The 2019 PSI Conference took place at the Queen Elizabeth II Centre (QEII), London, with the theme of “Data Driven Decision Making in Medical Research”.

The sessions included early phase innovative trial design, industry best practice, statistical issues in safety drug labelling, model-based dose-finding designs, an update from Transcelerate and much more.

In this series of interviews with the speakers at the conference, we talked about different topics:

  • Visualization software
  • Benefit risks approach
  • Global statistical test for multiple endpoint analysis
  • Estimands
  • AE analysis using a volcano plot

I also talked to Rachel Phillips at the PSI conference. She is an NIHR doctoral research fellow at Imperial College London. Please help her with her study. It will help all of us in the end and you can win something!

This is a survey of clinical trial statisticians with experience of planning and performing final data analyses for pharmacological RCTs to explore their awareness of available statistical methods to flag adverse events as potential adverse drug reactions (ADRs) and identify any potential barriers to their use, as well as gain feedback on ideas for new statistical methods. They would like participants to provide their personal views. This study is being organised and sponsored by Imperial College London. This study is funded by the National Institute for Health Research (NIHR). The survey should take no longer than 10 minutes to complete and all participants will be entered into a prize draw to win a £50 Amazon voucher.

The survey should take no longer than 10 minutes to complete and all participants will be entered into a prize draw to win a £50 Amazon voucher.

If you are happy to participate in the survey, please follow the link below: https://www.surveymonkey.com/r/R5M2R83

Listen to this episode, to get more insights into what’s possible and to learn more about the conference!

Transcript

Join The Effective Statistician LinkedIn group

I want to help the community of statisticians, data scientists, programmers and other quantitative scientists to be more influential, innovative, and effective. I believe that as a community we can help our research, our regulatory and payer systems, and ultimately physicians and patients take better decisions based on better evidence.

I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.

When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.

When my mother is sick, I want her to understand the evidence and being able to understand it.

When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.

I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.

Let’s work together to achieve this.