- Poster presentation
- Open Access
Central statistical monitoring in clinical trials
© Kirkwood and Hackshaw; licensee BioMed Central Ltd. 2011
- Published: 13 December 2011
- Statistical Monitoring
- Correlation Structure
- Data Error
- Data Pattern
- Ongoing Trial
On-site monitoring is a common but time-consuming and expensive activity, with little evidence that it is worthwhile. Centralised statistical monitoring (CSM) is a much cheaper alternative, where data checks are performed by the co-ordinating centre, reducing the need to visit every site. Although some publications have outlined possible methods, few have applied them to data from real clinical trials.
R-programs were developed to check data at either the patient or site level, for fraud or data errors. These included finding anomalous data patterns, digit preference, rounding, incorrect dates (eg weekends/holidays), values of variables too close or too far from the means, odd correlation structures and extreme values or variances. We applied these to 3 trials: (i) where data had already been checked, (ii) an ongoing trial where our findings could be checked in real-time, and (iii) where data errors and fake patients were created.
CSM appears to be a cost-effective and worthwhile alternative to on-site monitoring. It can identify incorrect patient data, or centre where the data considered together is too different to all other sites and therefore should be reviewed. However, more research is needed to identify which situations CSM does not work well in.
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.