Central statistical monitoring in clinical trials

Abstract

Clinical trial sponsors are required to set up appropriate measures to monitor the conduct of the trial. The aim of monitoring is to ensure the patients' well being, compliance with the approved protocol and regulatory requirements, as well as data accuracy and completeness. Classical monitoring approaches that rely on on-site visits are useful for some of these purposes, but extensive source data verification is extremely time consuming and may have only a limited impact on data quality. It is therefore not surprising that the current practice of performing intensive on-site monitoring is coming into question and that interest focuses on more pragmatic, risk- based approaches that improve the cost- effectiveness ratio without compromising the quality and integrity of clinical trials. A recent draft guidance of the Food and Drug Administration (FDA) reflects this trend and states unequivocally: "FDA encourages greater reliance on centralized monitoring practices than has been the case historically, with correspondingly less emphasis on on-site monitoring". In this presentation, we first review the potential sources of data errors in clinical trials. We then outline the principles of central statistical monitoring and the challenges of its implementation in actual trials. Results from both terminated and on-going trials are presented to illustrate typical findings that can be expected from the monitoring approach. We conclude by a discussion of the potential role and limitations of central statistical monitoring, and we argue that it can both optimize on-site monitoring and improve the quality of clinical trial data.