A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience

To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five art...
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Autor*in:	Ji Ryoun Gong [verfasserIn] Juhee Han [verfasserIn] Donghwan Lee [verfasserIn] SeungJin Bae [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	breast cancer utility preferences quality of life meta-regression

Übergeordnetes Werk:	In: International Journal of Environmental Research and Public Health - MDPI AG, 2005, 17(2020), 9412, p 9412
Übergeordnetes Werk:	volume:17 ; year:2020 ; number:9412, p 9412

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.3390/ijerph17249412

Katalog-ID:	DOAJ078498562

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spelling	10.3390/ijerph17249412 doi (DE-627)DOAJ078498562 (DE-599)DOAJd937003bf35340578e286e8b3b291f2a DE-627 ger DE-627 rakwb eng Ji Ryoun Gong verfasserin aut A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five articles were identified, reporting 224 utilities. A hierarchical linear model was used to conduct a meta-regression that included disease stages, assessment methods, respondent type, age of the respondents, and scale bounds as explanatory variables. The utility for early and late-stage breast cancer, as estimated by using the time-tradeoff with the scales anchored by death to perfect health with non-patients, were 0.742 and 0.525, respectively. The severity of breast cancer, assessment method, and respondent type were significant predictors of utilities, but the age of the respondents and bounds of the scale were not. Patients who experienced the health states valued 0.142 higher than did non-patients (<i<P</i< <0.001).”<b< </b<Besides the disease stage,<b< </b<the respondent type had the highest impact on breast cancer utility. breast cancer utility preferences quality of life meta-regression Medicine R Juhee Han verfasserin aut Donghwan Lee verfasserin aut SeungJin Bae verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 17(2020), 9412, p 9412 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:17 year:2020 number:9412, p 9412 https://doi.org/10.3390/ijerph17249412 kostenfrei https://doaj.org/article/d937003bf35340578e286e8b3b291f2a kostenfrei https://www.mdpi.com/1660-4601/17/24/9412 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2020 9412, p 9412
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allfieldsSound	10.3390/ijerph17249412 doi (DE-627)DOAJ078498562 (DE-599)DOAJd937003bf35340578e286e8b3b291f2a DE-627 ger DE-627 rakwb eng Ji Ryoun Gong verfasserin aut A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five articles were identified, reporting 224 utilities. A hierarchical linear model was used to conduct a meta-regression that included disease stages, assessment methods, respondent type, age of the respondents, and scale bounds as explanatory variables. The utility for early and late-stage breast cancer, as estimated by using the time-tradeoff with the scales anchored by death to perfect health with non-patients, were 0.742 and 0.525, respectively. The severity of breast cancer, assessment method, and respondent type were significant predictors of utilities, but the age of the respondents and bounds of the scale were not. Patients who experienced the health states valued 0.142 higher than did non-patients (<i<P</i< <0.001).”<b< </b<Besides the disease stage,<b< </b<the respondent type had the highest impact on breast cancer utility. breast cancer utility preferences quality of life meta-regression Medicine R Juhee Han verfasserin aut Donghwan Lee verfasserin aut SeungJin Bae verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 17(2020), 9412, p 9412 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:17 year:2020 number:9412, p 9412 https://doi.org/10.3390/ijerph17249412 kostenfrei https://doaj.org/article/d937003bf35340578e286e8b3b291f2a kostenfrei https://www.mdpi.com/1660-4601/17/24/9412 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2020 9412, p 9412
language	English
source	In International Journal of Environmental Research and Public Health 17(2020), 9412, p 9412 volume:17 year:2020 number:9412, p 9412
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authorswithroles_txt_mv	Ji Ryoun Gong @@aut@@ Juhee Han @@aut@@ Donghwan Lee @@aut@@ SeungJin Bae @@aut@@
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author	Ji Ryoun Gong
spellingShingle	Ji Ryoun Gong misc breast cancer misc utility misc preferences misc quality of life misc meta-regression misc Medicine misc R A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience
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topic_title	A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience breast cancer utility preferences quality of life meta-regression
topic	misc breast cancer misc utility misc preferences misc quality of life misc meta-regression misc Medicine misc R
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title	A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience
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author_browse	Ji Ryoun Gong Juhee Han Donghwan Lee SeungJin Bae
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title_sort	meta-regression analysis of utility weights for breast cancer: the power of patients’ experience
title_auth	A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience
abstract	To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five articles were identified, reporting 224 utilities. A hierarchical linear model was used to conduct a meta-regression that included disease stages, assessment methods, respondent type, age of the respondents, and scale bounds as explanatory variables. The utility for early and late-stage breast cancer, as estimated by using the time-tradeoff with the scales anchored by death to perfect health with non-patients, were 0.742 and 0.525, respectively. The severity of breast cancer, assessment method, and respondent type were significant predictors of utilities, but the age of the respondents and bounds of the scale were not. Patients who experienced the health states valued 0.142 higher than did non-patients (<i<P</i< <0.001).”<b< </b<Besides the disease stage,<b< </b<the respondent type had the highest impact on breast cancer utility.
abstractGer	To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five articles were identified, reporting 224 utilities. A hierarchical linear model was used to conduct a meta-regression that included disease stages, assessment methods, respondent type, age of the respondents, and scale bounds as explanatory variables. The utility for early and late-stage breast cancer, as estimated by using the time-tradeoff with the scales anchored by death to perfect health with non-patients, were 0.742 and 0.525, respectively. The severity of breast cancer, assessment method, and respondent type were significant predictors of utilities, but the age of the respondents and bounds of the scale were not. Patients who experienced the health states valued 0.142 higher than did non-patients (<i<P</i< <0.001).”<b< </b<Besides the disease stage,<b< </b<the respondent type had the highest impact on breast cancer utility.
abstract_unstemmed	To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five articles were identified, reporting 224 utilities. A hierarchical linear model was used to conduct a meta-regression that included disease stages, assessment methods, respondent type, age of the respondents, and scale bounds as explanatory variables. The utility for early and late-stage breast cancer, as estimated by using the time-tradeoff with the scales anchored by death to perfect health with non-patients, were 0.742 and 0.525, respectively. The severity of breast cancer, assessment method, and respondent type were significant predictors of utilities, but the age of the respondents and bounds of the scale were not. Patients who experienced the health states valued 0.142 higher than did non-patients (<i<P</i< <0.001).”<b< </b<Besides the disease stage,<b< </b<the respondent type had the highest impact on breast cancer utility.
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title_short	A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience
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