Placebos becoming too effective, pharma industry worries(asserttrue.blogspot.co.nz)
asserttrue.blogspot.co.nz
Placebos becoming too effective, pharma industry worries
http://asserttrue.blogspot.co.nz/2013/03/new-patents-aim-to-reduce-placebo-effect.html
10 comments
Good point! Though this one post does seem quite well reasoned its message is an easy one (big pharma is evil) and suspect to confirmation bias.
If only my browser gave me something to tag the site with your comment, so that next time it comes around I'll remember.
If only my browser gave me something to tag the site with your comment, so that next time it comes around I'll remember.
http://tldr.io/ occasionally helps.
I believe that's what Rbutr is trying to address: http://rbutr.com/
The real problem here of course, the unwritten and almost certainly valid assumption in the piece is that our regulatory bodies will almost certainly accept the fig leaf of these fudged trials as reason to grant license to drugs of questionable medical benefit in order to reward big pharma and its generous support of the political process through campaign contributions.
How is SPCD a "fig leaf of a fudged trial"?
I view the situations under which drug trials happen today to already be highly favorable to the drug companies. If even in those circumstances they're not getting strong signals that their drug is effective then changing the experiments until they show what you're hoping for is not the right approach. Indeed I think it's a good use of the term fudging.
If even in those circumstances they're not getting strong signals that their drug is effective then changing the experiments until they show what you're hoping for is not the right approach.
Inconclusive results are not conclusive negative results. Granted, the drugs here have small effects which can be masked by noise -- they cure only a small fraction of people who take them. Drugs are far from curing everyone all the time, and that's still valid. A couple percentage points translates to thousands of lives, which is better than nothing (if costs are taken into account too).
Inconclusive results are not conclusive negative results. Granted, the drugs here have small effects which can be masked by noise -- they cure only a small fraction of people who take them. Drugs are far from curing everyone all the time, and that's still valid. A couple percentage points translates to thousands of lives, which is better than nothing (if costs are taken into account too).
When did HN devolve into a place for conspiracy theorists? Your comment is an embarrassment.
Read Dr Ben Goldacre's book "Bad Pharma". Scientific misconduct is endemic in the pharmaceutical industry, most importantly in the form of publication bias. Vast swathes of research goes MIA, with the statistical analysis showing clearly that positive results are vastly more likely to be published than negative results. Industry-funded research is more than twice as likely to return a positive result than other research. This all takes place with the implicit endorsement of the FDA - the FDA have far greater access to trial data than any physician.
The pharma industry produces a lot of useful and important drugs, but they also do a lot of seriously shady shit. GSK habitually lied about the risks of Paroxetine and hid data showing serious safety issues. Merck committed fraud on a grand scale by falsifying and concealing data related to Rofecoxib, which led directly to around 60,000 deaths. It's quite clear that the ethical standards of the pharmaceutical industry are close to nil - most large companies are happy to kill patients with useless drugs as long as it's profitable.
The pharma industry produces a lot of useful and important drugs, but they also do a lot of seriously shady shit. GSK habitually lied about the risks of Paroxetine and hid data showing serious safety issues. Merck committed fraud on a grand scale by falsifying and concealing data related to Rofecoxib, which led directly to around 60,000 deaths. It's quite clear that the ethical standards of the pharmaceutical industry are close to nil - most large companies are happy to kill patients with useless drugs as long as it's profitable.
That might be. But reducing placebo effect is not shady shit. Publication bias is a difficult phenomenon to fight, but when a pharmaceutical company invests millions into a drug that does not significantly outperform placebo then that product has failed. You can't keep repeating the research over and over again until it succeeds if every research project costs millions.
You make it sound like a drug that performs as good as a placebo is useless. Maybe you haven't read about the placebo effect, it is pretty damn effective.
You make it sound like a drug that performs as good as a placebo is useless. Maybe you haven't read about the placebo effect, it is pretty damn effective.
"You make it sound like a drug that performs as good as a placebo is useless."
But it is useless, is it not? The placebo effect is effective, cheap and safe. If the new drug has the same effectiveness, it's probably just another placebo, just far more expensive and probably nowhere near as safe.
But it is useless, is it not? The placebo effect is effective, cheap and safe. If the new drug has the same effectiveness, it's probably just another placebo, just far more expensive and probably nowhere near as safe.
Not necessarily. A placebo might perform as good as a regular drug in clinical trials, where there is a 50% chance of it being the real thing and there is significant personal interaction with researchers. Also for some reason people always assume that if there is a clinical trial with humans involved the real drug will probably work very well.
In real world scenarios however drugs might be bought with _no_ personal interaction with professionals at all. Furthermore people are very sceptical of the long-term effects of any psychology related drug. In this case the placebo's might perform a lot worse than the actual drug, which may have an actual noticeable effect.
The placebo effect is effective, cheap and safe, and might be present in both the placebo and the tested drug. But the placebo can't be sold as medicine. And the tested drug might still work without the placebo effect.
In real world scenarios however drugs might be bought with _no_ personal interaction with professionals at all. Furthermore people are very sceptical of the long-term effects of any psychology related drug. In this case the placebo's might perform a lot worse than the actual drug, which may have an actual noticeable effect.
The placebo effect is effective, cheap and safe, and might be present in both the placebo and the tested drug. But the placebo can't be sold as medicine. And the tested drug might still work without the placebo effect.
Ultimately, I understand it as this.
Especially in terms of psychological effecting drugs
If the people getting the placebo get better (in the case of psychological drugs.. feel better) as often as those on the actual drug, then it's quite likely the drug is doing nothing and both sets of patients are getting better because the belief of taking a drug that makes them better is causing them to get better.
(apologizes for the confusing paragraph)
And hence, the drug is deemed worthless and thrown out, time to get on with a trial of another drug.
Especially in terms of psychological effecting drugs
If the people getting the placebo get better (in the case of psychological drugs.. feel better) as often as those on the actual drug, then it's quite likely the drug is doing nothing and both sets of patients are getting better because the belief of taking a drug that makes them better is causing them to get better.
(apologizes for the confusing paragraph)
And hence, the drug is deemed worthless and thrown out, time to get on with a trial of another drug.
"it is quite likely the drug is doing nothing"
The only way to be sure that the drug is doing nothing is to repress the placebo effect as much as possible.
There are people dying or suffering that could be helped with drugs that failed the placebo test. (Some of them could even have been helped with the placebos themselves)
The only way to be sure that the drug is doing nothing is to repress the placebo effect as much as possible.
There are people dying or suffering that could be helped with drugs that failed the placebo test. (Some of them could even have been helped with the placebos themselves)
But if the placebo effect is caused by human interaction, would this suggest that the best therapy is simply one-on-one counselling rather than a new chemical? In other words, we need to help people change their way of thinking more so than mess with the chemistry of their brain.
Yes, but one-on-one counselling is expensive and error-prone. In an ideal world everyone had access to a doctor that has the time and spirit to treat all of his patients with dedication and positivity.
In the real world enrollment to medical schools is heavily throttled and doctors in cities have many more patients then they can cope with.
There might be enough psychiatrists and other therapists, but they are not believed to be able to cure physical pain (even though they are), which renders them less effective. This is why these therapists rely so much on these medications that seem to have little effect over placebos.
In the real world enrollment to medical schools is heavily throttled and doctors in cities have many more patients then they can cope with.
There might be enough psychiatrists and other therapists, but they are not believed to be able to cure physical pain (even though they are), which renders them less effective. This is why these therapists rely so much on these medications that seem to have little effect over placebos.
What is problematic is when you set out to develop a statistical approach purely designed to increase the rates at which experiments deliver positive outcomes. You start letting the tail wag the dog when you start from the assumption you are testing stuff which must have a significant benefit, and ask how you can better demonstrate that benefit - rather than accepting that the results appear to show that the benefit is not particularly statistically significant.
Drug trials are already done in circumstances incredibly favorable to the drug companies. If even in such a situation a potential drug is struggling to show benefits the solution isn't to keep changing the way you're testing until you get the result you seek.
Drug trials are already done in circumstances incredibly favorable to the drug companies. If even in such a situation a potential drug is struggling to show benefits the solution isn't to keep changing the way you're testing until you get the result you seek.
You start letting the tail wag the dog when you start from the assumption you are testing stuff which must have a significant benefit, and ask how you can better demonstrate that benefit - rather than accepting that the results appear to show that the benefit is not particularly statistically significant.
There is no such bias in this method. It could just as easily show a drug to be worse than a placebo (harmful) than better: there is no prior assumption in either direction. The method merely increases the accuracy of this result.
The fact that it increases the number of positive drug outcomes is a good thing: we want more working drugs. Hiding drug effects with weaker tests, giving more inconclusive results, is not an advantage.
There is no such bias in this method. It could just as easily show a drug to be worse than a placebo (harmful) than better: there is no prior assumption in either direction. The method merely increases the accuracy of this result.
The fact that it increases the number of positive drug outcomes is a good thing: we want more working drugs. Hiding drug effects with weaker tests, giving more inconclusive results, is not an advantage.
Hah. It is hardly conspiracy theorist to observe that industries which donate vast sums in campaign contributions get favorable legislative and regulatory treatment.
You can pop up with your throwaway account and hurl insults but I'm fairly sure that it is a well observed pattern that US campaign contributions correlate with the direction if policy and enforcement. Of course that could just be a placebo effect - they may actually have no effect whatsoever. That being said I am persuaded by the balance of evidence that large campaign contributions are a rational and effective expenditure by industry to secure favorable treatment rather than money squandered by corporations out of idealistic democratic intentions.
So now the ad hominem is out of the way? Did you have a broader point? As someone with a background of scientific training I'm comfortable holding the position that I fail to be persuaded that this is a valid and unbiased statistical approach, rather from what I read I see this as a rather transparent attempt to justify huge expenditures on speculative potential drug investments which unfortunately delivered products for which there is not strong evidence of significant benefit.
When you get over your embarrassment at a comment on a discussion forum which your account has been registered on for 16 hours perhaps rather than try to shut down discussion with personal insults you can make a more sophisticated argument as to why you believe in the validity of this approach and why you believe that campaign contributions to politicians are an ineffective way to influence policy and regulation contrary to all evidence.
He who pays the piper calls the tune.
You can pop up with your throwaway account and hurl insults but I'm fairly sure that it is a well observed pattern that US campaign contributions correlate with the direction if policy and enforcement. Of course that could just be a placebo effect - they may actually have no effect whatsoever. That being said I am persuaded by the balance of evidence that large campaign contributions are a rational and effective expenditure by industry to secure favorable treatment rather than money squandered by corporations out of idealistic democratic intentions.
So now the ad hominem is out of the way? Did you have a broader point? As someone with a background of scientific training I'm comfortable holding the position that I fail to be persuaded that this is a valid and unbiased statistical approach, rather from what I read I see this as a rather transparent attempt to justify huge expenditures on speculative potential drug investments which unfortunately delivered products for which there is not strong evidence of significant benefit.
When you get over your embarrassment at a comment on a discussion forum which your account has been registered on for 16 hours perhaps rather than try to shut down discussion with personal insults you can make a more sophisticated argument as to why you believe in the validity of this approach and why you believe that campaign contributions to politicians are an ineffective way to influence policy and regulation contrary to all evidence.
He who pays the piper calls the tune.
Oh, please. I called your comment an embarrassment. You personally attacked me with insults.
Burden of proof is on you to prove your pet theory. Definitively show blatant corruption. Go for it.
Burden of proof is on you to prove your pet theory. Definitively show blatant corruption. Go for it.
I don't buy it.
>> reason to grant license to drugs of questionable medical benefit in order to reward big pharma and its generous support of the political process through campaign contributions
Is a fair (although not proven) interpretation of the available data:
One side needs to provide evidence - you or your parent, your parent's point is left open otherwise and your response doesn't counter it.
>> reason to grant license to drugs of questionable medical benefit in order to reward big pharma and its generous support of the political process through campaign contributions
Is a fair (although not proven) interpretation of the available data:
1. Big pharma make very large political campaign contributions, sometimes via indirect routes which has the effect (even if not the intention) of disguising the funding source.
2. Drugs are being tested against placebo, instead of the best available alternative. We know that unfavourable trial results are frequently not reported. It's fair to cast question on the medical benefit of such drugs.
3. The final question is the FDA's motivation to approve such borderline drugs - ostensibly it's to provide options to doctors where the preferred treatment is not possible (perhaps adverse reaction in the patient or everything else has already been tried), your parent posits that it could be as favour to these companies.
One side needs to provide evidence - you or your parent, your parent's point is left open otherwise and your response doesn't counter it.
Why? Because the burden of proof has somehow shifted. You're now guilty until proven innocent. Are you serious?
This looks genuinely useful. Getting more statistical power out of clinical trials, for free, means they can use smaller sample sizes and save millions. Lower entry barriers means more drug trials.
Not sure what the author finds "repulsive" in this.
Not sure what the author finds "repulsive" in this.
This is an interesting article about something important. I'm sad that it got flagged out of view and that the discussion was derailed by middlebrow dismissals (man am I envious that I did not think of that phrase!), tedious name-calling about "alternative medicine" and the like.
The idea of rigging a clinical protocol to titrate out placebo responders and redo the study on successively more favorable terms seems like a new variety of intellectual corruption — like epicycles, except these epicycles are worth billions of dollars. Now admittedly I got that impression by reading a tendentious blog post. What this thread ought to be for is a neutral discussion of how accurate and fair what the author is saying is. There are people here who could help with that, but I'm not sure the ecosystem of HN can tolerate it.
The idea of rigging a clinical protocol to titrate out placebo responders and redo the study on successively more favorable terms seems like a new variety of intellectual corruption — like epicycles, except these epicycles are worth billions of dollars. Now admittedly I got that impression by reading a tendentious blog post. What this thread ought to be for is a neutral discussion of how accurate and fair what the author is saying is. There are people here who could help with that, but I'm not sure the ecosystem of HN can tolerate it.
The idea of rigging a clinical protocol to titrate out placebo responders and redo the study on successively more favorable terms seems like a new variety of intellectual corruption.
They're not more favorable terms. A drug which has no effect will still perform identically to a placebo. What changes is the level of noise, and hence the sensitivity of the test.
The spread in placebo responses (the standard deviation of the binomial distribution) is sqrt(N p (1-p)). For N=100, if 20% of the sample has a placebo response, the s.d. of this is 4%. If you have only 5% placebo responses, it's half that: 2.2%. Higher signal-to-noise ratio. You find that more drugs work, because it's easier to tell if they work -- not because you're corrupting the test to show that work when they actually don't.
They're not more favorable terms. A drug which has no effect will still perform identically to a placebo. What changes is the level of noise, and hence the sensitivity of the test.
The spread in placebo responses (the standard deviation of the binomial distribution) is sqrt(N p (1-p)). For N=100, if 20% of the sample has a placebo response, the s.d. of this is 4%. If you have only 5% placebo responses, it's half that: 2.2%. Higher signal-to-noise ratio. You find that more drugs work, because it's easier to tell if they work -- not because you're corrupting the test to show that work when they actually don't.
Sorry, I'm not getting it—it sounds like tampering with a random sample after the fact. How does this not amount to throwing out data one doesn't like? Suppose I have a stock trading algorithm. I test it on random stocks, discard part of the data set, and run the tests again. Now it's easier to show that my system works. Is this ok?
You find that more drugs work, because it's easier to tell if they work
Previously, the definition of "works" was "can be shown to be significantly better than placebo". Why should that definition be changed? It seems very reasonable to me, whereas relabeling placebo effects "noise" to throw them out seems like eliminating the competition.
You find that more drugs work, because it's easier to tell if they work
Previously, the definition of "works" was "can be shown to be significantly better than placebo". Why should that definition be changed? It seems very reasonable to me, whereas relabeling placebo effects "noise" to throw them out seems like eliminating the competition.
Previously, the definition of "works" was "can be shown to be significantly better than placebo"
That's what they're testing -- except, on a subgroup which is less sensitive to placebos. If a drug works on this subgroup, and if (the assumption) the drug effect is independent of the placebo effect, then you infer it's better than a placebo on the whole population, though you haven't directly tested this.
Placebo effects don't vanish when you're given a real drug. Roughly, when you're testing a drug against a placebo, you're measuring {drug effect + placebo effect} against {placebo effect}. If drug and placebo are independent, than subtracting some "placebo effect" from both sides, equally, gives you the same comparison except with less statistical variation -- less "noise".
It's still possible that the drug and placebo effect are interacting in an unknown way -- if the drug works, and separately it weakens the placebo effect, then this test gives you the wrong inference. This adds some epistemic uncertainty, though maybe less uncertainty than the statistical uncertainty in the ordinary trials. Obviously an issue.
What this is isn't is biased. It's not set up in a way to make drugs seem systematically better: it's set up to find more drugs that actually are better.
That's what they're testing -- except, on a subgroup which is less sensitive to placebos. If a drug works on this subgroup, and if (the assumption) the drug effect is independent of the placebo effect, then you infer it's better than a placebo on the whole population, though you haven't directly tested this.
Placebo effects don't vanish when you're given a real drug. Roughly, when you're testing a drug against a placebo, you're measuring {drug effect + placebo effect} against {placebo effect}. If drug and placebo are independent, than subtracting some "placebo effect" from both sides, equally, gives you the same comparison except with less statistical variation -- less "noise".
It's still possible that the drug and placebo effect are interacting in an unknown way -- if the drug works, and separately it weakens the placebo effect, then this test gives you the wrong inference. This adds some epistemic uncertainty, though maybe less uncertainty than the statistical uncertainty in the ordinary trials. Obviously an issue.
What this is isn't is biased. It's not set up in a way to make drugs seem systematically better: it's set up to find more drugs that actually are better.
This thinking seems to me fraught with dangerous non sequiturs, or at least unproven assumptions. You mention one: on what basis can we assume that the drug effect and the placebo effect are independent? We don't understand the placebo effect. We should make as few assumptions about it as possible.
Here is another. If the drug is approved, it won't be given only to the "subgroup which is less sensitive to placebos" on which it was tested. It will be given to the general population. On what basis can you assume that since the drug beats placebo on the subgroup, it must also beat placebo on the general population?
It seems weird to allow a random sample to be taken from a population that is not the population you're trying to make claims about. Are there precedents for this in other fields?
Here is another. If the drug is approved, it won't be given only to the "subgroup which is less sensitive to placebos" on which it was tested. It will be given to the general population. On what basis can you assume that since the drug beats placebo on the subgroup, it must also beat placebo on the general population?
It seems weird to allow a random sample to be taken from a population that is not the population you're trying to make claims about. Are there precedents for this in other fields?
How can a drug work LESS than a placebo? Like if the drug does nothing then it should at least be as effective as a placebo shouldn't it?
Some prostate cancer is very slow growing. The man will die with it, not of it.
Treatment is harsh and aggressive and carries risks and has unpleasant side effects.
In that case doing nothing is better than doing something.
A very good question to ask of a doctor is "What happens if I do nothing?"
Treatment is harsh and aggressive and carries risks and has unpleasant side effects.
In that case doing nothing is better than doing something.
A very good question to ask of a doctor is "What happens if I do nothing?"
It is unlikely to work less than the placebo, just for 20 people you happened to choose some just got better anyway - and we're in the wrong group
That's why it's important to publish all trials - if the 20 people who got better anyway were receiving the active drug do you think they would be saying our drug might not be that effective?
That's why it's important to publish all trials - if the 20 people who got better anyway were receiving the active drug do you think they would be saying our drug might not be that effective?
It can have adverse effects worse than the nocebo effect (nocebo in Latin means "I will harm". It is the negative twin of the placebo effect).
I thought the nocebo effect described that a placebo even worked when the patient knew he was getting a placebo.
“In medicine, a nocebo is a harmless substance that creates harmful effects in a patient who takes it.”
http://en.wikipedia.org/wiki/Nocebo
http://en.wikipedia.org/wiki/Nocebo
It could be chance. Remember if you have a small sample size, it's possible that (by chance) the placebo control group just happen to get better faster, making it seem like the placebo works 'better'.
If the drug makes the condition worse?
Ben Goldacre makes a strong case for not using placebo. If there's already a widely used alternative, surely they should test against the best currently available treatment, instead of testing against nothing (placebo).
The more concerning point Goldacre raises is that unflattering trial data goes missing, and this is completely ok with the FDA.
The more concerning point Goldacre raises is that unflattering trial data goes missing, and this is completely ok with the FDA.
I'm still curious what would happen if we:
a) have a pill for every disease
b) give placebos if we don't have anything better
c) A/B-test viable new alternative drugs (or maybe multi armed bandit's minimum regret is appropriate here ;)
That way patients might get the benefits of placebo without resorting to alternative medicine and you would be able to test effectiveness of drugs much more accurately.
You could even offer people different tracks, such as 'conservative', 'regular', 'progressive' and 'experimental' where different (new) drugs with different risk profiles can be issued.
If you'd make regularly contributing data (completing questionnaires) on your progress / health status a requirement for participation we could even start doing big-data analysis on this (massively valuable) data set quite soon.
a) have a pill for every disease
b) give placebos if we don't have anything better
c) A/B-test viable new alternative drugs (or maybe multi armed bandit's minimum regret is appropriate here ;)
That way patients might get the benefits of placebo without resorting to alternative medicine and you would be able to test effectiveness of drugs much more accurately.
You could even offer people different tracks, such as 'conservative', 'regular', 'progressive' and 'experimental' where different (new) drugs with different risk profiles can be issued.
If you'd make regularly contributing data (completing questionnaires) on your progress / health status a requirement for participation we could even start doing big-data analysis on this (massively valuable) data set quite soon.
When ethics comittees kill (http://www.badscience.net/2011/03/when-ethics-committees-kil...)
> At present there is a bizarre paradox in medicine. When there is no evidence on which treatment is best, out of two available options, then you can choose one randomly at will, on a whim, in clinic, and be subject to no special safeguards. If, however, you decide to formally randomise in the same situation, and so generate new knowledge to improve treatments now and in the future, then suddenly a world of administrative obstruction opens up before you.
> At present there is a bizarre paradox in medicine. When there is no evidence on which treatment is best, out of two available options, then you can choose one randomly at will, on a whim, in clinic, and be subject to no special safeguards. If, however, you decide to formally randomise in the same situation, and so generate new knowledge to improve treatments now and in the future, then suddenly a world of administrative obstruction opens up before you.
The biggest problem A/B testing is ethical.
Every patient deserves the best medicine we can provide, so A/B testing, even though it would work in the long run, is unethical.
Every patient deserves the best medicine we can provide, so A/B testing, even though it would work in the long run, is unethical.
But it is simple - medicine has long demanded 95% confidence levels.
Keep them.
Do not budge. Do not allow drugs to come through that fail to meet those standards
Now offer really big X-prizes for malarial drugs
Now allow holistic treatment as part of the drug trial - drug plus recorded CBT, drug plus exercise regieme monitored
Keep them.
Do not budge. Do not allow drugs to come through that fail to meet those standards
Now offer really big X-prizes for malarial drugs
Now allow holistic treatment as part of the drug trial - drug plus recorded CBT, drug plus exercise regieme monitored
While I'm not against them, prizes are not enough to sustainbly drive research as they only reward the winners. It is the reality of research (as opposed to engineering) that outcomes are uncertain. Meanwhile researchers have to eat and typically have good (well-payed) alternatives.
It's normal for drug research to be prize driven after all if Viagra caused heart attacks none none of those billions would have shown up.
Seperating out the effects of mind and chemistry is a good thing for understanding our bodies better.
Question: If it works, why not heal with a [active] placebo?
Congratulations, you just invented "alternative medicine"
I mean, why not use placebos in real medicine? They obviously work, their rate of working is measurable and we have a list of specific diseases they work on and to what extent they work.
Because it opens up a lot of very important medical ethics problems.
During trials, the doctor and the patient don't know that the patient is getting a placebo (it's called "double blind"). If people know that what they are getting is a placebo, I don't think it works as well. So the only way to get an effective placebo is to lie to the patient and tell them it's a good drug.
But there is a long history of abuses in medicine (Nuremburg, Tuskegee syphilis experiment, etc.), so "informed consent" is very very very important in medical ethics. This means you can't lie to patients. To use placebos as you suggest, you'd have to throw that out. This is a dangerous path.
During trials, the doctor and the patient don't know that the patient is getting a placebo (it's called "double blind"). If people know that what they are getting is a placebo, I don't think it works as well. So the only way to get an effective placebo is to lie to the patient and tell them it's a good drug.
But there is a long history of abuses in medicine (Nuremburg, Tuskegee syphilis experiment, etc.), so "informed consent" is very very very important in medical ethics. This means you can't lie to patients. To use placebos as you suggest, you'd have to throw that out. This is a dangerous path.
"Can the recommendation for a treatment intended to promote the placebo effect be made without deception and also without undermining its therapeutic potential? Consider, for example, the case of a clinician who recommends treatment with acupuncture for a patient with chronic low back pain who has not been helped by standard medical therapy. Aware of the results of the recent acupuncture trials, described above, this clinician thinks that acupuncture may work by promoting a placebo response. The clinician might provide the following disclosure to the patient: “I recommend that you try acupuncture. Several large studies have shown that traditional acupuncture is not better than a fake acupuncture treatment, but that both of these produce considerably greater symptom improvement in patients with chronic low back pain condition as compared with those patients who receive no treatment or conventional medical therapy. Although the specific type of needling doesn't appear to make any difference, it is likely that acupuncture works by a psychological mechanism that promotes self-healing, known as the placebo effect.” On its face, this disclosure appears honest. A patient who received this disclosure and subsequently got better after undergoing acupuncture might nonetheless develop a false belief about why it worked. This does not mean, however, that the patient has been deceived by his physician."
from:
Placebo Effects: Biological, Clinical and Ethical Advances (Damien G Finniss, Ted J Kaptchuk, Franklin Miller, and Fabrizio Benedetti
PMCID: PMC2832199 / NIHMSID: NIHMS169379
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2832199/
from:
Placebo Effects: Biological, Clinical and Ethical Advances (Damien G Finniss, Ted J Kaptchuk, Franklin Miller, and Fabrizio Benedetti
PMCID: PMC2832199 / NIHMSID: NIHMS169379
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2832199/
But does the placebo effect work as well if the patient is told that type of words?
"Placebo effect works even if patients know they're getting a sham drug
Study suggests patients benefit from the placebo effect even when told explicitly that they're taking an 'inert substance'"
http://www.guardian.co.uk/science/2010/dec/22/placebo-effect...
http://www.guardian.co.uk/science/2010/dec/22/placebo-effect...
These effects are recorded when patients know they are taking part in new medical research trial, and prime their minds accordingly. The placebo is unlikely to do the same thing when they are in a different context.
[deleted]
Happens all the time, at least in the UK: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjourna...
AFAIK this is already done today. (Mostly in Hospitals.) If your doctor gives you a big red pill with some name like 'Ultracure2000 FORTE' it is most likely a placebo.
Plenty of techniques that were once considered alternative medicine have found their way into Western medicine, so it's not all as cut and clear as you present it.
By definition, I begin
Alternative Medicine, I continue
Has either not been proved to work,
Or been proved not to work.
You know what they call alternative medicine
That's been proved to work?
Medicine.
Tim Minchin is a comedian, but sadly he's not the only one saying things like that. Apparently, it's a great way for lazy doctors to always be right.
For instance, check this guy:
“Calling ‘alternative medicine’ medicine is kind," says Dr. George Demetri, director of the Center for Sarcoma and Bone Oncology at the Dana-Farber Cancer Institute in Boston. "We need to be careful about how we use language. Show me an alternative medicine that works and I’ll show you a medicine that is no longer alternative.” http://www.prweb.com/releases/2012/11/prweb10183664.htm
For instance, check this guy:
“Calling ‘alternative medicine’ medicine is kind," says Dr. George Demetri, director of the Center for Sarcoma and Bone Oncology at the Dana-Farber Cancer Institute in Boston. "We need to be careful about how we use language. Show me an alternative medicine that works and I’ll show you a medicine that is no longer alternative.” http://www.prweb.com/releases/2012/11/prweb10183664.htm
Plenty is a bit of a stretch.
@Samuel_Michon
Acupunture isn't accepted into western medicine because it doesn't actually work. It performs as good as any other placebo (reduces pain, makes patients feel better).
It's getting more mainstream, but that doesn't mean it's an accepted medicine.
A review of reviews:
http://www.painjournalonline.com/article/S0304-3959(10)00689...
Acupunture isn't accepted into western medicine because it doesn't actually work. It performs as good as any other placebo (reduces pain, makes patients feel better).
It's getting more mainstream, but that doesn't mean it's an accepted medicine.
A review of reviews:
http://www.painjournalonline.com/article/S0304-3959(10)00689...
Acupuncture, marijuana, diet therapy, light therapy, etc etc.
Because it (mostly) doesn't actually work.
It looks like it works because it exposes bias in both patients and researchers.
This is why it's more effective with subjective and self reported symptoms like pain, nausea, etc.
A great short article about placebo: http://www.sciencebasedmedicine.org/index.php/the-placebo-ef...
It looks like it works because it exposes bias in both patients and researchers.
This is why it's more effective with subjective and self reported symptoms like pain, nausea, etc.
A great short article about placebo: http://www.sciencebasedmedicine.org/index.php/the-placebo-ef...
The author's posts vary greatly in quality. Sometimes they're reasonable. Sometimes they're stuff like "antidepressants in tap water cause autism" (http://asserttrue.blogspot.com/2013/02/antidepressants-tap-w...) and "Do warnings on cigarette packs cause lung cancer?" (http://asserttrue.blogspot.com/2013/02/do-lung-cancer-warnin...). When an article makes it to the front page of HN, a domain expert usually comes along to tear it apart. See https://news.ycombinator.com/item?id=5140049 for a recent example.
Combined with the author's constant self-promotion (see https://news.ycombinator.com/submitted?id=techdog), I tend not to believe much written there. He's optimizing for page views, not scientific accuracy.