Interactive statistical monitoring to optimize review of potential clinical trial issues during study conduct

Background: Statistical monitoring involves the review of prospective study data collected in participating sites to detect intra/inter patients and sites inconsistencies. We report methods and results of statistical monitoring in a phase IV clinical trial. Method: PRO-MSACTIVE is a study evaluating ocrelizumab in active relapsing multiple sclerosis (RMS) patients in France. Specific statistical methods (volcano plots, mahalanobis distance, funnel plot …) have been applied to a SDTM database to detect potential issues. R-Shiny application was developed to generate an interactive web application in order to ease site and/or patients identification during statistical data review meetings. Results: The PRO-MSACTIVE study enrolled 422 patients in 46 centers between July 2018 and August 2019. Three data review meetings were held between April and October 2019 and 14 standard and planned tests were run on study data, with a total of 15 (32.6%) sites identified as needing review or investigation. Overall 36 findings were identified during the meetings: duplicate records, outliers, inconsistent delays between dates. Conclusion: Statistical monitoring is useful to identify unusual or clustered data patterns that might be revealing issues that could impact the data integrity and/or may potentially impact patients’ safety. With anticipated and appropriate interactive data visualization, early signals can easily be identified or reviewed by the study team and appropriate actions be set up and assigned to the most appropriate function for a close follow-up and resolution. Interactive statistical monitoring is time consuming to initiate using R-Shiny, but is time saving after the 1st data review meeting (DRV).(ClinicalTrials.gov identifier: NCT03589105; EudraCT identifier: 2018-000780-91)