title: Ensuring trial validity by data quality assurance and diversification of monitoring methods.
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.
authors.affiliation: Clinical Trial Service Unit & Epidemiological Studies Unit, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF. colin.baigent@ctsu.ox.ac.uk
authors.forename: Colin
authors.initials: C
authors.lastname: Baigent
authors.forename: Frank E
authors.initials: FE
authors.lastname: Harrell
authors.forename: Marc
authors.initials: M
authors.lastname: Buyse
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Emberson
authors.forename: Douglas G
authors.initials: DG
authors.lastname: Altman
mesh_terms: D015982:Bias; D026661:Clinical Trials Data Monitoring Committees / Q000458:organization & administration* / Q000706:statistics & numerical data; D006801:Humans; D011786:Quality Control; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D012107:Research Design; D018570:Risk Assessment