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Kamya C, Idro R, Ochanda P, Kalibbala D, Nkosi-Gondwe T, Akun PR, Phiri KS, O Ter Kuile F, Kaarboe O, Robberstad B. Health-Related Quality of Life in Children With Sickle Cell Anemia in Malaria-Endemic Regions: The Impact of Disease States and Malaria Prevention Strategies. Value Health Reg Issues 2025; 48:101120. [PMID: 40319619 DOI: 10.1016/j.vhri.2025.101120] [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: 06/13/2024] [Revised: 01/08/2025] [Accepted: 03/18/2025] [Indexed: 05/07/2025]
Abstract
OBJECTIVES To assess the health-related quality of life (HRQoL) of children with sickle cell anemia (SCA) in Uganda and Malawi during steady disease states and sick attacks and to examine the impact of malaria chemoprevention with weekly dihydroartemisinin-piperaquine compared to monthly sulfadoxine-pyrimethamine. METHODS This cohort study was nested within a clinical trial comparing weekly dihydroartemisinin-piperaquine with the standard of care (monthly sulfadoxine-pyrimethamine) among children with SCA. HRQoL was assessed using EQ-5D tools during steady states and sick attacks. Ordinary least squares regression identified factors associated with HRQoL. RESULTS A total of 633 children with SCA were enrolled (mean age 8.1 years, standard deviation [SD] 3.7). HRQoL was higher during steady states but deteriorated during sick attacks, with the most problems reported in pain and discomfort. Older children (ages 12-16: mean difference [MD] = 0.09, P < .0001) experienced higher HRQoL during steady states but lower HRQoL during sick attacks. Hospitalization negatively affected HRQoL; children hospitalized 1 to 3 times (MD = -0.27, P = .01) or ≥4 times (MD = -0.24, P = .02) had substantially lower HRQoL. There were no HRQoL differences between treatment arms. CONCLUSIONS The HRQoL of children with SCA was relatively high during steady states but declined substantially during sick attacks, especially because of severe pain and discomfort. HRQoL is influenced by a child's age and frequency of hospitalization. Results provide information for calculation of quality-adjusted life years for future economic evaluation.
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Affiliation(s)
- Carol Kamya
- Section for Ethics and Health Economics, Department of Global Public Health and Primary Care, University of Bergen, Norway.
| | - Richard Idro
- Makerere University College of Health Sciences, Kampala, Uganda
| | - Perez Ochanda
- Section for Ethics and Health Economics, Department of Global Public Health and Primary Care, University of Bergen, Norway
| | | | - Thandile Nkosi-Gondwe
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi; Training and Research Unit of Excellence, Malawi
| | - Pamela R Akun
- Makerere University College of Health Sciences, Kampala, Uganda
| | - Kamija S Phiri
- School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi; Training and Research Unit of Excellence, Malawi
| | - Feiko O Ter Kuile
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, England, UK
| | - Oddvar Kaarboe
- Section for Ethics and Health Economics, Department of Global Public Health and Primary Care, University of Bergen, Norway
| | - Bjarne Robberstad
- Section for Ethics and Health Economics, Department of Global Public Health and Primary Care, University of Bergen, Norway
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Hagiwara Y. Using a Sample Size Calculation Framework for Clinical Prediction Models When Developing and Selecting Mapping Algorithms Based on Linear Regression. Med Decis Making 2023; 43:992-996. [PMID: 37470312 DOI: 10.1177/0272989x231188134] [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] [Indexed: 07/21/2023]
Abstract
PURPOSE To propose using a framework for calculating the sample size for clinical prediction models when developing and selecting mapping algorithms from a health-related quality-of-life (HRQOL) measure onto the score of a preference-based measure (PBM) using linear regression. METHODS The framework was summarized for health economics researchers. Mapping studies that mapped the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 onto the EQ-5D-3L index using linear regression were evaluated in terms of sample size. The required sample size for each study was calculated using 4 criteria: global shrinkage factor ≥ 0.9, difference between the apparent and adjusted R2 ≤ 0.05, multiplicative margin of error in the estimated residual standard deviation ≤ 1.1, and absolute margin of error in the estimated model intercept ≤ 0.025. RESULTS Ten mapping studies were identified. The information required to calculate the sample size was successfully extracted from previous mapping studies. Four of 10 mapping studies did not have sufficient sample sizes. LIMITATIONS Further extension of this framework to other regression approaches used in mapping studies is necessary. CONCLUSIONS The sample size should be considered when developing and selecting a mapping algorithm based on linear regression. HIGHLIGHTS No recommendation or guidance is available for the sample size to develop and select a mapping algorithm from a health-related quality-of-life measure onto the score of a preference-based measure.This research proposes using a framework for calculating the sample size for clinical prediction models in sample size consideration for mapping algorithms using linear regression.A survey showed that the information required to calculate the sample size could be successfully extracted from previous mapping studies and that 4 of 10 mapping studies did not have sufficient sample sizes.
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Affiliation(s)
- Yasuhiro Hagiwara
- Department of Biostatistics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Kuo S, Yang C, Chen H, Ou H. Valuing health states of people with type 2 diabetes: Analyses of the nationwide representative linked databases. J Diabetes Investig 2021; 12:1749-1758. [PMID: 33539655 PMCID: PMC8409834 DOI: 10.1111/jdi.13520] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/29/2021] [Accepted: 02/02/2021] [Indexed: 11/27/2022] Open
Abstract
AIMS/INTRODUCTION To estimate preference-based measures of health-related quality of life associated with sociodemographic and clinical characteristics in type 2 diabetes patients. MATERIALS AND METHODS Individuals with EuroQol-5 dimensions-3 levels data were identified from Taiwan's National Health Interview Survey in 2009 and 2013. Status of diabetes, comorbidities, complications and treatments were ascertained through data linkage to Taiwan's National Health Insurance Research Database. Multivariable ordinary least squares, Tobit and median regression analyses were used to estimate the coefficients that represented independent impacts of patients' characteristics on health-related quality of life. RESULTS The mean health utility score for 2,104 participants was 0.838. Being female, aging, divorced/widowed, never worked or underweight, or having a lower monthly household income, injectable glucose-lowering therapy, comorbid connective tissue disease or depression were associated with lower health utilities. Having an amputation led to the largest reduction by 0.288 in health utilities, followed by debilitating stroke (0.266), heart failure (0.237), other coronary heart disease (0.185), kidney dialysis/transplant (0.148), coronary revascularizations (0.093), transient ischemic attack/stroke (0.078), diabetic neuropathy (0.062), polyneuropathy (0.055) and other neuropathy (0.043). CONCLUSIONS Major vascular complications, connective tissue disease and depression are associated with considerably worse health-related quality of life. These health utility estimates can facilitate health economic evaluations to determine cost-effective strategies for diabetes management.
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Affiliation(s)
- Shihchen Kuo
- Division of Metabolism, Endocrinology & DiabetesDepartment of Internal MedicineUniversity of Michigan Medical SchoolAnn ArborMichiganUSA
| | - Chun‐Ting Yang
- Institute of Clinical Pharmacy and Pharmaceutical SciencesCollege of MedicineNational Cheng Kung UniversityTainanTaiwan
| | - Hsuan‐Ying Chen
- Institute of Clinical Pharmacy and Pharmaceutical SciencesCollege of MedicineNational Cheng Kung UniversityTainanTaiwan
| | - Huang‐Tz Ou
- Institute of Clinical Pharmacy and Pharmaceutical SciencesCollege of MedicineNational Cheng Kung UniversityTainanTaiwan
- Department of PharmacyCollege of MedicineNational Cheng Kung UniversityTainanTaiwan
- Department of PharmacyNational Cheng Kung University HospitalTainanTaiwan
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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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Klapproth CP, van Bebber J, Sidey-Gibbons CJ, Valderas JM, Leplege A, Rose M, Fischer F. Predicting EQ-5D-5L crosswalk from the PROMIS-29 profile for the United Kingdom, France, and Germany. Health Qual Life Outcomes 2020; 18:389. [PMID: 33334351 PMCID: PMC7745375 DOI: 10.1186/s12955-020-01629-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 11/18/2020] [Indexed: 02/06/2023] Open
Abstract
Background EQ-5D health state utilities (HSU) are commonly used in health economics to compute quality-adjusted life years (QALYs). The EQ-5D, which is country-specific, can be derived directly or by mapping from self-reported health-related quality of life (HRQoL) scales such as the PROMIS-29 profile. The PROMIS-29 from the Patient Reported Outcome Measures Information System is a comprehensive assessment of self-reported health with excellent psychometric properties. We sought to find optimal models predicting the EQ-5D-5L crosswalk from the PROMIS-29 in the United Kingdom, France, and Germany and compared the prediction performances with that of a US model. Methods We collected EQ-5D-5L and PROMIS-29 profiles and three samples representative of the general populations in the UK (n = 1509), France (n = 1501), and Germany (n = 1502). We used stepwise regression with backward selection to find the best models to predict the EQ-5D-5L crosswalk from all seven PROMIS-29 domains. We investigated the agreement between the observed and predicted EQ-5D-5L crosswalk in all three countries using various indices for the prediction performance, including Bland–Altman plots to examine the performance along the HSU continuum. Results The EQ-5D-5L crosswalk was best predicted in France (nRMSEFRA = 0.075, nMAEFRA = 0.052), followed by the UK (nRMSEUK = 0.076, nMAEUK = 0.053) and Germany (nRMSEGER = 0.079, nMAEGER = 0.051). The Bland–Altman plots show that the inclusion of higher-order effects reduced the overprediction of low HSU scores. Conclusions Our models provide a valid method to predict the EQ-5D-5L crosswalk from the PROMIS-29 for the UK, France, and Germany.
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Affiliation(s)
- Christoph Paul Klapproth
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| | - J van Bebber
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - C J Sidey-Gibbons
- Department of Symptom Research, MD Anderson Cancer Center, University of Houston, Houston, TX, USA
| | - J M Valderas
- Health Services and Policy Research Group, University of Exeter, Exeter, UK.,NIHR Peninsula Collaboration for Leadership in Applied Health Research and Care, Exeter, UK
| | - A Leplege
- APEMAC, EA 4360, Paris Descartes University, Paris, France.,Département d'Histoire et de Philosophie des Sciences, Laboratoire SPHERE, UMR 7219, CNRS-Université Paris Diderot - Sorbonne Paris Cité, Paris, France
| | - M Rose
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, USA
| | - F Fischer
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
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Franken MD, de Hond A, Degeling K, Punt CJA, Koopman M, Uyl-de Groot CA, Versteegh MM, van Oijen MGH. Evaluation of the performance of algorithms mapping EORTC QLQ-C30 onto the EQ-5D index in a metastatic colorectal cancer cost-effectiveness model. Health Qual Life Outcomes 2020; 18:240. [PMID: 32690011 PMCID: PMC7370458 DOI: 10.1186/s12955-020-01481-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 07/07/2020] [Indexed: 02/06/2023] Open
Abstract
Background Cost-effectiveness models require quality of life utilities calculated from generic preference-based questionnaires, such as EQ-5D. We evaluated the performance of available algorithms for QLQ-C30 conversion into EQ-5D-3L based utilities in a metastatic colorectal cancer (mCRC) patient population and subsequently developed a mCRC specific algorithm. Influence of mapping on cost-effectiveness was evaluated. Methods Three available algorithms were compared with observed utilities from the CAIRO3 study. Six models were developed using 5-fold cross-validation: predicting EQ-5D-3L tariffs from QLQ-C30 functional scale scores, continuous QLQ-C30 scores or dummy levels with a random effects model (RE), a most likely probability method on EQ-5D-3L functional scale scores, a beta regression model on QLQ-C30 functional scale scores and a separate equations subgroup approach on QLQ-C30 functional scale scores. Performance was assessed, and algorithms were tested on incomplete QLQ-C30 questionnaires. Influence of utility mapping on incremental cost/QALY gained (ICER) was evaluated in an existing Dutch mCRC cost-effectiveness model. Results The available algorithms yielded mean utilities of 1: 0.87 ± sd:0.14,2: 0.81 ± 0.15 (both Dutch tariff) and 3: 0.81 ± sd:0.19. Algorithm 1 and 3 were significantly different from the mean observed utility (0.83 ± 0.17 with Dutch tariff, 0.80 ± 0.20 with U.K. tariff). All new models yielded predicted utilities drawing close to observed utilities; differences were not statistically significant. The existing algorithms resulted in an ICER difference of €10,140 less and €1765 more compared to the observed EQ-5D-3L based ICER (€168,048). The preferred newly developed algorithm was €5094 higher than the observed EQ-5D-3L based ICER. Disparity was explained by minimal diffences in incremental QALYs between models. Conclusion Available mapping algorithms sufficiently accurately predict utilities. With the commonly used statistical methods, we did not succeed in developping an improved mapping algorithm. Importantly, cost-effectiveness outcomes in this study were comparable to the original model outcomes between different mapping algorithms. Therefore, mapping can be an adequate solution for cost-effectiveness studies using either a previously designed and validated algorithm or an algorithm developed in this study.
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Affiliation(s)
- Mira D Franken
- University Medical Centre Utrecht, Utrecht University, Cancer Centre, Department of Medical Oncology, P.O. Box 85500, 3508, GA, Utrecht, the Netherlands.
| | - Anne de Hond
- IT Department, Leiden University Medical Center, Leiden, the Netherlands
| | - Koen Degeling
- Cancer Health Services Research Unit, Faculty of Medicine, Dentistry and Health Sciences, School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Cornelis J A Punt
- Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam University Medical Centers, location AMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Miriam Koopman
- University Medical Centre Utrecht, Utrecht University, Cancer Centre, Department of Medical Oncology, P.O. Box 85500, 3508, GA, Utrecht, the Netherlands
| | - Carin A Uyl-de Groot
- Institute for Medical Technology Assessment/institute of Health policy and Management, Erasmus University, Rotterdam, the Netherlands
| | - Matthijs M Versteegh
- Institute for Medical Technology Assessment/institute of Health policy and Management, Erasmus University, Rotterdam, the Netherlands
| | - Martijn G H van Oijen
- Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam University Medical Centers, location AMC, University of Amsterdam, Amsterdam, the Netherlands
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Meregaglia M, Whittal A, Nicod E, Drummond M. 'Mapping' Health State Utility Values from Non-preference-Based Measures: A Systematic Literature Review in Rare Diseases. PHARMACOECONOMICS 2020; 38:557-574. [PMID: 32152892 DOI: 10.1007/s40273-020-00897-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
BACKGROUND The use of patient-reported outcome measures (PROMs) to monitor the effects of disease and treatment on patient symptomatology and daily life is increasing in rare diseases (RDs) (i.e. those affecting less than one in 2000 people); however, these instruments seldom yield health state utility values (HSUVs) for cost-utility analyses. In such a context, 'mapping' allows HSUVs to be obtained by establishing a statistical relationship between a 'source' (e.g. a disease-specific PROM) and a 'target' preference-based measure [e.g. the EuroQol-5 Dimension (EQ-5D) tool]. OBJECTIVE This study aimed to systematically review all published studies using 'mapping' to derive HSUVs from non-preference-based measures in RDs, and identify any critical issues related to the main features of RDs, which are characterised by small, heterogeneous, and geographically dispersed patient populations. METHODS The following databases were searched during the first half of 2019 without time, study design, or language restrictions: MEDLINE (via PubMed), the School of Health and Related Research Health Utility Database (ScHARRHUD), and the Health Economics Research Centre (HERC) database of mapping studies (version 7.0). The keywords combined terms related to 'mapping' with Orphanet's list of RD indications (e.g. 'acromegaly') in addition to 'rare' and 'orphan'. 'Very rare' diseases (i.e. those with fewer than 1000 cases or families documented in the medical literature) were excluded from the searches. A predefined, pilot-tested extraction template (in Excel®) was used to collect structured information from the studies. RESULTS Two groups of studies were identified in the review. The first group (n = 19) developed novel mapping algorithms in 13 different RDs. As a target measure, the majority used EQ-5D, and the others used the Short-Form Six-Dimension (SF-6D) and 15D; most studies adopted ordinary least squares (OLS) regression. The second group of studies (n = 9) applied previously published algorithms in non-RDs to comparable RDs, mainly in the field of cancer. The critical issues relating to 'mapping' in RDs included the availability of very few studies, the relatively high number of cancer studies, and the absence of research in paediatric RDs. Moreover, the reviewed studies recruited small samples, showed a limited overlap between RD-specific and generic PROMs, and highlighted the presence of cultural and linguistic factors influencing results in multi-country studies. Lastly, the application of existing algorithms developed in non-RDs tended to produce inaccuracies at the bottom of the EQ-5D scale, due to the greater severity of RDs. CONCLUSIONS More research is encouraged to develop algorithms for a broader spectrum of RDs (including those affecting young children), improve mapping study quality, test the generalisability of algorithms developed in non-RDs (e.g. HIV) to rare variants or evolutions of the same condition (e.g. AIDS wasting syndrome), and verify the robustness of results when mapped HSUVs are used in cost-utility models.
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Affiliation(s)
- Michela Meregaglia
- Research Centre on Health and Social Care Management (CERGAS), Bocconi University, Milan, Italy.
| | - Amanda Whittal
- Research Centre on Health and Social Care Management (CERGAS), Bocconi University, Milan, Italy
| | - Elena Nicod
- Research Centre on Health and Social Care Management (CERGAS), Bocconi University, Milan, Italy
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Castro R, De Boni RB, Perazzo H, Grinsztejn B, Veloso VG, Ribeiro-Alves M. Development of algorithms to estimate EQ-5D and derive health utilities from WHOQOL-HIV Bref: a mapping study. Qual Life Res 2020; 29:2497-2508. [PMID: 32451983 DOI: 10.1007/s11136-020-02534-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/13/2020] [Indexed: 11/30/2022]
Abstract
PURPOSE This study aimed to develop and evaluate different families of applicable models available for utility mapping between World Health Organization Quality of Life for HIV-abbreviated version (WHOQOL-HIV Bref) and EQ-5D-3L and to propose an optimised algorithm to estimate health utilities of people living with HIV. METHODS Estimation dataset was collected between July 2014 and September 2016 in a cross-sectional study including 1526 people living with HIV/Aids (PLWH) under care at the Instituto Nacional de Infectologia Evandro Chagas-FIOCRUZ, in Brazil. Data of WHOQOL-HIV Bref and EQ-5D-3L questionnaires were collected. Fisher's exact tests were used for testing WHOQOL-HIV Bref response frequencies among groups of responses to each of the five EQ-5D-3L domains. Multiple correspondence analyses (MCA) were used to inspect the relationships between both instrument responses. Different families of applicable models available for utility mapping between WHOQOL-HIV Bref and EQ-5D-3L were adjusted for the prediction of disutility. RESULTS Candidate models' performances using mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE) were similarly good, which was evidenced by the overlapping of its 95% confidence intervals of the mean tenfold cross-validation or estimated generalisation errors. However, the Hurdle Logistic-Log-Normal model was better on average according to generalisation errors both in the prediction of Brazilian utility values (MAE = 0.1037, MSE = 0.0178, and RMSE = 0.1332) and for those of the UK (MAE = 0.1476, MSE = 0.0443, and RMSE = 0.2099). CONCLUSIONS Mapping EQ-5D-3L responses or deriving health utilities directly from WHOQOL-HIV Bref responses can be a valid alternative for settings with no preference-based health utility data.
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Affiliation(s)
- Rodolfo Castro
- Fundação Oswaldo Cruz, FIOCRUZ, Escola Nacional de Saúde Pública Sergio Arouca, Rua Leopoldo Bulhões, 1480, Manguinhos, Rio de Janeiro, RJ, ZIP 21041-210, Brazil. .,Universidade Federal do Estado do Rio de Janeiro, UNIRIO, Instituto de Saúde Coletiva, Rio de Janeiro, RJ, Brazil.
| | - Raquel B De Boni
- Fundação Oswaldo Cruz, FIOCRUZ, Instituto Nacional de Infectologia Evandro Chagas, Rio de Janeiro, RJ, Brazil
| | - Hugo Perazzo
- Fundação Oswaldo Cruz, FIOCRUZ, Instituto Nacional de Infectologia Evandro Chagas, Rio de Janeiro, RJ, Brazil
| | - Beatriz Grinsztejn
- Fundação Oswaldo Cruz, FIOCRUZ, Instituto Nacional de Infectologia Evandro Chagas, Rio de Janeiro, RJ, Brazil
| | - Valdiléa G Veloso
- Fundação Oswaldo Cruz, FIOCRUZ, Instituto Nacional de Infectologia Evandro Chagas, Rio de Janeiro, RJ, Brazil
| | - Marcelo Ribeiro-Alves
- Fundação Oswaldo Cruz, FIOCRUZ, Instituto Nacional de Infectologia Evandro Chagas, Rio de Janeiro, RJ, Brazil
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van den Hoven AT, Bons LR, Dykgraaf RHM, Dessens AB, Pastoor H, de Graaff LCG, Metselaar MR, Kneppers‐ Swets A, Kardys I, Mijnarends H, Zweerus F, Hazelzet JA, Utens EMWJ, van den Bosch AE, Roos‐Hesselink JW. A value-based healthcare approach: Health-related quality of life and psychosocial functioning in women with Turner syndrome. Clin Endocrinol (Oxf) 2020; 92:434-442. [PMID: 32003479 PMCID: PMC7216918 DOI: 10.1111/cen.14166] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 01/26/2020] [Accepted: 01/28/2020] [Indexed: 01/15/2023]
Abstract
OBJECTIVE As part of the value-based healthcare programme in our hospital, a set of patient-reported outcome measures was developed together with patients and implemented in the dedicated Turner Syndrome (TS) outpatient clinic. This study aims to investigate different aspects of health-related quality of life (HR-QoL) and psychosocial functioning in women with TS in order to establish new possible targets for therapy. DESIGN/PARTICIPANTS A comprehensive set of questionnaires (EQ-5D, PSS-10, CIS-20, Ferti-QoL, FSFI) was developed and used to capture different aspects of HR-QoL and psychosocial functioning in a large cohort of adult women with Turner syndrome. All consecutive women, ≥18 years, who visited the outpatient clinic of our tertiary centre were eligible for inclusion. RESULTS Of the eligible 201 women who were invited to participate, 177 women (age 34 ± 12 years, mean ± SD) completed at least one of the validated questionnaires (88%). Women with TS reported a lower health-related quality of life (EQ-5D: 0.857 vs 0.892, P = .003), perceived more stress (PSS-10:14.7 vs 13.3; P = .012) and experienced increased fatigue (CIS-20: P < .001) compared to the general Dutch population. A relationship between noncardiac comorbidities (eg diabetes, orthopaedic complaints) and HR-QoL was found (R = .508). CONCLUSIONS We showed that TS women suffer from impaired HR-QoL, more perceived stress and increased fatigue compared to healthy controls. A relationship between noncardiac comorbidities and HR-QoL was found. Especially perceived stress and increased fatigue can be considered targets for improvement of HR-QoL in TS women.
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Affiliation(s)
| | - Lidia R. Bons
- Department of CardiologyErasmus Medical CenterRotterdamThe Netherlands
| | | | - Arianne B. Dessens
- Department of Child and Adolescent Psychiatry/PsychologyErasmus Medical Center, University Medical Center RotterdamRotterdamThe Netherlands
| | - Hester Pastoor
- Department of GynecologyErasmus Medical CenterRotterdamThe Netherlands
| | | | - Mick R. Metselaar
- Department of OtolaryngologyErasmus Medical CenterRotterdamThe Netherlands
| | | | - Isabella Kardys
- Department of Clinical EpidemiologyErasmus Medical CenterRotterdamThe Netherlands
| | - Hester Mijnarends
- Department of CardiologyErasmus Medical CenterRotterdamThe Netherlands
| | - Frank Zweerus
- Department of Quality and Patient careErasmus Medical CenterRotterdamThe Netherlands
| | - Jan A. Hazelzet
- Department of Public HealthErasmus Medical CenterRotterdamThe Netherlands
| | - Elisabeth M. W. J. Utens
- Department of Child and Adolescent Psychiatry/PsychologyErasmus Medical Center, University Medical Center RotterdamRotterdamThe Netherlands
- Research Institute of Child Development and EducationUniversity of AmsterdamAmsterdamThe Netherlands
- Department of Child and Adolescent PsychiatryAcademic Center for Child Psychiatry the Bascule, Academic Medical CenterAmsterdamThe Netherlands
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Mitsakakis N, Bremner KE, Tomlinson G, Krahn M. Exploring the Benefits of Transformations in Health Utility Mapping. Med Decis Making 2020; 40:183-197. [PMID: 31928302 DOI: 10.1177/0272989x19896567] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background. Quality-of-life research and cost-effectiveness analyses frequently require data on health utility, a global measure of health-related quality of life. When utilities are unavailable, researchers have "mapped" descriptive instruments to utility instruments, using samples of responses to both instruments. Health utilities have an idiosyncratic distribution, with upper bound and probability mass at 1, left skewness, and kurtosis. Estimation of mean utility values conditional on covariates is of interest, particularly in health utility mapping applications. Traditional linear regression may be unsuitable because fundamental assumptions are violated. Complex statistical methods come with deficiencies that may outweigh their benefits. Aim. To investigate the benefits of transforming the health utility response variable before fitting a linear regression model. Methods. We compared log, logit, arcsin, and Box-Cox transformations with an untransformed model, using several measures of model accuracy. We made our evaluation by designing and conducting a simulation study and reanalyzing data from 2 published studies, which "mapped" a psychometric descriptive instrument to a utility instrument. Results. In the simulation study, log transformation with smearing estimator had in most cases the lowest bias but one of the highest variances, especially for estimating low utility values under small sample size. The untransformed model was outperformed by the transformed models. Findings were inconclusive for the analysis of real data, where arcsin gave the lowest error for one of the data sets, while the untransformed model had the best performance for the other. Conclusions. We identified the benefits of transformations and offered suggestions for future modeling of health utilities. However, the benefits were moderate and no single transformation appeared to be universally optimal, suggesting that selection requires examination on a case-by-case basis.
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Affiliation(s)
- Nicholas Mitsakakis
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.,Biostatistics Research Unit, Toronto General Hospital
| | - Karen E Bremner
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada.,Toronto Health Economics and Technology Assessment Collaborative
| | - George Tomlinson
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.,Biostatistics Research Unit, Toronto General Hospital
| | - Murray Krahn
- Toronto General Hospital Research Institute and Toronto Health Economics Technology Assessment Collaborative, University Health Network, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
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Lambe T, Frew E, Ives NJ, Woolley RL, Cummins C, Brettell EA, Barsoum EN, Webb NJA. Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales onto the Child Health Utility Index-9 Dimension (CHU-9D) Score for Economic Evaluation in Children. PHARMACOECONOMICS 2018; 36:451-465. [PMID: 29264866 DOI: 10.1007/s40273-017-0600-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
BACKGROUND The Paediatric Quality of Life Inventory (PedsQL™) questionnaire is a widely used, generic instrument designed for measuring health-related quality of life (HRQoL); however, it is not preference-based and therefore not suitable for cost-utility analysis. The Child Health Utility Index-9 Dimension (CHU-9D), however, is a preference-based instrument that has been primarily developed to support cost-utility analysis. OBJECTIVE This paper presents a method for estimating CHU-9D index scores from responses to the PedsQL™ using data from a randomised controlled trial of prednisolone therapy for treatment of childhood corticosteroid-sensitive nephrotic syndrome. METHODS HRQoL data were collected from children at randomisation, week 16, and months 12, 18, 24, 36 and 48. Observations on children aged 5 years and older were pooled across all data collection timepoints and were then randomised into an estimation (n = 279) and validation (n = 284) sample. A number of models were developed using the estimation data before internal validation. The best model was chosen using multi-stage selection criteria. RESULTS Most of the models developed accurately predicted the CHU-9D mean index score. The best performing model was a generalised linear model (mean absolute error = 0.0408; mean square error = 0.0035). The proportion of index scores deviating from the observed scores by < 0.03 was 53%. CONCLUSIONS The mapping algorithm provides an empirical tool for estimating CHU-9D index scores and for conducting cost-utility analyses within clinical studies that have only collected PedsQL™ data. It is valid for children aged 5 years or older. Caution should be exercised when using this with children younger than 5 years, older adolescents (> 13 years) or patient groups with particularly poor quality of life. ISRCTN REGISTRY NO 16645249.
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Affiliation(s)
- Tosin Lambe
- Health Economics Unit, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, UK
| | - Emma Frew
- Health Economics Unit, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, UK.
| | - Natalie J Ives
- Birmingham Clinical Trials Unit, University of Birmingham, Birmingham, UK
| | - Rebecca L Woolley
- Birmingham Clinical Trials Unit, University of Birmingham, Birmingham, UK
| | - Carole Cummins
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | | | - Emma N Barsoum
- Birmingham Clinical Trials Unit, University of Birmingham, Birmingham, UK
| | - Nicholas J A Webb
- Department of Paediatric Nephrology and NIHR Manchester Clinical Research Facility, Manchester Academic Health Science Centre, Royal Manchester Children's Hospital, Manchester, UK
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Khan I, Morris S, Pashayan N, Matata B, Bashir Z, Maguirre J. Comparing the mapping between EQ-5D-5L, EQ-5D-3L and the EORTC-QLQ-C30 in non-small cell lung cancer patients. Health Qual Life Outcomes 2016; 14:60. [PMID: 27072351 PMCID: PMC4830017 DOI: 10.1186/s12955-016-0455-1] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2015] [Accepted: 03/23/2016] [Indexed: 01/01/2023] Open
Abstract
Background Several mapping algorithms have been published with the EORTC-QLQ-C30 for estimating EQ-5D-3L utilities. However, none are available with EQ-5D-5L. Moreover, a comparison between mapping algorithms in the same set of patients has not been performed for these two instruments simultaneously. In this prospective data set of 100 non-small cell lung cancer (NSCLC) patients, we investigate three mapping algorithms using the EQ-5D-3L and EQ-5D-5L and compare their performance. Methods A prospective non-interventional cohort of 100 NSCLC patients were followed up for 12 months. EQ-5D-3L, EQ-5D-5L and EORTC-QLQ-C30 were assessed monthly. EQ-5D-5L was completed at least 1 week after EQ-5D-3L. A random effects linear regression model, a beta-binomial (BB) and a Limited Variable Dependent Mixture (LVDM) model were used to determine a mapping algorithm between EQ-5D-3L, EQ-5D-5L and QLQ-C30. Simulation and cross validation and other statistical measures were used to compare the performances of the algorithms. Results Mapping from the EQ-5D-5L was better: lower AIC, RMSE, MAE and higher R2 were reported with the EQ-5D-5L than with EQ-5D-3L regardless of the functional form of the algorithm. The BB model proved to be more useful for both instruments: for the EQ-5D-5L, AIC was –485, R2 of 75 %, MAE of 0.075 and RMSE was 0.092. This was –385, 69 %, 0.099 and 0.113 for EQ-5D-3L respectively. The mean observed vs. predicted utilities were 0.572 vs. 0.577 and 0.515 vs. 0.523 for EQ-5D-5L and EQ-5D-3L respectively, for OLS; for BB, these were 0.572 vs. 0.575 and 0.515 vs. 0.518 respectively and for LVDMM 0.532 vs 0.515 and 0.569 vs 0.572 respectively. Less over-prediction at poorer health states was observed with EQ-5D-5L. Conclusions The BB mapping algorithm is confirmed to offer a better fit for both EQ-5D-3L and EQ-5D-5L. The results confirm previous and more recent results on the use of BB type modelling approaches for mapping. It is recommended that in studies where EQ-5D utilities have not been collected, an EQ-5D-5L mapping algorithm is used.
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Affiliation(s)
- Iftekhar Khan
- Clinical Trials Unit & Department of Health Economics, University of Surrey, Guilford, UK. .,Department of Applied Health Research, University College London, London, UK.
| | - Steve Morris
- Department of Applied Health Research, University College London, London, UK
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London, UK
| | | | - Zahid Bashir
- University of Birmingham, Cancer School, Birmingham, UK
| | - Joe Maguirre
- Liverpool Heart and Chest Hospital, Liverpool, UK
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