T-07: Incremental Implementation of Risk-Based Monitoring in a Resource-Constrained
Lead Epidemiologist, Data Mgt & Implementation Team, Div of TB Elimination
Centers For Disease Control and Prevention (CDC) United States
To bring together the experiences of sponsor and Clinical Research Organization (CRO) representatives to develop a risk-based monitoring (RBM) strategy within an international, tuberculosis (TB) clinical research consortium.
ORAL PRESENTATION: 1:30PM
Prior to recruitment into a phase III trial, sponsor and CRO representatives collaborated to create a risk-based monitoring implementation strategy prioritizing components depending on study risks and available resources.
Tuberculosis Trials Consortium (TBTC) Study 31/AIDS Clinical Trials Group (A5349) is a phase 3 clinical trial evaluating shortened regimens for treatment of drug-susceptible TB. The US CDC is the sponsor of this trial, with Westat, Inc. as the CRO. The Data and Coordinating Center (DCC) for the TBTC is within CDC’s Division of TB Elimination, Clinical Research Branch. Prior to study start, DCC and Westat representatives developed an RBM strategy: identification of indicators with risk assignment; application of data visualization tools to monitor performance; and use of predictive statistics to revise indicators throughout the study.
We developed indicators in key performance domains. We prioritized site tasks related to good clinical practice compliance, and study-specific activities related to protocol compliance, outcomes assessment, and participant safety. We identified 35 risks, ranked them depending on the impact of poor performance on participant rights, safety, and the final analysis, and established acceptable performance ranges. DCC team members mapped the indicators to collected data elements, and coded programs to calculate performance. To date, reports are complete for 25% of the planned indicators. Indicators related to protocol compliance are exceeding expected performance ranges in the areas of provision of treatment regimen via directly observed therapy at least five days per week; completion of scheduled visits; and timely evaluation of possible poor treatment response.
We researched data visualization tools and predictive statistics. Resource limitations led us to prioritize incorporation of data visualization strategies into existing data reports. There are few data sets from TB studies implemented at sites similar to S31/A5349; we thus deferred implementation of predictive statistical methods. To address this gap, we are beginning to use the S31/A5349 dataset to predict potential challenges.
Implementing RBM within a large clinical trial consortium is challenging. Given existing financial and human resource constraints, the DCC has planned incremental implementation of the RBM plan within existing central and on-site monitoring strategies. Through the indicator construction and mapping activities, DCC staff identified specific, critical data elements related to protocol compliance and participant safety. DCC staff prioritized data monitoring, evaluation and cleaning tasks on those data elements. Presently, 25% of planned indicator reports evaluating individual site performance, and trends in protocol compliance are complete. There is confidence that the raw data underlying those indicators are complete and accurate, as we focused quality assurance activities on data feeding into the RBM indicators. Coding work continues in the DCC for the remaining indicators. Application of data visualization tools is being explored for the available indicator reports.
As the S31/A5349 dataset continues to grow, we continue to refine use of the existing data to focus monitoring and study-specific and site-specific intervention efforts. Results from indicator reports inform guidance memos sent to all sites, to ensure that identified protocol areas of higher risk (e.g. those in which sites have difficulty with correct implementation) receive more attention. The growing database is also used to prioritize participant records for review during TBTC on-site monitoring visits, with emphasis on participants with either serious adverse events and/or potential poor treatment response evaluations. Incremental implementation of our ambitious RBM strategy allowed us to focus on critical data while refining our indicators and researching data visualization tools and predictive statistical methods.