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    Multivariate prediction of motor diagnosis in Huntington's disease: 12 years of PREDICT-HD

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    Author
    Long, JD; Paulsen, JS
    Date
    2015-10-01
    Source Title
    Movement Disorders
    Publisher
    WILEY
    University of Melbourne Author/s
    Komiti, Angela; Goh, Anita; Loi, Samantha
    Affiliation
    Psychiatry
    Obstetrics and Gynaecology
    Metadata
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    Document Type
    Journal Article
    Citations
    Long, J. D. & Paulsen, J. S. (2015). Multivariate prediction of motor diagnosis in Huntington's disease: 12 years of PREDICT-HD. MOVEMENT DISORDERS, 30 (12), pp.1664-1672. https://doi.org/10.1002/mds.26364.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/258037
    DOI
    10.1002/mds.26364
    Abstract
    BACKGROUND: It is well known in Huntington's disease that cytosine-adenine-guanine expansion and age at study entry are predictive of the timing of motor diagnosis. The goal of this study was to assess whether additional motor, imaging, cognitive, functional, psychiatric, and demographic variables measured at study entry increased the ability to predict the risk of motor diagnosis over 12 years. METHODS: One thousand seventy-eight Huntington's disease gene-expanded carriers (64% female) from the Neurobiological Predictors of Huntington's Disease study were followed up for up to 12 y (mean = 5, standard deviation = 3.3) covering 2002 to 2014. No one had a motor diagnosis at study entry, but 225 (21%) carriers prospectively received a motor diagnosis. Analysis was performed with random survival forests, which is a machine learning method for right-censored data. RESULTS: Adding 34 variables along with cytosine-adenine-guanine and age substantially increased predictive accuracy relative to cytosine-adenine-guanine and age alone. Adding six of the common motor and cognitive variables (total motor score, diagnostic confidence level, Symbol Digit Modalities Test, three Stroop tests) resulted in lower predictive accuracy than the full set, but still had twice the 5-y predictive accuracy than when using cytosine-adenine-guanine and age alone. Additional analysis suggested interactions and nonlinear effects that were characterized in a post hoc Cox regression model. CONCLUSIONS: Measurement of clinical variables can substantially increase the accuracy of predicting motor diagnosis over and above cytosine-adenine-guanine and age (and their interaction). Estimated probabilities can be used to characterize progression level and aid in future studies' sample selection.

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