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A tartalmat a Uppsala Monitoring Centre biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Uppsala Monitoring Centre vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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#20 The evidence for signals – Daniele Sartori

45:41
 
Megosztás
 

Manage episode 424661247 series 2749727
A tartalmat a Uppsala Monitoring Centre biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Uppsala Monitoring Centre vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

Spontaneous reports of adverse drug reactions are a common source of evidence in pharmacovigilance, but as the science evolves, so do the types of data used to find and assess signals. Uppsala Monitoring Centre’s Daniele Sartori reviews how signal detection practices have changed over time.
Tune in to find out:

  • Which features of case reports are most often used to assess causality
  • Why pharmacovigilance experts should report clinical assessments clearly
  • How to shorten the time between signal detection and communication

Want to know more?
Check out the full scoping review that inspired this episode.
In 2002, Meyboom and colleagues discussed criteria to select and follow up on signals.
In the first chapter of Uncertainty in Pharmacology, Aronson explains the difference between evidence for a mechanism and evidence from a mechanism.
In 2018, Murad and colleagues published a method to evaluate the quality of evidence in a series of case reports.
UMC scientists have shown how chemical information can support timely signal detection.
This episode is the first of a three-part series on sources of evidence in pharmacovigilance. Listen to the other two episodes here:

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

Fejezetek

1. #20 The evidence for signals – Daniele Sartori (00:00:00)

2. Intro (00:00:15)

3. Welcome, Daniele! (00:01:43)

4. What is a signal? (00:02:13)

5. Sources of evidence (00:04:27)

6. Why did you research this? (00:06:14)

7. Scoping review (00:07:35)

8. Signals based on case reports (00:10:31)

9. Features of causality (00:12:53)

10. Experimental evidence (00:14:44)

11. Reporting clinical assessments (00:17:21)

12. Case-by-case assessment (00:19:36)

13. Unexpected findings (00:21:52)

14. Value of other types of evidence (00:24:08)

15. Pharmacological reasoning (00:26:38)

16. Time to communication (00:32:25)

17. Using signal information (00:36:02)

18. Is artificial intelligence a threat? (00:39:33)

19. Impact of the study (00:41:26)

20. Future research (00:42:43)

21. Outro (00:44:01)

48 epizódok

Artwork
iconMegosztás
 
Manage episode 424661247 series 2749727
A tartalmat a Uppsala Monitoring Centre biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Uppsala Monitoring Centre vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

Spontaneous reports of adverse drug reactions are a common source of evidence in pharmacovigilance, but as the science evolves, so do the types of data used to find and assess signals. Uppsala Monitoring Centre’s Daniele Sartori reviews how signal detection practices have changed over time.
Tune in to find out:

  • Which features of case reports are most often used to assess causality
  • Why pharmacovigilance experts should report clinical assessments clearly
  • How to shorten the time between signal detection and communication

Want to know more?
Check out the full scoping review that inspired this episode.
In 2002, Meyboom and colleagues discussed criteria to select and follow up on signals.
In the first chapter of Uncertainty in Pharmacology, Aronson explains the difference between evidence for a mechanism and evidence from a mechanism.
In 2018, Murad and colleagues published a method to evaluate the quality of evidence in a series of case reports.
UMC scientists have shown how chemical information can support timely signal detection.
This episode is the first of a three-part series on sources of evidence in pharmacovigilance. Listen to the other two episodes here:

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

Fejezetek

1. #20 The evidence for signals – Daniele Sartori (00:00:00)

2. Intro (00:00:15)

3. Welcome, Daniele! (00:01:43)

4. What is a signal? (00:02:13)

5. Sources of evidence (00:04:27)

6. Why did you research this? (00:06:14)

7. Scoping review (00:07:35)

8. Signals based on case reports (00:10:31)

9. Features of causality (00:12:53)

10. Experimental evidence (00:14:44)

11. Reporting clinical assessments (00:17:21)

12. Case-by-case assessment (00:19:36)

13. Unexpected findings (00:21:52)

14. Value of other types of evidence (00:24:08)

15. Pharmacological reasoning (00:26:38)

16. Time to communication (00:32:25)

17. Using signal information (00:36:02)

18. Is artificial intelligence a threat? (00:39:33)

19. Impact of the study (00:41:26)

20. Future research (00:42:43)

21. Outro (00:44:01)

48 epizódok

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