Okwuokenye Macaulay, Zhang Annie, Pace Amy, Peace Karl E
Biogen, Cambridge, MA, USA.
Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, USA.
Neurol Ther. 2017 Jun;6(1):1-9. doi: 10.1007/s40120-017-0063-y. Epub 2017 Feb 7.
Clinicians are expected to select a therapy based on their appraisal of evidence on benefit-to-risk profiles of therapies. In the management of relapsing-remitting multiple sclerosis (RRMS), evidence is typically expressed in terms of risk (proportion) of event, risk reduction, relative and hazard rate reduction, or relative reduction in the mean number of magnetic resonance imaging lesions. Interpreting treatment effect using these measures from a RRMS clinical trial is fairly reliable; however, this might not be the case when treatment effect is expressed in terms of the number needed to treat (NNT). The objective of this review is to discuss the utility of NNT in RRMS trials. This article presents an overview of the methodological definition and characteristics of NNT as well as the relative merit of NNT use in RRMS controlled clinical trials, where endpoints are typically time-to-event and frequency of recurrent events. The authors caution against using NNT in multiple sclerosis, a clinically heterogeneous disease that can change course and severity unpredictably. The authors also caution against the use of NNT to interpret results in comparative trials where the absolute risk difference is not statistically significant, computing NNT using the time-to-event endpoint at intermediate time points, computing NNT using the annualized relapse rate, and comparing NNT across trials.
临床医生应根据对治疗的获益-风险概况证据的评估来选择治疗方法。在复发缓解型多发性硬化症(RRMS)的管理中,证据通常以事件风险(比例)、风险降低、相对和风险率降低或磁共振成像病变平均数量的相对减少来表示。从RRMS临床试验中使用这些指标来解释治疗效果是相当可靠的;然而,当治疗效果以治疗所需人数(NNT)来表示时,情况可能并非如此。本综述的目的是讨论NNT在RRMS试验中的效用。本文概述了NNT的方法学定义和特征,以及在RRMS对照临床试验中使用NNT的相对优点,在这些试验中,终点通常是事件发生时间和复发事件的频率。作者告诫不要在多发性硬化症中使用NNT,这是一种临床异质性疾病,其病程和严重程度可能会不可预测地变化。作者还告诫不要在绝对风险差异无统计学意义的比较试验中使用NNT来解释结果,不要在中间时间点使用事件发生时间终点计算NNT,不要使用年化复发率计算NNT,以及不要在不同试验之间比较NNT。