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Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making
BACKGROUND: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. METHODS: In this study, we...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120963/ https://www.ncbi.nlm.nih.gov/pubmed/25105083 http://dx.doi.org/10.1097/GOX.0000000000000062 |
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author | Sun, Clement S. Cantor, Scott B. Reece, Gregory P. Crosby, Melissa A. Fingeret, Michelle C. Markey, Mia K. |
author_facet | Sun, Clement S. Cantor, Scott B. Reece, Gregory P. Crosby, Melissa A. Fingeret, Michelle C. Markey, Mia K. |
author_sort | Sun, Clement S. |
collection | PubMed |
description | BACKGROUND: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. METHODS: In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings. RESULTS: The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes. CONCLUSIONS: We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study. |
format | Online Article Text |
id | pubmed-4120963 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-41209632014-10-06 Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making Sun, Clement S. Cantor, Scott B. Reece, Gregory P. Crosby, Melissa A. Fingeret, Michelle C. Markey, Mia K. Plast Reconstr Surg Glob Open Original Articles BACKGROUND: Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction. METHODS: In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings. RESULTS: The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes. CONCLUSIONS: We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study. Wolters Kluwer Health 2014-04-07 /pmc/articles/PMC4120963/ /pubmed/25105083 http://dx.doi.org/10.1097/GOX.0000000000000062 Text en Copyright © 2013 The Authors. Published by Lippincott Williams & Wilkins on behalf of The American Society of Plastic Surgeons. PRS Global Open is a publication of the American Society of Plastic Surgeons. http://creativecommons.org/licenses/by-nc-nd/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivitives 3.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. |
spellingShingle | Original Articles Sun, Clement S. Cantor, Scott B. Reece, Gregory P. Crosby, Melissa A. Fingeret, Michelle C. Markey, Mia K. Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making |
title | Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making |
title_full | Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making |
title_fullStr | Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making |
title_full_unstemmed | Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making |
title_short | Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making |
title_sort | assessing women’s preferences and preference modeling for breast reconstruction decision making |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4120963/ https://www.ncbi.nlm.nih.gov/pubmed/25105083 http://dx.doi.org/10.1097/GOX.0000000000000062 |
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