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A systematic review of utility values in children with cerebral palsy

Quality of Life Research volume 28, pages 1–12 (2019)Cite this article

Abstract

Purpose

Project aims include the following: (i) to identify reported utility values associated with CP in children aged ≤ 18 years; (ii) to explore utility value elicitation techniques in published studies; and (iii) to examine performance of the measures and/or elicitation approaches.

Methods

Peer-reviewed studies published prior to March 2017 were identified from six electronic databases. Construct validity, convergent validity, responsiveness, and reliability of instruments were assessed.

Results

Five studies met the inclusion criteria. Utility values of hypothetical general CP states obtained from a general population of parents ranged from 0.55 to 0.88 using time trade off (TTO) and 0.60–0.87 using standard gamble (SG) techniques. Utility values reported by clinicians of three hypothetical spastic quadriplegic CP states, using the Health Utility Index Mark 2 (HUI-2), ranged from 0.40 to 0.13. Other sources of utilities identified were based on both proxy and child ratings using Health Utility Index Mark 3 (HUI-3) (values ranged from − 0.013 to 0.84 depending on the valuation source) and the Assessment of Quality of Life 4 Dimension instrument, with values ranging from 0.01 to 0.58. Construct validity of the HUI-3 varied from moderate to strong, whereas mixed results were found for convergent validity. Responsiveness and reliability were not reported.

Conclusion

There was substantial variation in reported utilities. Indirect techniques (i.e. via multi-attribute utility instruments) were more frequently used than direct techniques (e.g. TTO, SG). Further research is required to improve the robustness of utility valuation of health-related quality of life in children with CP for use in economic evaluation.

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References

  1. Rosenbaum, P., Paneth, N., Leviton, A., Goldstein, M., & Bax, M. (2007). A report: The definition and classification of cerebral Palsy. Developmental Medicine & Child Neurology, 49(Suppl s2), 9.

    Google Scholar 

  2. Novak, I., Hines, M., Goldsmith, S., & Barclay, R. (2012). Clinical prognostic messages from a systematic review on cerebral palsy. Pediatrics, 130(5), e1285–e1312.

    Article  PubMed  Google Scholar 

  3. Reid, S. M., McCutcheon, J., Reddihough, D. S., & Johnson, H. (2012). Prevalence and predictors of drooling in 7- to 14-year-old children with cerebral palsy: A population study. Developmental Medicine & Child Neurology, 54(11), 1032–1036.

    Article  Google Scholar 

  4. Australian Cerebral Palsy Register Group. (2017). Australian Cerebral Palsy Register Report 2016, Australian Cerebral Palsy Register.

  5. Cerebral Palsy Alliance. (2013) Key facts and statistics. Retrieved from https://www.cerebralpalsy.org.au/what-is-cerebral-palsy/facts-about-cerebral-palsy.

  6. Bourke-Taylor, H., Howie, L., & Law, M. (2011). Barriers to maternal workforce participation and relationship between paid work and health. Journal of Intellectual Disability Research, 55, 511–520.

    Article  CAS  PubMed  Google Scholar 

  7. Access Economics Pty. (2008). The economic impact of cerebral Palsy in Australia in 2007. Cerebral Palsy Australia.

  8. Drummond, M. F., Sculpher, M. J., Claxton, K., Stoddart, G. L., & Torrance, G. W. (2015). Methods for the economic evaluation of health care programmes (4th ed.). Oxford: Oxford University Press.

    Google Scholar 

  9. Brazier, J., Ratcliffe, J., Salomon, J. A., & Tsuchiya, A. (2017). Measuring and valuing health benefits for economic evaluation (2nd ed.). Oxford: Oxford University Press.

    Google Scholar 

  10. Brazier, J., Ratcliffe, J., Tsuchiya, A., & Solomon, J. A. (2017). Measuring and valuing health benefits for economic evaluation. New York: Oxford University Press.

    Google Scholar 

  11. Arnold, D., Girling, A., Stevens, A., & Lilford, R. (2009) Comparison of direct and indirect methods of estimating health state utilities for resource allocation: Review and empirical analysis. BMJ. https://doi.org/10.1136/bmj.b2688.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Chen, G., & Ratcliffe, J. (2015). A review of the development and application of generic multi-attribute utility instruments for paediatric populations. Pharmacoeconomics, 33(10), 1013–1028.

    Article  PubMed  Google Scholar 

  13. Seiber, W. J., Groessl, E. J., David, K. M., & Ganiats, T. G., Kaplan, R. M. (2008). Quality of Well Being Self-Administered (QWB-SA) Scale user’s manual. Sandiego: Health services Research Center, University of California.

    Google Scholar 

  14. Torrance, G., Feeny, D., Furlong, W., Barr, R., Zhang, Y., & Wang, Q. (1996). Multiattribute utility function for a comprehensive health status classification system: Health Utilities Index Mark 2. Medical Care, 34, 702–722.

    Article  CAS  PubMed  Google Scholar 

  15. Feeny, D., Furlong, W., & Torrance, G. (2002). Multi-attribute and single-attribute utility functions for Health utilities Index Mark 3 system. Medical Care, 40(2), 113–128.

    Article  PubMed  Google Scholar 

  16. Apajasalo, M., Sintonen, H., holmberg, C., Sinkkonen, J., Aalberg, V., Pihko, H., et al. (1996). Quality of life in early adolescence; a sixteen-dimensional health-related measure (16D). Quality of Life Research, 5(2), 205–211.

    Article  CAS  PubMed  Google Scholar 

  17. Apajassalo, M., Rautonen, J., holmberg, C., Sinkkonen, J., Aalberg, V., Pihko, H., et al. (1996). Quality of life in pre-adolescence: A 17-dimensional ehalth-related measure (17D). Quality of Life Research, 5(6), 532–538.

    Article  Google Scholar 

  18. Moodie, M., Richardson, J., Rankin, B., & Iezzi, A., Sinha, K. (2010). Prdicting time trade-off health state valuations of adolescents in four Pacific countries using the Assessment of Quality-of-Life (AQoL-6D) instrument. Value Health, 13(8), 1014–1027.

    Article  PubMed  Google Scholar 

  19. Stevens, K. (2009). Developing a descriptive system for a new preference-based measure of health-related quality of life for children. Quality of Life Research, 18, 1105–1113.

    Article  PubMed  Google Scholar 

  20. Wille, N., Badia, X., Bonsel, G., et al. (2010). Development of the EQ-5D-Y: A child friendly version of the EQ-5D. Quality of Life Research, 19(6), 875–886.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Beusterien, K., Yeung, J.-E., Pang, F., & Brazier, J. (2012). Development of the multi-attribute Adolescent Health Utility Measure (AHUM). Health and Quality of Life Outcomes, 10, 102.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Tosh, J., Brazier, J., Evans, P., & Longworth, L. (2012). A review of generic preference-based measures of health-related quality of life in visual disorders. Value In Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research, 15, 118–127.

    Article  Google Scholar 

  23. Longworth, L., Yang, Y., Young, T., Mulhern, B., Hernandez Alava, M., Mukuria, C., et al. (2014). Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: A systematic reveiw, statistical modelling and survey. Health Technology Assessment (Winchester, England), 18(9), 1–224

    Google Scholar 

  24. Papaioannou, D., Brazier, J., & Parry, G. (2011). How valid and responsive are generic health status measures, such as the EQ-5D and SF-36, in schizophrenia? A systematic review. Value Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research, 14, 907–920.

    Article  Google Scholar 

  25. Selai, C. E., Trimble, M. R., Price, M. J., & Remak, E. (2005). Evaluation of health status in epilepsy using the EQ-5D questionnaire: A prospective, observational, 6-month study of adjunctive therapy with anti-epileptic drugs. Current Medical Research and Opinion, 21(5), 733–739.

    Article  CAS  PubMed  Google Scholar 

  26. Neumann, P. J. (2005). Health utilities in Alzheimer’s disease and implications for cost-effectiveness analysis. Pharmacoeconomics, 23(6), 537–541.

    Article  PubMed  Google Scholar 

  27. Rowen, D., Brazier, J., Ara, R., & Azzabi, Z. I. (2017). The role of condition-specific preference-based measures in health technology assessment. Pharmacoeconomics, 35(Suppl 1), 33–41.

    Article  PubMed  Google Scholar 

  28. Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009) Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ. https://doi.org/10.1136/bmj.b2535.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Tonmukayakul, U., Le, L., Bohingamu, S., Engel, L., Bucholc, J., & Mihalopoulos, C. A systematic review of utility values in children with cerebral palsy. PROSPERO 2017 CRD42017058643. http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42017058643.

  30. Engel, L., Bansback, N., Bryan, S., Doyle-Waters, M. M., & Whitehurst, D. G. (2016). Exclusion Criteria in National Health State valuation studies: A systematic review. Medical Decision Making, 36(7), 798–810.

    Article  PubMed  Google Scholar 

  31. Kennedy-Martin, T., Paczkowski, R., & Rayner, S. (2015). Utility values in diabetic kidney disease: A literature review. Current Medical Research and Opinion, 31(7), 1271–1282.

    Article  PubMed  Google Scholar 

  32. Liem, Y. S., Bosch, J. L., & Hunink, M. G. (2008). Preference-based quality of life of patients on renal replacement therapy: A systematic review and meta-analysis. Value Health, 11(4), 733–741.

    Article  PubMed  Google Scholar 

  33. Wyld, M., Morton, R. L., Hayen, A., Howard, K., & Webster, A. C. (2012). A systematic review and meta-analysis of utility-based quality of life in chronic kidney disease treatments. PLoS Medicine, 9(9), e1001307.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Novak, I., McIntyre, S., Morgan, C., Campbell, L., Dark, L., Morton, N., Stumbles, E., Wilson, S. A., & Goldsmith, S. (2013). A systematic review of interventions for children with cerebral palsy: State of the evidence. Developmental Medicine & Child Neurology, 55(10), 855–910.

    Article  Google Scholar 

  35. Peasgood, T., & Brazier, J. (2015). Is meta-analysis for utility values appropriate given the potential impact different elicitation methods have on values? Pharmacoeconomics, 33(11), 1101–1105.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Brazier, J., & Deverill, M. (1999). A checklist for judging preference-based measures of health related quality of life: Learning from psychometrics. Health economics, 8(1), 41–51.

    Article  CAS  PubMed  Google Scholar 

  37. Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied statistics for the behavioural sciences (5th ed.). Boston: Houghton Mifflin.

    Google Scholar 

  38. Lissovoy, G. M., L. S.; Green, H.; Werner, M.; Edgar, T (2007). Cost-effectiveness of intrathecal baclofen therapy for the treatment of severe spasticity associated with cerebral palsy. Journal of Child Neurology, 22(1), 49–59.

    Article  PubMed  Google Scholar 

  39. Carroll, A. E., & Downs, S. M. (2009). Improving decision analyses: Parent preferences (utility values) for pediatric health outcomes. The Journal of Pediatrics, 155(1), 21.e1–25.e5.

    Article  Google Scholar 

  40. Petrou, S., & Kupek, E. (2009). Estimating preference-based health utilities index mark 3 utility scores for childhood conditions in England and Scotland. Medical Decision Making, 29(3), 291–303.

    Article  PubMed  Google Scholar 

  41. Young, N. L., Rochon, T. G., McCormick, A., Law, M., Wedge, J. H., & Fehlings, D. (2010). The health and quality of life outcomes among youth and young adults with cerebral palsy. Archives of Physical Medicine and Rehabilitation, 91(1), 143–148.

    Article  PubMed  Google Scholar 

  42. Rosenbaum, P. L., Livingston, M. H., Palisano, R. J., Galuppi, B. E., & Russell, D. J. (2007). Quality of life and health-related quality of life of adolescents with cerebral palsy. Developmental Medicine & Child Neurology, 49(7), 516–521.

    Article  Google Scholar 

  43. Sport England. (2000). Disability Survey: Survey of young people with a disability and sport. London, UK: Sport England.

    Google Scholar 

  44. Palisano, R. J., Rosenbaum, P., Bartlett, D., & Livingston, M. H. (2008). Content validity of the expanded and revised gross motor function classification system. Developmental Medicine & Child Neurology, 50(10), 744–750.

    Article  Google Scholar 

  45. Palisano, R., Rosenbaum, P., Walter, S., Russel, D., Wood, E., & Galuppi, B. (1997). Development and reliability of a system to classify gross motor function in children with cerebral palsy. Developmental Medicine & Child Neurology, 39, 214–223.

    Article  CAS  Google Scholar 

  46. Hawthorne, G., Richardson, J., & Osborne, R. (1999). The Assessment of Quality of Life (AQoL) instrument: A psychometric measure of health-related quality of life. Quality of Life Research, 8(3), 209–224.

    Article  CAS  PubMed  Google Scholar 

  47. Horsman, J., Furlong, W., Feeny, D., & Torrance, G. (2003) The Health Utilities Index (HUI(®)): Concepts, measurement properties and applications. Health and Quality of Life Outcomes, 1(1), 54.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Medical Care, 40(2), 113–128.

    Article  PubMed  Google Scholar 

  49. Hawthorne, G., & Richardson, J. (1997) The Assessment of Quality of Life (AQoL) instrument construction, initial validation and utility scaling. Melbourne: Centre for Health Program Evaluation.

    Google Scholar 

  50. Mihalopoulos, C., Chen, G., Iezzi, A., Khan, M. A., & Richardson, J. (2014). Assessing outcomes for cost-utility analysis in depression: Comparison of five multi-attribute utility instruments with two depression-specific outcome measures. British Journal of Psychiatry, 205(5), 390–397.

    Article  PubMed  Google Scholar 

  51. Renwick, R., Fudge Schormans, A., & Zekovic, B. (2003). Quality of life: A new conceptual framework for children with disabilities. Journal on Developmental Disabilities, 10, 107–114.

    Google Scholar 

  52. Varni, J. W., Limbers, C. A., & Burwinkle, T. M. (2007). How young can children reliably and validly self-report their health-related quality of life? An analysis of 8,591 children across age subgroups with the PedsQL™ 4.0 Generic Core Scales. Health and Quality of Life Outcomes, 5(1), 1.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Eiser, C. (1995). Choices in measuring quality of life in children with cancer: A comment. Psycho-Oncology, 4(2), 121–131.

    Article  Google Scholar 

  54. Thorrington, D., & Eames, K. (2015). Measuring health utilities in children and adolescents: A systematic reveiw of the literature. PLoS ONE, 10(8), e0135672.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Bray, N., Noyes, J., Harris, N., & Edwards, R. T. (2017). Measuring the health-related quality of life of children with impaired mobility: Examining correlation and agreement between children and parent proxies. BMC Research Notes, 10(1), 377.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Ungar, W. J. (2011). Challenges in health state valuation in paediatric economic evaluation: Are QALYs contraindicated? Pharmacoeconomics, 29(8), 641–652.

    Article  PubMed  Google Scholar 

  57. Petrou, S. (2003). Methodological issues raised by preference-based approaches to measuring the health status of children. Health Economics, 12(8), 697–702.

    Article  PubMed  Google Scholar 

  58. Ratcliffe, J., Huynh, E., Stevens, K., Brazier, J., Sawyer, M., & Flynn, T. (2015). Nothing about us without us? A compariosn of adolescent and adult health-state values for the child health utility-9D using profile case bast-worst scaling. Health Economics, 25(4), 486–496.

    Article  PubMed  Google Scholar 

  59. NICE. (2013). Guide to the methods of technology appraisal. London: NICE.

    Google Scholar 

  60. Canadian Agency for Drugs and Technologies in Health. (2006). Guidelines for the economic evaluation of health technologies (3rd ed.). Ottawa: Canadian Agency for Drugs and Technologies in Health.

    Google Scholar 

  61. Livingston, M. H., Rosenbaum, P. L., Russell, D. J., & Palisano, R. J. (2007). Quality of life among adolescents with cerebral palsy: What does the literature tell us? Developmental Medicine & Child Neurology, 49(3), 225–231.

    Article  Google Scholar 

  62. Whitehurst, D. G. T., Mittmann, N., Noonan, V. K., Dvorak, M. F., & Bryan, S. (2016). Health state descriptions, valuations and individuals’ capacity to walk: A comparative evaluation of preference-based instruments in the context of spinal cord injury. Quality of Life Research, 25(10), 2481–2496.

    Article  PubMed  Google Scholar 

  63. Griebsch, I., Coast, J., & Brown, J. (2005). Quality-adjusted life-years lack quality in pediatric care: A critical review of published cost-utility studies in child health. Pediatrics, 115(5), e600–e614.

    Article  PubMed  Google Scholar 

  64. Brazier, J. E., Rowen, D., Mavranezouli, I., Tsuchiya, A., Young, T., Yang, Y., et al. (2012). Developing and testing methods for deriving preference-based measures of health from condition-specific measures (and other patient-based measures of outcome). Health Technology Assessment ((Winchester, England)), 16(32), 1–114. https://doi.org/10.3310/hta16320.

    Article  CAS  PubMed  Google Scholar 

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Funding

This study was funded by the Centre of Research Excellence in Cerebral Palsy (NHMRC APP 1057997) for supporting the conduct of this systematic review. The author UT has received PhD scholarship from the Centre of Research Excellence in Cerebral Palsy.

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Affiliations

  1. Deakin Health Economics, Centre for Population Health Research, Deakin University, Locked Bag 20000, Geelong, VIC, 3220, Australia

    Utsana Tonmukayakul, Long Khanh-Dao Le, Shalika Bohingamu Mudiyanselage, Lidia Engel, Jessica Bucholc, Rob Carter & Cathrine Mihalopoulos

  2. Centre for Health Economics Research and Evaluation, University of Technology Sydney, 1-59 Quay Street, Hay Market, Sydney, NSW, 2000, Australia

    Brendan Mulhern

  3. Deakin Health Economics, Centre for Population Health Research, Deakin University, 3rd Floor BC Building 221 Burwood Highway, Burwood, Melbourne, VIC, 3125, Australia

    Utsana Tonmukayakul

Authors
  1. Utsana Tonmukayakul
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  2. Long Khanh-Dao Le
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  3. Shalika Bohingamu Mudiyanselage
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  4. Lidia Engel
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  5. Jessica Bucholc
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  6. Brendan Mulhern
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  7. Rob Carter
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  8. Cathrine Mihalopoulos
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Correspondence to Utsana Tonmukayakul.

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Tonmukayakul, U., Le, L.KD., Mudiyanselage, S.B. et al. A systematic review of utility values in children with cerebral palsy. Qual Life Res 28, 1–12 (2019). https://doi.org/10.1007/s11136-018-1955-8

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Keywords

  • Utility value
  • Children
  • Adolescent
  • Cerebral palsy
  • Quality of life
  • Quality-adjusted life years
  • Utility weight