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Density strips: visualisation of uncertainty in clinical data summaries and research findings
  1. Christopher J Weir1,
  2. Adrian W Bowman2
  1. 1 Edinburgh Clinical Trials Unit, Usher Institute, The University of Edinburgh, Edinburgh, UK
  2. 2 School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
  1. Correspondence to Professor Christopher J Weir, Edinburgh Clinical Trials Unit, The University of Edinburgh, Edinburgh, Edinburgh, UK;{at}


The disproportionate focus on statistical significance in reporting and interpreting clinical research studies contributes to publication bias and encourages selective reporting. This highlights a need for alternative approaches that clearly communicate the uncertainty in the data, enabling researchers to provide a more nuanced interpretation of clinical research findings.

Our purpose in this article is to introduce the density strip method as one potential approach that might act as a bridge between data visualisation for descriptive purposes and formal statistical inference. We build on existing theory, translating it to the applied research context to illustrate its utility to clinical researchers.

We achieve this by considering an exemplar clinical trial, Multiple Sclerosis-Secondary Progressive Multi-Arm Randomisation Trial (MS-SMART). MS-SMART was a multiarm randomised placebo-controlled trial of three potentially neuroprotective drugs in secondary progressive MS. We illustrate through MS-SMART the potential of the density strip as an effective visualisation of the distribution of clinical trial outcomes and as a complementary approach to aid the interpretation of formal, inferential, statistical analysis.

We conclude by summarising the advantages and disadvantages of the density strip methodology and provide suggestions for its potential extensions and possible further uses.

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  • Contributors CJW conceived this article and AWB performed the data analysis and created the figures and supplementary material. Both authors contributed equally to writing the manuscript. CJW is responsible for the overall content as guarantor.

  • Funding MS-SMART (reference 11/30/11) was funded by the Efficacy and Mechanism Evaluation (EME) Programme, a Medical Research Council (MRC) and National Institute for Health Research (NIHR) partnership. The UK and US (NMSS) MS Societies also provided funding. Additional support came from the University of Edinburgh, the NIHR-UCL Hospitals Biomedical Research Centre and UCL; and the NIHR Leeds Clinical Research Facility (Dental Translation and Clinical Research Unit). CJW was also supported in this work by NHS Lothian via the Edinburgh Clinical Trials Unit.

  • Disclaimer The views expressed in this publication are those of the author(s) and not necessarily those of the MRC, NIHR, or the Department of Health and Social Care.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; internally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.