A Hawton1, C Green, C J Telford, D E Wright, J P Zajicek. 1. Health Economics Group, PenCLAHRC, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK. annie.hawton@pms.ac.uk
Abstract
BACKGROUND: Walking impairment has a major influence on the quality of life of people with multiple sclerosis (MS). The Multiple Sclerosis Walking Scale (MSWS-12) assesses the impact of MS on walking ability from the patient's perspective, but in its current form, is not amenable for use in many policy decision-making settings. OBJECTIVES: Statistical 'mapping' methods were used to convert MSWS-12 scores to EQ-5D health state values. METHODS: The relationship between the measures was estimated using cohort data from people with MS in South West England. Regression analyses were conducted, estimation errors assessed, and predictive performance of the best models tested using longitudinal data. RESULTS: Model performance was in line with that of other mapping studies, with the best-performing models being an ordinary least squares (OLS) model using MSWS-12 item scores, and an OLS model using the total MSWS-12 score and its squared term. CONCLUSIONS: A process has been described whereby data from a patient-reported outcome measure (MSWS-12) can be converted to (EQ-5D) health state values. These values may be used to consider the health-related quality of life of people with MS, to estimate quality adjusted life-years for use in effectiveness and cost-effectiveness analyses, and to inform health policy decisions.
BACKGROUND: Walking impairment has a major influence on the quality of life of people with multiple sclerosis (MS). The Multiple Sclerosis Walking Scale (MSWS-12) assesses the impact of MS on walking ability from the patient's perspective, but in its current form, is not amenable for use in many policy decision-making settings. OBJECTIVES: Statistical 'mapping' methods were used to convert MSWS-12 scores to EQ-5D health state values. METHODS: The relationship between the measures was estimated using cohort data from people with MS in South West England. Regression analyses were conducted, estimation errors assessed, and predictive performance of the best models tested using longitudinal data. RESULTS: Model performance was in line with that of other mapping studies, with the best-performing models being an ordinary least squares (OLS) model using MSWS-12 item scores, and an OLS model using the total MSWS-12 score and its squared term. CONCLUSIONS: A process has been described whereby data from a patient-reported outcome measure (MSWS-12) can be converted to (EQ-5D) health state values. These values may be used to consider the health-related quality of life of people with MS, to estimate quality adjusted life-years for use in effectiveness and cost-effectiveness analyses, and to inform health policy decisions.
Authors: Stavros Petrou; Oliver Rivero-Arias; Helen Dakin; Louise Longworth; Mark Oppe; Robert Froud; Alastair Gray Journal: Pharmacoeconomics Date: 2015-10 Impact factor: 4.981
Authors: Jasmine Peak; Ilias Goranitis; Ed Day; Alex Copello; Nick Freemantle; Emma Frew Journal: Health Qual Life Outcomes Date: 2018-05-30 Impact factor: 3.186