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Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study.

Identifieur interne : 000216 ( Main/Exploration ); précédent : 000215; suivant : 000217

Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study.

Auteurs : Stephanie Archer [Royaume-Uni] ; Chantal Babb De Villiers [Royaume-Uni] ; Fiona Scheibl [Royaume-Uni] ; Tim Carver [Royaume-Uni] ; Simon Hartley [Royaume-Uni] ; Andrew Lee [Royaume-Uni] ; Alex P. Cunningham [Royaume-Uni] ; Douglas F. Easton [Royaume-Uni] ; Jennifer G. Mcintosh [Australie] ; Jon Emery [Royaume-Uni, Australie] ; Marc Tischkowitz [Royaume-Uni] ; Antonis C. Antoniou [Royaume-Uni] ; Fiona M. Walter [Royaume-Uni, Australie]

Source :

RBID : pubmed:32142536

Descripteurs français

English descriptors

Abstract

BACKGROUND

There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-based tool (CanRisk.org) has been developed to apply BOADICEA. This study aimed to explore the acceptability of the prototype CanRisk tool among two healthcare professional groups to inform further development, evaluation and implementation.

METHOD

A multi-methods approach was used. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype with two test cases (either face-to-face with a simulated patient or via a written vignette). Their views about the tool were examined via a semi-structured interview or equivalent open-ended questionnaire. Qualitative data were subjected to thematic analysis and organised around Sekhon's Theoretical Framework of Acceptability.

RESULTS

Seventy-five clinicians participated, 21 from primary care and 54 from specialist genetics clinics. Participants were from England (n = 37), France (n = 23) and Germany (n = 15). The prototype CanRisk tool was generally acceptable to most participants due to its intuitive design. Primary care clinicians were concerned about the amount of time needed to complete, interpret and communicate risk information. Clinicians from both settings were apprehensive about the impact of the CanRisk tool on their consultations and lack of opportunities to interpret risk scores before sharing them with their patients.

CONCLUSIONS

The findings highlight the challenges associated with developing a complex tool for use in different clinical settings; they also helped refine the tool. This prototype may not have been versatile enough for clinical use in both primary care and specialist genetics clinics where the needs of clinicians are different, emphasising the importance of understanding the clinical context when developing cancer risk assessment tools.


DOI: 10.1371/journal.pone.0229999
PubMed: 32142536
PubMed Central: PMC7059924


Affiliations:


Links toward previous steps (curation, corpus...)


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<term>Adult (MeSH)</term>
<term>Breast Neoplasms (diagnosis)</term>
<term>Female (MeSH)</term>
<term>Health Personnel (psychology)</term>
<term>Humans (MeSH)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Ovarian Neoplasms (diagnosis)</term>
<term>Primary Health Care (MeSH)</term>
<term>Risk (MeSH)</term>
<term>Self Efficacy (MeSH)</term>
<term>User-Computer Interface (MeSH)</term>
</keywords>
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<term>Adulte d'âge moyen (MeSH)</term>
<term>Auto-efficacité (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Interface utilisateur (MeSH)</term>
<term>Mâle (MeSH)</term>
<term>Personnel de santé (psychologie)</term>
<term>Risque (MeSH)</term>
<term>Soins de santé primaires (MeSH)</term>
<term>Tumeurs de l'ovaire (diagnostic)</term>
<term>Tumeurs du sein (diagnostic)</term>
</keywords>
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<term>Breast Neoplasms</term>
<term>Ovarian Neoplasms</term>
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<term>Personnel de santé</term>
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<term>Femelle</term>
<term>Humains</term>
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<b>BACKGROUND</b>
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<p>There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-based tool (CanRisk.org) has been developed to apply BOADICEA. This study aimed to explore the acceptability of the prototype CanRisk tool among two healthcare professional groups to inform further development, evaluation and implementation.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>METHOD</b>
</p>
<p>A multi-methods approach was used. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype with two test cases (either face-to-face with a simulated patient or via a written vignette). Their views about the tool were examined via a semi-structured interview or equivalent open-ended questionnaire. Qualitative data were subjected to thematic analysis and organised around Sekhon's Theoretical Framework of Acceptability.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>RESULTS</b>
</p>
<p>Seventy-five clinicians participated, 21 from primary care and 54 from specialist genetics clinics. Participants were from England (n = 37), France (n = 23) and Germany (n = 15). The prototype CanRisk tool was generally acceptable to most participants due to its intuitive design. Primary care clinicians were concerned about the amount of time needed to complete, interpret and communicate risk information. Clinicians from both settings were apprehensive about the impact of the CanRisk tool on their consultations and lack of opportunities to interpret risk scores before sharing them with their patients.</p>
</div>
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<p>
<b>CONCLUSIONS</b>
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<p>The findings highlight the challenges associated with developing a complex tool for use in different clinical settings; they also helped refine the tool. This prototype may not have been versatile enough for clinical use in both primary care and specialist genetics clinics where the needs of clinicians are different, emphasising the importance of understanding the clinical context when developing cancer risk assessment tools.</p>
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<Year>2020</Year>
<Month>06</Month>
<Day>22</Day>
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<ISSN IssnType="Electronic">1932-6203</ISSN>
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<Volume>15</Volume>
<Issue>3</Issue>
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<Year>2020</Year>
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<ArticleTitle>Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study.</ArticleTitle>
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<AbstractText Label="BACKGROUND">There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-based tool (CanRisk.org) has been developed to apply BOADICEA. This study aimed to explore the acceptability of the prototype CanRisk tool among two healthcare professional groups to inform further development, evaluation and implementation.</AbstractText>
<AbstractText Label="METHOD">A multi-methods approach was used. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype with two test cases (either face-to-face with a simulated patient or via a written vignette). Their views about the tool were examined via a semi-structured interview or equivalent open-ended questionnaire. Qualitative data were subjected to thematic analysis and organised around Sekhon's Theoretical Framework of Acceptability.</AbstractText>
<AbstractText Label="RESULTS">Seventy-five clinicians participated, 21 from primary care and 54 from specialist genetics clinics. Participants were from England (n = 37), France (n = 23) and Germany (n = 15). The prototype CanRisk tool was generally acceptable to most participants due to its intuitive design. Primary care clinicians were concerned about the amount of time needed to complete, interpret and communicate risk information. Clinicians from both settings were apprehensive about the impact of the CanRisk tool on their consultations and lack of opportunities to interpret risk scores before sharing them with their patients.</AbstractText>
<AbstractText Label="CONCLUSIONS">The findings highlight the challenges associated with developing a complex tool for use in different clinical settings; they also helped refine the tool. This prototype may not have been versatile enough for clinical use in both primary care and specialist genetics clinics where the needs of clinicians are different, emphasising the importance of understanding the clinical context when developing cancer risk assessment tools.</AbstractText>
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<Affiliation>Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom.</Affiliation>
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<Affiliation>Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom.</Affiliation>
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<Affiliation>Centre for Computational Biology, University of Birmingham, United Kingdom.</Affiliation>
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<Affiliation>Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, United Kingdom.</Affiliation>
</AffiliationInfo>
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<Affiliation>Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, United Kingdom.</Affiliation>
</AffiliationInfo>
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</AffiliationInfo>
<AffiliationInfo>
<Affiliation>Centre for Cancer Research and Department of General Practice, University of Melbourne, Australia.</Affiliation>
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<ForeName>Antonis C</ForeName>
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</AffiliationInfo>
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<Affiliation>Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom.</Affiliation>
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<AffiliationInfo>
<Affiliation>Centre for Cancer Research and Department of General Practice, University of Melbourne, Australia.</Affiliation>
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<GrantID>C12292/A20861</GrantID>
<Agency>Cancer Research UK</Agency>
<Country>United Kingdom</Country>
</Grant>
<Grant>
<GrantID>203477/B/16/Z</GrantID>
<Agency>Wellcome Trust</Agency>
<Country>United Kingdom</Country>
</Grant>
<Grant>
<GrantID>GPH-129344</GrantID>
<Agency>CIHR</Agency>
<Country>Canada</Country>
</Grant>
<Grant>
<Agency>Department of Health</Agency>
<Country>United Kingdom</Country>
</Grant>
<Grant>
<GrantID>C8640/A23385</GrantID>
<Agency>Cancer Research UK</Agency>
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<CoiStatement>The BOADICEA model has been licensed to Cambridge Enterprise for commercialization, with the authors D.F.E., A.C.A., A.P.C., A.L. and T.C. listed as its inventors. These authors may receive royalties in the future if commercialization is realized. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The other authors declare no conflicts of interest.</CoiStatement>
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Data generation: Mon Mar 15 15:24:36 2021. Site generation: Mon Mar 15 15:32:03 2021