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[P1–021]: IMPROVING THE STATISTICAL ANALYSIS OF COGNITIVE OUTCOMES IN RANDOMISED CONTROLLED TRIALS: THE ‘OPTIMISING THE ANALYSIS OF COGNITION COLLABORATION’ (OA‐COG)
Author(s) -
Scutt Polly,
Montgomery Alan,
Bath Philip M.
Publication year - 2017
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2017.06.088
Subject(s) - dementia , cognition , clinical trial , randomized controlled trial , cognitive decline , medicine , disease , psychology , psychiatry
Background:Over 800,000 people suffer with dementia in the UK. Despite being common, devastating to patients and their families, and costly in economic terms to society, the evidence base for the treatment of cognitive decline and dementia is small. One reason for this may be that the measures used to assess cognition in clinical trials are not sensitive to change and/or the analyses used are suboptimal. The ‘Optimising the analysis of cognition collaboration’ (OA-Cog) aims to identify the most efficient cognitive measurement and analysis technique for cognition data and dementia in randomised controlled trials including patients with or at risk of vascular dementia or Alzheimer’s disease. Methods: Chief investigators of randomised controlled trialswith cognitive outcome assessments are asked to share individual patient data from their trials. Variables requested include baseline prognostic factors, treatment group, cognitive measures (e.g. Mini Mental State Examination (MMSE), Alzheimer’s Disease Assessment Scale cognitive sub-score (ADAS-cog)) and other outcomemeasures (e.g. death, dementia). Shared trial data are merged into a single dataset and analysed using various endpoints (e.g. mean MMSE score at end of trial, MMSE score as a gradient over time) and statistical methods (e.g. Wilcoxon rank-sum test, repeated measures ANOVA) in order to identify which is the most efficient approach. Methods for dealing with missing data and, in particular, the case of missing data due to death will be addressed; currently, such patients are often ignored from analyses. Results:As of 23 December 2016, data from 32 clinical trials have been shared with the collaboration. Some of these trials havemore than two treatment arms, so 50 datasets are availablewith a total of 120,576 participants.Conclusions:Optimising the design and analysis of cognition trials will allow future trials to detect smaller but still clinically important effects, and/or have smaller sample sizes than current trials.