Automated Generation of CONSORT Diagrams Using Relational Database SoftwareFunding This work was supported by National Institutes of Health and National Heart, Lung, and Blood Institute grant R18HL108788.
27 February 2018
28 November 2018
23 January 2019 (online)
Background Investigators conducting prospective clinical trials must report patient flow using the Consolidated Standards of Reporting Trials (CONSORT) statement. Depending on how data are collected, this can be a laborious, time-intensive process. However, because many trials enter data electronically, CONSORT diagrams may be generated in an automated fashion.
Objective Our objective was to use an off-the-shelf software to develop a technique to generate CONSORT diagrams automatically.
Methods During a recent trial, data were entered into FileMaker Pro, a commercially available software, at enrollment and three waves of follow-up. Patient-level data were coded to automatically generate CONSORT diagrams for use by the study team.
Results From August 2012 to July 2014, 1,044 participants were enrolled. CONSORT diagrams were generated weekly for study team meetings to track follow-ups at 1, 6, and 12 months, for 960 (92%), 921 (90%), and 871 (88%) participants who were contacted or deceased, respectively. Reasons for loss to follow-up were captured at each follow-up.
Conclusion CONSORT diagrams can be generated using a standard software for any trial and can facilitate data collection, project management, and reporting.
Protection of Human and Animal Subjects
This study did not involve human or animal subjects. The parent trial from which this study was conducted was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the Human Investigation Committee of Yale University.
- 1 Higgins JP, Altman DG, Gøtzsche PC. , et al; Cochrane Bias Methods Group; Cochrane Statistical Methods Group. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ 2011; 343: d5928
- 2 OnCore Enterprise Research. Build a research center of excellence. Available at: https://forteresearch.com/enterprise-research-oncore/ . Accessed August 18, 2017
- 3 REDCap. Available at: https://projectredcap.org . Accessed August 18, 2017
- 4 Cavenaugh JS, Snell P, Jeffries D, Waight PA, McConkey SJ. A relational database for management of flow cytometry and ELISpot clinical trial data. Cytometry B Clin Cytom 2007; 72 (01) 49-62
- 5 The CONSORT Group. Welcome to the CONSORT Website. Available at: http://www.consort-statement.org/ . Accessed March 14, 2016
- 6 Bhatti P, Schemitsch EH, Bhandari M. Managing data in surgical trials: a guide to modern-day data management systems. J Bone Joint Surg Am 2012; 94 (01) (Suppl. 01) 45-48
- 7 Bernstein SL, Rosner J, DeWitt M. , et al. Design and implementation of decision support for tobacco dependence treatment in an inpatient electronic medical record: a randomized trial. Transl Behav Med 2017; 7 (02) 185-195
- 8 FileMaker Pro. Available at: https://www.filemaker.com . Accessed July 27, 2018
- 9 Leff DR, Lovegrove RE, Darzi LA, Athanasiou T. Data collection, database development and quality control: guidance for clinical research studies. In: Key Topics in Surgical Research and Methodology. Berlin, Heidelberg: Springer; 2010: 305-320
- 10 Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009; 42 (02) 377-381