IDEAS home Printed from https://ideas.repec.org/a/spr/pharme/v36y2018i4d10.1007_s40273-017-0600-7.html
   My bibliography  Save this article

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

Author

Listed:
  • Tosin Lambe

    (University of Birmingham)

  • Emma Frew

    (University of Birmingham)

  • Natalie J. Ives

    (University of Birmingham)

  • Rebecca L. Woolley

    (University of Birmingham)

  • Carole Cummins

    (University of Birmingham)

  • Elizabeth A. Brettell

    (University of Birmingham)

  • Emma N. Barsoum

    (University of Birmingham)

  • Nicholas J. A. Webb

    (Royal Manchester Children’s Hospital)

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 13 years) or patient groups with particularly poor quality of life. ISRCTN Registry No 16645249

Suggested Citation

  • Tosin Lambe & Emma Frew & Natalie J. Ives & Rebecca L. Woolley & Carole Cummins & Elizabeth A. Brettell & Emma N. Barsoum & Nicholas J. A. Webb, 2018. "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, Springer, vol. 36(4), pages 451-465, April.
  • Handle: RePEc:spr:pharme:v:36:y:2018:i:4:d:10.1007_s40273-017-0600-7
    DOI: 10.1007/s40273-017-0600-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40273-017-0600-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40273-017-0600-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, edition 2, number 9780198725923.
    2. Christine Mpundu-Kaambwa & Gang Chen & Remo Russo & Katherine Stevens & Karin Dam Petersen & Julie Ratcliffe, 2017. "Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15," PharmacoEconomics, Springer, vol. 35(4), pages 453-467, April.
    3. Reynolds, Anderson & Shonkwiler, J S, 1991. "Testing and Correcting for Distributional Misspecifications in the Tobit Model: An Application of the Information Matrix Test," Empirical Economics, Springer, vol. 16(3), pages 313-323.
    4. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    5. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    6. Karen Gerard & Gavin Mooney, 1993. "Qaly league tables: Handle with care," Health Economics, John Wiley & Sons, Ltd., vol. 2(1), pages 59-64, April.
    7. Erik Nord, 1994. "The qaly—a measure of social value rather than individual utility?," Health Economics, John Wiley & Sons, Ltd., vol. 3(2), pages 89-93, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chris Sampson;Martina Garau, 2019. "How Should We Measure Quality of Life Impact in Rare Disease? Recent Learnings in Spinal Muscular Atrophy," Briefing 002146, Office of Health Economics.
    2. Christine Mpundu-Kaambwa & Gang Chen & Elisabeth Huynh & Remo Russo & Julie Ratcliffe, 2019. "Mapping the PedsQL™ onto the CHU9D: An Assessment of External Validity in a Large Community-Based Sample," PharmacoEconomics, Springer, vol. 37(9), pages 1139-1153, September.
    3. Asrul Akmal Shafie & Irwinder Kaur Chhabra & Jacqueline Hui Yi Wong & Noor Syahireen Mohammed, 2021. "Mapping PedsQL™ Generic Core Scales to EQ-5D-3L utility scores in transfusion-dependent thalassemia patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 735-747, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Karin Dam Petersen & Gang Chen & Christine Mpundu-Kaambwa & Katherine Stevens & John Brazier & Julie Ratcliffe, 2018. "Measuring Health-Related Quality of Life in Adolescent Populations: An Empirical Comparison of the CHU9D and the PedsQLTM 4.0 Short Form 15," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(1), pages 29-37, February.
    2. John Hutton, 2012. "‘Health Economics’ and the evolution of economic evaluation of health technologies," Health Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 13-18, January.
    3. Valentina Prevolnik Rupel & Marko Ogorevc, 2021. "EQ-5D-Y Value Set for Slovenia," PharmacoEconomics, Springer, vol. 39(4), pages 463-471, April.
    4. Christine Mpundu-Kaambwa & Gang Chen & Remo Russo & Katherine Stevens & Karin Dam Petersen & Julie Ratcliffe, 2017. "Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15," PharmacoEconomics, Springer, vol. 35(4), pages 453-467, April.
    5. repec:prg:jnlcfu:v:2022:y:2022:i:1:id:572 is not listed on IDEAS
    6. Joanna Coast & Hareth Al‐Janabi & Eileen J. Sutton & Susan A. Horrocks & A. Jane Vosper & Dawn R. Swancutt & Terry N. Flynn, 2012. "Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 730-741, June.
    7. Pieter H. M. van Baal & Talitha L. Feenstra & Rudolf T. Hoogenveen & G. Ardine de Wit & Werner B. F. Brouwer, 2007. "Unrelated medical care in life years gained and the cost utility of primary prevention: in search of a ‘perfect’ cost–utility ratio," Health Economics, John Wiley & Sons, Ltd., vol. 16(4), pages 421-433, April.
    8. Joanna M Charles & Deirdre M Harrington & Melanie J Davies & Charlotte L Edwardson & Trish Gorely & Danielle H Bodicoat & Kamlesh Khunti & Lauren B Sherar & Thomas Yates & Rhiannon Tudor Edwards, 2019. "Micro-costing and a cost-consequence analysis of the ‘Girls Active’ programme: A cluster randomised controlled trial," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-17, August.
    9. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
    10. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    11. Ling Tang & Chengyuan Zhang & Tingfei Li & Ling Li, 2021. "A novel BEMD-based method for forecasting tourist volume with search engine data," Tourism Economics, , vol. 27(5), pages 1015-1038, August.
    12. Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
    13. Richard Norman & Brendan Mulhern & Emily Lancsar & Paula Lorgelly & Julie Ratcliffe & Deborah Street & Rosalie Viney, 2023. "The Use of a Discrete Choice Experiment Including Both Duration and Dead for the Development of an EQ-5D-5L Value Set for Australia," PharmacoEconomics, Springer, vol. 41(4), pages 427-438, April.
    14. Michael Vössing & Niklas Kühl & Matteo Lind & Gerhard Satzger, 2022. "Designing Transparency for Effective Human-AI Collaboration," Information Systems Frontiers, Springer, vol. 24(3), pages 877-895, June.
    15. Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    16. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    17. Jeon, Yunho & Seong, Sihyeon, 2022. "Robust recurrent network model for intermittent time-series forecasting," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1415-1425.
    18. Snyder, Ralph D. & Ord, J. Keith & Koehler, Anne B. & McLaren, Keith R. & Beaumont, Adrian N., 2017. "Forecasting compositional time series: A state space approach," International Journal of Forecasting, Elsevier, vol. 33(2), pages 502-512.
    19. Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
    20. Rivera, Nilza & Guzmán, Juan Ignacio & Jara, José Joaquín & Lagos, Gustavo, 2021. "Evaluation of econometric models of secondary refined copper supply," Resources Policy, Elsevier, vol. 73(C).
    21. Cameron Roach & Rob Hyndman & Souhaib Ben Taieb, 2021. "Non‐linear mixed‐effects models for time series forecasting of smart meter demand," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1118-1130, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:pharme:v:36:y:2018:i:4:d:10.1007_s40273-017-0600-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.