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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2015
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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. |
format | Online Article Text |
id | pubmed-4445013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
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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