Kairalla John A, Coffey Christopher S, Thomann Mitchell A, Shorr Ronald I, Muller Keith E
Department of Biostatistics, University of Florida, Gainesville, FL, USA.
Department of Biostatistics, University of Iowa, Iowa City, IA, USA.
Clin Res Regul Aff. 2015;32(1):36-44. doi: 10.3109/10601333.2014.977490. Epub 2014 Nov 13.
Medical and health policy decision makers require improved design and analysis methods for comparative effectiveness research (CER) trials. In CER trials, there may be limited information to guide initial design choices. In general settings, adaptive designs (ADs) have effectively overcome limits on initial information. However, CER trials have fundamental differences from standard clinical trials including population heterogeneity and a vaguer concept of a "minimum clinically meaningful difference".
To explore the use of a particular form of ADs for comparing treatments within the CER trial context.
We review the current state of clinical CER, identify areas of CER as particularly strong candidates for application of novel ADs, and illustrate potential usefulness of the designs and methods for two group comparisons.
ADs can stabilize power. The designs ensure adequate power for true effects are at least at clinically significant preplanned effect size, or when variability is larger than expected. The designs allow for sample size savings when the true effect is larger or when variability is smaller than planned.
ADs in CER have great potential to allow trials to successfully and efficiently make important comparisons.
医疗卫生政策决策者需要改进比较效果研究(CER)试验的设计和分析方法。在CER试验中,指导初始设计选择的信息可能有限。在一般情况下,适应性设计(ADs)有效克服了初始信息的局限性。然而,CER试验与标准临床试验存在根本差异,包括人群异质性以及“最小临床有意义差异”概念更为模糊。
探讨在CER试验背景下使用特定形式的ADs来比较治疗方法。
我们回顾了临床CER的现状,确定CER中特别适合应用新型ADs的领域,并举例说明设计和方法在两组比较中的潜在用途。
ADs可以稳定检验效能。这些设计可确保对于真实效应,至少在临床显著的预先计划效应大小水平上,或在变异性大于预期时,具备足够的检验效能。当真实效应较大或变异性小于计划时,这些设计允许节省样本量。
CER中的ADs有很大潜力使试验能够成功且高效地进行重要比较。