Swipe om te navigeren naar een ander artikel
The online version of this article (doi:10.1007/s11136-015-1145-x) contains supplementary material, which is available to authorized users.
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.
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.
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.
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.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
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. CrossRef
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. CrossRefPubMedPubMedCentral
Usha, C., Jennifer, E., & Philip, J. R. (2010). Age related macular degeneration. BMJ, 340, c981. CrossRef
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. CrossRef
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. CrossRef
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.
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. CrossRefPubMed
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. CrossRef
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.
NICE. (2013). Guide to the methods of technology appraisal. Manchester: The National Institute for Health and Care Excellence.
Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 12. CrossRef
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.
Wooldridge, J. M. (2009). Introductory econometrics: A modern approach. Mason: South Western, Cengage Learning.
Powell, J. L. (1984). Least absolute deviations estimation for the censored regression model. Journal of Econometrics, 25(3), 303–325. CrossRef
Jolliffe, D., Krushelnytskyy, B., & Semykina, A. (2000, November). Censored least absolute deviations estimator: CLAD. Stata Technical Bulletin, 58, 13–16.
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.
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.
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. CrossRefPubMedPubMedCentral
IVAN Study Team. (2011). IVAN study protocol V7.0: NIHR technology assessment programme.
- Generic and disease-specific estimates of quality of life in macular degeneration: mapping the MacDQoL onto the EQ-5D-3L
- Springer International Publishing