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 OJO  Vol.5 No.4 , April 2015
Mapping the EQ-5D-5L Utility Scores: A Pilot Study in Orthopaedic Patients
Abstract: Objective: The purpose of this study is to investigate whether the LE CAT, PROMIS PF CAT, Depression CAT, or Pain CAT can be used as a proxy for the EQ-5D-5L. Background: Patient-reported out-come measures have become vital tools for physicians to understand the effectiveness and value of treatment and care. Methods: This study was conducted in 2012 with 116 patients that took the EQ-5D-5L and a number of patient-reported outcome instruments in a university orthopaedic clinic. Regression analyses were conducted to predict EQ-5D-5L index scores from the LE CAT, PROMIS PF CAT, Depression CAT, and Pain CAT. Results: All predictors, separately or combined, significantly predicted the EQ-5D-5L index scores (p < 0.0001). The LE CAT was the best predictor; it alone accounted for 37% of the variability in the EQ-5D-5L. When combining patient-reported outcome measures, the best predicting model was the one consisting of the LE CAT, Depression CAT and Pain CAT; they explained for 43.9% of the variance in EQ-5D-5L. Conclusions: The findings provide encouraging news that the LE CAT, PF CAT, Depression CAT and Pain CAT can be used alone or in combination as a proxy for the EQ-5D-5L. Researchers have the options of using these patient-reported outcome measures for economic evaluations and medical intervention studies.
Cite this paper: Hung, M. , Cheng, C. , Hon, S. and Bounsanga, J. (2015) Mapping the EQ-5D-5L Utility Scores: A Pilot Study in Orthopaedic Patients. Open Journal of Orthopedics, 5, 67-81. doi: 10.4236/ojo.2015.54010.
References

[1]   Deshpande, P.R., Rajan, S., Sudeepthi, B.L. and Abdul Nazir, C.P. (2011) Patient-Reported Outcomes: A New Era in Clinical Research. Perspectives in Clinical Research, 2, 137-144.
http://dx.doi.org/10.4103/2229-3485.86879

[2]   Myers, A.M., Holliday, P.J., Harvey, K.A. and Hutchinson, K.S. (1993) Functional Performance Measures: Are They Superior to Self-Assessments? Journal of Gerontology, 48, M196-M206.
http://dx.doi.org/10.1093/geronj/48.5.M196

[3]   Hidding, A., van Santen, M., De Klerk, E., Gielen, X., Boers, M., Geenen, R., Vlaeyen, J., Kester, A. and van der Linden, S. (1994) Comparison between Self-Report Measures and Clinical Observations of Functional Disability in Ankylosing Spondylitis, Rheumatoid Arthritis and Fibromyalgia. The Journal of Rheumatology, 21, 818-823.

[4]   Reuben, D.B., Valle, L.A., Hays, R.D. and Siu, A.L. (1995) Measuring Physical Function in Community-Dwelling Older Persons: A Comparison of Self-Administered, Interviewer-Administered, and Performance-Based Measures. Journal of the American Geriatrics Society, 43, 17-23.

[5]   Hung, M., Clegg, D.O., Greene, T. and Saltzman, C.L. (2011) Evaluation of the PROMIS Physical Function Item Bank in Orthopaedic Patients. Journal of Orthopaedic Research, 29, 947-953.
http://dx.doi.org/10.1002/jor.21308

[6]   Hung, M., Baumhauer, J.F., Latt, L.D., Saltzman, C.L., SooHoo, N.F., Hunt, K.J., and National Orthopaedic Foot and Ankle Outcomes Research Network (2013) Validation of PROMIS® Physical Function Computerized Adaptive Tests for Orthopaedic Foot and Ankle Outcome Research. Clinical Orthopaedics and Related Research® 471, 3466-3474.
http://dx.doi.org/10.1007/s11999-013-3097-1

[7]   Hung, M., Clegg, D.O., Greene, T., Weir, C. and Saltzman, C.L. (2012) A Lower Extremity Physical Function Computerized Adaptive Testing Instrument for Orthopaedic Patients. Foot & Ankle International, 33, 326-335.
http://dx.doi.org/10.3113/FAI.2012.0326

[8]   Herdman, M., Gudex, C., Lloyd, A., Janssen, M.F., Kind, P., Parkin, D., Bonsel, G. and Badia, X. (2011) Development and Preliminary Testing of the New Five-Level Version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20, 1727-1736.
http://dx.doi.org/10.1007/s11136-011-9903-x

[9]   Janssen, M.F., Birnie, E. and Bonsel, G.J. (2008) Quantification of the Level Descriptors for the Standard EQ-5D Three-Level System and a Five-Level Version According to Two Methods. Quality of Life Research, 17, 463-473.
http://dx.doi.org/10.1007/s11136-008-9318-5

[10]   Janssen, M.F., Pickard, A.S., Golicki, D., Gudex, C., Niewada, M., Scalone, L., Swinburn, P. and Busschbach, J. (2013) Measurement Properties of the EQ-5D-5L Compared to the EQ-5D-3L across Eight Patient Groups: A Multi-Country Study. Quality of Life Research, 22, 1717-1727.
http://dx.doi.org/10.1007/s11136-012-0322-4

[11]   Pickard, A.S., De Leon, M.C., Kohlmann, T., Cella, D. and Rosenbloom, S. (2007) Psychometric Comparison of the Standard EQ-5D to a 5 Level Version in Cancer Patients. Medical Care, 45, 259-263.
http://dx.doi.org/10.1097/01.mlr.0000254515.63841.81

[12]   Tran, B.X., Ohinmaa, A. and Nguyen, L.T. (2012) Quality of Life Profile and Psychometric Properties of the EQ-5D-5L in HIV/AIDS Patients. Health and Quality of Life Outcomes, 10, 132.
http://dx.doi.org/10.1186/1477-7525-10-132

[13]   Brazier, J., Roberts, J. and Deverill, M. (2002) The Estimation of a Preference-Based Measure of Health from the SF-36. Journal of Health Economics, 21, 271-292.
http://dx.doi.org/10.1016/S0167-6296(01)00130-8

[14]   Brazier, J.E. and Roberts, J. (2004) The Estimation of a Preference-Based Measure of Health from the SF-12. Medical Care, 42, 851-859.
http://dx.doi.org/10.1097/01.mlr.0000135827.18610.0d

[15]   Cortesi, P.A., Scalone, L., Belisari, A., Bonamonte, D., Cannavo, S.P., Cristaudo, A., De Pità, O., Gallo, R., Giannetti, A., Gola, M., Pigatto, P.D. and Mantovani, L.G. (2014) Cost and Quality of Life in Patients with Severe Chronic Hand Eczema Refractory to Standard Therapy with Topical Potent Corticosteroids. Contact Dermatitis, 70, 158-168.
http://dx.doi.org/10.1111/cod.12130

[16]   Erickson, P. (1998) Evaluation of a Population-Based Measure of Quality of Life: The Health and Activity Limitation Index (HALex). Quality of Life Research, 7, 101-114.
http://dx.doi.org/10.1023/A:1008897107977

[17]   Shaw, J.W., Johnson, J.A. and Coons, S.J. (2005) US Valuation of the EQ-5D Health States: Development and Testing of the D1 Valuation Model. Medical Care, 43, 203-220.
http://dx.doi.org/10.1097/00005650-200503000-00003

[18]   Gray, A.M., Rivero-Arias, O. and Clarke, P.M. (2006) Estimating the Association between SF-12 Responses and EQ-5D Utility Values by Response Mapping. Medical Decision Making, 26, 18-29.
http://dx.doi.org/10.1177/0272989X05284108

[19]   Lawrence, W.F. and Fleishman, J.A. (2004) Predicting EuroQoL EQ-5D Preference Scores from the SF-12 Health Survey in a Nationally Representative Sample. Medical Decision Making, 24, 160-169.
http://dx.doi.org/10.1177/0272989X04264015

[20]   Nan, L., Johnson, J.A., Shaw, J.W. and Coons, S.J. (2007) A Comparison of EQ-5D Index Scores Derived from the US and UK population-Based Scoring Functions. Medical Decision Making, 27, 321-326.
http://dx.doi.org/10.1177/0272989X07300603

[21]   Sullivan, P.W. and Ghushchyan, V. (2006) Mapping the EQ-5D Index from the SF-12: US General Population Preferences in a Nationally Representative Sample. Medical Decision Making, 26, 401-409.
http://dx.doi.org/10.1177/0272989X06290496

[22]   Revicki, D.A., Kawata, A.K., Harnam, N., Chen, W.-H., Hays, R.D. and Cella, D. (2009) Predicting EuroQol (EQ-5D) Scores from the Patient-Reported Outcomes Measurement Information System (PROMIS) Global Items and Domain Item Banks in a United States Sample. Quality of Life Research, 18, 783-791.
http://dx.doi.org/10.1007/s11136-009-9489-8

 
 
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