Katz Nathaniel P, Paillard Florence C, Ekman Evan
Analgesic Solutions, 232 Pond Street, Natick, MA, 01760, USA.
Tufts University School of Medicine, 274 Tremont Street, Boston, MA, 02111, USA.
J Orthop Surg Res. 2015 Feb 3;10:24. doi: 10.1186/s13018-014-0144-x.
The overarching goals of treatments for orthopedic conditions are generally to improve or restore function and alleviate pain. Results of clinical trials are generally used to determine whether a treatment is efficacious; however, a statistically significant improvement may not actually be clinically important, i.e., meaningful to the patient. To determine whether an intervention has produced clinically important benefits requires a two-step process: first, determining the magnitude of change considered clinically important for a particular measure in the relevant population and, second, applying this yardstick to a patient's data to determine whether s/he has benefited from treatment. Several metrics have been devised to quantify clinically important differences, including the minimum clinically important difference (MCID) and clinically important difference (CID). Herein, we review the methods to generate the MCID and other metrics and their use and interpretation in clinical trials and practice. We particularly highlight the many pitfalls associated with the generation and utilization of these metrics that can impair their correct use. These pitfalls include the fact that different pain measures yield different MCIDs, that efficacy in clinical trials is impacted by various factors (population characteristics, trial design), that the MCID value is impacted by the method used to calculate it (anchor, distribution), by the type of anchor chosen and by the definition (threshold) of improvement. The MCID is also dependent on the population characteristics such as disease type and severity, sex, age, etc. For appropriate use, the MCID should be applied to changes in individual subjects, not to group changes. The MCID and CID are useful tools to define general guidelines to determine whether a treatment produces clinically meaningful effects. However, the many pitfalls associated with these metrics require a detailed understanding of the methods to calculate them and their context of use. Orthopedic surgeons that will use these metrics need to carefully understand them and be aware of their pitfalls.
骨科疾病治疗的总体目标通常是改善或恢复功能并减轻疼痛。临床试验结果通常用于确定一种治疗方法是否有效;然而,具有统计学意义的改善实际上可能在临床上并不重要,也就是说,对患者而言没有意义。要确定一种干预措施是否产生了临床上重要的益处需要经过两个步骤:首先,确定在相关人群中对于特定测量指标而言具有临床重要意义的变化幅度;其次,将这个标准应用于患者的数据,以确定其是否从治疗中获益。已经设计了几种指标来量化临床上重要的差异,包括最小临床重要差异(MCID)和临床重要差异(CID)。在此,我们回顾生成MCID和其他指标的方法及其在临床试验和实践中的应用与解读。我们特别强调与这些指标的生成和使用相关的许多陷阱,这些陷阱可能会妨碍其正确使用。这些陷阱包括不同的疼痛测量方法会产生不同的MCID,临床试验中的疗效受到多种因素(人群特征、试验设计)的影响,MCID值受到计算方法(锚定、分布)、所选锚定类型以及改善定义(阈值)的影响。MCID还取决于人群特征,如疾病类型和严重程度、性别、年龄等。为了正确使用,MCID应应用于个体受试者的变化,而不是组间变化。MCID和CID是定义一般指南以确定一种治疗是否产生临床上有意义效果的有用工具。然而,与这些指标相关的许多陷阱需要对计算它们的方法及其使用背景有详细的了解。使用这些指标的骨科医生需要仔细理解它们并意识到其陷阱。