> Every day, millions of people are taking medications that will not help them. The top ten highest-grossing drugs in the United States help between 1 in 25 and 1 in 4 of the people who take them (see 'Imprecision medicine'). For some drugs, such as statins — routinely used to lower cholesterol — as few as 1 in 50 may benefit. There are even drugs that are harmful to certain ethnic groups because of the bias towards white Western participants in classical clinical trials.
Those are stunningly small proportions. What is the explanation? People try out lots of drugs and stop taking those that seem not to be working?
The graphic in the article says the proportions are related to the https://en.wikipedia.org/wiki/Number_needed_to_treat but I think I'll have to read that article several times to understand. :) Not clear what reference in the article (the Nature one) provides the proportions or NNT data, but the nearest footnote is paywalled anyway.
Read again, the 'proportions' are literally 1 in NNT, I think. NNT is the number needed to treat in order to make a positive difference for 1 patient, vs control group with no treatment. NNT between two studies not directly comparable if they are of different durations.
I'm still curious then how such high NNT drugs are blockbusters. Restating what I wrote above, I guess it is worth trying many of these, even with potential side effects, for a 1 in 4 chance the drug will help (seems entirely plausible) to even a 1 in 50 chance (less so).
I suppose then that precision medicine could largely have people trying fewer drugs, as for people similar to the patient, the NNT might be lower (indicating a definite try) or higher -- but OTOH if people are taking a 1 in 50 chance now, what odds will actually make them bypass a drug?
Those are stunningly small proportions. What is the explanation? People try out lots of drugs and stop taking those that seem not to be working?
The graphic in the article says the proportions are related to the https://en.wikipedia.org/wiki/Number_needed_to_treat but I think I'll have to read that article several times to understand. :) Not clear what reference in the article (the Nature one) provides the proportions or NNT data, but the nearest footnote is paywalled anyway.