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Sequential patient recruitment monitoring in multi-center clinical trials
Commun. Stat. Appl. Methods, CSAM 2018;25:501-512
Published online September 30, 2018
© 2018 Korean Statistical Society.

Dong-Yun Kim1,a, Sung-Min Hanb, Marston Youngblood Jrc

aNational Heart, Lung and Blood Institute / National Institutes of Health, USA;
bOpen Source Electronic Health Record Alliance (OSEHRA), USA;
cThe University of North Carolina at Chapel Hill, USA
Correspondence to: Mathematical Statistician, Office of Biostatistics Research, National Heart, Lung and Blood Institute, National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD 20817, USA. E-mail: dong-yun.kim@nih.gov
Received March 2, 2018; Revised August 17, 2018; Accepted August 17, 2018.
 Abstract
We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.
Keywords : patient recruitment, continuous monitoring, clinical trial, sequential probability ratio test