日時
2024年10月2日(水)16:00 - 17:00 (JST)
講演者
言語
英語
ホスト
Catherine Beauchemin

Ever wondered what data is considered sufficient for approval of a new drug or vaccine? In this talk, I will talk about some of the errors and shortcomings with how clinical trials are run and regulated. I will also show how the data and analyses behind clinical trials can be very poorly done. I will show one example of very bad data and analysis, but I will also show an example of the valuable information that can come out of doing a good job in presenting, interpreting, and following the data. I will highlight how the over-reliance on summarizing measures like averages and the Gaussian assumption can lead to overlooking therapies that could otherwise have been extremely effective.

This talk should be of critical importance to those working in the fields of health, medical and clinical research. But this talk is about data and its analysis, and as such is also very relevant to physicists and other scientists who generate, present or analyse data as part of their research.

References

  1. Holst M, Haslberger M, Yerunkar S, et al., Frequency of multiple changes to prespecified primary outcomes of clinical trials completed between 2009 and 2017 in German university medical centers: A meta-research study, doi: 10.1371/journal.pmed.1004306
  2. Retraction Watch Leader Board
  3. Prasad V, Vandross A, Toomey C, et al., A decade of reversal: an analysis of 146 contradicted medical practices, doi: 10.1016/j.mayocp.2013.05.012
  4. Weissgerber TL, Milic NM, Winham SJ, Garovic VD, Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm, doi: 10.1371/journal.pbio.1002128

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