Detection of safety signals in randomised controlled trials using groupings

Raymond Carragher

Detection of safety signals in randomised controlled trials using groupings

Raymond Carragher^*

^*Corresponding author for this work

Research output: Contribution to conference › Poster › peer-review

Abstract

Many different types of adverse event are routinely recorded during clinical trials. The statistical analysis of this data may need to take into account:
1.potential multiple comparison issues;
2.low power - effect sizes of adverse events in clinical trials are generally small.
The use of methods which use possible groupings of adverse events (e.g. by System Organ Class) in their statistical analyses may result in an increase in the power to detect adverse event incidence while maintaining control over the Type-I error rate.

Original language	English
Publication status	Published - 5 Sept 2017
Externally published	Yes
Event	Royal Statistical Society Conference 2017 - University of Strathclyde, Glasgow, United Kingdom Duration: 4 Sept 2017 → 7 Sept 2017 https://rss.org.uk/training-events/conference2022/past-conferences/

Conference

Conference	Royal Statistical Society Conference 2017
Abbreviated title	RSS 2017
Country/Territory	United Kingdom
City	Glasgow
Period	4/09/17 → 7/09/17
Internet address	https://rss.org.uk/training-events/conference2022/past-conferences/

Keywords

Safety
Adverse Events
Bayesian
Medical
Hierarchy

Access to Document

https://pureportal.strath.ac.uk/en/publications/detection-of-safety-signals-in-randomised-controlled-trials-using

Cite this

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title = "Detection of safety signals in randomised controlled trials using groupings",

abstract = "Many different types of adverse event are routinely recorded during clinical trials. The statistical analysis of this data may need to take into account: 1.potential multiple comparison issues; 2.low power - effect sizes of adverse events in clinical trials are generally small. The use of methods which use possible groupings of adverse events (e.g. by System Organ Class) in their statistical analyses may result in an increase in the power to detect adverse event incidence while maintaining control over the Type-I error rate. ",

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AU - Carragher, Raymond

PY - 2017/9/5

Y1 - 2017/9/5

N2 - Many different types of adverse event are routinely recorded during clinical trials. The statistical analysis of this data may need to take into account: 1.potential multiple comparison issues; 2.low power - effect sizes of adverse events in clinical trials are generally small. The use of methods which use possible groupings of adverse events (e.g. by System Organ Class) in their statistical analyses may result in an increase in the power to detect adverse event incidence while maintaining control over the Type-I error rate.

AB - Many different types of adverse event are routinely recorded during clinical trials. The statistical analysis of this data may need to take into account: 1.potential multiple comparison issues; 2.low power - effect sizes of adverse events in clinical trials are generally small. The use of methods which use possible groupings of adverse events (e.g. by System Organ Class) in their statistical analyses may result in an increase in the power to detect adverse event incidence while maintaining control over the Type-I error rate.

KW - Safety

KW - Adverse Events

KW - Bayesian

KW - Medical

KW - Hierarchy

M3 - Poster

T2 - Royal Statistical Society Conference 2017

Y2 - 4 September 2017 through 7 September 2017

ER -

Detection of safety signals in randomised controlled trials using groupings

Abstract

Conference

Keywords

Access to Document

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Cite this