Clinical Trials

❘❙❚■ Chapter 14 | Noninferiority TrialsTable 2. Examples of noninferiority sample sizes.AssumptionsExample π N π S δ N E N TA 88% 88% –10% 222 592B 88% 88% –12% 155 414C 85% 85% –10% 268 716D 90% 88% –10% 143 382π N= rate of success with the new treatment; π S= rate of success with the standard treatment; δ = noninferioritymargin; N E= number of evaluable subjects per arm; N T= total number of subjects enrolled accounting for dropouts.Assumptions for sample size calculation: H aone-sided alternative hypothesis; α = 2.5%; power = 90%; dropout rate = 25%(to allow for subjects not eligible for efficacy analyses); confidence interval calculation method = normal approximation.that, conventionally, a one-sided CI is used to assess noninferiority [1]. In theanti-infectives therapeutic area, a 2.5% significance level has regularly been usedto assess the null hypothesis. This corresponds to assessing noninferiority basedon a one-sided 97.5% CI. However, estimation is often best based on a two-sided95% CI and sample sizes for this are very similar. Table 2 gives some examples ofsample size calculations [7].Example (continued)The total number of patients required for the study is 592 (see Table 2, row A).This is based on the following assumptions: one-sided H a, α = 2.5%, power = 90%,dropout rate = 25%, π N= 88%, π S= 88%, δ = –10%, CI calculation method= normal approximation, N S= 2 × (N E/ [1 – 0.25]).The choice of δ has a large impact on the number of subjects required for the trial,as seen when using a value of –12% rather than –10% (see Table 2, row B).Therefore, this clinical information is of high importance.The anticipated efficacy rates also strongly influence the required sample size,as can be seen by the increase in sample size when efficacy is assumed to be 85%instead of 88% (see Table 2, row C). On the probability scale, variance (and hencewidth of the CI) is a function of the efficacy rate. Therefore, larger sample sizesare required for efficacy rates towards the center of the 0–100% probability scale,where variance is greatest.If the clinician truly believes that a small advantage in efficacy will be observed forthe experimental treatment, but the primary goal remains to demonstratenoninferiority, the calculation should be performed under an assumption ofunequal efficacy. By assuming the efficacy for the experimental treatment is136