AbstractBackground/AimsIt is increasingly recognised that reliance on frequent site visits for monitoring clinical trials is inefficient. Regulators and trialists have in recent years encouraged more risk-based monitoring. Risk assessment should take place before a trial begins in order to define the overarching monitoring strategy. It can also be done on an ongoing basis, in order to target sites for monitoring activity. Various methods have been proposed for such prioritisation, often using terms like ‘central statistical monitoring’, ‘triggered monitoring’ or, as in ICH Good Clinical Practice guidance, ‘targeted on-site monitoring’. We conducted a scoping review to identify such methods, to establish if any published methods were supported by adequate evidence to allow wider implementation, and to point the way to future developments in this field of research.MethodsWe used 7 publication databases, 2 sets of methodological conference abstracts and an internet search engine to look for methods for using centrally held trial data to assess site conduct during a trial. We included only reports in English, and excluded reports published before 1996 and reports not directly relevant to our research question. We used reference and citation searches to find additional relevant reports. We extracted data using a pre- defined template. We contacted authors to request additional information about included reports and to check whether reports might be eligible.ResultsWe included 30 reports in our final dataset, of which 21 were peer-reviewed publications. 20 reports described central statistical monitoring methods (of which 7 focussed on detection of fraud or misconduct) and 9 described triggered monitoring methods. 21 reports included some assessment of their methods’ effectiveness. Most commonly this involved exploring the methods’ characteristics using real trial data with no known integrity issues. Of the 21 with some effectiveness assessment, most presented limited or no information about whether or not concerns identified through central monitoring constituted meaningful problems. Some reports commented on cost savings from reduced on-site monitoring, but none gave detailed costings for the development and maintenance of central monitoring methods themselves.ConclusionsOur review identified various proposed methods, some of which could be combined within the same trial. The apparent emphasis on fraud detection may not be proportionate in all trial settings. Although some methods have self-justifying benefits for data cleaning activity, many have limitations that may currently prevent their routine use for targeting trial monitoring activity. The implementation costs, or uncertainty about these, may also be a barrier. We make recommendations for how the evidence-base supporting these methods could be improved.
Detection of Fraud in a Clinical Trial Using Unsupervised Statistical Monitoring
