Multivariate prediction of motor diagnosis in Huntington's disease: 12 years of PREDICT‐HD
Open Access
- 4 September 2015
- journal article
- research article
- Published by Wiley in Movement Disorders
- Vol. 30 (12), 1664-1672
- https://doi.org/10.1002/mds.26364
Abstract
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. 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. 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. 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. © 2015 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder SocietyFunding Information
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke (5R01NS040068)
- CHDI Foundation, Inc (A6266, A2015)
- Cognitive and Functional Brain Changes in Preclinical Huntington's Disease (5R01NS054893)
This publication has 28 references indexed in Scilit:
- Random forests for genomic data analysisGenomics, 2012
- Cognitive Impairment in Huntington Disease: Diagnosis and TreatmentCurrent Neurology and Neuroscience Reports, 2011
- Indexing disease progression at study entry with individuals at‐risk for Huntington diseaseNeuropsychiatric Genetics, Part B of the American Journal of Medical Genetics (AJMG), 2011
- Challenges assessing clinical endpoints in early Huntington diseaseMovement Disorders, 2010
- High-Dimensional Variable Selection for Survival DataJournal of the American Statistical Association, 2010
- CAG‐repeat length and the age of onset in Huntington disease (HD): A review and validation study of statistical approachesAmerican Journal Of Medical Genetics Part B-Neuropsychiatric Genetics, 2010
- Detection of Huntington's disease decades before diagnosis: the Predict-HD studyJournal of Neurology, Neurosurgery & Psychiatry, 2008
- Huntington's DiseaseSeminars in Neurology, 2007
- Variable importance in binary regression trees and forestsElectronic Journal of Statistics, 2006
- A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomesCell, 1993