full transcript

From the Ted Talk by Ben Goldacre: What doctors don't know about the drugs they prescribe

Unscramble the Blue Letters

Now you might say, well, that's an extremely unusual example, and I wouldn't want to be guilty of the same kind of cherry-picking and selective rieefcrenng that I'm accusing other people of. But it turns out that this pooeennhmn of publication bias has actually been very, very well studied. So here is one example of how you approach it. The classic mdoel is, you get a bunch of studies where you know that they've been conducted and clmpeoted, and then you go and see if they've been published anywhere in the academic literature. So this took all of the trials that had ever been conducted on antidepressants that were approved over a 15-year period by the FDA. They took all of the trials which were submitted to the FDA as part of the approval package. So that's not all of the talris that were ever conducted on these drugs, because we can never know if we have those, but it is the ones that were conducted in order to get the marketing authorization. And then they went to see if these trials had been pbulhseid in the peer-reviewed academic literature. And this is what they found. It was pretty much a 50-50 split. Half of these trials were positive, half of them were negative, in rleaity. But when they went to look for these trials in the peer-reviewed academic lteuaitrre, what they found was a very different picture. Only three of the negative trials were published, but all but one of the positive trials were published. Now if we just filck back and forth between those two, you can see what a staggering difference there was between reality and what doctors, pnettais, commissioners of health services, and academics were able to see in the peer-reviewed academic literature. We were misled, and this is a systematic flaw in the core of medicine.

Open Cloze

Now you might say, well, that's an extremely unusual example, and I wouldn't want to be guilty of the same kind of cherry-picking and selective ___________ that I'm accusing other people of. But it turns out that this __________ of publication bias has actually been very, very well studied. So here is one example of how you approach it. The classic _____ is, you get a bunch of studies where you know that they've been conducted and _________, and then you go and see if they've been published anywhere in the academic literature. So this took all of the trials that had ever been conducted on antidepressants that were approved over a 15-year period by the FDA. They took all of the trials which were submitted to the FDA as part of the approval package. So that's not all of the ______ that were ever conducted on these drugs, because we can never know if we have those, but it is the ones that were conducted in order to get the marketing authorization. And then they went to see if these trials had been _________ in the peer-reviewed academic literature. And this is what they found. It was pretty much a 50-50 split. Half of these trials were positive, half of them were negative, in _______. But when they went to look for these trials in the peer-reviewed academic __________, what they found was a very different picture. Only three of the negative trials were published, but all but one of the positive trials were published. Now if we just _____ back and forth between those two, you can see what a staggering difference there was between reality and what doctors, ________, commissioners of health services, and academics were able to see in the peer-reviewed academic literature. We were misled, and this is a systematic flaw in the core of medicine.

Solution

  1. reality
  2. patients
  3. literature
  4. model
  5. published
  6. trials
  7. referencing
  8. flick
  9. completed
  10. phenomenon

Original Text

Now you might say, well, that's an extremely unusual example, and I wouldn't want to be guilty of the same kind of cherry-picking and selective referencing that I'm accusing other people of. But it turns out that this phenomenon of publication bias has actually been very, very well studied. So here is one example of how you approach it. The classic model is, you get a bunch of studies where you know that they've been conducted and completed, and then you go and see if they've been published anywhere in the academic literature. So this took all of the trials that had ever been conducted on antidepressants that were approved over a 15-year period by the FDA. They took all of the trials which were submitted to the FDA as part of the approval package. So that's not all of the trials that were ever conducted on these drugs, because we can never know if we have those, but it is the ones that were conducted in order to get the marketing authorization. And then they went to see if these trials had been published in the peer-reviewed academic literature. And this is what they found. It was pretty much a 50-50 split. Half of these trials were positive, half of them were negative, in reality. But when they went to look for these trials in the peer-reviewed academic literature, what they found was a very different picture. Only three of the negative trials were published, but all but one of the positive trials were published. Now if we just flick back and forth between those two, you can see what a staggering difference there was between reality and what doctors, patients, commissioners of health services, and academics were able to see in the peer-reviewed academic literature. We were misled, and this is a systematic flaw in the core of medicine.

Frequently Occurring Word Combinations

ngrams of length 2

collocation frequency
publication bias 5
basic science 3
negative results 3
drug called 3
abnormal heart 3
academic literature 3
cancer research 2
suppresses abnormal 2
dummy placebo 2
placebo sugar 2
sugar pill 2
commercial development 2
heart attacks 2
comparing reboxetine 2
research misconduct 2
fda amendment 2
amendment act 2
trials conducted 2

ngrams of length 3

collocation frequency
suppresses abnormal heart 2
dummy placebo sugar 2
placebo sugar pill 2
fda amendment act 2

ngrams of length 4

collocation frequency
dummy placebo sugar pill 2

Important Words

  1. academic
  2. academics
  3. accusing
  4. antidepressants
  5. approach
  6. approval
  7. approved
  8. authorization
  9. bias
  10. bunch
  11. classic
  12. commissioners
  13. completed
  14. conducted
  15. core
  16. difference
  17. doctors
  18. drugs
  19. extremely
  20. fda
  21. flaw
  22. flick
  23. guilty
  24. health
  25. kind
  26. literature
  27. marketing
  28. medicine
  29. misled
  30. model
  31. negative
  32. order
  33. package
  34. part
  35. patients
  36. people
  37. period
  38. phenomenon
  39. picture
  40. positive
  41. pretty
  42. publication
  43. published
  44. reality
  45. referencing
  46. selective
  47. services
  48. split
  49. staggering
  50. studied
  51. studies
  52. submitted
  53. systematic
  54. trials
  55. turns
  56. unusual