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Tonmukayakul U, Willoughby K, Mihalopoulos C, Reddihough D, Mulhern B, Carter R, Robinson S, Chen G. Development of algorithms for estimating the Child Health Utility 9D from Caregiver Priorities and Child Health Index of Life with Disability. Qual Life Res 2024; 33:1881-1891. [PMID: 38700756 PMCID: PMC11176203 DOI: 10.1007/s11136-024-03661-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/03/2024] [Indexed: 06/14/2024]
Abstract
PURPOSE The primary aim was to determine Child Health Utility 9D (CHU9D) utilities from the Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) for non-ambulatory children with cerebral palsy (CP). METHODS One hundred and eight surveys completed by Australian parents/caregivers of children with CP were analysed. Spearman's coefficients were used to investigate the correlations between the two instruments. Ordinary least square, robust MM-estimator, and generalised linear models (GLM) with four combinations of families and links were developed to estimate CHU9D utilities from either the CPCHILD total score or CPCHILD domains scores. Internal validation was performed using 5-fold cross-validation and random sampling validation. The best performing algorithms were identified based on mean absolute error (MAE), concordance correlation coefficient (CCC), and the difference between predicted and observed means of CHU9D. RESULTS Moderate correlations (ρ 0.4-0.6) were observed between domains of the CHU9D and CPCHILD instruments. The best performing algorithm when considering the CPCHILD total score was a generalised linear regression (GLM) Gamma family and logit link (MAE = 0.156, CCC = 0.508). Additionally, the GLM Gamma family logit link using CPCHILD comfort and emotion, quality of life, and health domain scores also performed well (MAE = 0.152, CCC = 0.552). CONCLUSION This study established algorithms for estimating CHU9D utilities from CPCHILD scores for non-ambulatory children with CP. The determined algorithms can be valuable for estimating quality-adjusted life years for cost-utility analysis when only the CPCHILD instrument is available. However, further studies with larger sample sizes and external validation are recommended to validate these findings.
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Affiliation(s)
- Utsana Tonmukayakul
- Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia.
| | - Kate Willoughby
- Orthopaedic Department, The Royal Children's Hospital, Parkville, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
| | - Cathrine Mihalopoulos
- Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia
- Division of Health Economics, Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Dinah Reddihough
- Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
| | - Brendan Mulhern
- Centre of Health Economics Research and Evaluation, University of Technology Sydney, Haymarket, Sydney, NSW, Australia
| | - Rob Carter
- Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia
| | - Suzanne Robinson
- Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia
| | - Gang Chen
- Centre for Health Economics, Monash Business School, Monash University, Melbourne, VIC, Australia
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Shi Z, Cao A, Li S, Wang J, Zhang J, Ratcliffe J, Chen G. Health-related quality of life and subjective well-being among children aged 9-12 years in Shandong Province, China. Health Qual Life Outcomes 2024; 22:41. [PMID: 38816861 PMCID: PMC11140898 DOI: 10.1186/s12955-024-02258-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 05/14/2024] [Indexed: 06/01/2024] Open
Abstract
PURPOSE To investigate the health-related quality of life (HRQoL) and subjective well-being (SWB) of children aged 9-12 years in eastern China, and examine concordance within child self-reported and parent proxy-assessed. METHODS Data was collected from 9 to 12 years old children (including their parents) in Shandong Province in 2018. Participants self-completed a hard-copy questionnaire including Child Health Utility 9D (CHU9D), Pediatric Quality of Life Inventory (PedsQL)™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL™), Student's Life Satisfaction Scale (SLSS), as well as information on socio-demographic characteristics and self-report health status. Spearman's correlation coefficients and the difference between sub-groups were conducted to assess and compare the agreement on HRQoL and SWB instruments. Exploratory factor analysis (EFA) was used to ascertain the number of unique underlying latent factors that were associated with the items covered by the two generic HRQoL and the SWB instruments. The concordance of child self-reported and parent proxy-assessed was analyzed using weighted kappa coefficient and Bland-Altman plots. RESULTS A total of 810 children and 810 parents were invited to participate in the survey. A valid sample of 799 (98.6%) children and 643 (79.4%) parents completed the questionnaire. The child self-reported mean scores were CHU9D = 0.87, PedsQL™ = 83.47, and SLSS = 30.90, respectively. The parent proxy-assessed mean scores were PedsQL™ = 68.61 and SLSS = 31.23, respectively. The child self-reported PedsQL™ was moderately correlated with the CHU9D (r = 0.52). There was a weak correlation between CHU9D and SLSS (r = 0.27). The EFA result found 3 factors whilst seven SLSS items grouped into a standalone factor (factor 3), and the nine dimensions of CHU9D shared two common factors with the PedsQL™ (factor 1 and factor 2). A low level of concordance was observed across all comparisons and in all domains (weighted kappa < 0.20) between parents and their children. Furthermore, a high level of discordance was observed between child self-reported and father proxy-assessed. CONCLUSIONS CHU9D and PedsQL™ instruments have a higher agreement in measuring the HRQoL in children. CHU9D/PedsQL™ and SLSS instruments showed a low agreement and EFA result suggested that measuring SWB in children potentially may provide further information, which might be overlooked by using HRQoL instruments exclusively. Concordance of child self-reported and parent proxy-assessed was poor. Overall, mother-child concordance was higher than father-child concordance.
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Affiliation(s)
- Zhao Shi
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- NHC Key Lab of Health Economics and Policy Research, Shandong University, Jinan, China
- Center for Health Preference Research, Shandong University, Jinan, China
| | - Aihua Cao
- Department of Pediatric, Qilu Hospital, Shandong University, Jinan, China
| | - Shunping Li
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
- NHC Key Lab of Health Economics and Policy Research, Shandong University, Jinan, China.
- Center for Health Preference Research, Shandong University, Jinan, China.
| | - Jianglin Wang
- Shandong Electric Power Central Hospital, Jinan, China
| | - Jin Zhang
- Qingdao Municipal Hospital, Qingdao, China
| | - Julie Ratcliffe
- College of Nursing and Health Sciences, Flinders University, Adelaide, Australia
| | - Gang Chen
- Centre for Health Economics, Monash Business School, Monash University, Melbourne, Australia
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Guo W, Xie S, Wang D, Wu J. Mapping IWQOL-Lite onto EQ-5D-5L and SF-6Dv2 among overweight and obese population in China. Qual Life Res 2024; 33:817-829. [PMID: 38167749 DOI: 10.1007/s11136-023-03568-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/15/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To develop the mapping functions from the Impact of Weight on Quality of Life-Lite (IWQOL-Lite) scores onto the EQ-5D-5L and SF-6Dv2 utility values among the overweight and obese population in China. METHODS A representative sample of the overweight and obese population in China stratified by age, sex, body mass index (BMI), and area of residence was collected by online survey and the sample was randomly divided into development (80%) and validation (20%) datasets. The conceptual overlap between the IWQOL-Lite and the EQ-5D-5L or SF-6Dv2 was evaluated by Spearman's correlation coefficients. Five models, including OLS, Tobit, CLAD, GLM, and PTM were explored to derive mapping functions using the development dataset. The model performance was assessed using MAE, RMSE, and the percentage of AE > 0.05 and AE > 0.1 in the validation dataset. RESULTS A total of 1000 respondents (48% female; mean [SD] age: 51.7 [15.3]; mean [SD] BMI: 27.4 [2.8]) were included in this study. The mean IWQOL-Lite scores and the utility values of EQ-5D-5L and SF-6Dv2 were 78.5, 0.851, and 0.734, respectively. The best-performing models predicting EQ-5D-5L and SF-6Dv2 utilities both used IWQOL-Lite total score as a predictor in the CLAD model (MAE: 0.083 and 0.076 for the EQ-5D-5L and SF-6Dv2; RMSE: 0.125 and 0.103 for the EQ-5D-5L and SF-6Dv2; AE > 0.05: 20.5% and 27.5% for the EQ-5D-5L and SF-6Dv2; AE > 0.10: 9.5% and 15.0% for the EQ-5D-5L and SF-6Dv2). CONCLUSION CLAD models with the IWQOL-Lite total score can be used to predict both the EQ-5D-5L and SF-6Dv2 utility values among overweight and obese population in China.
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Affiliation(s)
- Weihua Guo
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China
| | - Shitong Xie
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China
| | - Dingyao Wang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China
| | - Jing Wu
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China.
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China.
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Oliveira Gonçalves AS, Werdin S, Kurth T, Panteli D. Mapping Studies to Estimate Health-State Utilities From Nonpreference-Based Outcome Measures: A Systematic Review on How Repeated Measurements are Taken Into Account. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2023; 26:589-597. [PMID: 36371289 DOI: 10.1016/j.jval.2022.09.2477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 09/09/2022] [Accepted: 09/29/2022] [Indexed: 05/06/2023]
Abstract
OBJECTIVES Mapping algorithms are developed using data sets containing patient responses to a preference-based questionnaire and another health-related quality-of-life questionnaire. When data sets include repeated measurements from the same individuals over time, the assumption of observations' independence, required by standard models, is violated, and standard errors are underestimated. This review aimed to identify how studies deal with methodological challenges of repeated measurements, provide an overview of practice to date, and potential implications for future work. METHODS We conducted a systematic literature search of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, specialized databases, and previous systematic reviews. A data template was used to extract, among others, start and target instruments if the data set(s) used for estimation and validation had repeated measurements per patient, used regression techniques, and which (if any) adjustments were made for repeated measurements. RESULTS We identified 278 publications developing at least 1 mapping algorithm. Of the 278 publications, 121 used a data set with repeated measurements, among which 92 used multiple time points for estimation, and 39 selected specific time points to have 1 observation per participant. A total of 36 studies did not account for repeated measurements. An adjustment was conducted using cluster-robust standard errors (21), random-effects models (30), generalized estimating equations (7), and other methods (7). CONCLUSIONS The inconsistent use of methods to account for interdependent observations in the literature indicates that mapping guidelines should include recommendations on how to deal with repeated measurements, and journals should update their guidelines accordingly.
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Affiliation(s)
| | - Sophia Werdin
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Tobias Kurth
- Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Dimitra Panteli
- Department of Health Care Management, Technische Universität Berlin, Berlin, Germany; European Observatory on Health Systems and Policies, Brussels, Belgium
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Aghdaee M, Parkinson B, Sinha K, Gu Y, Sharma R, Olin E, Cutler H. An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values. HEALTH ECONOMICS 2022; 31:1525-1557. [PMID: 35704682 PMCID: PMC9545032 DOI: 10.1002/hec.4503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 12/07/2021] [Accepted: 01/09/2022] [Indexed: 06/15/2023]
Abstract
Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a multi-attribute utility instrument is one solution. While mapping is commonly conducted using econometric techniques, failing to specify the complex interactions between variables may lead to inaccurate prediction of utilities, resulting in inaccurate estimates of cost-effectiveness and suboptimal funding decisions. These issues can be addressed using machine learning. This paper evaluates the use of machine learning as a mapping tool. We adopt a comprehensive approach to compare six machine learning techniques with eight econometric techniques to map the Patient-Reported Outcomes Measurement Information System Global Health 10 (PROMIS-GH10) to the EuroQol five dimensions (EQ-5D-5L). Using data collected from 2015 Australians, we find the least absolute shrinkage and selection operator (LASSO) model out-performed all machine learning techniques and the adjusted limited dependent variable mixture model (ALDVMM) out-performed all econometric techniques, with the LASSO performing better than ALDVMM. The variable selection feature of LASSO was then used to enhance the performance of the ALDVMM in a hybrid model. Our analysis identifies the potential benefits and challenges of using machine learning techniques for mapping and offers important insights for future research.
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Affiliation(s)
- Mona Aghdaee
- Macquarie University Centre for the Health EconomyMacquarie UniversitySydneyNew South WalesAustralia
| | - Bonny Parkinson
- Macquarie University Centre for the Health EconomyMacquarie UniversitySydneyNew South WalesAustralia
| | - Kompal Sinha
- Department of EconomicsMacquarie Business SchoolMacquarie UniversitySydneyNew South WalesAustralia
| | - Yuanyuan Gu
- Macquarie University Centre for the Health EconomyMacquarie UniversitySydneyNew South WalesAustralia
| | - Rajan Sharma
- Macquarie University Centre for the Health EconomyMacquarie UniversitySydneyNew South WalesAustralia
| | - Emma Olin
- Macquarie University Centre for the Health EconomyMacquarie UniversitySydneyNew South WalesAustralia
| | - Henry Cutler
- Macquarie University Centre for the Health EconomyMacquarie UniversitySydneyNew South WalesAustralia
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O'Farrelly C, Barker B, Watt H, Babalis D, Bakermans-Kranenburg M, Byford S, Ganguli P, Grimås E, Iles J, Mattock H, McGinley J, Phillips C, Ryan R, Scott S, Smith J, Stein A, Stevens E, van IJzendoorn M, Warwick J, Ramchandani P. A video-feedback parenting intervention to prevent enduring behaviour problems in at-risk children aged 12-36 months: the Healthy Start, Happy Start RCT. Health Technol Assess 2021; 25:1-84. [PMID: 34018919 PMCID: PMC8182442 DOI: 10.3310/hta25290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Behaviour problems emerge early in childhood and place children at risk for later psychopathology. OBJECTIVES To evaluate the clinical effectiveness and cost-effectiveness of a parenting intervention to prevent enduring behaviour problems in young children. DESIGN A pragmatic, assessor-blinded, multisite, two-arm, parallel-group randomised controlled trial. SETTING Health visiting services in six NHS trusts in England. PARTICIPANTS A total of 300 at-risk children aged 12-36 months and their parents/caregivers. INTERVENTIONS Families were allocated in a 1 : 1 ratio to six sessions of Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) plus usual care or usual care alone. MAIN OUTCOME MEASURES The primary outcome was the Preschool Parental Account of Children's Symptoms, which is a structured interview of behaviour symptoms. Secondary outcomes included caregiver-reported total problems on the Child Behaviour Checklist and the Strengths and Difficulties Questionnaire. The intervention effect was estimated using linear regression. Health and social care service use was recorded using the Child and Adolescent Service Use Schedule and cost-effectiveness was explored using the Preschool Parental Account of Children's Symptoms. RESULTS In total, 300 families were randomised: 151 to VIPP-SD plus usual care and 149 to usual care alone. Follow-up data were available for 286 (VIPP-SD, n = 140; usual care, n = 146) participants and 282 (VIPP-SD, n = 140; usual care, n = 142) participants at 5 and 24 months, respectively. At the post-treatment (primary outcome) follow-up, a group difference of 2.03 on Preschool Parental Account of Children's Symptoms (95% confidence interval 0.06 to 4.01; p = 0.04) indicated a positive treatment effect on behaviour problems (Cohen's d = 0.20, 95% confidence interval 0.01 to 0.40). The effect was strongest for children's conduct [1.61, 95% confidence interval 0.44 to 2.78; p = 0.007 (d = 0.30, 95% confidence interval 0.08 to 0.51)] versus attention deficit hyperactivity disorder symptoms [0.29, 95% confidence interval -1.06 to 1.65; p = 0.67 (d = 0.05, 95% confidence interval -0.17 to 0.27)]. The Child Behaviour Checklist [3.24, 95% confidence interval -0.06 to 6.54; p = 0.05 (d = 0.15, 95% confidence interval 0.00 to 0.31)] and the Strengths and Difficulties Questionnaire [0.93, 95% confidence interval -0.03 to 1.9; p = 0.06 (d = 0.18, 95% confidence interval -0.01 to 0.36)] demonstrated similar positive treatment effects to those found for the Preschool Parental Account of Children's Symptoms. At 24 months, the group difference on the Preschool Parental Account of Children's Symptoms was 1.73 [95% confidence interval -0.24 to 3.71; p = 0.08 (d = 0.17, 95% confidence interval -0.02 to 0.37)]; the effect remained strongest for conduct [1.07, 95% confidence interval -0.06 to 2.20; p = 0.06 (d = 0.20, 95% confidence interval -0.01 to 0.42)] versus attention deficit hyperactivity disorder symptoms [0.62, 95% confidence interval -0.60 to 1.84; p = 0.32 (d = 0.10, 95% confidence interval -0.10 to 0.30)], with little evidence of an effect on the Child Behaviour Checklist and the Strengths and Difficulties Questionnaire. The primary economic analysis showed better outcomes in the VIPP-SD group at 24 months, but also higher costs than the usual-care group (adjusted mean difference £1450, 95% confidence interval £619 to £2281). No treatment- or trial-related adverse events were reported. The probability of VIPP-SD being cost-effective compared with usual care at the 24-month follow-up increased as willingness to pay for improvements on the Preschool Parental Account of Children's Symptoms increased, with VIPP-SD having the higher probability of being cost-effective at willingness-to-pay values above £800 per 1-point improvement on the Preschool Parental Account of Children's Symptoms. LIMITATIONS The proportion of participants with graduate-level qualifications was higher than among the general public. CONCLUSIONS VIPP-SD is effective in reducing behaviour problems in young children when delivered by health visiting teams. Most of the effect of VIPP-SD appears to be retained over 24 months. However, we can be less certain about its value for money. TRIAL REGISTRATION Current Controlled Trials ISRCTN58327365. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 29. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Christine O'Farrelly
- Division of Psychiatry, Imperial College London, London, UK
- Centre for Research on Play in Education, Development, and Learning, Faculty of Education, University of Cambridge, Cambridge, UK
| | - Beth Barker
- Division of Psychiatry, Imperial College London, London, UK
- Centre for Research on Play in Education, Development, and Learning, Faculty of Education, University of Cambridge, Cambridge, UK
| | - Hilary Watt
- School of Public Health, Imperial College London, London, UK
| | - Daphne Babalis
- Imperial Clinical Trials Unit, Imperial College London, London, UK
| | - Marian Bakermans-Kranenburg
- Clinical Child and Family Studies, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Sarah Byford
- Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, UK
| | - Poushali Ganguli
- Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, UK
| | - Ellen Grimås
- Division of Psychiatry, Imperial College London, London, UK
| | - Jane Iles
- Division of Psychiatry, Imperial College London, London, UK
- School of Psychology, University of Surrey, Guildford, UK
| | - Holly Mattock
- Division of Psychiatry, Imperial College London, London, UK
| | | | | | - Rachael Ryan
- Division of Psychiatry, Imperial College London, London, UK
| | - Stephen Scott
- Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, UK
| | - Jessica Smith
- Division of Psychiatry, Imperial College London, London, UK
- Imperial Clinical Trials Unit, Imperial College London, London, UK
| | - Alan Stein
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Eloise Stevens
- Division of Psychiatry, Imperial College London, London, UK
- Centre for Research on Play in Education, Development, and Learning, Faculty of Education, University of Cambridge, Cambridge, UK
| | - Marinus van IJzendoorn
- Department of Psychology, Education, and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Jane Warwick
- Warwick Clinical Trials Unit, University of Warwick, Coventry, UK
| | - Paul Ramchandani
- Division of Psychiatry, Imperial College London, London, UK
- Centre for Research on Play in Education, Development, and Learning, Faculty of Education, University of Cambridge, Cambridge, UK
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Current Status of Research on the Mapping Function of Health Utility Values in the Asia Pacific Region: A Systematic Review. Value Health Reg Issues 2021; 24:224-239. [PMID: 33894684 DOI: 10.1016/j.vhri.2020.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 11/11/2020] [Accepted: 12/06/2020] [Indexed: 11/22/2022]
Abstract
OBJECTIVES This systematic review aimed to analyze the published studies on the use of the mapping method between generic scales and disease-specific scales as well as between 2 universal scales. METHODS A systematic literature search was conducted using PubMed, ScienceDirect, Web of Science, CNKI, Weipa Database, Wanfang Database, and HERC Database to collect articles about the application of the mapping method to the measurement of health utility value from January 2000 to December 2019. RESULTS Overall, 59 articles met the inclusion requirements, and most of them were a mapping study between a disease-specific scale and a generic scale. Then all these articles were classified by the following study types: a clear functional relationship; unclear functional relationship; disease-specific scale and universality; mapping between generic scales and disease-specific scales, and mapping between universal scales. Most studies derived the best mapping model from the ordinary least squares regression, and fewer studies chose to use new regression methods. Sample sizes in the retrieved studies generally affected the reliability of the study results. CONCLUSIONS In recent years, as more attention has been paid to the research of the mapping method, a large number of problems have followed, such as the selection of scale types, the coverage of the study sample, and the selection of evaluation index of model performance and sample size. It is hoped that these problems can be properly solved in the future research.
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