Algorithm Finds Thousands of Unknown Drug Interaction Side Effects 121
ananyo writes "An algorithm designed by U.S. scientists to trawl through a plethora of drug interactions has yielded thousands of previously unknown side effects caused by taking drugs in combination (abstract). The work provides a way to sort through the hundreds of thousands of 'adverse events' reported to the U.S. Food and Drug Administration each year. The researchers developed an algorithm that would match data from each drug-exposed patient to a nonexposed control patient with the same condition. The approach automatically corrected for several known sources of bias, including those linked to gender, age and disease. The team then used this method to compile a database of 1,332 drugs and possible side effects that were not listed on the labels for those drugs. The algorithm came up with an average of 329 previously unknown adverse events for each drug — far surpassing the average of 69 side effects listed on most drug labels."
I was wondered about something (Score:3, Interesting)
Re:not surprising (Score:5, Interesting)
Re:not surprising (Score:5, Interesting)
There are databases and search applications that can be made more accurate with the new data. For example, Denmark has an online system where citizens can enter the name of two drugs and get a list of possible side effects and warnings. There are also big US and European databases of this kind, although less open to the public (I believe).
Multiple testing problem? (Score:5, Interesting)
I am a statistician.
I've only done a light skim of the paper, but it seems to me that the OP (but not the paper itself) is being way too positive here. Their methodology seems to be very vulnerable to false positives - with a massive database of drugs and potential adverse effects, you'd expect a *lot* of apparent side effects occuring solely by chance. For example:
"We constructed a database of 438,801 off-label side effects for 1332 drugs and 10,097 adverse events."
Supposing you are doing a hypothesis test at the standard 0.05 significance level, for each of the 1332*10097 drug-side effect combinations. Then, with naive assumptions, on a null hypothesis, you'd be picking up an average of 666k+ 'side effects' anyway, purely by chance. With the drug interactions case, this multiple testing problem gets even worse.
Now, there are ways to correct for multiple testing, but for things as large and complicated as this problem, I'm not sure the standard methods are going to cut it. At best, this study should be considered more a *filter* on the set of potential side effects, than really an enumeration of effects that are actually there. This is ignoring other issues like the placebo effect.
Are these really the result of drug interactions? (Score:5, Interesting)
Simple (Score:1, Interesting)
All drugs have side-effects. In some those side-effects can be serious and even deadly, but it's pretty unpredictable what the side-effects will be and/or their severity in a particular patient, let alone one that takes other drugs. In others, the side-effects will never appear.
For instance, I'm one of those annoying people who doesn't take drugs unless absolutely necessary - not because I distrust the medical establishment (because I don't) but because if I don't need a drug, I won't take it - and even then, I never experience side-effects or, if I'm honest, much of the drug's effect anyway).
About the only thing I "take" is caffeine, and that only in drinks that happen to contain it - I don't deliberately seek it out or have a drink BECAUSE I need caffeine or because it's caffeinated (i.e. I've never said "Oh, I need a coffee" or had one to "perk me up").
People keep telling me to take headache tablets, cold/flu "remedies", painkillers, etc. etc. etc. and I avoid them like the plague. The people who use them use them CONSTANTLY and still get headaches, flu and pain worse than I ever have. If you have a pack of pills in your bag "just in case" of headache, cold, etc. then you should be made to throw them away - they are purely placebo. In any group of people, you'll find one who has pills for things like that. I *will* give you migraine relief, but that's a different thing entirely.
When I have had surgical work, I take the antibiotics and never get the painkillers. I don't see the point in them if I'm not hurting, but the antibiotics might *actually* be doing something (but I doubt it very much, to be honest).
But, literally ANYTHING I pop into my mouth that I haven't had before could kill me the instant it touches my stomach. You have no way to know. The question is now, and has only ever been, does the risk of the thing that the drug "fixes" overcome the risk of the drug itself? Hell, even paracetamol comes with a huge list of very-dangerous effects it can produce in some people. You can't read them all or not expect them to happen.
All this does is help doctors avoid risk-factors. Maybe they might spot a slightly increased risk that one drug has over a nearly-identical drug. But you're really playing tiny odds anyway. Any serious interactions that weren't down to just plain intolerance of the drug anyway have almost certainly already been found. That's why you do large-scale, long-term medical trials. Any new side-effects discovered will just go into a list of "possibles" but eventually every drug will list every side-effect as a "possible" effect, it's just a question of time and sufficient numbers.
Unless there is a known, dangerous interaction (in which case your doctor won't prescribe them to you simultaneously), nothing has changed, and you cannot begin to second-guess the drug itself. Hell, some people still only find out they are allergic to something in their 40's when they first try it. You can't account for that, and the majority of drug side-effects are minor and rare.
Look for them, by all means, but you might as well just write "There is always a risk of side-effects with any medication" on everything and have done with it, unless you know about a particularly dangerous interaction. Listing them only helps medical databases, not the average guy.