Statistics in medicine
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Statistics in medicine · Nov 2007
Implementing a decision-theoretic design in clinical trials: why and how?
This paper addresses two main questions: first, why should Bayesian and other innovative, data-dependent design models be put into practice and, secondly, given the past dearth of actual applications, how might one example of such a design be implemented in a genuine example trial? Clinical trials amalgamate theory, practice and ethics, but this last point has become relegated to the background, rather than taking often a more appropriate primary role. Trial practice has evolved but has its roots in R. A. ⋯ For comparison, a fixed sample size trial, with standard 5 per cent level of significance and 80 per cent power to detect a 10 per cent difference, requires treating over 700 patients in two groups, with the half allocated to inferior treatment considerably outnumbering the 68 expected under the decision-theoretic design, and the overall number simply too high for realistic application. In brief, the keys to answering the above 'why?' and 'how?' questions are ethics and software, respectively. Wider implications, both pros and cons, of implementing the particular method described will be discussed, with the overall conclusion that, where appropriate, clinical trials are now ready to undergo modernization from the agricultural age to the information age.