Skip to main content

Advertisement

SpringerLink
Log in

Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients

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

Abstract

Objectives

The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined.

Methods

A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D.

Results

The OLS model (RMSE = 0.207, R 2 = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states.

Conclusions

This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context of RA by means of the MHAQ alone.

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

References

  1. Tsuchiya, A., Brazier, J.E., McColl, E., Parkin, D.: Deriving preference-based single indices from non-preference based condition-specific instruments: converting AQLQ into EQ5D indices: Sheffield Health Economics Group Discussion Paper Series 02/1, University of Sheffield (2002)

  2. Brazier, J.E., Yang, Y., Tsuchiya, A., Rowen, D.L.: A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur. J. Health Econ. 11, 215–225 (2010)

    Article  PubMed  Google Scholar 

  3. Buxton, M.J., Lacey, L.A., Feagan, B.G., Niecko, T., Miller, D.W., Townsend, R.J.: Mapping from disease-specific measures to utility: an analysis of the relationships between the Inflammatory Bowel Disease Questionnaire and Crohn’s Disease Activity Index in Crohn’s disease and measures of utility. Value Health 10, 214–220 (2007)

    Article  PubMed  Google Scholar 

  4. Brazier, J.E., Kolotkin, R.L., Crosby, R.D., Williams, G.R.: Estimating a preference-based single index for the Impact of Weight on Quality of Life (IWQOL-Lite) Instrument from the SF-6D. Value Health 7, 490–498 (2004)

    Article  PubMed  Google Scholar 

  5. Longworth, L., Buxton, M.J., Sculpher, M., Smith, D.H.: Estimating utility data from clinical indicators for patients with stable angina. Eur. J. Health Econ. 6, 347–353 (2005)

    Article  PubMed  Google Scholar 

  6. Brennan, D.S., Spencer, A.J.: Mapping oral health related quality of life to generic health state values. BMC Health Serv. Res. 6, 96 (2006)

    Article  PubMed  Google Scholar 

  7. Bartman, B.A., Rosen, M.J., Bradham, D.D., Weissman, J., Hochberg, M., Revicki, D.A.: Relationship between health status and utility measures in older claudicants. Qual. Life Res. 7, 67–73 (1998)

    Article  PubMed  CAS  Google Scholar 

  8. Wu, E.Q., Mulani, P., Farrell, M.H., Sleep, D.: Mapping FACT-P and EORTC QLQ-C30 to patient health status measured by EQ-5D in metastatic hormone-refractory prostate cancer patients. Value Health 10, 408–414 (2007)

    Article  PubMed  Google Scholar 

  9. McKenzie, L., van der Pol, M.: Mapping the EORTC QLQ C-30 onto the EQ-5D Instrument: the potential to estimate QALYs without generic preference data. Value Health 12, 167–171 (2009)

    Article  PubMed  Google Scholar 

  10. Kontodimopoulos, N., Aletras, V.H., Paliouras, D., Niakas, D.A.: Mapping the cancer-specific EORTC QLQ-C30 instrument to preference-based EQ-5D, SF-6D and 15D indices. Value Health 12, 1151–1157 (2009)

    Article  PubMed  Google Scholar 

  11. Bansback, N., Marra, C., Tsuchiya, A., Anis, A., Guh, D., Hammond, T., et al.: Using the health assessment questionnaire to estimate preference-based single indices in patients with rheumatoid arthritis. Arthritis Rheum. 57, 963–971 (2007)

    Article  PubMed  Google Scholar 

  12. Amjadi, S.S., Maranian, P.M., Paulus, H.E., Kaplan, R.M., Ranganath, V.K., Furst, D.E., et al.: Validating and assessing the sensitivity of the Health Assessment Questionnaire-Disability Index-derived Short Form-6D in patients with early aggressive rheumatoid arthritis. J. Rheumatol. 36, 1150–1157 (2009)

    Article  PubMed  Google Scholar 

  13. Wolfe, F., Michaud, K., Wallenstein, G.: Scale Characteristics and Mapping Accuracy of the US EQ-5D, UK EQ-5D, and SF-6D in Patients with Rheumatoid Arthritis. J. Rheumatol. 37, 1615–1625 (2010)

    Article  PubMed  Google Scholar 

  14. Kosinski, M., Kujawski, S.C., Martin, R., Wanke, L.A., Buatti, M.C., Ware Jr, J.E., et al.: Health-related quality of life in early rheumatoid arthritis: impact of disease and treatment response. Am. J. Manag. Care 8, 231–240 (2002)

    PubMed  Google Scholar 

  15. Majithia, V., Geraci, S.A.: Rheumatoid arthritis: diagnosis and management. Am. J. Med. 120, 936–939 (2007)

    Article  PubMed  Google Scholar 

  16. Lillegraven, S., Kvien, T.K.: Measuring disability and quality of life in established rheumatoid arthritis. Best Pract. Res. Clin. Rheumatol. 21, 827–840 (2007)

    Article  PubMed  Google Scholar 

  17. Brooks, R.: EuroQol: the current state of play. Health Policy 37, 53–72 (1996)

    Article  PubMed  CAS  Google Scholar 

  18. Dolan, P., Gudex, C., Kind, P., Williams, A.: The time trade-off method: results from a general population study. Health Econ. 5, 141–154 (1996)

    Article  PubMed  CAS  Google Scholar 

  19. Dolan, P.: Modeling valuations for EuroQol health states. Med. Care 35, 1095–1108 (1997)

    Article  PubMed  CAS  Google Scholar 

  20. Yfantopoulos, J.: The Greek version of the EuroQol (EQ-5D) instrument. Arch. Hell. Med. 18, 180–191 (2001)

    Google Scholar 

  21. Kontodimopoulos, N., Pappa, E., Niakas, D., Yfantopoulos, J., Dimitrakaki, C., Tountas, Y.: Validity of the EQ-5D instrument in a Greek general population. Value Health 7, 1162–1169 (2008)

    Article  Google Scholar 

  22. Fries, J.F., Spitz, P.W., Kraines, R.G., Holman, H.R.: Measurement of patient outcome in arthritis. Arthritis Rheum. 23, 137–145 (1980)

    Article  PubMed  CAS  Google Scholar 

  23. Pincus, T., Summey, J.A., Soraci Jr, S.A., Wallston, K.A., Hummon, N.P.: Assessment of patient satisfaction in activities of daily living using a modified Stanford Health Assessment Questionnaire. Arthritis Rheum. 26, 1346–1353 (1983)

    Article  PubMed  CAS  Google Scholar 

  24. Uhlig, T., Haavardsholm, E.A., Kvien, T.K.: Comparison of the Health Assessment Questionnaire (HAQ) and the modified HAQ (MHAQ) in patients with rheumatoid arthritis. Rheumatology (Oxford) 45, 454–458 (2006)

    Article  CAS  Google Scholar 

  25. Ziebland, S., Fitzpatrick, R., Jenkinson, C., Mowat, A.: Comparison of two approaches to measuring change in health status in rheumatoid arthritis: the Health Assessment Questionnaire (HAQ) and modified HAQ. Ann. Rheum. Dis. 51, 1202–1205 (1992)

    Article  PubMed  CAS  Google Scholar 

  26. Serrano, M.A., Fabregat, J.B., Garzon, J.O.: Should the MHAQ ever be used? Ann. Rheum. Dis. 55, 271 (1996)

    Article  PubMed  CAS  Google Scholar 

  27. Stucki, G., Stucki, S., Bruhlmann, P., Michel, B.A.: Should the MHAQ ever be used? [reply to letter]. Ann. Rheum. Dis. 55, 271–272 (1996)

    Article  Google Scholar 

  28. Prevoo, M.L., van ‘t Hof, M.A., Kuper, H.H., van Leeuwen, M.A., van de Putte, L.B., van Riel, P.L.: Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum. 38, 44–48 (1995)

    Article  PubMed  CAS  Google Scholar 

  29. van Gestel, A.M., Prevoo, M.L., van ‘t Hof, M.A., van Rijswijk, M.H., van de Putte, L.B., van Riel, P.L.: Development and validation of the European League Against Rheumatism response criteria for rheumatoid arthritis. Comparison with the preliminary American College of Rheumatology and the World Health Organization/International League Against Rheumatism Criteria. Arthritis Rheum. 39, 34–40 (1996)

    Article  PubMed  Google Scholar 

  30. Grootendorst, P., Marshall, D., Pericak, D., Bellamy, N., Feeny, D., Torrance, G.W.: A model to estimate health utilities index mark 3 utility scores from WOMAC index scores in patients with osteoarthritis of the knee. J. Rheumatol. 34, 534–542 (2007)

    PubMed  Google Scholar 

  31. Sullivan, P.W., Lawrence, W.F., Ghushchyan, V.: A national catalog of preference-based scores for chronic conditions in the United States. Med. Care 43, 736–749 (2005)

    Article  PubMed  Google Scholar 

  32. Walters, S.J., Brazier, J.E.: Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Qual. Life Res. 14, 1523–1532 (2005)

    Article  PubMed  Google Scholar 

  33. Kaplan, R.M., Groessl, E.J., Sengupta, N., Sieber, W.J., Ganiats, T.G.: Comparison of measured utility scores and imputed scores from the SF-36 in patients with rheumatoid arthritis. Med. Care 43, 79–87 (2005)

    PubMed  Google Scholar 

  34. Harrison, M.J., Lunt, M., Verstappen, S.M., Watson, K.D., Bansback, N.J., Symmons, D.P.: Exploring the validity of estimating EQ-5D and SF-6D utility values from the Health Assessment Questionnaire in patients with inflammatory arthritis. Health Qual. Life Outcomes 8, 21 (2010)

    Article  PubMed  Google Scholar 

  35. Barton, G.R., Sach, T.H., Jenkinson, C., Avery, A.J., Doherty, M., Muir, K.R.: Do estimates of cost-utility based on the EQ-5D differ from those based on the mapping of utility scores? Health Qual. Life Outcomes 6, 51 (2008)

    Article  PubMed  Google Scholar 

  36. Harrison, M.J., Davies, L.M., Bansback, N.J., McCoy, M.J., Farragher, T.M., Verstappen, S.M., et al.: Why do patients with inflammatory arthritis often score states “worse than death” on the EQ-5D? An Investigation of the EQ-5D classification system. Value Health 12, 1026–1034 (2009)

    Article  PubMed  Google Scholar 

  37. Adams, R., Walsh, C., Veale, D., Bresnihan, B., FitzGerald, O., Barry, M.: Understanding the relationship between the EQ-5D, SF-6D, HAQ and disease activity in inflammatory arthritis. Pharmacoeconomics 28, 477–487 (2010)

    Article  PubMed  Google Scholar 

  38. Wolfe, F.: Which HAQ is best? A comparison of the HAQ, MHAQ and RA-HAQ, a difficult 8 item HAQ (DHAQ), and a rescored 20 item HAQ (HAQ20): analyses in 2,491 rheumatoid arthritis patients following leflunomide initiation. J. Rheumatol. 28, 982–989 (2001)

    PubMed  CAS  Google Scholar 

  39. Scott, D.L., Garrood, T.: Quality of life measures: use and abuse. Baillieres Best Pract. Res. Clin. Rheumatol. 14, 663–687 (2000)

    Article  PubMed  CAS  Google Scholar 

  40. Harrison, M.J., Davies, L.M., Bansback, N.J., Ingram, M., Anis, A.H., Symmons, D.P.: The validity and responsiveness of generic utility measures in rheumatoid arthritis: a review. J. Rheumatol. 35, 592–602 (2008)

    PubMed  Google Scholar 

  41. Marra, C.A., Woolcott, J.C., Kopec, J.A., Shojania, K., Offer, R., Brazier, J.E., et al.: A comparison of generic, indirect utility measures (the HUI2, HUI3, SF-6D, and the EQ-5D) and disease-specific instruments (the RAQoL and the HAQ) in rheumatoid arthritis. Soc. Sci. Med. 60, 1571–1582 (2005)

    Article  PubMed  Google Scholar 

  42. Marra, C.A., Esdaile, J.M., Guh, D., Kopec, J.A., Brazier, J.E., Koehler, B.E., et al.: A comparison of four indirect methods of assessing utility values in rheumatoid arthritis. Med. Care 42, 1125–1131 (2004)

    Article  PubMed  Google Scholar 

  43. Marra, C.A., Marion, S.A., Guh, D.P., Najafzadeh, M., Wolfe, F., Esdaile, J.M., et al.: Not all “quality-adjusted life years” are equal. J. Clin. Epidemiol. 60, 616–624 (2007)

    Article  PubMed  CAS  Google Scholar 

  44. Barton, G.R., Sach, T.H., Avery, A.J., Doherty, M., Jenkinson, C., Muir, K.R.: Comparing the performance of the EQ-5D and SF-6D when measuring the benefits of alleviating knee pain. Cost Eff. Resour. Alloc. 7, 12 (2009)

    Article  PubMed  Google Scholar 

  45. 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)

    Article  PubMed  Google Scholar 

  46. Versteegh, M.M., Rowen, D., Brazier, J.E., Stolk, E.A.: Mapping onto EQ-5D for patients in poor health. Health Qual. Life Outcomes 8, 141 (2010)

    Article  PubMed  Google Scholar 

  47. Anderson, J., Sayles, H., Curtis, J.R., Wolfe, F., Michaud, K.: Converting MHAQ, MDHAQ and HAQII scores into HAQ scores using models developed with a large cohort of RA patients. Arthritis Care Res. 62, 1481–1488 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Social Sciences, Hellenic Open University, Bouboulinas 57, 26222, Patras, Greece

    Nick Kontodimopoulos, Panagiotis Bozios, John Yfantopoulos & Dimitris Niakas

  2. Rheumatology Clinic, General Hospital Asklipieio Voulas, Athens, Greece

    Panagiotis Bozios

  3. National and Kapodistrian University of Athens, Athens, Greece

    John Yfantopoulos

Authors
  1. Nick Kontodimopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Panagiotis Bozios
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John Yfantopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dimitris Niakas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nick Kontodimopoulos.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kontodimopoulos, N., Bozios, P., Yfantopoulos, J. et al. Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients. Eur J Health Econ 14, 307–314 (2013). https://doi.org/10.1007/s10198-012-0376-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10198-012-0376-9

Keywords

JEL Classification

Search

Navigation