Nimble data in ALOIS, a study based register: a cross-sectional analysis of dementia trials

Article type
Authors
Noel-Storr A1, Hall S2
1Cochrane Dementia and Cognitive Improvement Group, Oxford University, United Kingdom
2Cochrane Dementia and Cognitive Improvement Group, Oxford University, Canada
Abstract
Background: The Cochrane Dementia Group's Specialised Register housed in the Cochrane Register of Studies (CRS) and made available online in ALOIS, named after Alois Alzheimer, is a register of controlled trials in the area of dementia treatment, management and prevention. The register provides two main functions. It links trial reports related to each study together, and each trial is described in a structured way according to structured reporting guidance. ALOIS currently contains over 5000 fully annotated trials in dementia.
Objectives: The objective of this study is to perform a cross-sectional analysis on trials added to the Dementia Group's register in 2014 in order to calculate a number of key metrics concerning trial aims, trial status, trial size and trial interventions.
Methods: We will run a search for trials added to the dementia segment in 2014. We will download the results into Excel and perform the following analyses: total number of trials; number of trials that were pharmacological in nature and number of trials that were non-pharmacological; total number of participants across all trials and then split into non-pharmacological and pharmacological; number of trials completed, ongoing or planned; trial aims; and trials for which there is, as yet, no Cochrane Review.
Results: The results from this cross-sectional analysis will be presented in the poster.
Conclusions: ALOIS, a study based register, provides us with a simple, yet very effective way to assess the evidence landscape of a particular domain, namely dementia. It has proved an invaluable tool in helping to identify potentially relevant trials for Cochrane Reviews. It also helps to horizon scan for gaps in evidence synthesis and could help funders and researchers avoid unnecessary duplication of effort.