13039/100014653; Grant(s): IS-BRC-1215-20007
dc.descriptionFunder: Genesis Research Trust; doi: http://dx.doi.org/10.13039/100012156; Grant(s): GA15-003
dc.descriptionFunder: Prevent Breast Cancer; Grant(s): GA18-001
dc.descriptionFunder: Breast Cancer Now; Grant(s): 2018RP005
dc.description.abstractAbstract: 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 < 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. Trial registration: Retrospectively registered with clinicaltrials.gov (NCT04359420).
dc.languageen
dc.publisherBioMed Central
dc.rightsLicence for this article: http://creativecommons.org/licenses/by/4.0/
dc.sourceeissn: 1471-2407
dc.subjectStudy Protocol
dc.subjectEpidemiology, prevention and public health
dc.subjectScreening
dc.subjectBreast cancer
dc.subjectRisk stratification
dc.subjectHigh risk
dc.subjectPsychological impact
dc.subjectEarly detection
dc.subjectMammographic density
dc.subjectChemoprevention
dc.subjectTyrer-Cuzick
dc.subjectAnxiety
dc.titleWhat 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)
dc.typearticle
dc.date.updated2021-06-18T15:40:16Z
dc.date.accepted2020-06-09


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