Whitehead, John and Kelly, Patrick J. and Stallard, Nigel and Zhou, Yinghui and Bowman, Clive (2006) Sequential genome-wide association studies for monitoring adverse events in clinical evaluation of new drugs. Statistics in Medicine, 25 (18). pp. 3081-3092.Full text not available from this repository.
Pharmacovigilance, the monitoring of adverse events (AEs), is an integral part in the clinical evaluation of a new drug. Until recently, attempts to relate the incidence of AEs to putative causes have been restricted to the evaluation of simple demographic and environmental factors. The advent of large-scale genotyping, however, provides an opportunity to look for associations between AEs and genetic markers, such as single nucleotides polymorphisms (SNPs). It is envisaged that a very large number of SNPs, possibly over 500 000, will be used in pharmacovigilance in an attempt to identify any genetic difference between patients who have experienced an AE and those who have not. We propose a sequential genome-wide association test for analysing AEs as they arise, allowing evidence-based decision-making at the earliest opportunity. This gives us the capability of quickly establishing whether there is a group of patients at high-risk of an AE based upon their DNA. Our method provides a valid test which takes account of linkage disequilibrium and allows for the sequential nature of the procedure. The method is more powerful than using a correction, such as idák, that assumes that the tests are independent. Copyright © 2006 John Wiley & Sons, Ltd.
|Journal or Publication Title:||Statistics in Medicine|
|Additional Information:||RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research|
|Uncontrolled Keywords:||drug development • pharmacogenetics • pharmacovigilance • safety monitoring • sequential methods|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Mathematics and Statistics|
|Deposited On:||31 Mar 2008 11:16|
|Last Modified:||26 Jul 2012 16:25|
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