Abstract
The estimation of utilities outside of clinical trials remains a challenge, and in the context of rare diseases there are few options. In a recent trial in patients with non-dystrophic myotonia one of the main endpoints was a disease-specific QoL tool (Individualised Neuromuscular Quality of Life Questionnaire (InQoL)). This study describes mapping research to estimate utilities from this scale. With input from three clinical experts items (n=8) from the InQoL were selected which conceptually matched EQ-5D. A discrete choice experiment (DCE) survey described outcomes defined by the InQoL items and four response levels. UK general public participants completed the survey online (n=507). Conditional logit regression estimated the strength of preference for each item. These coefficient weights were then rescaled so that the worst state defined by InQoL had a value of -0.594, and the best state a value of 1.0 (in line with EQ-5D). Linear and exponential interpolation was used to estimate missing weights. Each InQoL item and response level was a significant predictor of choice. Some logical inconsistencies occurred between response levels – such that people preferred Someproblems to the upper anchor (Very little). To avoid this problem the coefficient weight was changed to be the same as the higher level. Items describing pain and depression had the greatest impact on utility. For moderate problems the weights were- Weakness (-0.02), Muscle locking (-0.03), Pain (-0.204), Tiredness (0), Daily activities (0), Leisure activities (-0.04); Anxiety (-0.04) and Depression (-0.08). This DCE approach allowed us to estimate utility weights from a measure collected in the trial despite the availability of only limited trial data. This method may help to address data shortages in rare disease evaluations where the collection of new data can be extremely challenging.
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