Skip to main content

Advertisement

SpringerLink
Log in

Mapping of the EORTC QLQ-C30 to EQ-5D-5L index in patients with lymphomas

  • Original Paper
  • Published:
The European Journal of Health Economics Aims and scope Submit manuscript

Abstract

Objective

The objective of this study was to develop algorithms to map the EORTC QLQ-C30 (QLQ-C30) onto EQ-5D-5L in a sample of patients with lymphomas.

Methods

An online nationwide survey of patients with lymphoma was carried out in China. Ordinary least squares (OLS), beta-based mixture, adjusted limited dependent variable mixture regression, and a Tobit regression model were used to develop the mapping algorithms. The QLQ-C30 subscales/items, their squared and interaction terms, and respondents’ demographic variables were used as independent variables. The root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2) were estimated based on tenfold cross-validation to assess the predictive ability of the selected models.

Results

Data of 2222/4068 respondents who self-completed the online survey were elicited for analyses. The mean EQ-5D-5L index score was 0.81 (SD 0.21, range − 0.81–1.0). 19.98% of respondents reported an index score at 1.0. In total, 72 models were generated based on four regression methods. According to the RMSE, MAE and R2, the OLS model including QLQ-C30 subscales, squared terms, interaction terms, and demographic variables showed the best fit for overall and the Non-Hodgkin’s lymphoma sample; for Hodgkin’s lymphoma, the ALDVMM with 1-component model, including QLQ-C30 subscales, squared terms, interaction terms, and demographic variables, showed a better fit than the other models.

Conclusion

The mapping algorithms enable the EQ-5D-5L index scores to be predicted by QLQ-C30 subscale/item scores with good precision in patients living with lymphomas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

Data may be accessed by contacting the corresponding author.

References

  1. Tantai, N., Chaikledkaew, U., Tanwandee, T., et al.: A cost-utility analysis of drug treatments in patients with HBeAg-positive chronic hepatitis B in Thailand. BMC Health Serv Res 14, 170 (2014). https://doi.org/10.1186/1472-6963-14-170

    Article  PubMed  PubMed Central  Google Scholar 

  2. Ameri, H., Yousefi, M., Yaseri, M., et al.: Mapping EORTC-QLQ-C30 and QLQ-CR29 onto EQ-5D-5L in colorectal cancer patients. J Gastrointest Cancerd (2019). https://doi.org/10.1007/s12029-019-00229-6

    Article  Google Scholar 

  3. Proskorovsky, I., Lewis, P., Williams, C., et al.: Mapping EORTC QLQ-C30 and QLQ-MY20 to EQ-5D in patients with multiple myeloma. Health Qual Life Outcomes 12, 35 (2014). https://doi.org/10.1186/1477-7525-12-35

    Article  PubMed  PubMed Central  Google Scholar 

  4. Brazier, J., Yang, Y., Tsuchiya, A., et al.: A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Heal Econ Prev Care 11, 215–225 (2010). https://doi.org/10.1007/s10198-009-0168-z

    Article  Google Scholar 

  5. Gray, L.A., Wailoo, A.J., Hernandez, A.M.: Mapping the FACT-B instrument to EQ-5D-3L in patients with breast cancer using adjusted limited dependent variable mixture models versus response mapping. Value Heal 21, 1399–1405 (2018). https://doi.org/10.1016/j.jval.2018.06.006

    Article  Google Scholar 

  6. Young, T.A., Mukuria, C., Rowen, D., et al.: Mapping functions in health-related quality of life : mapping from two quality-of-life instruments to EQ-5D-3L. Med Decis Mak (2015). https://doi.org/10.1177/0272989X15587497

    Article  Google Scholar 

  7. Longworth, L., Rowen, D.: Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value Heal 16, 202–210 (2013). https://doi.org/10.1016/j.jval.2012.10.010

    Article  Google Scholar 

  8. Tolley K, Morgan G, Cartwright R et al (1998) Economic aspects of Non-Hodgkin’s Lymphoma. https://www.ohe.org/publications/economic-aspects-non-hodgkins-lymphoma. Accessed 17 Sept 2020

  9. Lamy, S., Bettiol, C., Grosclaude, P., et al.: The care center influences the management of lymphoma patients in a universal health care system: an observational cohort study. BMC Health Serv Res 16, 1–10 (2016). https://doi.org/10.1186/s12913-016-1553-9

    Article  Google Scholar 

  10. International agency for research on cancer (IARC). https://www.iarc.fr/. Accessed 17 Sept 2020

  11. Kyriaki, M., Eleni, T., Efi, P., et al.: The EORTC core quality of life questionnaire (QLQ-C30, version 3.0) in terminally ill cancer patients under palliative care: validity and reliability in a Hellenic sample. Int J cancer 94, 135–139 (2001)

    Article  CAS  PubMed  Google Scholar 

  12. Herdman, M., Gudex, C., Lloyd, A., et al.: Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res 20, 1727–1736 (2011). https://doi.org/10.1007/s11136-011-9903-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Mctaggart-Cowan, H., Teckle, P., Peacock, S.: Mapping utilities from cancer-specific health-related quality of life instruments: a review of the literature. Expert Rev Pharmacoecon Outcomes Res 13, 753–765 (2013). https://doi.org/10.1586/14737167.2013.850420

    Article  PubMed  Google Scholar 

  14. Versteegh, M.M., Leunis, A., Luime, J.J., et al.: Mapping QLQ-C30, HAQ, and MSIS-29 on EQ-5D. Med Decis Mak 32, 554–568 (2012). https://doi.org/10.1177/0272989X11427761

    Article  Google Scholar 

  15. Van Reenen M, Janssen B (2015) EQ-5D-5L User Guide - Basic information on how to use the EQ-5D-5L instrument. Version 2.1. EuroQol Research Foundation

  16. Luo, N., Liu, G., Li, M., et al.: Estimating an EQ-5D-5L value set for China. Value Heal 20, 662–669 (2017). https://doi.org/10.1016/j.jval.2016.11.016

    Article  Google Scholar 

  17. Yang, Z., Busschbach, J., Liu, G., et al.: EQ-5D-5L norms for the urban Chinese population in China. Health Qual Life Outcomes (2018). https://doi.org/10.1186/s12955-018-1036-2

    Article  PubMed  PubMed Central  Google Scholar 

  18. Aaronson, N.K., Ahmedzai, S., Bergman, B., et al.: The European organization for research and treatment of cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 85, 365 (1993). https://doi.org/10.1093/jnci/85.5.365

    Article  CAS  PubMed  Google Scholar 

  19. Round, J., Hawton, A.: Statistical alchemy: conceptual validity and mapping to generate health state utility values. Pharmacoecono Open 1, 233–239 (2017). https://doi.org/10.1007/s41669-017-0027-2

    Article  Google Scholar 

  20. Yang, F., Wong, C.K.H., Luo, N., et al.: Mapping the kidney disease quality of life 36-item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L in patients undergoing dialysis. Eur J Heal Econ 20, 1195 (2019). https://doi.org/10.1007/s10198-019-01088-5

    Article  CAS  Google Scholar 

  21. DeVellis, R.F.: Scale development : theory and applications, 4th edn. SAGE, Los Angeles (2017)

    Google Scholar 

  22. Dakin, H., Abel, L., Burns, R., et al.: Review and critical appraisal of studies mapping from quality of life or clinical measures to EQ-5D: an online database and application of the MAPS statement. Heal Qual Life Outcomes (2018). https://doi.org/10.1186/s12955-018-0857-3

    Article  Google Scholar 

  23. Rowen, D., Brazier, J., Roberts, J.: Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? Health Qual Life Outcomes 7, 27 (2009). https://doi.org/10.1186/1477-7525-7-27

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gray, L.A., Hernández Alava, M., Wailoo, A.J.: Development of methods for the mapping of utilities using mixture models: mapping the AQLQ-S to the EQ-5D-5L and the HUI3 in patients with asthma. Value Heal 21, 748–757 (2018). https://doi.org/10.1016/j.jval.2017.09.017

    Article  Google Scholar 

  25. Wu, M., Brazier, J.E., Kearns, B., et al.: Examining the impact of 11 long-standing health conditions on health-related quality of life using the EQ-5D in a general population sample. Eur J Heal Econ 16, 141–151 (2014). https://doi.org/10.1007/s10198-013-0559-z

    Article  Google Scholar 

  26. Gray LA, Alava MH (2018) A command for fitting mixture regression models for bounded dependent variables using the beta distribution. Stata J 18:51–75

  27. Alava MH, Wailoo A (2015) Fitting adjusted limited dependent variable mixture models to EQ-5D. Stata J 15:737–50

  28. Kay, S., Ferreira, A.: Mapping the 25-item national eye institute visual functioning questionnaire (NEI VFQ-25) to EQ-5D utility scores. Ophthalmic Epidemiol 21, 66–78 (2014). https://doi.org/10.3109/09286586.2014.888456

    Article  PubMed  Google Scholar 

  29. Wong, C.K.H., Cheung, P.W.H., Samartzis, D., et al.: Mapping the SRS-22r questionnaire onto the EQ-5D-5L utility score in patients with adolescent idiopathic scoliosis. PLoS ONE 12, e0175847 (2017). https://doi.org/10.1371/journal.pone.0175847

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ara, R., Brazier, J.: Deriving an Algorithm To Convert The Eight Mean SF-36 dimension scores into a mean eq-5d preference-based score from published studies (where patient level data are not available). Value Heal 11, 1131–1143 (2008). https://doi.org/10.1111/j.1524-4733.2008.00352.x

    Article  Google Scholar 

  31. Judd, C.M.: Data analysis : a model comparison approach, 2nd edn. Routledge, New York (2009)

    Google Scholar 

  32. Crott, R., Briggs, A.: Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences. Heal Econ Prev Care 11, 427–434 (2010). https://doi.org/10.1007/s10198-010-0233-7

    Article  Google Scholar 

  33. Askew, R.L., Swartz, R.J., Xing, Y., et al.: Mapping FACT-melanoma quality-of-life scores to EQ-5D health utility weights. Value Heal 14, 900–906 (2011). https://doi.org/10.1016/j.jval.2011.04.003

    Article  Google Scholar 

  34. Jang, R.W., Isogai, P.K., Mittmann, N., et al.: Derivation of utility values from european organization for research and treatment of cancer quality of life-core 30 questionnaire values in lung cancer. J Thorac Oncol 5, 1953–1957 (2010). https://doi.org/10.1097/JTO.0b013e3181f77a6a

    Article  PubMed  Google Scholar 

Download references

Acknowledgement

We thank the staff from the House086 for their assistance in distributing the survey, and all study participants for contributing their time to complete the questionnaire. We thank Dr. YANG Fan and Dr. LUO Nan for the comments that greatly improved the manuscript. We would like to thank the anonymous reviewers for their insights and comments on the preparation of this manuscript.

Funding

No funding supported this study.

Author information

Authors and Affiliations

  1. The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China

    Richard Huan Xu, Eliza Lai Yi Wong & Dong Dong

  2. Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong, China

    Richard Huan Xu, Eliza Lai Yi Wong & Dong Dong

  3. Department of Sociology, School of Social Sciences, Tsinghua University, Beijing, China

    Jun Jin & Ying Dou

  4. Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, Guangdong, China

    Dong Dong

Authors
  1. Richard Huan Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eliza Lai Yi Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jun Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ying Dou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dong Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

DD was the Principle Investigator of the survey study. All authors jointly designed the research. DD drafted the survey questionnaire and collected the data. RX completed the statistical analysis and prepared the manuscript. DD revised the manuscript. All authors have full access to all the data in the study and have reviewed the manuscript

Corresponding author

Correspondence to Dong Dong.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 3895 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, R.H., Wong, E.L.Y., Jin, J. et al. Mapping of the EORTC QLQ-C30 to EQ-5D-5L index in patients with lymphomas. Eur J Health Econ 21, 1363–1373 (2020). https://doi.org/10.1007/s10198-020-01220-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10198-020-01220-w

Keywords

Search

Navigation