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 screeningCitation formats

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

In: B M C Cancer, 09.06.2020.

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@article{cd5eb928021c484c9609af6b8c992fc6,
title = "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",
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 <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.",
author = "David French and Susan Astley and Brentnall, {Adam R.} and Jack Cuzick and Richard Dobrashian and Duffy, {Stephen W.} and Louise Donnelly and Elaine Harkness and Fiona Harrison and Michelle Harvie and Tony Howell and Andrew Jerrison and Matthew Machin and Anthony Maxwell and Lorna McWilliams and Katherine Payne and Nadeem Qureshi and Helen Ruane and Sarah Sampson and Paula Stavrinos and Emma Thorpe and Fiona Ulph and {Van Staa}, Tjeerd and Victoria Woof and Evans, {D Gareth}",
year = "2020",
month = jun,
day = "9",
language = "English",
journal = "BMC Cancer",
issn = "1471-2407",
publisher = "Springer Nature",

}

RIS

TY - JOUR

T1 - 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

AU - French, David

AU - Astley, Susan

AU - Brentnall, Adam R.

AU - Cuzick, Jack

AU - Dobrashian, Richard

AU - Duffy, Stephen W.

AU - Donnelly, Louise

AU - Harkness, Elaine

AU - Harrison, Fiona

AU - Harvie, Michelle

AU - Howell, Tony

AU - Jerrison, Andrew

AU - Machin, Matthew

AU - Maxwell, Anthony

AU - McWilliams, Lorna

AU - Payne, Katherine

AU - Qureshi, Nadeem

AU - Ruane, Helen

AU - Sampson, Sarah

AU - Stavrinos, Paula

AU - Thorpe, Emma

AU - Ulph, Fiona

AU - Van Staa, Tjeerd

AU - Woof, Victoria

AU - Evans, D Gareth

PY - 2020/6/9

Y1 - 2020/6/9

N2 - 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.

AB - 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.

M3 - Article

JO - BMC Cancer

JF - BMC Cancer

SN - 1471-2407

ER -