Cahan Amos, Cahan Sorel, Cimino James J
IBM T.J. Watson Research Center, Yorktown Heights, NY, United States.
The Hebrew University of Jerusalem, Jerusalem, Israel.
Int J Med Inform. 2017 Mar;99:60-66. doi: 10.1016/j.ijmedinf.2016.12.008. Epub 2017 Jan 6.
The effects of an intervention on patients from populations other than that included in a trial may vary as a result of differences in population features, treatment administration, or general setting. Determining the generalizability of a trial to a target population is important in clinical decision making at both the individual practitioner and policy-making levels. However, awareness to the challenges associated with the assessment of generalizability of trials is low and tools to facilitate such assessment are lacking.
We review the main factors affecting the generalizability of a clinical trial results beyond the trial population. We then propose a framework for a standardized evaluation of parameters relevant to determining the external validity of clinical trials to produce a "generalizability score". We then apply this framework to populations of patients with heart failure included in trials, cohorts and registries to demonstrate the use of the generalizability score and its graphic representation along three dimensions: participants' demographics, their clinical profile and intervention setting. We use the generalizability score to compare a single trial to multiple "target" clinical scenarios. Additionally, we present the generalizability score of several studies with regard to a single "target" population.
Similarity indices vary considerably between trials and target population, but inconsistent reporting of participant characteristics limit head-to-head comparisons.
We discuss the challenges involved in performing automatic assessment of trial generalizability at scale and propose the adoption of a standard format for reporting the characteristics of trial participants to enable better interpretation of their results.
由于人群特征、治疗实施或总体环境的差异，一项干预措施对试验纳入人群以外的其他人群的影响可能会有所不同。在个体从业者和政策制定层面的临床决策中，确定试验对目标人群的可推广性都很重要。然而，人们对与试验可推广性评估相关的挑战认识不足，且缺乏便于此类评估的工具。
我们回顾了影响临床试验结果在试验人群之外的可推广性的主要因素。然后，我们提出了一个框架，用于对与确定临床试验外部有效性相关的参数进行标准化评估，以得出一个“可推广性分数”。接着，我们将这个框架应用于试验、队列研究和注册研究中纳入的心力衰竭患者人群，以展示可推广性分数的使用及其在三个维度上的图形表示：参与者的人口统计学特征、临床特征和干预环境。我们使用可推广性分数将单个试验与多个“目标”临床场景进行比较。此外，我们还展示了几项针对单一“目标”人群的研究的可推广性分数。
试验与目标人群之间的相似性指数差异很大，但参与者特征报告不一致限制了直接比较。
我们讨论了大规模自动评估试验可推广性所涉及的挑战，并建议采用标准格式报告试验参与者的特征，以便更好地解释试验结果。
