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Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma

BACKGROUND. The objectives of this study were to elicit the preferences of patients with multiple myeloma regarding the possible benefits and risks of cancer treatments and to illustrate how such data may be used to estimate patients’ acceptance of new treatments. PATIENTS AND METHODS. Patients with...

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Autores principales: Postmus, Douwe, Richard, Sarah, Bere, Nathalie, van Valkenhoef, Gert, Galinsky, Jayne, Low, Eric, Moulon, Isabelle, Mavris, Maria, Salmonsson, Tomas, Flores, Beatriz, Hillege, Hans, Pignatti, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AlphaMed Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759823/
https://www.ncbi.nlm.nih.gov/pubmed/29079638
http://dx.doi.org/10.1634/theoncologist.2017-0257
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author Postmus, Douwe
Richard, Sarah
Bere, Nathalie
van Valkenhoef, Gert
Galinsky, Jayne
Low, Eric
Moulon, Isabelle
Mavris, Maria
Salmonsson, Tomas
Flores, Beatriz
Hillege, Hans
Pignatti, Francesco
author_facet Postmus, Douwe
Richard, Sarah
Bere, Nathalie
van Valkenhoef, Gert
Galinsky, Jayne
Low, Eric
Moulon, Isabelle
Mavris, Maria
Salmonsson, Tomas
Flores, Beatriz
Hillege, Hans
Pignatti, Francesco
author_sort Postmus, Douwe
collection PubMed
description BACKGROUND. The objectives of this study were to elicit the preferences of patients with multiple myeloma regarding the possible benefits and risks of cancer treatments and to illustrate how such data may be used to estimate patients’ acceptance of new treatments. PATIENTS AND METHODS. Patients with multiple myeloma from the cancer charity Myeloma UK were invited to participate in an online survey based on multicriteria decision analysis and swing weighting to elicit individual stated preferences for the following attributes: (a) 1‐year progression‐free survival (PFS, ranging from 50% to 90%), (b) mild or moderate toxicity for 2 months or longer (ranging from 85% to 45%), and (c) severe or life‐threatening toxicity (ranging from 80% to 20%). RESULTS. A total of 560 participants completed the survey. The average weight given to PFS was 0.54, followed by 0.32 for severe or life‐threatening toxicity and 0.14 for mild or moderate chronic toxicity. Participants who ranked severe or life‐threatening toxicity above mild or moderate chronic toxicity (56%) were more frequently younger, working, and looking after dependent family members and had more frequently experienced severe or life‐threatening side effects. The amount of weight given to PFS did not depend on any of the collected covariates. The feasibility of using the collected preference data to estimate the patients’ acceptance of specific multiple myeloma treatments was demonstrated in a subsequent decision analysis example. CONCLUSION. Stated preference studies provide a systematic approach to gain knowledge about the distribution of preferences in the population and about what this implies for patients’ acceptance of specific treatments. IMPLICATIONS FOR PRACTICE. This study demonstrated how quantitative preference statements from a large group of participants can be collected through an online survey and how such information may be used to explore the acceptability of specific treatments based on the attributes studied. Results from such studies have the potential to become an important new tool for gathering patient views and studying heterogeneity in preferences in a systematic way, along with other methods, such as focus groups and expert opinions.
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spelling pubmed-57598232018-07-01 Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma Postmus, Douwe Richard, Sarah Bere, Nathalie van Valkenhoef, Gert Galinsky, Jayne Low, Eric Moulon, Isabelle Mavris, Maria Salmonsson, Tomas Flores, Beatriz Hillege, Hans Pignatti, Francesco Oncologist Health Outcomes and Economics of Cancer Care BACKGROUND. The objectives of this study were to elicit the preferences of patients with multiple myeloma regarding the possible benefits and risks of cancer treatments and to illustrate how such data may be used to estimate patients’ acceptance of new treatments. PATIENTS AND METHODS. Patients with multiple myeloma from the cancer charity Myeloma UK were invited to participate in an online survey based on multicriteria decision analysis and swing weighting to elicit individual stated preferences for the following attributes: (a) 1‐year progression‐free survival (PFS, ranging from 50% to 90%), (b) mild or moderate toxicity for 2 months or longer (ranging from 85% to 45%), and (c) severe or life‐threatening toxicity (ranging from 80% to 20%). RESULTS. A total of 560 participants completed the survey. The average weight given to PFS was 0.54, followed by 0.32 for severe or life‐threatening toxicity and 0.14 for mild or moderate chronic toxicity. Participants who ranked severe or life‐threatening toxicity above mild or moderate chronic toxicity (56%) were more frequently younger, working, and looking after dependent family members and had more frequently experienced severe or life‐threatening side effects. The amount of weight given to PFS did not depend on any of the collected covariates. The feasibility of using the collected preference data to estimate the patients’ acceptance of specific multiple myeloma treatments was demonstrated in a subsequent decision analysis example. CONCLUSION. Stated preference studies provide a systematic approach to gain knowledge about the distribution of preferences in the population and about what this implies for patients’ acceptance of specific treatments. IMPLICATIONS FOR PRACTICE. This study demonstrated how quantitative preference statements from a large group of participants can be collected through an online survey and how such information may be used to explore the acceptability of specific treatments based on the attributes studied. Results from such studies have the potential to become an important new tool for gathering patient views and studying heterogeneity in preferences in a systematic way, along with other methods, such as focus groups and expert opinions. AlphaMed Press 2017-10-27 2018-01 /pmc/articles/PMC5759823/ /pubmed/29079638 http://dx.doi.org/10.1634/theoncologist.2017-0257 Text en © AlphaMed Press 2017
spellingShingle Health Outcomes and Economics of Cancer Care
Postmus, Douwe
Richard, Sarah
Bere, Nathalie
van Valkenhoef, Gert
Galinsky, Jayne
Low, Eric
Moulon, Isabelle
Mavris, Maria
Salmonsson, Tomas
Flores, Beatriz
Hillege, Hans
Pignatti, Francesco
Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma
title Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma
title_full Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma
title_fullStr Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma
title_full_unstemmed Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma
title_short Individual Trade‐Offs Between Possible Benefits and Risks of Cancer Treatments: Results from a Stated Preference Study with Patients with Multiple Myeloma
title_sort individual trade‐offs between possible benefits and risks of cancer treatments: results from a stated preference study with patients with multiple myeloma
topic Health Outcomes and Economics of Cancer Care
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759823/
https://www.ncbi.nlm.nih.gov/pubmed/29079638
http://dx.doi.org/10.1634/theoncologist.2017-0257
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