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. 2024 Aug:143:107581.
doi: 10.1016/j.cct.2024.107581. Epub 2024 May 27.

A risk-based monitoring approach to source data monitoring and documenting monitoring findings

Maryse Brulotte  1 , Jessica S Alvey  2 , T Charles Casper  2 , Lawrence J Cook  2 , Jamie P Dwyer  2 , John M VanBuren  2
Affiliations

A risk-based monitoring approach to source data monitoring and documenting monitoring findings

Maryse Brulotte et al. Contemp Clin Trials. 2024 Aug.

Abstract

Background: Clinical trial monitoring is evolving from labor-intensive to targeted approaches. The traditional 100% Source Data Monitoring (SDM) approach fails to prioritize data by significance, diverting attention from critical elements. Despite regulatory guidance on Risk-Based Monitoring (RBM), its widespread implementation has been slow.

Methods: Our study teams assess the study's overall risk, document heightened and critical risks, and create a study-specific risk-based monitoring plan, integrating SDM and Central Data Monitoring (CDM). SDM combines a fixed list of pre-identified variables and a list of randomly identified variables to monitor. Identifying variables follows a two-step approach: first, a random sample of participants is selected, second, a random set of variables for each participant selected is identified. Sampling weights prioritize critical variables. Regular team meetings are held to discuss and compile significant findings into a Study Monitoring Report.

Results: We present a random SDM sample and a Study Monitoring Report. The random SDM output includes a look-up table for selected database elements. The report provides a holistic view of the study issues and overall health.

Conclusions: The proposed random sampling method is used to monitor a representative set of critical variables, while the Study Monitoring Report is written to summarize significant monitoring findings and data trends. The report allows the sponsor to assess the current status of the study and data effectively. Communicating and sharing emerging insights facilitates timely adjustments of future monitoring activities, optimizing efficiencies, and study outcomes.

Keywords: Central data monitoring; Risk assessment risk management; Risk-based monitoring; Source data monitoring; Statistical sampling; Study monitoring report.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1:
Figure 1:
Lifecycle of Study Monitoring – An Iterative Process
Figure 2.
Figure 2.
Risk-Based Quality Management Cycle for a Study
Figure 3:
Figure 3:
Hypothetical example of source data monitoring sampling schema
Figure 4:
Figure 4:
In this example, Part A represents a random sample of participant outcomes selected for monitoring for 5 participants. Part B lists the corresponding database elements that match each outcome.
Figure 5:
Figure 5:
Example of a Study Monitoring Report
See this image and copyright information in PMC

References

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