Skip to main content

Advertisement

SpringerLink
Log in

Generic and disease-specific estimates of quality of life in macular degeneration: mapping the MacDQoL onto the EQ-5D-3L

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

The macular degeneration quality of life (MacDQoL) instrument is a validated condition-specific measure of quality of life in patients with macular degeneration. This paper presents the first mapping algorithm to predict EQ-5D from responses to the MacDQoL instrument.

Methods

Responses to the MacDQoL and EQ-5D-3L instruments from 482 patients were collected from the IVAN multicentre trial of two alternative drug treatments for neovascular age-related macular degeneration. Regression specifications were estimated using OLS, censored least absolute deviation, Tobit and two-part models. Their predictive performance was assessed using mean squared error. An internal validation sample based on a random selection of 25 % of patients was used to assess the performance of the model estimated on the remaining 75 % of patients.

Results

A two-part model had the best predictive performance on the full sample. The covariates of this model include responses and weighted impact scores for all 23 condition-specific domains of the MacDQoL, and responses to a general MacDQoL quality of life question. The selected models were successful at predicting means and standard deviations of target populations, but prediction is weaker at the upper and lower extremes of the EQ-5D-3L distribution.

Conclusion

The mapping algorithms provide a means of predicting EQ-5D-3L index scores from MacDQoL scores, and could facilitate cost-effectiveness analyses when the latter but not the former are available to researchers. Further validation of the performance of the algorithms using external data would provide a means of establishing the robustness of the algorithms.

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

Similar content being viewed by others

Notes

  1. Impact response categories are answered in response to questions such as ‘If I did not have macular degeneration, friendships and social life would be…’. Typical categories are ‘very much better' [scoring −3], ‘much better' [scoring −2], ‘a little better' [scoring −1], ‘the same' [scoring 0], and ‘worse’ [scoring +1].

  2. Importance response categories are answered in response to questions such as ‘My friendships and social life are…’ with response categories ‘very important' [scoring 3], ‘important' [scoring 2], ‘somewhat important' [scoring 1], ‘not at all important’ [scoring 0].

References

  1. Longworth, L., & Rowen, D. (2013). Mapping to obtain EQ-5D utility values for use in NICE health technology assessments. Value in Health, 16(1), 202–210.

    Article  PubMed  Google Scholar 

  2. 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, 15(100883818), 118–127.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Dakin, H. (2013). Review of studies mapping from quality of life or clinical measures to EQ-5D: An online database. Health and Quality of Life Outcomes, 11, 6.

    Article  Google Scholar 

  4. Brazier, J., & Dixon, S. (1995). The use of condition specific outcome measures in economic appraisal. Health Economics, 4(4), 255–264.

    Article  CAS  PubMed  Google Scholar 

  5. Longworth, L., Yang, Y., Young, T., Mulhern, B., Hernández 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 review, statistical modelling and survey. Health Technology Assessment, 18(9), 1.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Usha, C., Jennifer, E., & Philip, J. R. (2010). Age related macular degeneration. BMJ, 340, c981.

    Article  Google Scholar 

  7. Woo, J. H., Sanjay, S., & Au Eong, K.-G. (2009). The epidemiology of age-related macular degeneration in the Indian subcontinent. Acta Ophthalmologica, 87(3), 262–269.

    Article  PubMed  Google Scholar 

  8. Owen, C. G., Jarrar, Z., Wormald, R., Cook, D. G., Fletcher, A. E., & Rudnicka, A. R. (2012). The estimated prevalence and incidence of late stage age related macular degeneration in the UK. British Journal of Ophthalmology, 96(5), 752–756.

    Article  Google Scholar 

  9. Mitchell, J., & Bradley, C. (2004). Design of an individualised measure of the impact of macular disease on quality of life (the MacDQoL). Quality of Life Research, 13(6), 1163–1175.

    Article  PubMed  Google Scholar 

  10. Mitchell, J., Wolffsohn, J., Woodcock, A., Anderson, S., McMillan, C., Rubinstein, M., et al. (2005). + Psychometric evaluation of the MacDQoL individualised measure of the impact of macular degeneration on quality of life. Health and Quality of Life Outcomes, 3(1), 25.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Mitchell, J., Wolffsohn, J., Woodcock, A., Anderson, S. J., Ffytche, T., Rubinstein, M., et al. (2008). The MacDQoL individualized measure of the impact of macular degeneration on quality of life: Reliability and responsiveness. American Journal of Ophthalmology, 146(3), 447.e442–454.e442.

    Article  Google Scholar 

  12. Berdeaux, G., Mesbah, M., & Bradley, C. (2011). Metric properties of the MacDQoL, individualized macular-disease-specific quality of life instrument, and newly identified subscales in French, German, Italian, and American populations. Value in Health, 1(1524-4733 (Electronic)), 10.

  13. Chakravarthy, U., Harding, S. P., Rogers, C. A., Downes, S. M., Lotery, A. J., Wordsworth, S., & Reeves, B. C. (2012). Ranibizumab versus bevacizumab to treat neovascular age-related macular degeneration: One-year findings from the IVAN randomized trial. Ophthalmology, 119(7), 1399–1411.

    Article  PubMed  Google Scholar 

  14. Chakravarthy, U., Harding, S. P., Rogers, C. A., Downes, S. M., Lotery, A. J., Culliford, L. A., & Reeves, B. C. (2013). Alternative treatments to inhibit VEGF in age-related choroidal neovascularisation: 2-year findings of the IVAN randomised controlled trial. The Lancet, 382, 1258.

    Article  CAS  Google Scholar 

  15. van Reenen, M., & Oppe, M. (2015). EQ-5D-3L user guide: Basic information on how to use the EQ-5D-3L instrument version 5.1. Rotterdam: EuroQol Research Foundation.

    Google Scholar 

  16. NICE. (2013). Guide to the methods of technology appraisal. Manchester: The National Institute for Health and Care Excellence.

  17. Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 12.

    Article  Google Scholar 

  18. Petrou, S., Rivero-Arias, O., Dakin, H., Longworth, L., Oppe, M., Froud, R., & Gray, A. (2015). Preferred reporting items for studies mapping onto preference-based outcome measures: The MAPS statement. Quality of Life Research, 30, 1–7.

    Google Scholar 

  19. Wooldridge, J. M. (2009). Introductory econometrics: A modern approach. Mason: South Western, Cengage Learning.

    Google Scholar 

  20. Pullenayegum, E. M., Tarride, J.-E., Xie, F., Goeree, R., Gerstein, H. C., & O’Reilly, D. (2010). Analysis of health utility data when some subjects attain the upper bound of 1: Are Tobit and CLAD models appropriate? Value in Health, 13(4), 487–494.

    Article  PubMed  Google Scholar 

  21. Powell, J. L. (1984). Least absolute deviations estimation for the censored regression model. Journal of Econometrics, 25(3), 303–325.

    Article  Google Scholar 

  22. Jolliffe, D., Krushelnytskyy, B., & Semykina, A. (2000, November). Censored least absolute deviations estimator: CLAD. Stata Technical Bulletin, 58, 13–16.

  23. Longworth, L., & Rowen, D. (2011). NICE DSU technical support document 10: The use of mapping methods to estimate health state utility values. Decision Support Unit, ScHARR, University of Sheffield.

  24. Browne, C., Brazier, J., Carlton, J., Alavi, Y., & Jofre-Bonet, M. (2012). Estimating quality-adjusted life years from patient-reported visual functioning. Eye, 26(10), 1295–1301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Sengupta, N., Nichol, M. B., Wu, J., & Globe, D. (2004). Mapping the SF-12 to the HUI3 and VAS in a managed care population. Medical Care, 42(9), 927–937.

    Article  PubMed  Google Scholar 

  26. Brazier, J., Yang, Y., Tsuchiya, A., & Rowen, D. (2010). A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. The European Journal of Health Economics, 11(2), 215–225.

    Article  PubMed  Google Scholar 

  27. Payakachat, N., Summers, K., Pleil, A., Murawski, M., Thomas, J., Jennings, K., et al. (2009). 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. Quality of Life Research, 18(9210257, bqm), 801–813.

  28. Dakin, H., Gray, A., & Murray, D. (2013). Mapping analyses to estimate EQ-5D utilities and responses based on Oxford Knee Score. Quality of Life Research, 22(3), 683–694.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Brazier, J., Connell, J., Papaioannou, D., Mukuria, C., Mulhern, B., Peasgood, T., et al. (2014). A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures. Health Technology Assessment, 18(34), 1.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ara, R., & Brazier, J. E. (2010). Populating an economic model with health state utility values: Moving toward better practice. Value in Health, 13(5), 509–518.

    Article  PubMed  Google Scholar 

  31. IVAN Study Team. (2011). IVAN study protocol V7.0: NIHR technology assessment programme.

  32. Gray, A. M., Rivero-Arias, O., & Clarke, P. M. (2006). Estimating the association between SF-12 responses and EQ-5D utility values by response mapping. Medical Decision Making, 26(1), 18–29.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The IVAN trial (Trial Registration: ISRCTN92166560) was funded by the National Institute for Health Research (NIHR) Health Technology Assessment (HTA) programme (Project Number 07/36/01). The views and opinions expressed are those of the authors and do not necessarily reflect those of the HTA programme, NIHR, the UK National Health Service or the Department of Health. The NIHR had no role in the design, conduct or reporting of this mapping study. We are grateful to all IVAN trial participants and to the IVAN research team. We are extremely grateful to the IVAN site staff, who collected the EQ-5D-3L data and also the Clinical Trials Evaluation Unit (University of Bristol) who made all the phone calls to collect the MacDQoL data, then managed and cleaned the data for the analyses for this paper. We thank two anonymous reviewers for helpful comments.

Author information

Authors and Affiliations

  1. School of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK

    Padraig Dixon

  2. Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Old Road Campus, Oxford, OX3 7LF, United Kingdom

    Helen Dakin & Sarah Wordsworth

Authors
  1. Padraig Dixon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Helen Dakin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sarah Wordsworth
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Padraig Dixon.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written, informed consent was obtained from all individual participants included in the study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 103 kb)

Supplementary material 2 (XLSX 404 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dixon, P., Dakin, H. & Wordsworth, S. Generic and disease-specific estimates of quality of life in macular degeneration: mapping the MacDQoL onto the EQ-5D-3L. Qual Life Res 25, 935–945 (2016). https://doi.org/10.1007/s11136-015-1145-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-015-1145-x

Keywords

Search

Navigation