Publications

BibTex format

@article{Phillips:2022:10.1136/bmj-2021-068983,
author = {Phillips, R and Cro, S and Wheeler, G and Bond, S and Morris, TP and Creanor, S and Hewitt, C and Love, S and Lopes, A and Schlackow, I and Gamble, C and MacLennan, G and Habron, C and Gordon, A and Vergis, N and Li, T and Qureshi, R and Everett, C and Holmes, J and Kirkham, A and Peckitt, C and Pirrie, S and Ahmed, N and Collett, L and Cornelius, V},
doi = {10.1136/bmj-2021-068983},
journal = {BMJ: British Medical Journal},
title = {Visualising harms in publications of randomised controlled trials: consensus and recommendations},
url = {http://dx.doi.org/10.1136/bmj-2021-068983},
volume = {377},
year = {2022}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Objective: To improve communication of harm in publications of randomised controlled trials via the development of recommendations for visually presenting harm outcomes.Design: Consensus study.Setting: 15 clinical trials units registered with the UK Clinical Research Collaboration, an academic population health department, Roche Products, and TheBMJ.Participants: Experts in clinical trials: 20 academic statisticians, one industry statistician, one academic health economist, one data graphics designer, and two clinicians.Main outcome measures: A methodological review of statistical methods identified visualisations along with those recommended by consensus group members. Consensus on visual recommendations was achieved (at least 60% of the available votes) over a series of three meetings with participants. The participants reviewed and critically appraised candidate visualisations against an agreed framework and voted on whether to endorse each visualisation. Scores marginally below this threshold (50-60%) were revisited for further discussions and votes retaken until consensus was reached.Results: 28 visualisations were considered, of which 10 are recommended for researchers to consider in publications of main research findings. The choice of visualisations to present will depend on outcome type (eg, binary, count, time-to-event, or continuous), and the scenario (eg, summarising multiple emerging events or one event of interest). A decision tree is presented to assist trialists in deciding which visualisations to use. Examples are provided of each endorsed visualisation, along with an example interpretation, potential limitations, and signposting to code for implementation across a range of standard statistical software. Clinician feedback was incorporated into the explanatory information provided in the recommendations to aid understanding and interpretation.Conclusions: Visualisations provide a powerful tool to communicate harms in clinical trials, offering an alt
AU  - Phillips,R
AU  - Cro,S
AU  - Wheeler,G
AU  - Bond,S
AU  - Morris,TP
AU  - Creanor,S
AU  - Hewitt,C
AU  - Love,S
AU  - Lopes,A
AU  - Schlackow,I
AU  - Gamble,C
AU  - MacLennan,G
AU  - Habron,C
AU  - Gordon,A
AU  - Vergis,N
AU  - Li,T
AU  - Qureshi,R
AU  - Everett,C
AU  - Holmes,J
AU  - Kirkham,A
AU  - Peckitt,C
AU  - Pirrie,S
AU  - Ahmed,N
AU  - Collett,L
AU  - Cornelius,V
DO  - 10.1136/bmj-2021-068983
PY  - 2022///
SN  - 0959-535X
TI  - Visualising harms in publications of randomised controlled trials: consensus and recommendations
T2  - BMJ: British Medical Journal
UR  - http://dx.doi.org/10.1136/bmj-2021-068983
UR  - http://hdl.handle.net/10044/1/96885
VL  - 377
ER  -

Download

ProfessorVictoriaCornelius

Contact

Assistant

Location

Summary

Citation

BibTex format

RIS format (EndNote, RefMan)