This is a guest post by John Johnson, Ph.D. John is a Senior Biostatistician and the Associate Director, Statistics at Cato Research.
Clinical trial protocol amendments occur for good reasons. An unanticipated safety issue may arise, new information about the disease or treatment may suggest alterations, or recruitment and enrollment may not go as planned.
One aspect of protocol amendments that often gets overlooked is the statistical analysis. This is because it is not always obvious that an alteration to one non-statistical section of the protocol can have an impact on the statistics.
Take, for instance, the relaxing of inclusion/exclusion criteria to speed enrollment. This usually has the effect of enlarging the target patient population, which in turn can make the uncertainty in the estimate of the treatment effect larger. This has the effect of lowering the power of the study, unless the sample size is increased.
Statistical methods are being developed to account for this possibility now. However, these methods often require more complex programming and require more care (i.e. time and money) to assure correctness.
These hidden costs, along with others, should be kept in mind when first developing a protocol, and later when protocol amendments are being considered.
Related articles:
- Novel Approaches to Clinical Trial Recruitment (ask-cato.com)
- Adaptive Designs and Clinical Supplies (ask-cato.com)
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