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Optimising data completeness and quality in multicentre randomised clinical trials using central data monitoring: a
Markus Harboe Olsen1,2, Mathias Lühr Hansen3,4, Janus Engstrøm3
1Copenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital ─Rigshospitalet, Copenhagen, Denmark. oel@oelfam.com.
Background:
Randomised clinical trial data monitoring is essential for ensuring quality and adherence to protocols, often achieved through on-site methods. However, challenges like the COVID-19 pandemic have highlighted limitations. Central data monitoring offers an alternative, leveraging digital capabilities and diverse expertise.
Methods:
The SafeBoosC-III trial, randomising 1,601 preterm infants across 70 sites, was a pragmatic trial offering detailed education of the investigators before launch. During the trial, we conducted pre-protocolised central data monitoring encompassing monthly data checks, data completeness assessments, and statistical analyses. Discrepancies were primarily identified through visual interpretation of data.
Results:
Throughout the trial, meticulous central monitoring helped keeping missing data at only 1.4%. Of 43,965 data points reviewed, 338 were flagged, with 81 (0.2% of all data and 24.0% of flagged data) corrected after investigation.
Conclusions:
The methodology of combining manual investigation with statistical tools effectively minimised data errors, enhancing validity. This approach in the SafeBoosC-III trial emphasises the importance of ongoing central data monitoring in clinical trials. Standardised protocols for such monitoring are crucial for ensuring data quality and accelerating the validation process in future trials.
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