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Published in: PharmacoEconomics 7/2014

01-07-2014 | Original Research Article

Mapping EQ-5D Utility Scores from the PedsQL™ Generic Core Scales

Authors: Kamran A. Khan, Stavros Petrou, Oliver Rivero-Arias, Stephen J. Walters, Spencer E. Boyle

Published in: PharmacoEconomics | Issue 7/2014

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Abstract

Purpose

The Pediatric Quality of Life Inventory™ (PedsQL™) General Core Scales (GCS) were designed to provide a modular approach to measuring health-related quality of life in healthy children, as well as those with acute and chronic health conditions, across the broadest, empirically feasible, age groups (2–18 years). Currently, it is not possible to estimate health utilities based on the PedsQL™ GCS, either directly or indirectly. This paper assesses different mapping methods for estimating EQ-5D health utilities from PedsQL™ GCS responses.

Methods

This study is based on data from a cross-sectional survey conducted in four secondary schools in England amongst children aged 11–15 years. We estimate models using both direct and response mapping approaches to predict EQ-5D health utilities and responses. The mean squared error (MSE) and mean absolute error (MAE) were used to assess the predictive accuracy of the models. The models were internally validated on an estimation dataset that included complete PedsQL™ GCS and EQ-5D scores for 559 respondents. Validation was also performed making use of separate data for 337 respondents.

Results

Ordinary least squares (OLS) models that used the PedsQL™ GCS subscale scores, their squared terms and interactions (with and without age and gender) to predict EQ-5D health utilities had the best prediction accuracy. In the external validation sample, the OLS model with age and gender had a MSE (MAE) of 0.036 (0.115) compared with a MSE (MAE) of 0.036 (0.114) for the OLS model without age and gender. However, both models generated higher prediction errors for children in poorer health states (EQ-5D utility score <0.6). The response mapping models encountered some estimation problems because of insufficient data for some of the response levels.

Conclusion

Our mapping algorithms provide an empirical basis for estimating health utilities in childhood when EQ-5D data are not available; they can be used to inform future economic evaluations of paediatric interventions. They are likely to be robust for populations comparable to our own (children aged 11–15 years in attendance at secondary school). The performance of these algorithms in childhood populations, which differ according to age or clinical characteristics to our own, remains to be evaluated.
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Literature
2.
go back to reference Culyer AJ. The dictionary of health economics. Cheltenham: Edward Elgar Publishing; 2005. Culyer AJ. The dictionary of health economics. Cheltenham: Edward Elgar Publishing; 2005.
3.
go back to reference National Institute for Health and Care Excellence, (NICE). Guide to the methods of technology appraisal. National Institute for Health and Clinical Excellence (NICE); 2013. National Institute for Health and Care Excellence, (NICE). Guide to the methods of technology appraisal. National Institute for Health and Clinical Excellence (NICE); 2013.
4.
go back to reference Petrou S. Methodological issues raised by preference-based approaches to measuring the health status of children. Health Econ. 2003;12(8):697–702.PubMedCrossRef Petrou S. Methodological issues raised by preference-based approaches to measuring the health status of children. Health Econ. 2003;12(8):697–702.PubMedCrossRef
5.
go back to reference Tilford JM, Payakachat N, Kovacs E, Pyne JM, Brouwer W, Nick TG, et al. Preference-based health-related quality-of-life outcomes in children with autism spectrum disorders. Pharmacoeconomics. 2012;30(8):661–79.PubMedCentralPubMedCrossRef Tilford JM, Payakachat N, Kovacs E, Pyne JM, Brouwer W, Nick TG, et al. Preference-based health-related quality-of-life outcomes in children with autism spectrum disorders. Pharmacoeconomics. 2012;30(8):661–79.PubMedCentralPubMedCrossRef
6.
go back to reference Ungar WJ, Boydell K, Dell S, Feldman BM, Marshall D, Willan A, et al. A parent-child dyad approach to the assessment of health status and health-related quality of life in children with asthma. Pharmacoeconomics. 2012;30(8):697–712.PubMedCrossRef Ungar WJ, Boydell K, Dell S, Feldman BM, Marshall D, Willan A, et al. A parent-child dyad approach to the assessment of health status and health-related quality of life in children with asthma. Pharmacoeconomics. 2012;30(8):697–712.PubMedCrossRef
7.
go back to reference Griebsch I, Coast J, Brown J. Quality-adjusted life-years lack quality in pediatric care: a critical review of published cost-utility studies in child health. Pediatrics. 2005;115(5):e600–14.PubMedCrossRef Griebsch I, Coast J, Brown J. Quality-adjusted life-years lack quality in pediatric care: a critical review of published cost-utility studies in child health. Pediatrics. 2005;115(5):e600–14.PubMedCrossRef
8.
go back to reference Eiser C, Morse R. Quality-of-life measures in chronic diseases of childhood. Health Technol Assess (Winchester, England). 2001;5(4):1. Eiser C, Morse R. Quality-of-life measures in chronic diseases of childhood. Health Technol Assess (Winchester, England). 2001;5(4):1.
9.
go back to reference Longworth L, Bojke L, Tosh J, Sculpher M. MRC-NICE scoping project: identifying the National Institute for Health and Clinical Excellence’s methodological research priorities and an initial set of priorities. Centre for Health Economics, University of York Working Papers; 2009. Longworth L, Bojke L, Tosh J, Sculpher M. MRC-NICE scoping project: identifying the National Institute for Health and Clinical Excellence’s methodological research priorities and an initial set of priorities. Centre for Health Economics, University of York Working Papers; 2009.
10.
go back to reference Stevens K. Valuation of the child health utility index 9D (CHU9D). 2010. Stevens K. Valuation of the child health utility index 9D (CHU9D). 2010.
11.
go back to reference Longworth L, Rowen D. NICE DSU Technical Support Document 10: the use of mapping methods to estimate health state utility values; 2011. Longworth L, Rowen D. NICE DSU Technical Support Document 10: the use of mapping methods to estimate health state utility values; 2011.
12.
go back to reference Boyle SE, Jones GL, Walters SJ. Physical activity, quality of life, weight status and diet in adolescents. Qual Life Res. 2010;19(7):943–54.PubMedCrossRef Boyle SE, Jones GL, Walters SJ. Physical activity, quality of life, weight status and diet in adolescents. Qual Life Res. 2010;19(7):943–54.PubMedCrossRef
13.
go back to reference The EQG. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(3):199–208.CrossRef The EQG. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(3):199–208.CrossRef
14.
go back to reference Räsänen P, Roine E, Sintonen H, Semberg-Konttinen V, Ryynänen OP, Roine R. Use of quality-adjusted life years for the estimation of effectiveness of health care: a systematic literature review. Int J Technol Assess Health Care. 2006;22(02):235–41.PubMedCrossRef Räsänen P, Roine E, Sintonen H, Semberg-Konttinen V, Ryynänen OP, Roine R. Use of quality-adjusted life years for the estimation of effectiveness of health care: a systematic literature review. Int J Technol Assess Health Care. 2006;22(02):235–41.PubMedCrossRef
15.
go back to reference Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35(11):1095–108. Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35(11):1095–108.
16.
go back to reference Szende A, Oppe M, Devlin N. EQ-5D value sets: inventory, comparative review and user guide, vol. 2. Berlin: Springer; 2006. Szende A, Oppe M, Devlin N. EQ-5D value sets: inventory, comparative review and user guide, vol. 2. Berlin: Springer; 2006.
17.
go back to reference Eidt-Koch D, Mittendorf T, Greiner W. Cross-sectional validity of the EQ-5D-Y as a generic health outcome instrument in children and adolescents with cystic fibrosis in Germany. BMC Pediatr. 2009;9(1):55.PubMedCentralPubMedCrossRef Eidt-Koch D, Mittendorf T, Greiner W. Cross-sectional validity of the EQ-5D-Y as a generic health outcome instrument in children and adolescents with cystic fibrosis in Germany. BMC Pediatr. 2009;9(1):55.PubMedCentralPubMedCrossRef
18.
go back to reference Wille N, Ravens-Sieberer U. Age-appropriateness of the EQ-5D adult and child-friendly version: testing the feasibility, reliability and validity in children and adolescents. In: 23rd Scientific Plenary Meeting of the EuroQol Group in Barcelona, Spain, September 14, vol 16. 2006. p. 217–9. Wille N, Ravens-Sieberer U. Age-appropriateness of the EQ-5D adult and child-friendly version: testing the feasibility, reliability and validity in children and adolescents. In: 23rd Scientific Plenary Meeting of the EuroQol Group in Barcelona, Spain, September 14, vol 16. 2006. p. 217–9.
19.
go back to reference Varni JW, Burwinkle TM, Seid M. The PedsQL TM 4.0 as a school population health measure: feasibility, reliability, and validity. Qual Life Res. 2006;15(2):203–15.PubMedCrossRef Varni JW, Burwinkle TM, Seid M. The PedsQL TM 4.0 as a school population health measure: feasibility, reliability, and validity. Qual Life Res. 2006;15(2):203–15.PubMedCrossRef
20.
go back to reference McCullagh P, Nelder JA. Generalized linear models, vol. 37. London: Chapman & Hall/CRC; 1989.CrossRef McCullagh P, Nelder JA. Generalized linear models, vol. 37. London: Chapman & Hall/CRC; 1989.CrossRef
21.
go back to reference Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461–94.PubMedCrossRef Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461–94.PubMedCrossRef
22.
go back to reference Pearson E, Please N. Relation between the shape of population distribution and the robustness of four simple test statistics. Biometrika. 1975;62(2):223–41.CrossRef Pearson E, Please N. Relation between the shape of population distribution and the robustness of four simple test statistics. Biometrika. 1975;62(2):223–41.CrossRef
23.
go back to reference Pregibon D. Goodness of link tests for generalized linear models. Appl Stat. 1980;29:15–23. Pregibon D. Goodness of link tests for generalized linear models. Appl Stat. 1980;29:15–23.
24.
go back to reference Hosmer D. In: Lemeshow S (ed). Applied logistic regression. New York: Wiley; 1989. p. 8–20. Hosmer D. In: Lemeshow S (ed). Applied logistic regression. New York: Wiley; 1989. p. 8–20.
25.
go back to reference Glick HA, Doshi JA, Sonnad SS, Polsky D. Economic evaluation in clinical trials. USA: Oxford University Press; 2007. Glick HA, Doshi JA, Sonnad SS, Polsky D. Economic evaluation in clinical trials. USA: Oxford University Press; 2007.
26.
go back to reference Powell JL. Least absolute deviations estimation for the censored regression model. J Econometr. 1984;25(3):303–25.CrossRef Powell JL. Least absolute deviations estimation for the censored regression model. J Econometr. 1984;25(3):303–25.CrossRef
27.
go back to reference Chay KY, Powell JL. Semiparametric censored regression models. J Econ Perspect. 2001;15(4):29–42.CrossRef Chay KY, Powell JL. Semiparametric censored regression models. J Econ Perspect. 2001;15(4):29–42.CrossRef
28.
go back to reference Tobin J. Estimation of relationships for limited dependent variables. Econometrica: J Econ Soc. 1958;26(1):24–36. Tobin J. Estimation of relationships for limited dependent variables. Econometrica: J Econ Soc. 1958;26(1):24–36.
29.
30.
go back to reference Pullenayegum EM, Tarride J-E, Xie F, Goeree R, Gerstein HC, O’Reilly D. Analysis of health utility data when some subjects attain the upper bound of 1: are Tobit and CLAD models appropriate? Val Health. 2010;13(4):487–94.CrossRef Pullenayegum EM, Tarride J-E, Xie F, Goeree R, Gerstein HC, O’Reilly D. Analysis of health utility data when some subjects attain the upper bound of 1: are Tobit and CLAD models appropriate? Val Health. 2010;13(4):487–94.CrossRef
31.
go back to reference Pullenayegum EM, Tarride J-E, Xie F, O’Reilly D. Calculating utility decrements associated with an adverse event marginal Tobit and CLAD coefficients should be used with caution. Med Decis Making. 2011;31(6):790–9.PubMedCrossRef Pullenayegum EM, Tarride J-E, Xie F, O’Reilly D. Calculating utility decrements associated with an adverse event marginal Tobit and CLAD coefficients should be used with caution. Med Decis Making. 2011;31(6):790–9.PubMedCrossRef
32.
go back to reference Papke LE, Wooldridge JM. Econometric methods for fractional response variables with an application to 401 (K) plan participation rates. J Appl Econ. 1996;11(6):619–32. doi:10.2307/2285155.CrossRef Papke LE, Wooldridge JM. Econometric methods for fractional response variables with an application to 401 (K) plan participation rates. J Appl Econ. 1996;11(6):619–32. doi:10.​2307/​2285155.CrossRef
33.
go back to reference Levy A, Christensen T, Johnson J. Utility values for symptomatic non-severe hypoglycaemia elicited from persons with and without diabetes in Canada and the United Kingdom. Health Qual Life Outcomes. 2008;6(1):73.PubMedCentralPubMedCrossRef Levy A, Christensen T, Johnson J. Utility values for symptomatic non-severe hypoglycaemia elicited from persons with and without diabetes in Canada and the United Kingdom. Health Qual Life Outcomes. 2008;6(1):73.PubMedCentralPubMedCrossRef
34.
go back to reference Dakin H, Gray A, Murray D. Mapping analyses to estimate EQ-5D utilities and responses based on Oxford Knee Score. Qual Life Res. 2012;1–12. Dakin H, Gray A, Murray D. Mapping analyses to estimate EQ-5D utilities and responses based on Oxford Knee Score. Qual Life Res. 2012;1–12.
36.
go back to reference Le QAPP, Doctor JNP. Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: an empirical analysis converting SF-12 into EQ-5D utility index in a National US sample. Med Care. 2011;49(5):451–60.PubMedCrossRef Le QAPP, Doctor JNP. Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: an empirical analysis converting SF-12 into EQ-5D utility index in a National US sample. Med Care. 2011;49(5):451–60.PubMedCrossRef
38.
40.
go back to reference Cremeens J, Eiser C, Blades M. Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory™ 4.0 (PedsQL™) Generic Core Scales. Health Qual Life Outcomes. 2006;4(1):58.PubMedCentralPubMedCrossRef Cremeens J, Eiser C, Blades M. Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory™ 4.0 (PedsQL™) Generic Core Scales. Health Qual Life Outcomes. 2006;4(1):58.PubMedCentralPubMedCrossRef
41.
go back to reference Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.PubMedCentralPubMedCrossRef Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.PubMedCentralPubMedCrossRef
42.
go back to reference Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2012. 1–11. doi:10.1007/s11136-012-0322-4. Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2012. 1–11. doi:10.​1007/​s11136-012-0322-4.
45.
go back to reference van Hout B, Janssen M, Feng Y-S, Kohlmann T, Busschbach J, Golicki D, et al. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Val Health. 2012;15(5):708–15.CrossRef van Hout B, Janssen M, Feng Y-S, Kohlmann T, Busschbach J, Golicki D, et al. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Val Health. 2012;15(5):708–15.CrossRef
Metadata
Title
Mapping EQ-5D Utility Scores from the PedsQL™ Generic Core Scales
Authors
Kamran A. Khan
Stavros Petrou
Oliver Rivero-Arias
Stephen J. Walters
Spencer E. Boyle
Publication date
01-07-2014
Publisher
Springer International Publishing
Published in
PharmacoEconomics / Issue 7/2014
Print ISSN: 1170-7690
Electronic ISSN: 1179-2027
DOI
https://doi.org/10.1007/s40273-014-0153-y

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