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Title: Prognosis of neurodegenerative diseases : methodological and empirical results for Multiple Sclerosis and Parkinson's disease
Author: Lawton, Michael A.
ISNI:       0000 0004 9359 1910
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2020
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Neurodegenerative diseases, like Multiple Sclerosis and Parkinson’s disease, lead to disability that worsens with time. Being able to predict prognosis in these diseases is important for both patients and clinicians when making medication choices and planning for the future. My aim was to look at drug effectiveness over a ten-year period in Multiple Sclerosis, in the absence of a long-term clinical trial, and to look at prognosis in Parkinson’s disease by deriving subtypes. I developed a longitudinal model for the untreated natural history of patients with Multiple Sclerosis using multilevel models. This model was used to predict the untreated trajectories of treated MS patients over a ten year period. A comparison between the observed treated trajectories and the predicted untreated trajectories gave an estimate of long-term drug effectiveness. I carried out intention-to-treat and per-protocol approaches along with imputed analyses to adjust for missing data. The medications were found to be effective in the long term. I used a k-means cluster analysis on the baseline phenotype of a large cohort of recently diagnosed Parkinson’s patients to attempt to derive subtypes. These subtypes were subsequently found to be associated with medication response. This approach was extended in another large inception cohort using a development and validation approach. Before combining the two cohorts in an analysis I had to harmonise the data from the cohorts as olfaction was measured using two different tests. I used Item Response Theory to convert the two tests onto the same scale. The harmonised baseline phenotypic data from both cohorts was used to estimate subtypes. This approach was relatively stable when comparing the actual and predicted subtypes in the smaller cohort. These subtypes were associated with differing rates of motor progression and to medication response.
Supervisor: Ben-Shlomo, Yoav ; Tilling, Kate Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available