Marc Buyse1, Everardo D Saad2, Julien Peron3, Jean-Christophe Chiem2, Mickaël De Backer4, Eva Cantagallo5, Oriana Ciani6. 1. International Drug Development Institute, San Francisco, CA, USA; Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium. Electronic address: marc.buyse@iddi.com. 2. International Drug Development Institute, Louvain-la-Neuve, Belgium. 3. Hospices Civils de Lyon, departments of Oncology and Biostatistics, Pierre-Benite, France; University of Lyon 1, CNRS UMR 5558, Biometry and Evolutive Biology Laboratory, Biostatistics-Health Team, Villeurbanne, France. 4. Institut de statistique, biostatistique et sciences actuarielles, Université Catholique de Louvain, Louvain-la-Neuve, Belgium. 5. European Organisation for Research and Treatment of Cancer (EORTC), Brussels, Belgium. 6. CERGAS - Università Commerciale L. Bocconi, Milan, Italy; University of Exeter Medical School, Evidence Synthesis & Modelling for Health Improvement, Exeter, UK.
Abstract
OBJECTIVE: 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. RESULTS: 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. CONCLUSION: 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.
OBJECTIVE: 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. RESULTS: 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. CONCLUSION: 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.
Authors: V J Zonjee; I L Abma; M J de Mooij; S M van Schaik; R M Van den Berg-Vos; L D Roorda; C B Terwee Journal: Qual Life Res Date: 2022-05-27 Impact factor: 3.440