Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9752
Title: Ensuring trial validity by data quality assurance and diversification of monitoring methods
Authors: Baigent, C.
Harrell, F.
BUYSE, Marc 
Emberson, J.
Altman, D.
Issue Date: 2008
Publisher: SAGE PUBLICATIONS LTD
Source: CLINICAL TRIALS. p. 49-55.
Abstract: Errors in the design, the conduct, the data collection process, and the analysis of a randomized trial have the potential to affect not only the safety of the patients in the trial, but also, through the introduction of bias, the safety of future patients. Trial monitoring, defined broadly to include methods of oversight which begin when the study is designed and continue until it is reported in a publication, has a role to play in eliminating such errors. On-site monitoring can be extremely inefficient for the identification of errors most likely to compromise patient safety or bias study results. However, a variety of other monitoring strategies offer alternatives to on-site monitoring. Each new trial should conduct a risk assessment to identify the optimal means of monitoring, taking into account the likely sources of error, their consequences for patients, the study's validity, and the available resources. Trial management committees should consider central statistical monitoring a key aspect of such monitoring. 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.
Notes: [Baigent, Colin; Emberson, Jonathan R.] Clin Trial Serv Unit, Oxford OX3 7LF, England. [Baigent, Colin; Emberson, Jonathan R.] Epidemiol Studies Unit, Oxford OX3 7LF, England. [Harrell, Frank E.] Vanderbilt Univ, Sch Med, Dept Biostat, Nashville, TN 37212 USA. [Buyse, Marc] IDDI, Louvain, Belgium. [Altman, Douglas G.] Univ Oxford Wolfson Coll, Ctr Stat Med, Oxford OX2 6UD, England.
Document URI: http://hdl.handle.net/1942/9752
DOI: 10.1177/1740774507087554
ISI #: 000254649200007
Category: C1
Type: Proceedings Paper
Validations: ecoom 2010
Appears in Collections:Research publications

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