Abstract
In clinical trials, data quality is one of the key factors in determining the success or failure of a drug development program. Data audit is an important step in assessing and ensuring the quality of clinical databases. However, despite the availability of many sophisticated statistical methodologies in analyzing clinical data, there are few data audit methods that are both efficient and statistically sound. A frequent method is auditing data for a fixed percentage of the subjects in a clinical study. Such a method either wastes too many resources or lacks statistical rigor in determining the quality status of a database. In this article, we give a short review of some recent developments and provide an example of database audit strategy. The methodology was developed for, and applied to, a real clinical study. Such a method is both statistically sound and efficient in saving resources needed for the conduct of the audit.
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References
International Conference on Harmonisation. E6: Good Clinical Practice: Consolidated Guideline. Rockville, MD: US Food and Drug Administration; 1996.
Sullivan EM, Gorko MA, Stellon RC, Chao G. A statistically-based process for auditing clinical data listings. Drug Inf J. 1997;31:647–653.
Brunelle R, Kleyle R. A database quality review Process with interim checks. Drug Inf J. 2002; 36:357–367.
Zhang P. Statistical issues in clinical trial data audit. Drug Inf J. 2004;38:371–386.
Larsen JL, Marx ML. An Introduction to Mathematical Statistics and Its Applications. Englewood Cliffs, NJ: Prentice-Hall; 1986.
Shen LZ. Sample size calculation for controlling the exact upper confidence limit of the probability of a binomial endpoint. JBiopharm Stat. 1998; 8:489–496.
Mittag HJ, Rinne H. Statistical Methods of Quality Assurance. New York: Chapman and Hall;1993.
Zhou J, Shen L. Prepare data listings with SAS software for database audit. Proceedings of the Annual Conference of the Pharmaceutical Industry SAS Users Group. May 2005; Phoenix, AZ.
Study Data Specifications. Rockville, MD: Center for Drug Evaluation and Research, US Food and Drug Administration; 2004.
Sampling Procedures for Inspection by Attributes. International Standard, ISO 2859-1:1999. Geneva, Switzerland: ISO; 1999.
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Shen, L.Z., Zhou, J. A Practical and Efficient Approach to Database Quality Audit in Clinical Trials. Ther Innov Regul Sci 40, 385–393 (2006). https://doi.org/10.1177/216847900604000403
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DOI: https://doi.org/10.1177/216847900604000403