http://www.medscape.com/viewarticle/727323?sssdmh=dm1.633691
I have to read the paper but the analysis on the press release is useful.
Piggot, H. et al. 2010, Efficacy and Effectiveness of Antidepressants:
Current Status of Research, Psychotherapy and psychosomatics
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America has the advantage of massive research budgets, a huge population
and a population where mental health is much more part of the culture
than the UK. They can invest in very high quality trails such as STAR*D
and these become highly infleuntial across the world because few other
countries do similiar quality studies. In fact their research and
diagnosis system is independent of the rest of the Western world though
their diagnostic criteria (DSM) is commonly used in research across the
world.
The press release shows the lead author of the paper is critical of the
evidence and the methods. The problem with all trials is their
theoretically perfect designs are open to criticism when they're
implemented. The science of mental health is far from a science like the
natural sciences so it's easy to criticise.
For example the author has used a meta-analysis. Very simply a
meta-analysis is a bit like finding out the average from lots of trails
but uses sophisticated techniques to make the average as accurate as
possible. A funnel plot is a technique used to identify publication bias
- where negative trial results aren't published - and with large numbers
of trails the effect of publication bias can be compensated for. The
criticism of the meta-analytic technique is it compares apples and
oranges, i.e. the trials are not the same but they're still averaged
together. Measures, statistical techniques, reference diagnostic
criteria and interviewing and many other of the aspects where trials
difference (because of siibjective choices made by the authors) mean
that meta-analysis doesn't compare things that are the same. The high
quality meta-analyses uses many techniques to overcome this problem but
still fall foul of the apples and oranges problem, and subjective
decisions by the authors of meta-analyses mean that combining results
from meta-analyses can also have the apples and oranges problem.
The press release has lots of information about the problems of finding
a scientifically reliable truth in mental health.
The last section is about the possible use of biomarkers in the future.
This is one of the fundamental criticisms of psychiatric prractice:
supposed biological illnesses are not detected by biological measures.
Depression is diagnosed by knowing how a person is behaving and feels.
The biomedical model - the one that the use of medication is based upon
- considers the problem of lack of efficacy in high quality
antidepressants trials to be a problem of inclusion of people who meet
the strict diagnostic criteria used in academic research but don't have
a biological brain illness.
In fact there have been different depression hypotheses for many years
but it's noteworthy how the authors consider the lack of efficacy to be
a problem of lack of correct diagnosis of biological depression. The
other hypothesis of depression consider it a non-biological problem and
as a reaction to life.
Netdoctor has a good page explaining just how complex depression is.
Endogenous and reactive depression are the types of depression the
authors of the STAR*D trial want to able to differentiation between. If
the biomedical hypothesis is correct then the former can be detected
using biomarkers and will always successfully respond to antidepressant
treatment.
Unfortuneately for researchers, doctors and patients the way depression
is diagnosed is through the cluster of symptoms approach which uses
operational definitions to define the symptoms. This approach was one of
the most significant advances in the science of psychiatry in the 20th
century. The work to create these definitions using positivitic methods
was one of the greatest works of humankind in the 20th century and it
brought mental health out of the doldrums of a pseudo-science to become
the quasi-science it is today. The approach is still flawed though if
biomedical theories of depression are correct.
My opinion is the biomedical paradigm still hasn't got it quite right.
Biomarkers may one day be able to identify people with a true mental
illness acording to Kraeplin's paradigm however even if this is detected
it may be a type of human being rather than a dysfunctional human being.
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