Reply With QuoteIt may be true that they are "no better than" but they are certainly not the same as placebos.
I've taken various anti-depressants, not prescribed, in my youth and they certainly had a kick. Sugar pills wouldn't work as recreational drugs.
http://www.dailymail.co.uk/health/ar...=feeds-newsxml
Yeah I know it's the Daily Mail but I'd like to know your opinions people. Good research? Any support for his point of view?
It may be true that they are "no better than" but they are certainly not the same as placebos.
I've taken various anti-depressants, not prescribed, in my youth and they certainly had a kick. Sugar pills wouldn't work as recreational drugs.
Depression may be a placebo-responsive condition. If so a placebo may have a very noticeable effect.
If something works it works, whether or not it's simple sugar pill doesn't change that.
Meta-analysis generally show what the researcher wants them to show. Despite being given huge credit, they must be regarded as a single strand of evidence rather than the whole picture - as presented here. Cochrane still agrees that antidepressants work.
What is really being pointed out here is that they are no where near as effective as the promotional hype would suggest.
However, for those with severe depression, there is a substantial risk to stopping what are effective medicines, so articles like this are quite irresponsible. Yes for the average patient these medicines are little better then placebo, for some patient groups no better. For those at the severe end of the spectrum they are life saving, lets not go back to ECT.
My understanding was that properly conducted meta analysis was more reliable than smaller studies. I thought the whole point was to rule out inconsistencies and cherry picking that may result from smaller studies. Have I misunderstood you, or are you simply saying that meta analysis too can, if not done correctly, involve bias?Originally Posted by Pebble
Metaanalysis was developed as a method of rigourously combining the information from a large number of smaller trials. Correctly done this hugely increases the statistical power and because internal consistency between trial design is checked for, reliable data can be extracted.
A number of problems arise when they are not quite as rigorous as they need to be. Like any successful technique this is now an industry, with papers and analyses being churned out because they can, not because they should - hence the fishing expedition mentality has crept in, which renders the statistical robustness meaningless.
Often secondary endpoints are analysed, even though populations are chosen for their ability to give information about the primary endpoints, so although the data are robust the populations are not appropriate for the conslusions reached in the subsequent metaanalyses.
In any one field we get multiple metaanalyses giving contradictory outcomes. Thus for example one will criticise the previous for not including unpublished data, the next will criticise that one for the quality of the trials that were unpublished - incomplete follow up etc biasing results.
So basically they are not a panacea, and one must as with all fields looks at the track record of the authors. In the field of depression lumping all populations that have been studied together and assuming that the agent should work equally well for all forms of depression is just nonsense. Needless to say those populations where least efficacy is expected will be the largest trials, if these are negative lumping them together with smaller trials of populations where efficacy is high will overwhelm the positive trials.
This seems to be another strand of the developing work which shows that different people respond very differently to medicines, depending on their genetic makeup.
Having made a little more exploration on the fella i've come to the conclusion that his meta-analyses have changed how the non-scientific community look at medical research and in one positive way: they have made it harder to hide non-supportive case studies by big-pharma. That being said it seems to me that his main argument, that drugs are less effective in many cases is undermined by his secondary "finding", that the placebo effect is greater in these cases.
So do we now have the point of view that in cases of minor level depression that either a placebo or a drug will be equally ( or near enough) effective? How does that score against doing nothing?
That loopy and criminally irresponsible claim has been around for at least a decade.It is demonstrably untrue of the various families of antidpressents as well as untrue about SSRI's,which is the type against which that claim is most often made.
Anything that appears in the Daily Mail should be viewed with more than a dose of healthy skepticism and this particular story feeds in pretty well to nebulous fears of the evils surrounding "Big Pharma". Pebble makes some great points about the perils of Meta-Analysis, and perhaps another point for consideration is to ask what exactly is depression? I'm sure we all have a fair idea of what it is, but in terms of clinical studies including in that metanalysis How is it defined?
There's a beautiful blog post over at NeuroSKeptic explaining why this is important Clicky here to read "Very Severely Stupid about Depresssion "
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