Importance of understanding medical statistics
Here is an excellent article by Maggie Mahar over at Health Beat. This article provides an excellent example of the power of statistics in medical research and how they can be manipulated to paint a positive picture.
This article also gives a better, more concrete explanation of the significance of the number needed to treat statistic. Here is the most relevant part:
He notes that “to spare one person a heart attack, 100 people had to take Lipitor for more than three years [i.e. the duration of the trial].” Think about it—if the trial only tells us that Lipitor only helps one out of a 100 people who take it faithfully for three years than working with a pool of less than 100 would produce no benefits. You can’t help one-third of a person not have a heart attack. Conversely, a success rate of one out of 100 means that “the other 99 got no measurable benefit” from Lipitor.
These numbers are a lot less comforting than the more superficial statistic of cutting heart attacks by 36 percent. But this data is what ultimately matters, because it represents the number needed to treat (NNT) for one person to benefit. For Lipitor, that number is 100—in other words, an honest doctor would have to tell her patient that “only 1 in 100 [people who take Lipitor] is likely” to be positively affected by the drug. Of course, doctors are subjected to the same lobbying from drug companies as consumers, and more often than not, according to Dr. Darshak Sanghavi from UMass Medical School, “many physicians don’t know the NNT” of specific drugs. This isn’t information we hear very often—even from medical experts.