Aim Maturity-onset diabetes of the young is a monogenic form of familial, young-onset diabetes. It is rare (∼1% diabetes) and may be misdiagnosed as Type 1 diabetes and inappropriately treated with insulin. Type 1 diabetes is characterized by the presence of islet autoantibodies, including glutamate decarboxylase (GAD) and islet antigen-2 (IA-2) antibodies. The prevalence of islet autoantibodies is unknown in maturity-onset diabetes of the young and may have the potential to differentiate this form of diabetes from Type 1 diabetes. The aim of this study was to determine the prevalence of GAD and IA-2 antibodies in patients with maturity-onset diabetes of the young and Type 1 diabetes. Methods We measured plasma GAD and IA-2 antibodies in 508 patients with the most common forms of maturity-onset diabetes of the young (GCK: n = 227; HNF1A: n = 229; HNF4A: n = 52) and 98 patients with newly diagnosed Type 1 diabetes (diagnosed <6 months). Autoantibodies were considered positive if ≥ 99th centile of 500 adult control subjects. Results GAD and/or IA-2 antibodies were present in 80/98 (82%) patients with Type 1 diabetes and 5/508 (1%) patients with maturity-onset diabetes of the young. In the cohort with Type 1 diabetes, both GAD and IA-2 antibodies were detected in 37.8% of patients, GAD only in 24.5% and IA-2 only in 19.4%. All five patients with maturity-onset diabetes of the young with detectable antibodies had GAD antibodies and none had detectable IA-2 antibodies. Health services researchers are increasingly using discrete choice experiments (DCEs) to model a latent variable, be it health, health-related quality of life or utility. Unfortunately it is not widely recognised that failure to model variance heterogeneity correctly leads to bias in the point estimates. This paper compares variance heterogeneity latent class models with traditional multinomial logistic (MNL) regression models. Using the ICECAP-O quality of life instrument which was designed to provide a set of preference-based general quality of life tariffs for the UK population aged 65+, it demonstrates that there is both mean and variance heterogeneity in preferences for quality of life, which covariate-adjusted MNL is incapable of separating. Two policy-relevant mean groups were found: one group that particularly disliked impairments to independence was dominated by females living alone (typically widows). Males who live alone (often widowers) did not display a preference for independence, but instead showed a strong aversion to social isolation, as did older people (of either sex) who lived with a spouse. Approximately 6-10% of respondents can be classified into a third group that often misunderstood the task. Having a qualification of any type and higher quality of life was associated with smaller random component variances. This illustrates how better understanding of random utility theory enables richer inferences to be drawn from discrete choice experiments. The methods have relevance for all health studies using discrete choice tasks to make inferences about a latent scale, particular QALY valuation exercises that use DCEs, best-worst scaling and ranking tasks.
|Translated title of the contribution||Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters|
|Pages (from-to)||1957 - 1965|
|Number of pages||9|
|Journal||Social Science and Medicine|
|Publication status||Published - Jun 2010|