c212: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)

Raymond Carragher (Developer)

Research output: Non-textual formSoftware

Abstract

This software package implements a number of methods for the detection of safety signals in Clinical Trials based on groupings of adverse events by body-system or system organ class. The methods include an implementation of the Three-Level Hierarchical model for Clinical Trial Adverse Event Incidence Data of Berry and Berry (2004) , an implementation of the same model without the Point Mass (Model 1a from Xia et al (2011)), and extended Bayesian hierarchical methods based on system organ class or body-system groupings for interim analyses. The package also implements a number of methods for error control when testing multiple hypotheses, specifically control of the False Discovey Rate (FDR). The FDR control methods implemented are the Benjamini-Hochberg procedure, the Double False Discovery Rate, the Group Benjamini-Hochberg and subset Benjamini-Hochberg methods. Also included are the Bonferroni correction and the unadjusted testing procedure.
LanguageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Media of outputOnline
Publication statusPublished - 7 Jan 2017

Fingerprint

Clinical Trials
Safety
Fruit
Bayes Theorem
Software
Incidence

Keywords

  • System organ class
  • clinical trials
  • safety signals

Cite this

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title = "c212: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)",
abstract = "This software package implements a number of methods for the detection of safety signals in Clinical Trials based on groupings of adverse events by body-system or system organ class. The methods include an implementation of the Three-Level Hierarchical model for Clinical Trial Adverse Event Incidence Data of Berry and Berry (2004) , an implementation of the same model without the Point Mass (Model 1a from Xia et al (2011)), and extended Bayesian hierarchical methods based on system organ class or body-system groupings for interim analyses. The package also implements a number of methods for error control when testing multiple hypotheses, specifically control of the False Discovey Rate (FDR). The FDR control methods implemented are the Benjamini-Hochberg procedure, the Double False Discovery Rate, the Group Benjamini-Hochberg and subset Benjamini-Hochberg methods. Also included are the Bonferroni correction and the unadjusted testing procedure.",
keywords = "System organ class, clinical trials, safety signals",
author = "Raymond Carragher",
year = "2017",
month = "1",
day = "7",
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publisher = "University of Strathclyde",

}

c212: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes). Carragher, Raymond (Developer). 2017. Glasgow : University of Strathclyde.

Research output: Non-textual formSoftware

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AB - This software package implements a number of methods for the detection of safety signals in Clinical Trials based on groupings of adverse events by body-system or system organ class. The methods include an implementation of the Three-Level Hierarchical model for Clinical Trial Adverse Event Incidence Data of Berry and Berry (2004) , an implementation of the same model without the Point Mass (Model 1a from Xia et al (2011)), and extended Bayesian hierarchical methods based on system organ class or body-system groupings for interim analyses. The package also implements a number of methods for error control when testing multiple hypotheses, specifically control of the False Discovey Rate (FDR). The FDR control methods implemented are the Benjamini-Hochberg procedure, the Double False Discovery Rate, the Group Benjamini-Hochberg and subset Benjamini-Hochberg methods. Also included are the Bonferroni correction and the unadjusted testing procedure.

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