Background: Primary results from randomized clinical trials (RCT) only inform on the average treatment effect in the studied population, and it is critical to understand how treatment effect varies across subpopulations. In this paper we describe a clustering-based approach for the assessment of Heterogeneity of Treatment Effect (HTE) over patient phenotypes, which maintains the unsupervised nature of classical subgroup analysis while jointly accounting for relevant patient characteristics.
Methods: We applied phenotype-based stratification in the ENGAGE AF-TIMI 48 trial, a non-inferiority trial comparing the effects of higher-dose edoxaban regimen (direct anticoagulant) versus warfarin (vitamin K antagonist) on a composite endpoint of stroke and systemic embolism in 14,062 patients with atrial fibrillation.
Background: There is a need to understand the relationship between COVID-19 Convalescent Plasma (CCP) anti-SARS-CoV-2 IgG levels and clinical outcomes to optimize CCP use. This study aims to evaluate the relationship between recipient baseline clinical status, clinical outcomes, and CCP antibody levels.
Methods: The study analyzed data from the COMPILE study, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) assessing the efficacy of CCP vs.
Background: Cardiovascular trials often use a composite end point and a time-to-first event model. We sought to compare edoxaban versus warfarin using the win ratio, which offers data complementary to time-to-first event analysis, emphasizing the most severe clinical events.
Methods: ENGAGE AF-TIMI 48 (Effective Anticoagulation With Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48) was a double-blind, randomized trial in which patients with atrial fibrillation were assigned 1:1:1 to a higher dose edoxaban regimen (60/30 mg daily), a lower dose edoxaban regimen (30/15 mg daily), or warfarin.