title: The potential of composite cognitive scores for tracking progression in Huntington's disease.
abstract: BACKGROUND
  Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression.
  
  
  OBJECTIVE
  We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls.
  
  
  METHODS
  Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample.
  
  
  RESULTS
  In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period.
  
  
  CONCLUSIONS
  Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.
authors: Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
authors: Rebecca
authors: R
authors: Jones
authors: School of Psychology and Psychiatry, Monash University, Melbourne, Australia.
authors: Julie C
authors: JC
authors: Stout
authors: School of Psychology and Psychiatry, Monash University, Melbourne, Australia.
authors: Izelle
authors: I
authors: Labuschagne
authors: UCL Institute of Neurology, University College London, London, UK.
authors: Miranda
authors: M
authors: Say
authors: Inserm, UMR_S975, CRICM and UPMC Univ Paris 06, UMR_S975 and CNRS UMR 7225, Paris, France.
authors: Damian
authors: D
authors: Justo
authors: Department of Medical Genetics, University of British Columbia, Vancouver, Canada.
authors: Allison
authors: A
authors: Coleman
authors: Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.
authors: Eve M
authors: EM
authors: Dumas
authors: Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.
authors: Ellen
authors: E
authors: Hart
authors: UCL Institute of Neurology, University College London, London, UK.
authors: Gail
authors: G
authors: Owen
authors: Inserm, UMR_S975, CRICM and UPMC Univ Paris 06, UMR_S975 and CNRS UMR 7225, Paris, France AP-HP, Hôpital de la Salpêtriére, Département de Génétique et Cytogénétique, Paris, France.
authors: Alexandra
authors: A
authors: Durr
authors: Department of Medical Genetics, University of British Columbia, Vancouver, Canada.
authors: Blair R
authors: BR
authors: Leavitt
authors: Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.
authors: Raymund
authors: R
authors: Roos
authors: School of Psychology and Psychiatry, Monash University, Melbourne, Australia.
authors: Alison
authors: A
authors: O'Regan
authors: Departments of Psychiatry and Biostatistics, University of Iowa, IA, USA.
authors: Doug
authors: D
authors: Langbehn
authors: UCL Institute of Neurology, University College London, London, UK.
authors: Sarah J
authors: SJ
authors: Tabrizi
authors: Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.
authors: Chris
authors: C
authors: Frost
mesh_terms: D000328:Adult; D000375:Aging / Q000502:physiology; D003072:Cognition Disorders / Q000175:diagnosis* / Q000209:etiology* / Q000503:physiopathology; D018450:Disease Progression; D005260:Female; D006801:Humans; D006816:Huntington Disease / Q000150:complications* / Q000503:physiopathology; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009483:Neuropsychological Tests
keywords: 0.632 bootstrap; Huntington disease; cognition; composite score; effect size