July 05, 2020

Recommendations to visualise treatment harm profiles in Randomised Controlled Trials – a national consensus

In collaboration with the UKCRC CTU Statistics Operation group, Rachel Phillips, Victoria Cornelius and Suzie Cro hosted three half day meetings to develop a national consensus of recommendations to display harm events in Randomised Controlled Trials. The meeting was attended by national senior statisticians from academia and industry, and delegates with info-graphic expertise.  The groups’ aim is to develop practical guidelines to support clinical trial researchers in their choice of visualisations for communicating AE data in publications. The next stage will seek input from clinicians and patients and the group will be publishing their work for trialists later this year.

June 24, 2020

A dose-finding design for early phase trials with continuous re-assessment

As part of the NIHR Statistics – Early Phase Trials Group webinar series on “Practical applications of advanced designs in Phase I Trials” Suzie Cro shared her recent experience of designing a dose finding study. The trial requires two agents to be combined where one has discrete dose levels and the other having doses that are patient specific. In the presentation Suzie Cro and Pavel Mozgunov from Lancaster University explained how they will evaluate the different discrete doses of the primary agent and allow for different ranges of the patient specific doses of the second agent.

June 11, 2020

NIHR Statistics Group Virtual Conference

As part of the 2020 NIHR Statistics Group virtual conference Rachel Phillips and Victoria Cornelius hosted a workshop on the use of visualisations to communicate information on harms in RCTs. In the workshop they demonstrated the use of four graphical displays and contrasted the visual summaries with data presented in the original published journal articles demonstrating impact for interpretation. Delegates provided feedback on the applications across settings. The responses in this session will contribute to the development of practical guidance for communicating harm data.

May 28, 2020

Evidence of unexplained discrepancies between planned and conducted statistical analyses

Different methods of analysis applied to the same clinical trial data set can lead to different conclusions. It is therefore important that the statistical analysis approach for a randomised controlled trial is pre-specified, and any changes or additions to the planned analysis should be flagged alongside trial results. This provides full transparency and allows for a thorough evaluation of the results. In a new review of trials published in high impact journals, we identified a large proportion of trials (61%) with one or more undisclosed change to the planned primary analysis approach. To see more results click the below link for the full open access publication of the review.    

May 17, 2020

New Tutorial: Controlled Multiple Imputation for Missing Data Sensitivity Analysis in Clinical Trials

In clinical trials it is most typical that some participant outcomes will not be available. This may be due to missed participant visits, trial withdrawal or other unplanned and uncontrollable events. Therefore often some required data will be missing from the analysis. When there are missing data, it is important that the primary analysis of the trial is conducted under the most plausible assumption for the missing data. Sensitivity analysis under a range of different credible assumptions should then be undertaken to assess how robust the trial results are. One method which readily enables contextually relevant sensitivity analysis, and has recently seen increased discussion and developments in the statistical literature, is Controlled Multiple Imputation.  In this new tutorial article, an overview of Controlled Multiple Imputation procedures, and a practical guide to their use for sensitivity analysis of a continuous outcome is provided. Worked examples and Stata code are included to facilitate adoption of such methods, to enable robust evaluation of clinical trial results.

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