IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v32y2012i4p554-568.html

Mapping QLQ-C30, HAQ, and MSIS-29 on EQ-5D

Author

Listed:
  • Matthijs M. Versteegh
  • Annemieke Leunis
  • Jolanda J. Luime
  • Mike Boggild
  • Carin A. Uyl-de Groot
  • Elly A. Stolk

Abstract

Background Responses on condition-specific instruments can be mapped on the EQ-5D to estimate utility values for economic evaluation. Mapping functions differ in predictive quality, and not all condition-specific measures are suitable for estimating EQ-5D utilities. We mapped QLQ-C30, HAQ, and MSIS-29 on the EQ-5D and compared the quality of the mapping functions with statistical and clinical indicators. Methods We used 4 data sets that included both the EQ-5D and a condition-specific measure to develop ordinary least squares regression equations. For the QLQ-C30, we used a multiple myeloma data set and a non-Hodgkin lymphoma one. An early arthritis cohort was used for the HAQ, and a cohort of patients with relapsing remitting or secondary progressive multiple sclerosis was used for the MSIS-29. We assessed the predictive quality of the mapping functions with the root mean square error (RMSE) and mean absolute error (MAE) and the ability to discriminate among relevant clinical subgroups. Pearson correlations between the condition-specific measures and items of the EQ-5D were used to determine if there is a relationship between the quality of the mapping functions and the amount of correlated content between the used measures. Results The QLQ-C30 had the highest correlation with EQ-5D items. Average %RMSE was best for the QLQ-C30 with 10.9%, 12.2% for the HAQ, and 13.6% for the MSIS-29. The mappings predicted mean EQ-5D utilities without significant differences with observed utilities and discriminated between relevant clinical groups, except for the HAQ model. Conclusions The preferred mapping functions in this study seem suitable for estimating EQ-5D utilities for economic evaluation. However, this research shows that lower correlations between instruments lead to less predictive quality. Using additional validation tests besides reporting statistical measures of error improves the assessment of predictive quality.

Suggested Citation

  • Matthijs M. Versteegh & Annemieke Leunis & Jolanda J. Luime & Mike Boggild & Carin A. Uyl-de Groot & Elly A. Stolk, 2012. "Mapping QLQ-C30, HAQ, and MSIS-29 on EQ-5D," Medical Decision Making, , vol. 32(4), pages 554-568, July.
    • Handle: RePEc:sae:medema:v:32:y:2012:i:4:p:554-568
    DOI: 10.1177/0272989X11427761
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X11427761
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X11427761?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
    ---><---

    References listed on IDEAS

    as
    1. Torrance, George W., 1986. "Measurement of health state utilities for economic appraisal : A review," Journal of Health Economics, Elsevier, vol. 5(1), pages 1-30, March.
    2. Walters, SJ & Brazier, JE, 2002. "Sample sizes for the SF-6D preference based measure of health from the SF-36: a practical guide," MPRA Paper 29742, University Library of Munich, Germany.
    3. Tsuchiya, A & Brazier, J & McColl, E & Parkin, D, 2002. "Deriving preference-based single indices from non-preference based condition-specific instruments: converting AQLQ into EQ5D indices," MPRA Paper 29740, University Library of Munich, Germany.
    4. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
    5. L. M. Lamers & J. McDonnell & P. F. M. Stalmeier & P. F. M. Krabbe & J. J. V. Busschbach, 2006. "The Dutch tariff: results and arguments for an effective design for national EQ‐5D valuation studies," Health Economics, John Wiley & Sons, Ltd., vol. 15(10), pages 1121-1132, October.
    6. 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.
    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. Tracey A. Young & Clara Mukuria & Donna Rowen & John E. Brazier & Louise Longworth, 2015. "Mapping Functions in Health-Related Quality of Life," Medical Decision Making, , vol. 35(7), pages 912-926, October.
    2. Richard Huan Xu & Eliza Lai Yi Wong & Jun Jin & Ying Dou & Dong Dong, 2020. "Mapping of the EORTC QLQ-C30 to EQ-5D-5L index in patients with lymphomas," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(9), pages 1363-1373, December.
    3. Michela Meregaglia & Ludovica Borsoi & John Cairns & Rosanna Tarricone, 2019. "Mapping health-related quality of life scores from FACT-G, FAACT, and FACIT-F onto preference-based EQ-5D-5L utilities in non-small cell lung cancer cachexia," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(2), pages 181-193, March.

    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. Bansback, Nick & Brazier, John & Tsuchiya, Aki & Anis, Aslam, 2012. "Using a discrete choice experiment to estimate health state utility values," Journal of Health Economics, Elsevier, vol. 31(1), pages 306-318.
    2. Brazier, JE & Yang, Y & Tsuchiya, A, 2008. "A review of studies mapping (or cross walking) from non-preference based measures of health to generic preference-based measures," MPRA Paper 29808, University Library of Munich, Germany.
    3. Renske J. Hoefman & Job van Exel & Werner Brouwer, 2013. "How to Include Informal Care in Economic Evaluations," PharmacoEconomics, Springer, vol. 31(12), pages 1105-1119, December.
    4. Bansback, Nick & Brazier, John & Tsuchiya, Aki & Anis, Aslam, 2010. "Using a discrete choice experiment to estimate societal health state utility values," MPRA Paper 29933, University Library of Munich, Germany.
    5. Rowen, D & Brazier, J & Tsuchiya, A & Hernández, M & Ibbotson, R, 2009. "The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results," MPRA Paper 29841, University Library of Munich, Germany.
    6. Arthur Attema & Yvette Edelaar-Peeters & Matthijs Versteegh & Elly Stolk, 2013. "Time trade-off: one methodology, different methods," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(1), pages 53-64, July.
    7. Nan Luo & Pei Wang & Julian Thumboo & Yee-Wei Lim & Hubertus Vrijhoef, 2014. "Valuation of EQ-5D-3L Health States in Singapore: Modeling of Time Trade-Off Values for 80 Empirically Observed Health States," PharmacoEconomics, Springer, vol. 32(5), pages 495-507, May.
    8. Syed Mohiuddin & Katherine Payne, 2014. "Utility Values for Adults with Unipolar Depression," Medical Decision Making, , vol. 34(5), pages 666-685, July.
    9. Jeff Round & Annie Hawton, 2017. "Statistical Alchemy: Conceptual Validity and Mapping to Generate Health State Utility Values," PharmacoEconomics - Open, Springer, vol. 1(4), pages 233-239, December.
    10. Xinyu Qian & Rachel Lee-Yin Tan & Ling-Hsiang Chuang & Nan Luo, 2020. "Measurement Properties of Commonly Used Generic Preference-Based Measures in East and South-East Asia: A Systematic Review," PharmacoEconomics, Springer, vol. 38(2), pages 159-170, February.
    11. 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.
    12. Garry R. Barton & Tracey H. Sach & Anthony J. Avery & Claire Jenkinson & Michael Doherty & David K. Whynes & Kenneth R. Muir, 2008. "A comparison of the performance of the EQ‐5D and SF‐6D for individuals aged ≥ 45 years," Health Economics, John Wiley & Sons, Ltd., vol. 17(7), pages 815-832, July.
    13. McCabe, Christopher & Brazier, John & Gilks, Peter & Tsuchiya, Aki & Roberts, Jennifer & O'Hagan, Anthony & Stevens, Katherine, 2006. "Using rank data to estimate health state utility models," Journal of Health Economics, Elsevier, vol. 25(3), pages 418-431, May.
    14. Makai, Peter & Brouwer, Werner B.F. & Koopmanschap, Marc A. & Stolk, Elly A. & Nieboer, Anna P., 2014. "Quality of life instruments for economic evaluations in health and social care for older people: A systematic review," Social Science & Medicine, Elsevier, vol. 102(C), pages 83-93.
    15. Stevens, K, 2010. "Valuation of the Child Health Utility Index 9D (CHU9D)," MPRA Paper 29938, University Library of Munich, Germany.
    16. Ian M. McCarthy, 2015. "Putting the Patient in Patient Reported Outcomes: A Robust Methodology for Health Outcomes Assessment," Health Economics, John Wiley & Sons, Ltd., vol. 24(12), pages 1588-1603, December.
    17. Versteegh, MM & Attema, AE & Oppe, M & Devlin, NJ & Stolk, EA, 2012. "Time to tweak the TTO. But how?," MPRA Paper 37989, University Library of Munich, Germany.
    18. Billingsley Kaambwa & Gang Chen & Julie Ratcliffe & Angelo Iezzi & Aimee Maxwell & Jeff Richardson, 2017. "Mapping Between the Sydney Asthma Quality of Life Questionnaire (AQLQ-S) and Five Multi-Attribute Utility Instruments (MAUIs)," PharmacoEconomics, Springer, vol. 35(1), pages 111-124, January.
    19. P. Wang & M. Li & G. Liu & J. Thumboo & N. Luo, 2015. "Do Chinese have similar health-state preferences? A comparison of mainland Chinese and Singaporean Chinese," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(8), pages 857-863, November.
    20. Louis S. Matza & Katherine J. Kim & Holly Yu & Katherine A. Belden & Antonia F. Chen & Mark Kurd & Bruce Y. Lee & Jason Webb, 2019. "Health state utilities associated with post-surgical Staphylococcus aureus infections," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 819-827, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:sae:medema:v:32:y:2012:i:4:p:554-568. 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: SAGE Publications (email available below). General contact details of provider: .

    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.