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14, 15 Central monitoring of data using statistical methods is increasingly being found useful in large multicentre trials for identification of unusual patterns of data.
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It was pointed out at the workshop that this would be a difficult concept to convey in a study protocol and would probably require real time central monitoring of the data with individualized stopping rules conveyed to the site.
Central monitoring of multicenter clinical trials becomes an ever more feasible quality assurance tool, in particular for the detection of data fabrication.
Many of these studies have used central monitoring station data as a proxy measure of exposure for all residents of a community; thus, health effect estimates are based on between-community comparisons (Gotschi et al. 2008b).
Professor Richard Cooke (Chair) Dr Simon Newell Dr John Puntis Ms Ly-Mee Yu As a result of central monitoring the trial data, it has become clear that the primary end point has not been achieved in a small number of cases.
Using a combination of central monitoring and personal microenvironment monitoring data for PM2.5, a significant association was reported between CRP and ambient levels, particularly among persons with diabetes, obesity, and hypertension, including combinations of these conditions (Dubowsky et al. 2006).
We expected pseudo-independent central monitoring to produce higher-quality data than decentralized monitoring, and a decentralized monitoring regime to produce higher-quality data than no monitoring.
Monitor watchers at the central monitoring station completed a standard data sheet assessing 64 variables.
Most studies used air pollution measurements from central monitoring sites that provide daily data.
Central coordination of data collection is crucial.
We acquired daily measurements of PM2.5 and meteorologic data at central monitoring sites.
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