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Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420)
BACKGROUND: Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a s...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10066938/ https://www.ncbi.nlm.nih.gov/pubmed/37005486 http://dx.doi.org/10.1038/s41416-023-02250-w |
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author | Gareth Evans, D. McWilliams, Lorna Astley, Susan Brentnall, Adam R. Cuzick, Jack Dobrashian, Richard Duffy, Stephen W. Gorman, Louise S. Harkness, Elaine F. Harrison, Fiona Harvie, Michelle Jerrison, Andrew Machin, Matthew Maxwell, Anthony J. Howell, Sacha J. Wright, Stuart J. Payne, Katherine Qureshi, Nadeem Ruane, Helen Southworth, Jake Fox, Lynne Bowers, Sarah Hutchinson, Gillian Thorpe, Emma Ulph, Fiona Woof, Victoria Howell, Anthony French, David P. |
author_facet | Gareth Evans, D. McWilliams, Lorna Astley, Susan Brentnall, Adam R. Cuzick, Jack Dobrashian, Richard Duffy, Stephen W. Gorman, Louise S. Harkness, Elaine F. Harrison, Fiona Harvie, Michelle Jerrison, Andrew Machin, Matthew Maxwell, Anthony J. Howell, Sacha J. Wright, Stuart J. Payne, Katherine Qureshi, Nadeem Ruane, Helen Southworth, Jake Fox, Lynne Bowers, Sarah Hutchinson, Gillian Thorpe, Emma Ulph, Fiona Woof, Victoria Howell, Anthony French, David P. |
author_sort | Gareth Evans, D. |
collection | PubMed |
description | BACKGROUND: Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS). METHODS: Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer–Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5–<8% 10-year) to have appointments to discuss prevention and additional screening. RESULTS: Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication. DISCUSSION: We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420). |
format | Online Article Text |
id | pubmed-10066938 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100669382023-04-03 Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) Gareth Evans, D. McWilliams, Lorna Astley, Susan Brentnall, Adam R. Cuzick, Jack Dobrashian, Richard Duffy, Stephen W. Gorman, Louise S. Harkness, Elaine F. Harrison, Fiona Harvie, Michelle Jerrison, Andrew Machin, Matthew Maxwell, Anthony J. Howell, Sacha J. Wright, Stuart J. Payne, Katherine Qureshi, Nadeem Ruane, Helen Southworth, Jake Fox, Lynne Bowers, Sarah Hutchinson, Gillian Thorpe, Emma Ulph, Fiona Woof, Victoria Howell, Anthony French, David P. Br J Cancer Article BACKGROUND: Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS). METHODS: Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer–Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5–<8% 10-year) to have appointments to discuss prevention and additional screening. RESULTS: Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication. DISCUSSION: We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420). Nature Publishing Group UK 2023-04-01 2023-06-15 /pmc/articles/PMC10066938/ /pubmed/37005486 http://dx.doi.org/10.1038/s41416-023-02250-w Text en © The Authors 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Gareth Evans, D. McWilliams, Lorna Astley, Susan Brentnall, Adam R. Cuzick, Jack Dobrashian, Richard Duffy, Stephen W. Gorman, Louise S. Harkness, Elaine F. Harrison, Fiona Harvie, Michelle Jerrison, Andrew Machin, Matthew Maxwell, Anthony J. Howell, Sacha J. Wright, Stuart J. Payne, Katherine Qureshi, Nadeem Ruane, Helen Southworth, Jake Fox, Lynne Bowers, Sarah Hutchinson, Gillian Thorpe, Emma Ulph, Fiona Woof, Victoria Howell, Anthony French, David P. Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) |
title | Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) |
title_full | Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) |
title_fullStr | Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) |
title_full_unstemmed | Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) |
title_short | Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420) |
title_sort | quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the bc-predict non-randomised controlled study (nct04359420) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10066938/ https://www.ncbi.nlm.nih.gov/pubmed/37005486 http://dx.doi.org/10.1038/s41416-023-02250-w |
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