International Drug Development Institute, San Francisco, CA, USA; Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.
International Drug Development Institute, Louvain-la-Neuve, Belgium.
J Clin Epidemiol. 2021 Sep;137:148-158. doi: 10.1016/j.jclinepi.2021.03.018. Epub 2021 Mar 24.
The assessment of benefits and harms from experimental treatments often ignores the association between outcomes. In a randomized trial, generalized pairwise comparisons (GPC) can be used to assess a Net Benefit that takes this association into account.
We use GPC to analyze a fictitious trial of treatment versus control, with a binary efficacy outcome (response) and a binary toxicity outcome, as well as data from two actual randomized trials in oncology. In all cases, we compute the Net Benefit for scenarios with different orders of priority between response and toxicity, and a range of odds ratios (ORs) for the association between these outcomes.
The GPC Net Benefit was quite different from the benefit/harm computed using marginal treatment effects on response and toxicity. In the fictitious trial using response as first priority, treatment had an unfavorable Net Benefit if OR < 1, but favorable if OR > 1. With OR = 1, the Net Benefit was 0. Results changed drastically using toxicity as first priority.
Even in a simple situation, marginal treatment effects can be misleading. In contrast, GPC assesses the Net Benefit as a function of the treatment effects on each outcome, the association between outcomes, and individual patient priorities.
实验性治疗的获益和危害评估往往忽略了结局之间的关联性。在随机试验中，可以使用广义成对比较（GPC）来评估考虑到这种关联性的净获益。
我们使用 GPC 分析了一项治疗与对照的虚构试验，该试验具有二元疗效结局（反应）和二元毒性结局，以及来自肿瘤学的两项实际随机试验的数据。在所有情况下，我们都计算了在反应和毒性之间具有不同优先级顺序的情况下的净获益，以及这些结局之间关联的一系列比值比（OR）。
GPC 净获益与使用反应和毒性的边际治疗效果计算的获益/危害有很大不同。在使用反应作为第一优先级的虚构试验中，如果 OR < 1，则治疗具有不利的净获益，但如果 OR > 1，则治疗具有有利的净获益。如果 OR = 1，则净获益为 0。使用毒性作为第一优先级时，结果发生了巨大变化。
即使在简单的情况下，边际治疗效果也可能具有误导性。相比之下，GPC 评估净获益是作为对每个结局的治疗效果、结局之间的关联以及个体患者优先级的函数。
