Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15

Brazier J, Ratcliffe J, Tsuchiya A, Salomon J. Measuring and valuing health benefits for economic evaluation. Oxford: Oxford University Press; 2007.

Fontaine KR, Barofsky I. Obesity and health-related quality of life. Obes Rev. 2001;2(3):173–82.

Drummond MF, Sculpher MJ, Torrance GW, O’Brien BJ, Stoddart GL. Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press; 2005.

Harris A, Bulfone L. Getting value for money: “The Australian experience”. In: International M-H, Jost T, editors. Health care coverage determinations: an international comparative study. Maidenhead: Open University Press; 2004.

National Institute for Health and Care Excellence. Guide to the methods of technology appraisal. National Health Service. 2010.

Varni JW, Burwinkle TM, Seid M, Skarr D. The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity. Ambul Pediatr. 2003;3(6):329–41.

Brazier JE, Yang Y, Tsuchiya A, Rowen DL. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ. 2010;11(2):215–25. doi: 10.1007/s10198-009-0168-z .

Chen G, Stevens K, Rowen D, Ratcliffe J. From KIDSCREEN-10 to CHU9D: creating a unique mapping algorithm for application in economic evaluation. Health Qual Life Outcomes. 2014;12:134. doi: 10.1186/s12955-014-0134-z .

Furber G, Segal L, Leach M, Cocks J. Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values. Qual Life Res. 2014;23(2):403–11. doi: 10.1007/s11136-013-0494-6 .

Khan KA, Petrou S, Rivero-Arias O, Walters SJ, Boyle SE. Mapping EQ-5D utility scores from the PedsQL generic core scales. Pharmacoeconomics. 2014;32(7):693–706. doi: 10.1007/s40273-014-0153-y .

Payakachat N, Tilford JM, Kuhlthau KA, van Exel NJ, Kovacs E, Bellando J, et al. Predicting health utilities for children with autism spectrum disorders. Autism Res. 2014;7(6):649–63. doi: 10.1002/aur.1409 .

Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations. Med Care. 2001;39(8):800–12.

Stevens K. Assessing the performance of a new generic measure of health-related quality of life for children and refining it for use in health state valuation. Appl Health Econ Health Policy. 2011;9(3):157–69. doi: 10.2165/11587350-000000000-00000 .

Stevens K. Valuation of the Child Health Utility 9D Index. Pharmacoeconomics. 2012;30(8):729–47. doi: 10.2165/11599120-000000000-00000 .

Ratcliffe J, Flynn T, Terlich F, Stevens K, Brazier J, Sawyer M. Developing adolescent-specific health state values for economic evaluation: an application of profile case best-worst scaling to the Child Health Utility 9D. Pharmacoeconomics. 2012;30(8):713–27. doi: 10.2165/11597900-000000000-00000 .

Ratcliffe J, Huynh E, Chen G, Stevens K, Swait J, Brazier J, et al. Valuing the child health utility 9D: using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm. Soc Sci Med. 2016;157:48–59. doi: 10.1016/j.socscimed.2016.03.042 .

Boyce W, Torsheim T, Currie C, Zambon A. The Family Affluence Scale as a measure of national wealth: validation of an adolescent self-report measure. Soc Indic Res. 2006;78(3):473–87.

Stevens K, Ratcliffe J. Measuring and valuing health benefits for economic evaluation in adolescence: an assessment of the practicality and validity of the child health utility 9D in the Australian adolescent population. Value Health. 2012;15(8):1092–9. doi: 10.1016/j.jval.2012.07.011 .

Ratcliffe J, Stevens K, Flynn T, Brazier J, Sawyer M. An assessment of the construct validity of the CHU9D in the Australian adolescent general population. Qual Life Res. 2012;21(4):717–25. doi: 10.1007/s11136-011-9971-y .

Chen G, Flynn T, Stevens K, Brazier J, Huynh E, Sawyer M, et al. Assessing the health-related quality of life of Australian adolescents: an empirical comparison of the child health utility 9D and EQ-5D-Y instruments. Value Health. 2015;18(4):432–8. doi: 10.1016/j.jval.2015.02.014 .

Petrou S, Rivero-Arias O, Dakin H, Longworth L, Oppe M, Froud R, et al. The MAPS reporting statement for studies mapping onto generic preference-based outcome measures: explanation and elaboration. PharmacoEconomics. 2015;33(10):993–1011. doi: 10.1007/s40273-015-0312-9 .

Boers M, Verhoeven AC, Markusse HM, van de Laar MA, Westhovens R, van Denderen JC, et al. Randomised comparison of combined step-down prednisolone, methotrexate and sulphasalazine with sulphasalazine alone in early rheumatoid arthritis. Lancet. 1997;350(9074):309–18. doi: 10.1016/s0140-6736(97)01300-7 .

International CLL-IPI Working Group. An international prognostic index for patients with chronic lymphocytic leukaemia (CLL-IPI): a meta-analysis of individual patient data. Lancet Oncol. 2016;17(6):779–90. doi: 10.1016/s1470-2045(16)30029-8 .

Chappell LC, Seed PT, Myers J, Taylor RS, Kenny LC, Dekker GA, et al. Exploration and confirmation of factors associated with uncomplicated pregnancy in nulliparous women: prospective cohort study. Bmj. 2013;347:f6398. doi: 10.1136/bmj.f6398 .

Kuk D, Varadhan R. Model selection in competing risks regression. Stat Med. 2013;32(18):3077–88. doi: 10.1002/sim.5762 .

Allen LA, Yager JE, Funk MJ, Levy WC, Tulsky JA, Bowers MT, et al. Discordance between patient-predicted and model-predicted life expectancy among ambulatory heart failure patients. JAMA J Am Med Assoc. 2008;299(21):2533–42. doi: 10.1001/jama.299.21.2533 .

StataCorp. Stata Statistical Software: Release 14. 2015.

Dakin H. Review of studies mapping from quality of life or clinical measures to EQ-5D: an online database. Health Qual Life Outcomes. 2013;11:151. doi: 10.1186/1477-7525-11-151 .

Longworth L, Rowen D. Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value Health. 2013;16(1):202–10. doi: 10.1016/j.jval.2012.10.010 .

Hernandez Alava M, Wailoo A, Wolfe F, Michaud K. A comparison of direct and indirect methods for the estimation of health utilities from clinical outcomes. Med Decis Making. 2014;34(7):919–30. doi: 10.1177/0272989x13500720 .

Huang IC, Frangakis C, Atkinson MJ, Willke RJ, Leite WL, Vogel WB, et al. Addressing ceiling effects in health status measures: a comparison of techniques applied to measures for people with HIV disease. Health Serv Res. 2008;43(1 Pt 1):327–39. doi: 10.1111/j.1475-6773.2007.00745.x .

Payakachat N, Summers KH, Pleil AM, Murawski MM, Thomas J 3rd, Jennings K, et al. Predicting EQ-5D utility scores from the 25-item National Eye Institute Vision Function Questionnaire (NEI-VFQ 25) in patients with age-related macular degeneration. Qual Life Res. 2009;18(7):801–13. doi: 10.1007/s11136-009-9499-6 .

Gujarati DN. Basic econometrics. 4th ed. Boston. Mass. London: McGraw-Hill; 2003.

Chen G, Khan MA, Iezzi A, Ratcliffe J, Richardson J. Mapping between 6 multiattribute utility instruments. Med Decis Making. 2016;36(2):160–75. doi: 10.1177/0272989x15578127 .

McCullagh P, Nelder JA. Generalized linear models. 2nd ed. London: Chapman & Hall; 1989.

Royston P, Sauerbrei W. Multivariable modeling with cubic regression splines: a principled approach. Stata J. 2007;7(1):45–70.

Briggs A, Sculpher M, Claxton K. Decision modelling for health economic evaluation. Oxford: Oxford University Press; 2006.

Ospina R, Ferrari SL. A general class of zero-or-one inflated beta regression models. Comput Stat Data Anal. 2012;56(6):1609–23.

Basu A, Manca A. Regression estimators for generic health-related quality of life and quality-adjusted life years. Med Decis Making. 2012;32(1):56–69. doi: 10.1177/0272989x11416988 .

Khan I, Morris S. A non-linear beta-binomial regression model for mapping EORTC QLQ-C30 to the EQ-5D-3L in lung cancer patients: a comparison with existing approaches. Health Qual Life Outcomes. 2014;12(1):1–16. doi: 10.1186/s12955-014-0163-7 .

Everitt B, Hand D. Finite mixture distributions. London and New York: Chapman and Hall; 1981.

McLachlan G, Peel D. Finite mixture models. New York: Wiley; 2000.

Kent S, Gray A, Schlackow I, Jenkinson C, McIntosh E. Mapping from the Parkinson’s disease questionnaire PDQ-39 to the generic EuroQol EQ-5D-3L: the value of mixture models. Med Decis Making. 2015;35(7):902–11. doi: 10.1177/0272989x15584921 .

Deb P. Finite mixture models. 2008. http://repec.org/snasug08/deb_fmm_slides.pdf . Accessed 11 Sept 2016.

Gray AM, Rivero-Arias O, Clarke PM. Estimating the association between SF-12 responses and EQ-5D utility values by response mapping. Med Decis Making. 2006;26(1):18–29. doi: 10.1177/0272989x05284108 .

Le QA, Doctor JN. 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. doi: 10.1097/MLR.0b013e318207e9a8 .

Koch GG. Intraclass Correlation Coefficient.  Encyclopedia of Statistical Sciences. John Wiley & Sons, Inc.; 2004. doi: 10.1002/0471667196.ess1275

Hyndman RJ, Koehler AB. Another look at measures of forecast accuracy. Int J Forecast. 2006;22(4):679–88. doi: 10.1016/j.ijforecast.2006.03.001 .

Shcherbakov MV, Brebels B, Shcherbakova NL, Tyukov AP, Janovsky TA, Kamae VA. A survey of forecast error measures. World Appl Sci J 24 (Information Technologies in Modern Industry, Education and Society). 2013;24(24):171–6.

Wong CK, Lam CL, Rowen D, McGhee SM, Ma KP, Law WL, et al. Mapping the functional assessment of cancer therapy-general or -colorectal to SF-6D in Chinese patients with colorectal neoplasm. Value Health. 2012;15(3):495–503. doi: 10.1016/j.jval.2011.12.009 .

Wu EQ, Mulani P, Farrell MH, Sleep D. Mapping FACT-P and EORTC QLQ-C30 to patient health status measured by EQ-5D in metastatic hormone-refractory prostate cancer patients. Value Health. 2007;10(5):408–14. doi: 10.1111/j.1524-4733.2007.00195.x .

Petrou S, Rivero-Arias O, Dakin H, Longworth L, Oppe M, Froud R, et al. Preferred reporting items for studies mapping onto preference-based outcome measures: the MAPS statement. Qual Life Res. 2016;25(2):275–81. doi: 10.1007/s11136-015-1082-8 .

Chuang LH, Whitehead SJ. Mapping for economic evaluation. Br Med Bull. 2012;101:1–15. doi: 10.1093/bmb/ldr049 .

Pinedo-Villanueva RA, Turner D, Judge A, Raftery JP, Arden NK. Mapping the Oxford hip score onto the EQ-5D utility index. Qual Life Res. 2013;22(3):665–75. doi: 10.1007/s11136-012-0174-y .

Tsuchiya A, Brazier JE, McColl E, Parkin D. Deriving preference-based single indices from non-preference based condition-specific instruments: Converting AQLQ into EQ5D indices Sheffield Health Economics Group Discussion Paper Series. 2002; Ref 02/1.

Brennan DS, Spencer AJ. Mapping oral health related quality of life to generic health state values. BMC Health Serv Res. 2006;6:96. doi: 10.1186/1472-6963-6-96 .

Sauerland S, Weiner S, Dolezalova K, Angrisani L, Noguera CM, Garcia-Caballero M, et al. Mapping utility scores from a disease-specific quality-of-life measure in bariatric surgery patients. Value Health. 2009;12(2):364–70. doi: 10.1111/j.1524-4733.2008.00442.x .

Bansback N, Marra C, Tsuchiya A, Anis A, Guh D, Hammond T, et al. Using the health assessment questionnaire to estimate preference-based single indices in patients with rheumatoid arthritis. Arthritis Rheum. 2007;57(6):963–71. doi: 10.1002/art.22885 .

Australian Demographic Statistics, 2015, ‘Table 8: Estimated resident population, by age and sex—at 30 June 2015’, data cube: Excel spreadsheet, cat. no. 31010do002_201512 [database on the Internet]. Australian Bureau of Statistics 2015. Available from: http://www.abs.gov.au/AUSSTATS/[email protected]/DetailsPage/3101.0Dec%202015?OpenDocument . Accessed: 6 Sept 2016.

Australian Institute of Health and Welfare. Young Australians: their health and wellbeing 2011 (Cat. no. PHE 140). Canberra, Australia: Australian Institute of Health and Welfare; 2011.

Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461–94