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Open Access 01-12-2021 | Anastrozole | Research

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

Authors: Márcio A. Diniz, Gillian Gresham, Sungjin Kim, Michael Luu, N. Lynn Henry, Mourad Tighiouart, Greg Yothers, Patricia A. Ganz, André Rogatko

Published in: BMC Medical Research Methodology | Issue 1/2021

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, domains, terms and their combinations. In addition, we developed a Shiny app built in an R-package, visae, publicly available on Comprehensive R Archive Network (CRAN), to interactively investigate CA configurations based on the contribution to the explained variance and relative frequency of AEs. Data from two randomized controlled trials (RCT) were used to illustrate the proposed methods: NSABP R-04, a neoadjuvant rectal 2 × 2 factorial trial comparing radiation therapy with either capecitabine (Cape) or 5-fluorouracil (5-FU) alone with or without oxaliplatin (Oxa), and NSABP B-35, a double-blind RCT comparing tamoxifen to anastrozole in postmenopausal women with hormone-positive ductal carcinoma in situ.

Results

In the R04 trial (n = 1308), CA biplots displayed the discrepancies between single agent treatments and their combinations with Oxa at all levels of AE classes, such that these discrepancies were responsible for the largest portion of the explained variability among treatments. In addition, an interaction effect when adding Oxa to Cape/5-FU was identified when the distance between Cape+Oxa and 5-FU + Oxa was observed to be larger than the distance between 5-FU and Cape, with Cape+Oxa and 5-FU + Oxa in different quadrants of the CA biplots. In the B35 trial (n = 3009), CA biplots showed different patterns for non-adherent Anastrozole and Tamoxifen compared with their adherent counterparts.

Conclusion

CA with contribution biplot is an effective tool that can be used to summarize AE data in a two-dimensional display while minimizing the loss of information and interpretation.

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Title: Visualizing adverse events in clinical trials using correspondence analysis with R-package visae
Authors: Márcio A. Diniz
Gillian Gresham
Sungjin Kim
Michael Luu
N. Lynn Henry
Mourad Tighiouart
Greg Yothers
Patricia A. Ganz
André Rogatko
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Anastrozole
Tamoxifen
Published in: BMC Medical Research Methodology / Issue 1/2021
Electronic ISSN: 1471-2288
DOI: https://doi.org/10.1186/s12874-021-01368-w

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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