title: Site-specific predictors of successful recruitment to a perinatal clinical trial.
abstract: BACKGROUND
  With large collaborations needed to reach sample size requirements for relatively rare events, a major challenge for multi-centre clinical trials is efficiency of recruitment at individual sites. We used data from an international, multi-centre, randomised trial of preterm prelabour rupture of membranes to assess any impact on recruitment following the introduction of a new Clinical Trial Agreement and to identify site-specific predictors of recruitment to the trial for the purpose of targeting future recruitment sites and strategies.
  
  
  METHODS
  The outcome measure was recruitment rate per 10,000 births, and according to this, an average recruitment rate was determined. Factors that were considered potentially predictive of recruitment above the average rate were classified according to three broad themes: 'ethics and regulatory requirements', 'characteristics of site investigators' and the 'research culture' at the collaborating site. Data were analysed using contingency tables and logistic regression modelling.
  
  
  RESULTS
  At 31 January 2009, following the introduction of the Clinical Trial Agreement, 39 centres had obtained ethics approval to commence recruitment, and 38 centres had enrolled at least one woman. Time to first recruit ranged from 25 days to 584 days. Recruitment rates ranged from 0.18 to 6.0 per 10,000 births (mean 1.71/10,000 births) per month. Factors most associated with above-average recruitment rate were the following: implementation of a clearly defined 'system' of recruitment, engagement of other staff, time from ethics approval to first recruit and provision of a dedicated trial coordinator.
  
  
  CONCLUSIONS
  A delay of greater than 3 months in approval of the new Clinical Trial Agreement had an effect which extended into the third year of the trial. Characteristics that were indicative of the presence of a 'system' were the best predictors of recruitment. It may be more effective to limit recruitment sites and focus resources on those sites where investigators are engaged with trial processes and have adequate resources and structures to support them.
authors: School of Medicine, Sydney, University of Notre Dame Australia, Darlinghurst, NSW, Australia Kolling Institute of Medical Research, Northern Clinical School, Medicine, University of Sydney, Sydney, NSW, Australia kate.levett@nd.edu.au.
authors: Kate M
authors: KM
authors: Levett
authors: Kolling Institute of Medical Research, Northern Clinical School, Medicine, University of Sydney, Sydney, NSW, Australia.
authors: Christine L
authors: CL
authors: Roberts
authors: School of Public Health, University of Sydney, Sydney, NSW, Australia.
authors: Judy M
authors: JM
authors: Simpson
authors: Kolling Institute of Medical Research, Northern Clinical School, Medicine, University of Sydney, Sydney, NSW, Australia.
authors: Jonathan M
authors: JM
authors: Morris
mesh_terms: D001118:Argentina; D001315:Australia; D004534:Egypt; D005260:Female; D005322:Premature Rupture of Fetal Membranes; D061847:Hospitals, High-Volume / Q000706:statistics & numerical data; D061846:Hospitals, Low-Volume / Q000706:statistics & numerical data; D006771:Hospitals, Maternity / Q000706:statistics & numerical data*; D006801:Humans; D007231:Infant, Newborn; D007363:Intensive Care Units, Neonatal / Q000706:statistics & numerical data*; D015337:Multicenter Studies as Topic / Q000706:statistics & numerical data*; D009520:New Zealand; D009664:Norway; D018579:Patient Selection; D011247:Pregnancy; D016032:Randomized Controlled Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D013019:South Africa; D006113:United Kingdom
keywords: perinatal; predictive factors; randomised controlled trial; recruitment