Mapping the Modified Rankin Scale (mRS) Measurement into the Generic EuroQol (EQ-5D) Health Outcome

Background. Mapping disease-specific instruments into generic health outcomes or utility values is an expanding field of interest in health economics. This article constructs an algorithm to translate the modified Rankin scale (mRS) into EQ-5D utility values. Methods. mRS and EQ-5D information was derived from stroke or transient ischemic attack (TIA) patients identified as part of the Oxford Vascular study (OXVASC). Ordinary least squares (OLS) regression was used to predict UK EQ-5D tariffs from mRS scores. An alternative method, using multinomial logistic regression with a Monte Carlo simulation approach (MLogit) to predict responses to each EQ-5D question, was also explored. The performance of the models was compared according to the magnitude of their predicted-to-actual mean EQ-5D tariff difference, their mean absolute and mean squared errors (MAE and MSE), and associated 95% confidence intervals (CIs). Out-of-sample validation was carried out in a subset of coronary disease and peripheral vascular disease (PVD) patients also identified as part of OXVASC but not used in the original estimation. Results. The OLS and MLogit yielded similar MAE and MSE in the internal and external validation data sets. Both approaches also underestimated the uncertainty around the actual mean EQ-5D tariff producing tighter 95% CIs in both data sets. Conclusions. The choice of algorithm will be dependent on the study aim. Individuals outside the United Kingdom may find it more useful to use the multinomial results, which can be used with different country-specific tariff valuations. However, these algorithms should not replace prospective collection of utility data.

[1]  J. Brazier,et al.  Predicting the short form-6D preference-based index using the eight mean short form-36 health dimension scores: estimating preference-based health-related utilities when patient level data are not available. , 2009, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[2]  Haomiao Jia,et al.  Mapping the SF-12 to the EuroQol EQ-5D Index in a National US Sample , 2004, Medical decision making : an international journal of the Society for Medical Decision Making.

[3]  B. Norrving,et al.  Assessment of Functional Outcome in a National Quality Register for Acute Stroke: Can Simple Self-Reported Items Be Transformed Into the Modified Rankin Scale? , 2007, Stroke.

[4]  Vahram Ghushchyan,et al.  Mapping the EQ-5D Index from the SF-12: US General Population Preferences in a Nationally Representative Sample , 2006, Medical decision making : an international journal of the Society for Medical Decision Making.

[5]  A. Mattioli,et al.  Collaborative meta-analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients , 2002, BMJ : British Medical Journal.

[6]  John Brazier,et al.  Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? , 2009, Health and quality of life outcomes.

[7]  N. Taub,et al.  Assessment of Scales of Disability and Handicap for Stroke Patients , 1991, Stroke.

[8]  Marthe R. Gold,et al.  Mapping the SF-12 to Preference-Based Instruments: Convergent Validity in a Low-Income, Minority Population , 2003, Medical care.

[9]  U. Schulz,et al.  Improving the Assessment of Outcomes in Stroke: Use of a Structured Interview to Assign Grades on the Modified Rankin Scale , 2002, Stroke.

[10]  Anthony O'Hagan,et al.  Modelling SF-6D health state preference data using a nonparametric Bayesian method. , 2007, Journal of health economics.

[11]  G. Bonsel,et al.  Comparing the standard EQ-5D three-level system with a five-level version. , 2008, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[12]  M. Hennerici,et al.  High-dose atorvastatin after stroke or transient ischemic attack. , 2006, The New England journal of medicine.

[13]  S. Gutnikov,et al.  Change in stroke incidence, mortality, case-fatality, severity, and risk factors in Oxfordshire, UK from 1981 to 2004 (Oxford Vascular Study) , 2004, The Lancet.

[14]  Uwe Siebert,et al.  Long-Term Outcome After Stroke Evaluating Health-Related Quality of Life Using Utility Measurement , 2006 .

[15]  J. Brazier,et al.  The estimation of a preference-based measure of health from the SF-36. , 2002, Journal of health economics.

[16]  Timothy W. Cooke,et al.  Improving the assessment of outcomes in stroke: use of a structured interview to assign grades on the modified Rankin Scale. , 2002, Stroke.

[17]  Oliver Rivero-Arias,et al.  Estimating the Association between SF-12 Responses and EQ-5D Utility Values by Response Mapping , 2006, Medical decision making : an international journal of the Society for Medical Decision Making.

[18]  Leandro Provinciali,et al.  Secondary prevention in non-rheumatic atrial fibrillation after transient ischaemic attack or minor stroke , 1993 .

[19]  J. A. Calvin Regression Models for Categorical and Limited Dependent Variables , 1998 .

[20]  Uwe Siebert,et al.  Long-Term Outcome After Stroke: Evaluating Health-Related Quality of Life Using Utility Measurements , 2006, Stroke.

[21]  R. Holman,et al.  A model to estimate the lifetime health outcomes of patients with Type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68) , 2004, Diabetologia.

[22]  W. Greene,et al.  计量经济分析 = Econometric analysis , 2009 .

[23]  D. Feeny,et al.  Responsiveness of generic health-related quality of life measures in stroke , 2005, Quality of Life Research.

[24]  Eaft Study Group Secondary prevention in non-rheumatic atrial fibrillation after transient ischaemic attack or minor stroke , 1993, The Lancet.

[25]  M. Eliasziw,et al.  Endarterectomy for symptomatic carotid stenosis in relation to clinical subgroups and timing of surgery , 2004, The Lancet.

[26]  Catherine Sudlow,et al.  Collaborative meta-analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients , 2002, BMJ : British Medical Journal.

[27]  P. Dolan,et al.  The time trade-off method: results from a general population study. , 1996, Health economics.