El-Hagrassy Mirret M, Duarte Dante G G, Thibaut Aurore, Lucena Mariana F G, Fregni Felipe
Neuromodulation Center, Spaulding Rehabilitation Hospital, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, United States.
Coma Science Group, GIGA-Research, University and University Hospital of Liege, Liege, Belgium.
Curr Behav Neurosci Rep. 2018 Jun;5(2):143-152. doi: 10.1007/s40473-018-0152-y. Epub 2018 May 2.
Clinical trials are essential to advance health care and develop new therapies. In this review we discuss the underlying principles of clinical trial design with an emphasis on assessing design risks that lead to trial failure as well as negative trials. While of general interest, this is perhaps particularly timely for the neuromodulation community, given the paucity of well-designed trials in the field. We give some examples from the phantom limb pain (PLP) literature.
It is critical to gather as much preliminary data as possible and to know how to interpret it in order to choose an appropriate trial design. Therefore, the investigator needs to effectively assess the likely trial design risk/benefit ratio with a view to maximizing the chance of a meaningful outcome, whether this outcome rejects or fails to reject the null hypothesis. This analysis is especially important in a complex and heterogeneous disorder such as PLP, which has had many negative trials.
We discuss the factors pertaining to a strong trial design benefit/risk assessment, how late trial phases require greater support from preliminary data, how to design trials to minimize risks, maximize benefits, and optimize internal validity as well as the chances of a positive outcome. We highlight the need for investigators to incorporate best practice in trial design to increase the chances of success, to always anticipate unexpected challenges during the trial.
临床试验对于推动医疗保健和开发新疗法至关重要。在本综述中，我们讨论临床试验设计的基本原则，重点是评估导致试验失败以及阴性试验结果的设计风险。鉴于该领域精心设计的试验较少，尽管这是普遍感兴趣的话题，但对于神经调节领域而言可能尤为及时。我们从幻肢痛（PLP）文献中举了一些例子。
尽可能收集大量初步数据并知道如何解读这些数据对于选择合适的试验设计至关重要。因此，研究者需要有效地评估可能的试验设计风险/收益比，以最大化获得有意义结果的机会，无论该结果是拒绝还是未能拒绝原假设。在像PLP这样复杂且异质性的疾病中，这种分析尤为重要，因为PLP已经有许多阴性试验结果。
我们讨论了与强大的试验设计收益/风险评估相关的因素，试验后期阶段如何需要来自初步数据的更多支持，如何设计试验以最小化风险、最大化收益并优化内部有效性以及获得阳性结果的机会。我们强调研究者需要在试验设计中纳入最佳实践以增加成功的机会，并始终预期试验期间意想不到的挑战。
