Imperial College Healthcare NHS Trust, London, UK.
Mult Scler. 2011 Oct;17(10):1211-7. doi: 10.1177/1352458511406309. Epub 2011 May 17.
Sample size calculation is a key aspect in the planning of any trial. Planning a randomized placebo-controlled trial in relapsing-remitting multiple sclerosis (RRMS) requires knowledge of the annualized relapse rate (ARR) in the placebo group.
This paper aims (i) to characterize the uncertainty in ARR by conducting a systematic review of placebo-controlled, randomized trials in RRMS and by modelling the ARR over time; and (ii) to assess the feasibility and utility of blinded sample size re-estimation (BSSR) procedures in RRMS.
A systematic literature review was carried out by searching PubMed, Ovid Medline and the Cochrane Register of Controlled Trials. The placebo ARRs were modelled by negative binomial regression. Computer simulations were conducted to assess the utility of BSSR in RRMS.
Data from 26 placebo-controlled randomized trials were included in this analysis. The placebo ARR decreased by 6.2% per year (p < 0.0001; 95% CI (4.2%; 8.1%)) resulting in substantial uncertainty in the planning of future trials. BSSR was shown to be feasible and to maintain power at a prespecified level also if the ARR was misspecified in the planning phase.
Our investigations confirmed previously reported trends in ARR. In this context adaptive strategies such as BSSR designs are recommended for consideration in the planning of future trials in RRMS.
样本量计算是任何试验规划的关键方面。在复发缓解型多发性硬化症（RRMS）中规划随机安慰剂对照试验需要了解安慰剂组的年复发率（ARR）。
本文旨在（i）通过对 RRMS 的安慰剂对照、随机试验进行系统评价，并通过对 ARR 随时间的建模，来描述 ARR 的不确定性；（ii）评估 RRMS 中盲法样本量重新估计（BSSR）程序的可行性和实用性。
通过搜索 PubMed、Ovid Medline 和 Cochrane 对照试验登记处，进行了系统文献回顾。通过负二项式回归对安慰剂 ARR 进行建模。进行了计算机模拟，以评估 BSSR 在 RRMS 中的实用性。
本分析纳入了 26 项安慰剂对照随机试验的数据。安慰剂 ARR 每年下降 6.2%（p<0.0001；95%CI（4.2%；8.1%）），这导致未来试验的规划存在很大的不确定性。BSSR 被证明是可行的，如果在规划阶段 ARR 被错误指定，也能维持预定水平的功效。
我们的研究结果证实了之前报道的 ARR 趋势。在这种情况下，建议在 RRMS 的未来试验规划中考虑适应性策略，如 BSSR 设计。
