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Project status: In progress
Parkinson's disease (PD) is a common neurological disorder with unknown etiology and complex symptom patterns, ranging from characteristic motor skill impairments to cognitive and psychiatric disability.
With only symptomatic treatments available for slowing progression and reducing overall severity, this research is focussed on better understanding patient responses to treatment and the identification of subgroups of patients for whom post treatment benefit is maximised. In particular, this work explores the effects of surgical intervention for PD, namely pallidotomy and deep brain stimulation (DBS).
Initial work into the effects of pallidotomy has investigated the allocation of subjects into groups of similar treatment outcome, based on a set of clinical and demographic variables. This was achieved using Classification and Regression Trees (CART) in order to derive rules to classify patients into various risk categories. There has been further research into the classification of patients prior to treatment using finite mixture modelling. In time, these models will be used to assess the effects of DBS for different patient subgroups.
Other areas of research in this project will include the analysis of preoperative fMRI data and deep brain electrode recordings, a common source of data arising from DBS. It is envisaged that the combination of these areas will provide detailed insights into patient responses and eventually, future patient selection.