Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification.
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TLDR
It should be possible to save time required to conduct SDV leading to more available time for other productive activities, and concepts of optimum monitoring and SDV at site and off-site monitoring techniques are combined.Abstract:
For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV). This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the RD investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.read more
Citations
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Journal ArticleDOI
The impact of clinical trial monitoring approaches on data integrity and cost--a review of current literature.
TL;DR: An overview of publications on different monitoring methods and their impact on subject safety data, data integrity, and monitoring cost indicates that reduced SDV is a viable monitoring method.
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Evaluating Source Data Verification as a Quality Control Measure in Clinical Trials
Nicole Sheetz,Brett Wilson,Joanne Benedict,Esther Huffman,Andy Lawton,Mark Travers,Patrick Nadolny,Stephen Young,Kyle Given,Lawrence Florin +9 more
TL;DR: The results support the hypothesis that generalized SDV has limited value as a quality control measure and reinforce the value of other risk-based monitoring activities.
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Keith A.A. Fox,Bernard J. Gersh,Sory Traore,A. John Camm,Gloria Kayani,Anders Krogh,Shweta Shweta,Ajay K Kakkar,Garfield-Af Investigators +8 more
TL;DR: The quality standards developed for Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) have the potential to inform a future 'reference' for registries.
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Exploring Data Quality Management within Clinical Trials
Lauren Houston,Lauren Houston,Yasmine Probst,Yasmine Probst,Ping Yu,Allison Martin,Allison Martin +6 more
TL;DR: Clinical trial sites are implementing ad hoc methods pragmatically to ensure data quality, highlighting the necessity for further research into "standard practice" focusing on developing and implementing publically available data quality monitoring procedures.
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Data-driven risk identification in phase III clinical trials using central statistical monitoring
TL;DR: It is claimed that CSM has a key role to play in identifying the “risks to the most critical data elements and processes” that will drive targeted oversight in clinical trials.
References
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The role of biostatistics in the prevention, detection and treatment of fraud in clinical trials
Marc Buyse,Stephen L. George,Stephen J. W. Evans,Nancy L. Geller,Jonas Ranstam,Bruno Scherrer,Emmanuel Lesaffre,Gordon D Murray,Lutz Edler,Jane L. Hutton,Theodore Colton,Peter A. Lachenbruch,Babu L. Verma +12 more
TL;DR: It is argued that biostatisticians should be involved in preventing fraud (as well as unintentional errors), detecting it, and quantifying its impact on the outcome of clinical trials.
Journal ArticleDOI
Ensuring trial validity by data quality assurance and diversification of monitoring methods.
TL;DR: Trial management committees should consider central statistical monitoring a key aspect of such monitoring, and the systematic application of this approach would be likely to lead to tangible benefits, and resources that are currently wasted on inefficient on-site monitoring could be diverted to increasing trial sample sizes or conducting more trials.