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Antidepressants Work No Better Than a Placebo
Matthew Whalley writes "Researchers got hold of published and unpublished data from drug companies regarding the effectiveness of the most common antidepressant drugs. Previously, when meta-analyses have been conducted on only the published data, the drugs were shown to have a clinically significant effect. However, when the unpublished data is taken into account the difference between the effects of drug and placebo becomes clinically meaningless — just a 1 or 2 point difference on a 30-point depression rating scale — except for the most severely depressed patients. Doctors do not recommend that patients come off antidepressant drugs without support, but this study is likely to lead to a rethink regarding how the drugs are licensed and prescribed."
I just listened to the CEO of Eli Lilly speak for an hour last night, and he said most prescription drugs work at best in 80% of patients who are diagnosed with the disease it's supposed to treat. Their least effective drugs only treat 20% of patients. Until effective genomics, proteinomics, and metabonomics testing systems come out, which will show exactly how people react differently to drugs, they have to train doctors in choosing criteria where the drug will work, and ensure that they don't prescibe drugs that don't work in that circumstance. Selling drugs that don't work is an unsustainable business policy.
He talked about Strattera, a nonstimulant ADHD drug, that works works best in people with ADHD combined with clinical anxiety. Otherwise, the patient should be prescribed a stimulant based ADHD drug, which works more often in other cases.
Anyways, a lot of drug trial data is needed to find the population where the drug works. In a lot of cases the drug might not work at all. Prescribing methicillin against methicillin-resistant Staphtacaccous aureus will probably an efficacy similar to placebo.
Disclamer first, I work for an R&D company that develops interactive voice response systems (ie: phone surveys) that are used to apply traditional depression and mental health tests in a consistent manner. My company is in part funded by grants and projects paid for by large pharma comps. Although I personally have no contact with them.
When pharma's want to do a study, they set up sites, each site will have one or more doctor and each doctor will have one or more patient who is participating. Quite often, these studies pay a bonus for each patient up to the quota, or the docs will want to try to help and fill their quota. When they do this, it introduces people into the programs who really should not be there. It's not that they are being purposely decietful or anything, they just aren't being as consistent and strict as they should be. I know this to be a fact, we have done numerous studies in which our system's performance is compared to real world docs across the US. And each and every time, our system would exclude over 20% of the patients that the doctors would enroll.
Since these studies are being poluted with people who do not reach the level of condition the drug was ment to treat, the drug will be ineffective on them. You can't "undepress" people who aren't depressed to start with. So they will reduce the effective correlation of the drug. There is also another natural bias that clinicians apply that causes a deflation of scores at the end of the study due to the double blind factor being eliminated by side effects.
In short, traditional ways of performing these studies are heavily flawed and will often result in a lower apparent effectiveness than the drug actually has.
-Rick
"Most people in the U.S. wouldn't know they live in a tyrannical state if it walked up and grabbed their junk." - MyFirs
"A few days after I'd quit the pills cold turkey"
Just a note - whether or not you think your pills are helping you, don't try this. It's extremely dangerous with most medications. I'm not posting to berate the Parent, just letting others know that it's a really bad practice that can lead to serious consequences with a lot of these drugs.