Adam B Smith, Darren C Greenwood, Paul Williams, Joseph Kwon, Stavros Petrou, Mike Horton, Thomas Osborne, Ruairidh Milne, Manoj Sivan
{"title":"长期COVID与健康相关的生活质量：将特定条件的C19-YRSm测量映射到EQ-5D-5L。","authors":"Adam B Smith, Darren C Greenwood, Paul Williams, Joseph Kwon, Stavros Petrou, Mike Horton, Thomas Osborne, Ruairidh Milne, Manoj Sivan","doi":"10.2147/PROM.S490870","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Long COVID (LC) is a clinical syndrome with persistent, fluctuating symptoms subsequent to COVID-19 infection. LC has significant detrimental effects on health-related quality of life (HRQoL), activities of daily living (ADL), and work productivity. Condition-specific patient-reported outcome measures (PROMs), such as the modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) do not provide the health utility data required for cost-utility analyses of LC interventions. The aim of this study was to derive a mapping algorithm for the C19-YRSm to enable health utilities to be generated from this PROM.</p><p><strong>Methods: </strong>Data were collected from a large study evaluating LC services in the UK. A total of 1434 people with LC had completed both the C19-YRSm and the EQ-5D. Correlation and linear regression analyses were applied to determine items from the C19-YRSm and covariates for inclusion in the algorithm. Model fit, mean differences across the range of EQ-5D-3L utility scores, and Bland-Altman plots were evaluated. Responsiveness (standardised response mean; SRM) of the mapped utilities was investigated on a subset of participants with repeat assessments.</p><p><strong>Results: </strong>There was a strong level of association between 8 items and one domain on the C19-YRSm with the EQ-5D single-item dimensions. Model fit was good (R<sup>2</sup> = 0.7). The mean difference between observed and mapped scores was <0.10 for the range from 0 to 1 indicating good targeting for positive values of the EQ-5D-3L. The SRM for the mapped EQ-5D-3L was 0.37 compared to 0.17 for the observed utility scores, suggesting the mapped EQ-5D-3L is more responsive to change.</p><p><strong>Conclusion: </strong>A simple, responsive, and robust mapping algorithm was developed to generate enable EQ-5D-3L health utilities from the C19-YRSm. This will facilitate economic evaluations of LC interventions, treatment, and management, as well as further helping to describe and characterise patients with LC irrespective of any treatment and interventions.</p>","PeriodicalId":19747,"journal":{"name":"Patient Related Outcome Measures","volume":"16 ","pages":"55-66"},"PeriodicalIF":1.8000,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11776923/pdf/","citationCount":"0","resultStr":"{\"title\":\"Health-Related Quality of Life in Long COVID: Mapping the Condition-Specific C19-YRSm Measure Onto the EQ-5D-5L.\",\"authors\":\"Adam B Smith, Darren C Greenwood, Paul Williams, Joseph Kwon, Stavros Petrou, Mike Horton, Thomas Osborne, Ruairidh Milne, Manoj Sivan\",\"doi\":\"10.2147/PROM.S490870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Long COVID (LC) is a clinical syndrome with persistent, fluctuating symptoms subsequent to COVID-19 infection. LC has significant detrimental effects on health-related quality of life (HRQoL), activities of daily living (ADL), and work productivity. Condition-specific patient-reported outcome measures (PROMs), such as the modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) do not provide the health utility data required for cost-utility analyses of LC interventions. The aim of this study was to derive a mapping algorithm for the C19-YRSm to enable health utilities to be generated from this PROM.</p><p><strong>Methods: </strong>Data were collected from a large study evaluating LC services in the UK. A total of 1434 people with LC had completed both the C19-YRSm and the EQ-5D. Correlation and linear regression analyses were applied to determine items from the C19-YRSm and covariates for inclusion in the algorithm. Model fit, mean differences across the range of EQ-5D-3L utility scores, and Bland-Altman plots were evaluated. Responsiveness (standardised response mean; SRM) of the mapped utilities was investigated on a subset of participants with repeat assessments.</p><p><strong>Results: </strong>There was a strong level of association between 8 items and one domain on the C19-YRSm with the EQ-5D single-item dimensions. Model fit was good (R<sup>2</sup> = 0.7). The mean difference between observed and mapped scores was <0.10 for the range from 0 to 1 indicating good targeting for positive values of the EQ-5D-3L. The SRM for the mapped EQ-5D-3L was 0.37 compared to 0.17 for the observed utility scores, suggesting the mapped EQ-5D-3L is more responsive to change.</p><p><strong>Conclusion: </strong>A simple, responsive, and robust mapping algorithm was developed to generate enable EQ-5D-3L health utilities from the C19-YRSm. This will facilitate economic evaluations of LC interventions, treatment, and management, as well as further helping to describe and characterise patients with LC irrespective of any treatment and interventions.</p>\",\"PeriodicalId\":19747,\"journal\":{\"name\":\"Patient Related Outcome Measures\",\"volume\":\"16 \",\"pages\":\"55-66\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-01-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11776923/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Patient Related Outcome Measures\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/PROM.S490870\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Patient Related Outcome Measures","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/PROM.S490870","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Health-Related Quality of Life in Long COVID: Mapping the Condition-Specific C19-YRSm Measure Onto the EQ-5D-5L.
Background: Long COVID (LC) is a clinical syndrome with persistent, fluctuating symptoms subsequent to COVID-19 infection. LC has significant detrimental effects on health-related quality of life (HRQoL), activities of daily living (ADL), and work productivity. Condition-specific patient-reported outcome measures (PROMs), such as the modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) do not provide the health utility data required for cost-utility analyses of LC interventions. The aim of this study was to derive a mapping algorithm for the C19-YRSm to enable health utilities to be generated from this PROM.
Methods: Data were collected from a large study evaluating LC services in the UK. A total of 1434 people with LC had completed both the C19-YRSm and the EQ-5D. Correlation and linear regression analyses were applied to determine items from the C19-YRSm and covariates for inclusion in the algorithm. Model fit, mean differences across the range of EQ-5D-3L utility scores, and Bland-Altman plots were evaluated. Responsiveness (standardised response mean; SRM) of the mapped utilities was investigated on a subset of participants with repeat assessments.
Results: There was a strong level of association between 8 items and one domain on the C19-YRSm with the EQ-5D single-item dimensions. Model fit was good (R2 = 0.7). The mean difference between observed and mapped scores was <0.10 for the range from 0 to 1 indicating good targeting for positive values of the EQ-5D-3L. The SRM for the mapped EQ-5D-3L was 0.37 compared to 0.17 for the observed utility scores, suggesting the mapped EQ-5D-3L is more responsive to change.
Conclusion: A simple, responsive, and robust mapping algorithm was developed to generate enable EQ-5D-3L health utilities from the C19-YRSm. This will facilitate economic evaluations of LC interventions, treatment, and management, as well as further helping to describe and characterise patients with LC irrespective of any treatment and interventions.
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