The Net Benefit of a treatment should take the correlation between benefits and harms into account
The assessment of benefits and harms from experimental treatments often ignores the association between outcomes
The method of generalized pairwise comparisons (GPC) takes into account the association between endpoints
A Net Benefit computed using GPC leads to very different conclusions about the benefit/risk of treatment than when only marginal benefits are used
When data from randomized clinical trials are available, the benefit/risk assessment should use GPC rather than marginal treatment effects
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.
Study design and settings
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.
LEGGI TUTTO https://doi.org/10.1016/j.jclinepi.2021.03.018