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051 Novel patient pre-screening model improves patient recruitment and reduces screen-failure rates for AD clinical trials
  1. Lucianne Dobson1,2,
  2. Miguel Rosa-Grilo1,2,
  3. Catherine Mummery1,2
  1. 1Dementia Research Centre, UCL Queen Square Institute of Neurology
  2. 2National Hospital for Neurology and Neurosurgery

Abstract

Rapid recruitment of participants is essential for the execution of clinical trials in Alzheimer’s disease (AD). Our objective was to improve site-led recruitment and screen-failure rates for clinical trials in AD by developing a novel patient pre-screening model. Information relating to sources of patient pre-screening activities was collated from recruitment data sources across two interventional and eight observational clinical trials in AD. The most efficient sources of recruitment were via the Cognitive Disorders Clinics, Join Dementia Research (JDR) website and referrals across research teams within the department. Adaptations to the patient identification and pre-screening processes led to a significant increase in identification of patients and recruitment to studies: 800% increase in patient identification and 430% increase in patient enrolment 2015–2018. Our model has also been consistently shown to decrease screen-failure rate (IONIS MAPTRx trial - local screen-fail rate of 40% compared with 70% rest of the world; ENGAGE - 50% screened were randomised locally compared with 27% globally). We have developed a novel pre-screening model which we have shown to consistently increase patient identification numbers, improve recruitment and decrease screen-failure rates. Implementation on a wider scale could significantly reduce costs and delays incurred by the majority of AD clinical trials.

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