Assessing and visualizing fragility of clinical results with binary outcomes in R using the fragility package

Lifeng Lin, Haitao Chu

Research output: Contribution to journalArticlepeer-review

Abstract

With the growing concerns about research reproducibility and replicability, the assessment of scientific results’ fragility (or robustness) has been of increasing interest. The fragility index was proposed to quantify the robustness of statistical significance of clinical studies with binary outcomes. It is defined as the minimal event status modifications that can alter statistical significance. It helps clinicians evaluate the reliability of the conclusions. Many factors may affect the fragility index, including the treatment groups in which event status is modified, the statistical methods used for testing for the association between treatments and outcomes, and the pre-specified significance level. In addition to assessing the fragility of individual studies, the fragility index was recently extended to both conventional pairwise meta-analyses and network meta-analyses of multiple treatment comparisons. It is not straightforward for clinicians to calculate these measures and visualize the results. We have developed an R package called “fragility” to offer user-friendly functions for such purposes. This article provides an overview of methods for assessing and visualizing the fragility of individual studies as well as pairwise and network meta-analyses, introduces the usage of the “fragility” package, and illustrates the implementations with several worked examples.

Original languageEnglish (US)
Article numbere0268754
JournalPloS one
Volume17
Issue number6 June
DOIs
StatePublished - Jun 2022

Bibliographical note

Funding Information:
This research was supported in part by the US National Institutes of Health/National Institute of Mental Health grant R03 MH128727, National Institutes of Health/National Library of Medicine grant R01 LM012982 (LL and HC), and National Institutes of Health/National Center for Advancing Translational Sciences grant UL1 TR001427 (LL). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2022 Lin, Chu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural

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