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08 September 2021

The Wonderful Wednesday of September is about the display of treatment differences in time-series data on the example of Continuous Glucose Monitoring (CGM) data. Zachary Skrivanek presents the visualisations proposed for this challenger ranging from explanatory plots with condensed information to an exploratory interactive dashboard. All visualisations are available on the Wonderful Wednesday blog.

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The Wonderful Wednesday of September is about the display of treatment differences in time-series data on the example of Continuous Glucose Monitoring  (CGM) data. Zachary Skrivanek presents the visualisations proposed for this challenger ranging from explanatory plots with condensed information to an exploratory interactive dashboard. All visualisations are available on the Wonderful Wednesday blog.

The main message of successful glycemic control is nicely transported in a box plot using intuitive coloring. For a detailed look at the subject level data the CGM dashboard gives the possibility to combine different displays while being able to sort and filter the data. In addition it plots the results of recursive partitioning models that can be interactively applied to a huge set of parameters.

Last but not least a set of different multi-plots are discussed highlighting pros and cons of overlayed bands, averages, modelled averages, and scatter plots. This includes the usage of various visual elements as well as effective decluttering of a visualisation.

The October challenge is on a competing risk in a recent COVID-19 data example. How to find a way to display the impact of different risk factors on the risk of death considering the competing risk of recovery? See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes: Bodo Kirsch, Alexander Schacht, Mark Baillie, Daniel Saure, Zachary Skrivanek, Lorenz Uhlmann, Rachel Phillips, Markus Vogler, David Carr, Steve Mallett, Abi Williams, Julia Igel, Gakava Lovemore, Katie Murphy, Rhys Warham, Sara Zari, Irene de la Torre Arenas



11 August 2021

For this edition of the Wonderful Wednesdays, the audience was asked to send examples of visualizations representing coronavirus data. Mark Baillie guided the webinar, showcasing different types of visualizations, such as area graphs, forest plots, streamgraphs, or network analysis. All visualizations are available on the Wonderful Wednesday blog.

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For this edition of the Wonderful Wednesdays, the audience was asked to send examples of visualizations representing coronavirus data. Mark Baillie guided the webinar, showcasing different types of visualizations, such as area graphs, forest plots, streamgraphs, or network analysis. All visualizations are available on the Wonderful Wednesday blog.

The webinar starts by showing an example of a governmental COVID dashboard. Clean and straight to the point, the UK site provides information about the pandemic in the country. It includes numbers and texts that answer the main questions that users might have: are cases rising? What are the vaccinations rates? By clicking each of the topics, users can see specific information in the form of interactive charts. 

The next visualization, by the Financial Times, represents the excess of deaths caused by the Coronavirus pandemic. It shows a set of small multiples -one per country- highlighting when the number of deaths was higher than the average in recent years. Although the information is impressive, the chart is very crowded with data and annotations which makes understanding it a bit difficult. A similar project, done by The Economist, included interactivity to avoid this problem. Their implementation of tooltips to extract information is very well done.

The following visualization is an unusual chart done again by The Financial Times: a streamgraph. This type of plot is a stacked area chart displaced around a central axis. Its organic shapes and different looks might make them unconventional and attractive. However, with this type of chart is difficult to compare the size of the areas. And users who are not familiarized with them might have a hard time understanding them.

But visualizing the coronavirus pandemic doesn’t mean using rare charts, or interactive projects. One forest plot from The Economist shows how this traditional chart can be extremely successful at highlighting stories. The key is to include labels and annotations to make the information accessible and declutter the axis to make the data be the main protagonist.

Many of the projects around COVID used gamification and interactivity to explain complex scientific terms to the general audience. The webinar highlighted two that explained how the virus can expand slower or faster depending on people staying or not at home. Users can understand better how simulations and models work by interacting with the different variables that feed the interactive visualizations.

The last example is a network analysis of how the virus moved in Hong Kong during the different waves.

14 July 2021

Abi Williams presents the visualisations of the SDQ-12 in conjunction with different anchor measures. For this challenge very different plot types have been proposed. All visualisations are available on the Wonderful Wednesday blog.

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Abi Williams presents the visualisations of the SDQ-12 in conjunction with different anchor measures. For this challenge very different plot types have been proposed. All visualisations are available on the Wonderful Wednesday blog.

Two ways of multiplot staggered bar charts are shown to get a quick overview of the SDQ-12 data. The waterfall plot nicely displayed the relation of the SDQ change to the self-reported outcome. A network plot showed the relation to the other anchor measurements. And then there is that great interactive tool with multiple display options including a plot like it’s used for the principle compound analyses and a scatterplot matrix using also mosaic plots for the categorical variables. Last but not least a wright map visualised the item response models. The new challenge is asking for your favorite plot around COVID-19. Where have you seen it? What do you like about it? How could it even be improved?

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes: Bodo Kirsch, Alexander Schacht, Mark Baillie, Daniel Saure, Zachary Skrivanek, Lorenz Uhlmann, Rachel Phillips, Markus Vogler, David Carr, Steve Mallett, Abi Williams, Julia Igel, Gakava Lovemore, Katie Murphy, Rhys Warham, Sara Zari, Irene de la Torre Arenas.

06 July 2021

Watch Chris Harbron (Roche) and Margaret Gamalo (Pfizer) present their recent work. The webinar will be chaired by Elizabeth Williamson (London School of Hygiene and Tropical Medicine).

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Watch Chris Harbron (Roche) and Margaret Gamalo (Pfizer) present their recent work. The webinar will be chaired by Elizabeth Williamson (London School of Hygiene and Tropical Medicine).

06 July 2021

View now to find out about all the exciting events and content PSI have got planned for the rest of this year and beyond.

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This year's Annual General Meeting focused on how PSI has navigated the challenges of the past year and adapted to the new online world, as well as how we plan to embrace a new Board structure and new opportunities as we move forward. View now to find out about all the exciting events and content PSI have got planned for the rest of this year and beyond.

29 June 2021

This presentation gives some background regarding the ‘Carcinogenicity Statistics Discussion Group’, which is an industry group started by the ‘Nonclinical Biostatistics Leadership Forum’. The talk reviews the history of the group, outlines the current status, and gives an overview of the types of topics discussed. Highlights from some past discussion topics are also reviewed.

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Steven Bailey

This presentation gives some background regarding the ‘Carcinogenicity Statistics Discussion Group’, which is an industry group started by the ‘Nonclinical Biostatistics Leadership Forum’. The talk reviews the history of the group, outlines the current status, and gives an overview of the types of topics discussed. Highlights from some past discussion topics are also reviewed.

09 June 2021

Steve Mallett leads the discussion around the proposed visualisations of multiple endpoints over time. As a special guest Agustin Calatroni joined the panel to answer questions on his submitted visualisations. He also let us know how he’s approaching the visualization challenges in general and what is helping him. All visualisations are available on the Wonderful Wednesday blog.

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Steve Mallett leads the discussion around the proposed visualisations of multiple endpoints over time. As a special guest Agustin Calatroni joined the panel to answer questions on his submitted visualisations. He also let us know how he’s approaching the visualization challenges in general and what is helping him. All visualisations are available on the Wonderful Wednesday blog.

Simplicity is helping to concentrate on the main message. The presented KM plot is a good example for this. The per-subject plot is combining two endpoints allowing to see individual outcomes. A detailed exploration of all four endpoints is realized with the interactive Trelliscope submitted by Agustin. The next challenge is on psychometric data. How can PROs can be visually related to anchor measurements? And what are your ideas to explore validity and reliability of the results?

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes: Bodo Kirsch, Alexander Schacht, Mark Baillie, Daniel Saure, Zachary Skrivanek, Lorenz Uhlmann, Rachel Phillips, Markus Vogler, David Carr, Steve Mallett, Abi Williams, Julia Igel, Gakava Lovemore, Katie Murphy, Rhys Warham, Sara Zari, Irene de la Torre Arenas.

02 June 2021

You will be guided through a case study (CheckMate 037) and interactively deepen the knowledge to gain hands-on experience in developing estimands. You will be introduced to the background and disease context of the case study, the concept of an estimand, and important clinical events (increased dropout rate and crossover therapy) that occurred in the trial and affected interpretation of the results. Using non-technical language and clear graphical presentation of the concepts, you will experience how the estimand framework provides a common language to describe the diversity of patient journeys and why it is important to address the right question in clinical trials.

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You will be guided through a case study (CheckMate 037) and interactively deepen the knowledge to gain hands-on experience in developing estimands. You will be introduced to the background and disease context of the case study, the concept of an estimand, and important clinical events (increased dropout rate and crossover therapy) that occurred in the trial and affected interpretation of the results. Using non-technical language and clear graphical presentation of the concepts, you will experience how the estimand framework provides a common language to describe the diversity of patient journeys and why it is important to address the right question in clinical trials. Target audience (no prior knowledge in oncology or of estimands required): Clinicians, Investigators, Regulatory Experts, Medical Writers, Ethics Committees, Statisticians.

The targeted learning outcomes are as follows: - Recognize the benefits of following the estimand framework (ICH E9 (R1) addendum) in the context of a clinical trial, in order to: - have a common language to describe the diversity of patient journeys - address the right question in clinical trials - Be able to construct an estimand, including identification of relevant intercurrent events and application of relevant strategies to address them - Gain insights from a cross-industry international working group on estimands in oncology Presented by members of the Estimands in Oncology special interest group www.oncoestimand.org 

Contents
05:33 Learning Outcomes
06:30 Introduction to the case study
15:55 Intermezzo - Comic
17:20 Estimands in Oncology - How and Why
     17:20 ICH E9 (R1) Estimand Framework
     21:40 Five Components of an Estimand
     25:15 Five Strategies for Intercurrent Events
42:43 Revisiting the case study
     45:00 Estimand for the primary analysis
     47:21 Estimand for the post-hoc analysis
49:20 Interactive quiz with Q&A
1:18:40 Concluding Remarks
1:20:30 General Q&A
 

25 May 2021

The objective of this PSI webinar is to enable practical interaction among clinical statisticians actively working in oncology and those interested to work in this area. The format of this meeting specifically facilitates these interactions, by balancing equally time dedicated to short talks covering a broad range of relevant topics and to Q&A.​

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Presented by Rachel Hodge (AstraZeneca), Thomas Jaki (MRC Biostatistics Unit), Archan Bhattacharya (Janssen), Nigel Stallard (University of Warwick) and Emma Clark (Roche).

Effective treatment, early detection and prevention of cancer remain fundamental challenges to current clinical research. Discovering and developing successful oncology treatments requires design and execution of an increasing variety of clinical studies, calling for a commensurate range of fit-for-purpose statistical methods. Clinical statisticians working in oncology are thus exposed to a flow of evolving objectives, endpoints, measurement technologies, methodological and operational challenges. The objective of this PSI webinar is to enable practical interaction among clinical statisticians actively working in oncology and those interested to work in this area. The format of this meeting specifically facilitates these interactions, by balancing equally time dedicated to short talks covering a broad range of relevant topics and to Q&A.
This webinar was sponsored by Janssen R&D.

19 May 2021

Presented by Mine Çetinkaya-Rundel, in this talk we'll introduce the Grammar of Graphics, which allows you to compose graphs by combining independent components, and the implementation of this theory in R -- the ggplot2 package. We will describe the basics of building plots with ggplot2 and touch on a few approaches for customizing the plots. We will also highlight a few packages that are built to supplement ggplot2.

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Presented by Mine Çetinkaya-Rundel, in this talk we'll introduce the Grammar of Graphics, which allows you to compose graphs by combining independent components, and the implementation of this theory in R -- the ggplot2 package. We will describe the basics of building plots with ggplot2 and touch on a few approaches for customizing the plots. We will also highlight a few packages that are built to supplement ggplot2.

Key learnings include: - Fundamentals of the theory of the Grammar of Graphics - Basics of building plots with ggplot2, layer by layer - Customising plots with functionality that comes with the ggplot2 package as well as supplemented by other packages. To access the slides from this presentation, please visit: http://bit.ly/ggplot2-vissig

12 May 2021

Lorenz Uhlmann presents the visualisation proposals for sustained response. The challenge was to display the timing of response and how this response was sustained over time. This was approached by showing individual as well as summary data. All visualisations are available on the Wonderful Wednesday blog.

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Lorenz Uhlmann presents the visualisation proposals for sustained response. The challenge was to display the timing of response and how this response was sustained over time. This was approached by showing individual as well as summary data. All visualisations are available on the Wonderful Wednesday blog.

On the individual data level a lasagna plot is suitable to clearly show how quick the response was obtained and if it was sustained. Intelligent sorting supports the visual impression. The interactive bar chart allows for treatment comparison on summarised data. A complete new approach combines trajectory clustering with a set of displays to describe the clusters. The next challenge is on vasculitis data. How can visualisation help to explore the effectiveness of the treatment across a range of different clinical outcomes?

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes: Bodo Kirsch, Alexander Schacht, Mark Baillie, Daniel Saure, Zachary Skrivanek, Lorenz Uhlmann, Rachel Phillips, Markus Vogler, David Carr, Steve Mallett, Abi Williams, Julia Igel, Gakava Lovemore, Katie Murphy, Rhys Warham, Sara Zari, Irene de la Torre Arenas.

05 May 2021

Incomplete datasets due to missing data is an issue that has been, and will be, around for a long time. At this meeting we will present the evolution of missing data approaches, looking at how they have been handled in the past, the current established missing data approaches and the impact of the new ICH E9 R1 addendum on the handling of missing data, focussing in particular on the treatment policy estimand.

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David Wright (AstraZeneca), James Bell (Elderbrook solutions GmbH), Michael O’Kelly (IQVIA), Daniel Bratton (GSK)

Incomplete datasets due to missing data is an issue that has been, and will be, around for a long time. At this meeting we will present the evolution of missing data approaches, looking at how they have been handled in the past, the current established missing data approaches and the impact of the new ICH E9 R1 addendum on the handling of missing data, focussing in particular on the treatment policy estimand.

David Wright (AstraZeneca) Aligning how subjects with missing data due to study discontinuation are handled in the primary analysis with the primary estimand. James Bell (Elderbrook solutions GmbH) The Practicalities of Treatment Policy Estimation Michael O’Kelly (IQVIA) Even a “treatment policy” estimand may have missing data: how can we take account of this? Daniel Bratton (GSK) Treatment policy estimands for recurrent event data using data collected after cessation of randomised treatment. Panel discussion (led by David Wright) and closing remarks.

Key Timings
03:38 
- Introduction & Welcome
05:20 - David Wright
45:08 - James Bell
1:27:05 - Michael O'Kelly
2:10:00 - Daniel Bratton
2:34:00 - Panel Q&A
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