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Uppsala Monitoring Centre에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Uppsala Monitoring Centre 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Uppsala Reports Long Reads – Unmasking data in the COVID-19 vaccine era

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Manage episode 353571612 series 2749727
Uppsala Monitoring Centre에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Uppsala Monitoring Centre 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Most pharmacovigilance professionals will have heard of masking – a statistical issue where reports for one drug hide signals for other drugs. But the problem gained fresh attention when record amounts of reports began piling up for the COVID-19 vaccines. How should we be unmasking data in the COVID-19 vaccine era?
This episode is part of the Uppsala Reports Long Reads series – the most topical stories from UMC’s pharmacovigilance magazine, brought to you in audio format. Find the original article here.
After the read, we speak to data scientist Sara Vidlin, who authored the article, to learn more about masking and how to deal with it.
Tune in to find out:

  • How masking evolves with the data
  • Which methods can be used to unmask data
  • What other pitfalls to watch out for when performing quantitative analyses

Want to know more?
In the very beginning of the vaccine rollout, the USA FDA observed how early signals for COVID-19 vaccines were delayed because of other drugs masking them, highlighting how masking is not a static phenomenon.
In 2013, Uppsala Monitoring Centre developed a simple strategy to uncover masking by identifying and removing influential outliers.

Join the conversation on social media
Follow us on X, LinkedIn, or Facebook and share your thoughts about the show with the hashtag #DrugSafetyMatters.
Got a story to share?
We’re always looking for new content and interesting people to interview. If you have a great idea for a show, get in touch!
About UMC
Read more about Uppsala Monitoring Centre and how we work to advance medicines safety.

  continue reading

43 에피소드

Artwork
icon공유
 
Manage episode 353571612 series 2749727
Uppsala Monitoring Centre에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Uppsala Monitoring Centre 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Most pharmacovigilance professionals will have heard of masking – a statistical issue where reports for one drug hide signals for other drugs. But the problem gained fresh attention when record amounts of reports began piling up for the COVID-19 vaccines. How should we be unmasking data in the COVID-19 vaccine era?
This episode is part of the Uppsala Reports Long Reads series – the most topical stories from UMC’s pharmacovigilance magazine, brought to you in audio format. Find the original article here.
After the read, we speak to data scientist Sara Vidlin, who authored the article, to learn more about masking and how to deal with it.
Tune in to find out:

  • How masking evolves with the data
  • Which methods can be used to unmask data
  • What other pitfalls to watch out for when performing quantitative analyses

Want to know more?
In the very beginning of the vaccine rollout, the USA FDA observed how early signals for COVID-19 vaccines were delayed because of other drugs masking them, highlighting how masking is not a static phenomenon.
In 2013, Uppsala Monitoring Centre developed a simple strategy to uncover masking by identifying and removing influential outliers.

Join the conversation on social media
Follow us on X, LinkedIn, or Facebook and share your thoughts about the show with the hashtag #DrugSafetyMatters.
Got a story to share?
We’re always looking for new content and interesting people to interview. If you have a great idea for a show, get in touch!
About UMC
Read more about Uppsala Monitoring Centre and how we work to advance medicines safety.

  continue reading

43 에피소드

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