Sample size cost issues

Several specialized reviews on detection of QT liability in the clinical development phase have already been published and the reader is referred to these publications [63]. Guidelines of the International Society for Holter and Noninvasive Electrocardiology (IS H N E) for electrocardiographic evaluation of drug-related QT prolongation are also available [161]. The main issues related to measurement of the QT interval in clinical studies are summarized in Table 3.4. An important aspect is the calculation of sample size usually 40-60 subjects per treatment arm are required, implying high cost [162-164]. 

Hypothesis-driven study and the results are easy to interpret small sample size requirement simple analysis no multiple comparison issue low cost easy to validate... 

In Sections 2 to 4, we review the technology of synthetic oligonucleotide microarrays and describe some of the popular statistical methods that are used to discover genes with differential expression in simple comparative experiments. A novel Bayesian procedure is introduced in Section 5 to analyze differential expression that addresses some of the limitations of current procedures. We proceed, in Section 6, by discussing the issue of sample size and describe two approaches to sample size determination in screening experiments with microarrays. The first approach is based on the concept of reproducibility, and the second approach uses a Bayesian decision-theoretic criterion to trade off information gain and experimental costs. We conclude, in Section 7, with a discussion of some of the open problems in the design and analysis of microarray experiments that need further research. 

A very unsatisfactory feature of conventional approaches to sample size calculation is that there is no mention of cost. This means that for any two quite different indications with the same effect size, that is to say the same ratio of clinically relevant difference to standard deviation, the sample size would be the same whatever the cost or difficulty of recruiting and treating patients. This is clearly illogical and trialists probably manage this issue informally by manipulating the clinically relevant difference in the way discussed in Section 13.2.3. Clearly, it would be better to include the cost explicitly, and this suggests decision-analytic approaches to sample size determination. There are various Bayesian suggestions and these will be discussed in the next section. 

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