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."
Re:not surprising (Score:4, Insightful)
Presumably so doctors can better select functionally similar drugs to minimise these interactions...
For example, TFA says that the high-blood-pressure medication class thiazides and SSRIs can interact. Neither of these is available without prescription therefore a doctor could use such data to make better treatment decisions...
Re:not surprising (Score:5, Insightful)
Re:Simple (Score:4, Insightful)
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.
Look, somebody should hit your head with a hammer to make sure you know what you're talking about.
You ignore the fact that we are all different from each other. Headaches are a good example: I practically never get headaches.Other people I'm close to get absolutely terrible headaches from time to time that are so bad that they keep them awake and only the strongest Paracetamol can give some remedy for a short time. You either lack empathy (working in management?) or have really no idea how bad headaches or migraine can be.
Re:Multiple testing problem? (Score:3, Insightful)
"Their methodology seems to be very vulnerable to false positives..."
I would agree, and go on to suggest that this is intentional. Even after applying "corrective" measures, one has to pick a preference: false negative or false positive, and then show your work (just like in math class). When it comes to drugs, the control methods are never *really* enough. If you're doing an in silico screen, depending on the algorithms used, you may want false positives, because you're just going to throw everything into a high-throughput screen and let the robots do the rest of the work.
But further on down the pipeline, you want to bias towards false negatives, because you're looking for chemicals that have a strong interaction with their target and a week interaction with other targets. The statistics become a tool for making a decision, but never provide 100% assurance.
This study apparently seeks to show the possibilities of side effects, and then let patients/doctors decide if they apply. It's better than not saying anything at all. ...and serotonin reuptake inhibitors? You really want to know even the false positives for those!
Finally, it's likely that the methods of Tatonetti et al. require further refinement, but the rush to publish is an ugly spectre we all have to deal with in science.
Re:I can imagine the commercials already.. (Score:4, Insightful)
A better solution would be to just ban the placement of ads for prescription drugs anywhere other than medical literature.
Re:Multiple testing problem? (Score:4, Insightful)
I both agree and disagree. In principle people really should stop using frequentist methods. In practice, though... There's still substantial disadvantages with Bayesian methodologies. For example, off the top of my head:
1. Relative slowness of computational algorithms for large datasets
2. Difficulty of presenting results to people with different prior beliefs. (Strictly speaking, in Bayesian terms, the answer you give must always be relative to *someone*.)
3. Ease of 'cheating', even unintentionally, by choosing priors to favour a certain result.
4. Proliferation of methods that pretend to be Bayesian but are in fact probably not. (e.g. Empirical bayes methods)
I'm saying this because this always comes up, but people don't realise the bayesian approach is necessarily a magic bullet either.
Re:not surprising (Score:4, Insightful)
>> Medical doctors are going to read that, it's their job.
I think you mean "Medical doctors SHOULD read that...", or under the best cases "Medical doctors are going to TRY to read that..."
Realistically? They won't have the time to do it properly. Doctors are massively overworked, trying to see far too many patients and dealing with a field that is too broad and grows way too rapidly to keep up with even if they *didn't* have the inconvenience of actually applying their knowledge. I mean, this study alone claims to have discovered 438,228 new drug interactions and side effects. (329 side effects per drug x 1332 drugs) You try to do a thorough read-through and analysis of that kind of data without taking any time off from work; and work quick, you probably only have a week at most until something new you need to learn comes along....