Visualizing adverse events in clinical trials using correspondence analysis with R-package visae.

ABSTRACT:

Background

Graphical displays and data visualization are essential components of statistical analysis that can lead to improved understanding of clinical trial adverse event (AE) data. Correspondence analysis (CA) has been introduced decades ago as a multivariate technique that can communicate AE contingency tables using two-dimensional plots, while quantifying the loss of information as other dimension reduction techniques such as principal components and factor analysis.

Methods

We propose the application of stacked CA using contribution biplots as a tool to explore differences in AE data among treatments in clinical trials. We defined five levels of refinement for the analysis based on data derived from the Common Terminology Criteria for Adverse Events (CTCAE) grades, do

SUBMITTER: Diniz MA 

PROVIDER: S-EPMC8579548 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature