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Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach

PURPOSE: Risk prediction models (RPM) in breast cancer quantify survival benefit from adjuvant systemic treatment. These models [e.g. Adjuvant! Online (AO)] are increasingly used during consultations, despite their not being designed for such use. As still little is known about oncologists' vie...

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Autores principales: Engelhardt, Ellen G., Pieterse, Arwen H., van Duijn-Bakker, Nanny, Kroep, Judith R., de Haes, Hanneke C. J. M., Smets, Ellen M. A., Stiggelbout, Anne M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445013/
https://www.ncbi.nlm.nih.gov/pubmed/25307407
http://dx.doi.org/10.3109/0284186X.2014.964810
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author Engelhardt, Ellen G.
Pieterse, Arwen H.
van Duijn-Bakker, Nanny
Kroep, Judith R.
de Haes, Hanneke C. J. M.
Smets, Ellen M. A.
Stiggelbout, Anne M.
author_facet Engelhardt, Ellen G.
Pieterse, Arwen H.
van Duijn-Bakker, Nanny
Kroep, Judith R.
de Haes, Hanneke C. J. M.
Smets, Ellen M. A.
Stiggelbout, Anne M.
author_sort Engelhardt, Ellen G.
collection PubMed
description PURPOSE: Risk prediction models (RPM) in breast cancer quantify survival benefit from adjuvant systemic treatment. These models [e.g. Adjuvant! Online (AO)] are increasingly used during consultations, despite their not being designed for such use. As still little is known about oncologists' views on and use of RPM to communicate prognosis to patients, we investigated if, why, and how they use RPM. METHODS: We disseminated an online questionnaire that was based on the literature and individual and group interviews with oncologists. RESULTS: Fifty-one oncologists (partially) completed the questionnaire. AO is the best known (95%) and most frequently used RPM (96%). It is used to help oncologists decide whether or not to recommend chemotherapy (> 85%), to inform (86%) and help patients decide about treatment (> 80%), or to persuade them to follow the proposed course of treatment (74%). Most oncologists (74%) believe that using AO helps patients understand their prognosis. CONCLUSION: RPM have found a place in daily practice, especially AO. Oncologists think that using AO helps patients understand their prognosis, yet studies suggest that this is not always the case. Our findings highlight the importance of exploring whether patients understand the information that RPM provide.
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spelling pubmed-44450132015-05-27 Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach Engelhardt, Ellen G. Pieterse, Arwen H. van Duijn-Bakker, Nanny Kroep, Judith R. de Haes, Hanneke C. J. M. Smets, Ellen M. A. Stiggelbout, Anne M. Acta Oncol Original Article PURPOSE: Risk prediction models (RPM) in breast cancer quantify survival benefit from adjuvant systemic treatment. These models [e.g. Adjuvant! Online (AO)] are increasingly used during consultations, despite their not being designed for such use. As still little is known about oncologists' views on and use of RPM to communicate prognosis to patients, we investigated if, why, and how they use RPM. METHODS: We disseminated an online questionnaire that was based on the literature and individual and group interviews with oncologists. RESULTS: Fifty-one oncologists (partially) completed the questionnaire. AO is the best known (95%) and most frequently used RPM (96%). It is used to help oncologists decide whether or not to recommend chemotherapy (> 85%), to inform (86%) and help patients decide about treatment (> 80%), or to persuade them to follow the proposed course of treatment (74%). Most oncologists (74%) believe that using AO helps patients understand their prognosis. CONCLUSION: RPM have found a place in daily practice, especially AO. Oncologists think that using AO helps patients understand their prognosis, yet studies suggest that this is not always the case. Our findings highlight the importance of exploring whether patients understand the information that RPM provide. Taylor & Francis 2015-03 2014-10-13 /pmc/articles/PMC4445013/ /pubmed/25307407 http://dx.doi.org/10.3109/0284186X.2014.964810 Text en © 2014 Informa Healthcare http://www.informaworld.com/mpp/uploads/iopenaccess_tcs.pdf This is an open access article distributed under the Supplemental Terms and Conditions for iOpenAccess articles published in Taylor & Francis journals (http://www.informaworld.com/mpp/uploads/iopenaccess_tcs.pdf) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Engelhardt, Ellen G.
Pieterse, Arwen H.
van Duijn-Bakker, Nanny
Kroep, Judith R.
de Haes, Hanneke C. J. M.
Smets, Ellen M. A.
Stiggelbout, Anne M.
Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach
title Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach
title_full Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach
title_fullStr Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach
title_full_unstemmed Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach
title_short Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach
title_sort breast cancer specialists' views on and use of risk prediction models in clinical practice: a mixed methods approach
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445013/
https://www.ncbi.nlm.nih.gov/pubmed/25307407
http://dx.doi.org/10.3109/0284186X.2014.964810
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