Tianxin Pan, Bram Roudijk, Nancy Devlin, Brendan Mulhern, Richard Norman
{"title":"澳大利亚EQ-5D-Y-3L的价值设置。","authors":"Tianxin Pan, Bram Roudijk, Nancy Devlin, Brendan Mulhern, Richard Norman","doi":"10.1186/s12955-025-02402-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Australia has a well-established health technology assessment process and there is extensive use of generic health related quality of life (HRQoL) instruments in evidence presented to it. However, there are gaps in tools and evidence available to support evaluation of paediatric health. The aim of this paper is to produce an Australian EQ-5D-Y-3L (Y-3L) value set.</p><p><strong>Methods: </strong>The methods follow the international Y-3L valuation protocol, but with an expanded design. Data were collected using Composite Time Trade Off (cTTO) and Discrete Choice Experiment (DCE) data from two independent samples of adult members of the Australian general public. In total, 52 Y-3L health states, assigned into four blocks of 14 health states each containing health state 33333, were valued using cTTO. cTTO data were collected via videoconferencing interview and each respondent valued 14 health states. Mean observed cTTO values were adjusted for censoring at -1 using a Tobit model. For the DCE component, 150 latent scale DCE choice pairs were collected via an online survey with each participant completing 15 pairs. DCE data were modelled using a garbage class mixed logit model. Two approaches to anchor DCE data to the Quality Adjusted Life Years (QALYs) scale were explored: anchoring on the value for the worst health state (33333); and mapping DCE data onto the mean cTTO values using all 52 health states. Two evaluation criteria were used to select the final value set: (1) coefficient significance and logical consistency; (2) prediction accuracy of the mean observed cTTO values.</p><p><strong>Results: </strong>In total, 268 individuals participated in the cTTO interviews, and 1002 completed the DCE. The linear mapping without intercept performed best and was selected as the final value set. Health state values ranged between 0.142 and 1. The relative importance of domains by level 3 coefficients (ordered from most to least important) was: pain/discomfort, then feeling worried, sad or unhappy, usual activities, looking after myself, and mobility.</p><p><strong>Conclusion: </strong>This study reports an Australian value set for the Y-3L, which enables the calculation of QALYs for use in the economic evaluation of paediatric interventions and can support evidence development and decision making.</p>","PeriodicalId":12980,"journal":{"name":"Health and Quality of Life Outcomes","volume":"23 1","pages":"72"},"PeriodicalIF":3.2000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Australian Value Set for the EQ-5D-Y-3L.\",\"authors\":\"Tianxin Pan, Bram Roudijk, Nancy Devlin, Brendan Mulhern, Richard Norman\",\"doi\":\"10.1186/s12955-025-02402-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Australia has a well-established health technology assessment process and there is extensive use of generic health related quality of life (HRQoL) instruments in evidence presented to it. However, there are gaps in tools and evidence available to support evaluation of paediatric health. The aim of this paper is to produce an Australian EQ-5D-Y-3L (Y-3L) value set.</p><p><strong>Methods: </strong>The methods follow the international Y-3L valuation protocol, but with an expanded design. Data were collected using Composite Time Trade Off (cTTO) and Discrete Choice Experiment (DCE) data from two independent samples of adult members of the Australian general public. In total, 52 Y-3L health states, assigned into four blocks of 14 health states each containing health state 33333, were valued using cTTO. cTTO data were collected via videoconferencing interview and each respondent valued 14 health states. Mean observed cTTO values were adjusted for censoring at -1 using a Tobit model. For the DCE component, 150 latent scale DCE choice pairs were collected via an online survey with each participant completing 15 pairs. DCE data were modelled using a garbage class mixed logit model. Two approaches to anchor DCE data to the Quality Adjusted Life Years (QALYs) scale were explored: anchoring on the value for the worst health state (33333); and mapping DCE data onto the mean cTTO values using all 52 health states. Two evaluation criteria were used to select the final value set: (1) coefficient significance and logical consistency; (2) prediction accuracy of the mean observed cTTO values.</p><p><strong>Results: </strong>In total, 268 individuals participated in the cTTO interviews, and 1002 completed the DCE. The linear mapping without intercept performed best and was selected as the final value set. Health state values ranged between 0.142 and 1. The relative importance of domains by level 3 coefficients (ordered from most to least important) was: pain/discomfort, then feeling worried, sad or unhappy, usual activities, looking after myself, and mobility.</p><p><strong>Conclusion: </strong>This study reports an Australian value set for the Y-3L, which enables the calculation of QALYs for use in the economic evaluation of paediatric interventions and can support evidence development and decision making.</p>\",\"PeriodicalId\":12980,\"journal\":{\"name\":\"Health and Quality of Life Outcomes\",\"volume\":\"23 1\",\"pages\":\"72\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health and Quality of Life Outcomes\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12955-025-02402-x\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health and Quality of Life Outcomes","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12955-025-02402-x","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Background: Australia has a well-established health technology assessment process and there is extensive use of generic health related quality of life (HRQoL) instruments in evidence presented to it. However, there are gaps in tools and evidence available to support evaluation of paediatric health. The aim of this paper is to produce an Australian EQ-5D-Y-3L (Y-3L) value set.
Methods: The methods follow the international Y-3L valuation protocol, but with an expanded design. Data were collected using Composite Time Trade Off (cTTO) and Discrete Choice Experiment (DCE) data from two independent samples of adult members of the Australian general public. In total, 52 Y-3L health states, assigned into four blocks of 14 health states each containing health state 33333, were valued using cTTO. cTTO data were collected via videoconferencing interview and each respondent valued 14 health states. Mean observed cTTO values were adjusted for censoring at -1 using a Tobit model. For the DCE component, 150 latent scale DCE choice pairs were collected via an online survey with each participant completing 15 pairs. DCE data were modelled using a garbage class mixed logit model. Two approaches to anchor DCE data to the Quality Adjusted Life Years (QALYs) scale were explored: anchoring on the value for the worst health state (33333); and mapping DCE data onto the mean cTTO values using all 52 health states. Two evaluation criteria were used to select the final value set: (1) coefficient significance and logical consistency; (2) prediction accuracy of the mean observed cTTO values.
Results: In total, 268 individuals participated in the cTTO interviews, and 1002 completed the DCE. The linear mapping without intercept performed best and was selected as the final value set. Health state values ranged between 0.142 and 1. The relative importance of domains by level 3 coefficients (ordered from most to least important) was: pain/discomfort, then feeling worried, sad or unhappy, usual activities, looking after myself, and mobility.
Conclusion: This study reports an Australian value set for the Y-3L, which enables the calculation of QALYs for use in the economic evaluation of paediatric interventions and can support evidence development and decision making.
期刊介绍:
Health and Quality of Life Outcomes is an open access, peer-reviewed, journal offering high quality articles, rapid publication and wide diffusion in the public domain.
Health and Quality of Life Outcomes considers original manuscripts on the Health-Related Quality of Life (HRQOL) assessment for evaluation of medical and psychosocial interventions. It also considers approaches and studies on psychometric properties of HRQOL and patient reported outcome measures, including cultural validation of instruments if they provide information about the impact of interventions. The journal publishes study protocols and reviews summarising the present state of knowledge concerning a particular aspect of HRQOL and patient reported outcome measures. Reviews should generally follow systematic review methodology. Comments on articles and letters to the editor are welcome.