F102 Huntington’s disease in Australia, socioeconomic and clinical aspects: a longitudinal analysis of the ENROLL-HD dataset

<h3>Background</h3> There has been a paucity of systematic information in Australia on how having HD, or having confirmed HD genetic risk, relates to quality of life and/or employment status. Better descriptive information on HD in Australia may inform policy-based and public health strategies for HD clinical care in Australia. <h3>Methods</h3> We examined visit 1 data from Australian Enroll-HD participants, grouped as HD-CAG expanded premanifest and manifest participants (n = 292 and n = 377, respectively) and non-CAG-expanded participants as a control group (n = 96). We used generalized mixed effects models to characterize associations between clinical, demographic measures, employment, and Quality of Life (QoL) measured using the SF-12, followed by multivariable logistic regression analysis of pairwise group comparisons. <h3>Results</h3> Average ages for the premanifest and manifest groups were 41.3 (SD = 12.4) and 54.3 (SD = 12.4) years respectively. 56.5% of participants were female. In the sample, 15.8% of the females and 23.8% of male participants were receiving disability support. The mean scores for the physical component summary score (PCS) and mental component summary score (MCS) of the quality of life in the manifest HD were 50.08 (SD = 9.36) and 49.99 (SD = 10.92), respectively, this figure was significantly lower than the control group for PCS (mean difference: 6.82, p-value=0.003). Comparing with other regions, the PCS and MCS were significantly higher in Australian HD manifest HD cases (PCS and MCS mean differences of 2.78, SD =0.60, p-value &lt;0.001 and 5.1, SD=0.95, p-value &lt;0.001, respectively, comparing with Europe HD cases). The mean CAP score was 91.48 (24.6 SD), which was significantly predictive for the level of quality of life and employment status. <h3>Conclusions</h3> This study characterizes the HD cases and their progression in the Australian context, with a focus on the QoL as an outcome measure and its predictive elements. The initial analysis showed that there are distinctive factors within the Australian healthcare system that enhance the QoL of HD patients.