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The quality-adjusted life-year (QALY) is recommended for use as an outcome measure for cost-effectiveness analyses by several national decision-making bodies, eg the National Institute for Health and Care Excellence (NICE). Symptom-specific outcome measures, such as the FSS, provide a standardised means of describing вЂњhealth statesвЂќ that may be experienced by patients, but do not provide data in the format required by many decision-making bodies to assess cost-effectiveness. The Fatigue Severity Scale (FSS) is frequently used in clinical trials of interventions for fatigue in people with MS, including carnitine, amantadine, aspirin, modafinil and cognitive behavioural therapy. Fatigue is the most common symptom experienced by people with MS, and has a considerable impact on quality of life. Clinical trials of interventions that target particular symptoms frequently use symptom-specific outcome measures in order to maximise sensitivity and responsiveness to change.

Meanwhile, increasing emphasis has been placed on achieving вЂњvalue for moneyвЂќ within healthcare systems. Over the last two decades, various disease-modifying and symptomatic treatments have been developed for people with Multiple Sclerosis (MS). These values may be used to estimate quality-adjusted life-years for use in cost-effectiveness analyses and to consider the health-related quality of life of people with multiple sclerosis, thereby informing health policy decisions. Here we present algorithms to convert Fatigue Severity Scales scores to health state utility values based on three preference-based measures. For the SF-6D, the best performing model used an ordinary least squares specification, with Fatigue Severity Scale total score as the only predictor.

ResultsДЇor the EQ-5D and the Multiple Sclerosis Impact Scale-8D, the best performing models used a censored least absolute deviation specification, with Fatigue Severity Scale total score, age and gender as predictors. Estimation errors were assessed and predictive performance of the best models as tested in a separate sample ( nВ =вЂ‰352). The relationships between the measures were estimated through regression analysis using cohort data from 1056 people with multiple sclerosis in South West England. The objective of this study was to use statistical mapping methods to convert Fatigue Severity Scale scores to health state utility values from three preference-based measures: the EQ-5D-3L, SF-6D and Multiple Sclerosis Impact Scale-8D. The Fatigue Severity Scale is a frequently used patient-reported measure of fatigue impact, but does not generate the health state utility values required to inform cost-effectiveness analysis, limiting its applicability within decision-making contexts. It is possible to influence this decision by using the 'Edit -> Options -> Interactive -> Reading pre-8.0 data files' menus.Fatigue has a major influence on the quality of life of people with multiple sclerosis. However, if you import the Excel file and save it right away, then the measurement levels are considered defined and SPSS won't change them.

SPSS will try to assign a measurement level using the rules above when you do a data pass. When the data first comes in, even though you see the default 'scale' for most of them, they are not really defined yet. These are the rules that apply to data files that do not have measurement levels defined, such as in the case of importing an Excel file. Numeric variables without defined value labels and more than a specified number of unique values are set to scale. Numeric variables without defined value labels but less than a specified number of unique values are set to nominal/ordinal. String and numeric variables with defined value labels are set to ordinal. String (alphanumeric) variables are set to nominal. From our documentation on measurement level:ДЇor SPSS-format data files created in earlier versions of SPSS products, the following rules apply:

Eazydraw independent scale not available