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. 2016 Jul 22;17(1):336.
doi: 10.1186/s13063-016-1457-3.

Bayesian Accrual Prediction for Interim Review of Clinical Studies: Open Source R Package and Smartphone Application

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Free PMC article

Bayesian Accrual Prediction for Interim Review of Clinical Studies: Open Source R Package and Smartphone Application

Yu Jiang et al. Trials. .
Free PMC article

Abstract

Background: Subject recruitment for medical research is challenging. Slow patient accrual leads to increased costs and delays in treatment advances. Researchers need reliable tools to manage and predict the accrual rate. The previously developed Bayesian method integrates researchers' experience on former trials and data from an ongoing study, providing a reliable prediction of accrual rate for clinical studies.

Methods: In this paper, we present a user-friendly graphical user interface program developed in R. A closed-form solution for the total subjects that can be recruited within a fixed time is derived. We also present a built-in Android system using Java for web browsers and mobile devices.

Results: Using the accrual software, we re-evaluated the Veteran Affairs Cooperative Studies Program 558- ROBOTICS study. The application of the software in monitoring and management of recruitment is illustrated for different stages of the trial.

Conclusions: This developed accrual software provides a more convenient platform for estimation and prediction of the accrual process.

Keywords: Bayesian methods; Smartphone application; Statistical software; Subject accrual.

Figures

Fig. 1
Fig. 1
The flowchart of the accrual software
Fig. 2
Fig. 2
The main menu of the R accrual package with three options
Fig. 3
Fig. 3
(a) An example of the use of accrual web-based software to calculate the number of patients can be recruited when one-quarter of the projected subjects has been recruited. (b) Use of the accrual smartphone application
Fig. 4
Fig. 4
The R accrual package can be used at the beginning of the clinical trial to calculate the number of patients that can be recruited. The red line is the investigators’ original expected recruitment. The white line and gray tunnel are the projected accrual with 95 % credible interval
Fig. 5
Fig. 5
Projected patient recruitment with 95 % credible interval for the Robot study at each month: the red line indicates the proposed sample size n = 158 and the blue line is final recruitment n = 126
Fig. 6
Fig. 6
Evaluation of the patient recruitment for each of the four sites in the ROBOTICS study with enrollment data from (a) the first 6 months (b) the first 12 months, and the TEAM-AD study with enrollment data from (c) the first 12 months and (d) the first 24 months. The red lines are the investigators’ original expected recruitment for each site. The white lines and gray tunnels are the averages of recruitment for the four sites with projected accrual with 95 % credible interval. The black lines are the accumulated patient enrollment for each of the 14 sites

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