Advantages of visualisations to evaluate and communicate adverse event information in randomised controlled trials
Victoria Cornelius, Suzie Cro, Rachel Phillips
This article demonstrates the use of two plots to better support investigators to assimilate large volumes of adverse events data in randomised controlled trials. It examines the value of the use a plot provides in two trials- Remdesivir for COVID-19 and GDNF for Parkinson’s disease. It demonstrated that asymmetry in the volcano plot can flag extreme events that are less obvious from review of frequency tables, and the dot plot provides a more comprehensive representation by means of a more detailed summary.
Statistical methods for the analysis of adverse event data in randomised controlled trials: a scoping review and taxonomy
Phillips R, Sauzet O, Cornelius V
This article examines whether any statistical methods have been specifically developed to analyse prespecified secondary harm outcomes or non-specific emerging adverse events (AEs) in phase II-IV parallel controlled group trials.
A randomised controlled feasibility trial of E-health application supported care vs usual care after exacerbation of COPD: the RESCUE trial
Mal North, Simon Bourne, Ben Green, Anoop J. Chauhan, Tom Brown, Jonathan Winter, Tom Jones, Dan Neville, Alison Blythin, Alastair Watson, Matthew Johnson, David Culliford, Jack Elkes, Victoria Cornelius & Tom M. A. Wilkinson
This paper describes a feasibility study of a digital health intervention with initial evidence that it supports self-management of patients with COPD.
How to design a pre-specified statistical analysis approach to limit p-hacking in clinical trials: the Pre-SPEC framework
Kahan BC, Forbes G, Cro S.
This article describes a five-point framework (the Pre-SPEC framework) for designing a pre-specified analysis approach that does not allow p-hacking. The framework is based on the principles in the SPIRIT and ICH-E9 guidelines and is intended to be used in conjunction with these guidelines to help investigators design the statistical analysis strategy for the trial’s primary outcome in the trial protocol.
A four-step strategy for handling missing outcome data in randomised trials affected by a pandemic
Cro S, Morris TP, Kahan BC, Cornelius VR, Carpenter JR
This paper presents a four-step strategy for handling missing outcome data in the analysis of randomised trials that are ongoing during a pandemic. Settings where treatment effects for a ‘pandemic-free world’ and ‘world including a pandemic’ are of interest are considered.
Public availability and adherence to prespecified statistical analysis approaches was low in published randomized trials
Kahan BC, Ahmad T, Forbes G, Cro S.
This article reviews how often a prespecified statistical analysis approach was publicly available for randomized trials indexed in PubMed. For most published trials, there was insufficient information available to determine whether the results may be subject to p-hacking.
Understanding current practice, identifying barriers and exploring priorities for adverse event analysis in randomised controlled trials: an online, cross-sectional survey of statisticians from academia and industry
Phillips R, Cornelius V
This article reports the findings of a survey of statisticians that aimed to gain a better understanding of current adverse event analysis practices and explored statisticians' priorities, concerns and barriers when analysing adverse events.
Current approaches to handling rescue medication in asthma and eczema randomized controlled trials are inadequate: a systematic review
Chis Ster A, Cornelius V, Cro S
This review examines how rescue medication is defined, reported, and accounted for in randomized controlled trials in eczema and asthma populations. We found that while rescue medication is frequently permitted in trials alongside the treatment under evaluation, there is minimal attention or interest in isolating the underlying treatment effect of interest.