Depression
There are different kinds of antidepressant medications known
such as the conventional tricyclic antidepressants (TCA: Doxepine),
MAO inhibitors and the modern SSRIs (Selective Serotonin Reuptake
Inhibitors such as Fluoxetine (Prozac), Paroxetine (Seroxat) en
Citalopram (Cipramil)) and also the SNRI’s (Serotonine
Noradrenaline Reuptake inhibitors such as Venlafaxine
(Effexor)). These all have a relative different pharmacological
profile. The prescription of these different antidepressant drugs,
however, still depends on trial-and-error due to a lack of reliable
indicators in order to predict the effectiveness of these
medications (pharmaceutical compass, 2007). On the basis of the
results of a large scale study called STAR*D (Sequenced Treatment
Alternatives to Relieve Depression) Trivedi et al (2006) concluded
that approximately 70% of the patients do not respond adequately to
treatment with an SSRI. These kinds of effects could also be
explained through factors such as therapy loyalty, right dosage etc.
On the basis of all clinical research done on the effects of
antidepressant drugs during the past decades, however, it is at
least clear that the effectiveness of antidepressant themselves is
between 40 and 60% (Keller et al., 2000). A recent meta analysis
based on research done by pharmaceutical companies themselves
(submitted to the FDA) even shows that modern antidepressants do not
have a clinically relevant effect for most patients (Kirsch et al.,
2008).
A lot of research has been conducted in order to find predictors
of treatment outcome in depression. Biological measures such as
serotonin and noradrenalin neurotransmitter metabolites have not
been found to be reliable in predicting treatment effectiveness
(Joyce & Paykel, 1989; Bruder et al., 1999). The more
psychological techniques such as NEO-FFI big-five personality
questionnaire (Petersen et al., 2002) and the Tridimensional
Personality Questionnaire (Newman et al., 2000) do no appear to be
good predictors either. Recent investigations show, however, that
neurophysiological measures such as EEG / QEEG, PET
scans and some neuropsychological
measures can be good measures for drug treatment of depression.
Several studies demonstrate the following predictors for successful
treatment with SSRI: an increased alpha EEG activity frontally
(Suffin & Emory, 1995; Prichep et al., 1993), relatively intact
executive functions (Dunkin et al., 2000) and an intact P300
amplitude (Bruder et al, 1995; 2001). Surely it seems worthwhile to
re-valuate the effectiveness of antidepressants on the basis of such
information. This will most likely lead to a much higher
effectiveness and a clearly clinically relevant effect of
antidepressants. This year the iSPOT-D study (international Study
for the prediction of Optimized Treatment Response – Depression) of
the Brain Resource Company will start which includes 3000 patients
who will be treated with antidepressants and who will get an
extensive brain function examination (QEEG, ERPs, Neuropsychology,
DNA) before and during treatment. It is our expectation that this
study will lead to more decisive results with regards to
personalizing the treatment of depression in the future.
Furthermore research has shown the following brain structures to
play an important role in mood: (1) the dorsolateral
pre-frontal (DLPFC) cortex (Wasserman & Lisanby, 2001); (2) the
subgenual cingulate (SCC) cortex (Mayberg et al., 2005) and 3)
frontal asymmetry (Davidson, 2004). This knowledge has already been
successfully applied in the treatment of mood disorders, as can be
seen from the following examples: (1) stimulation of the left DLPFC
by means of magnetic stimulation or rTMS as a treatment of
depression (Wasserman & Lisanby, 2001); (2) deep brain
stimulation of the SCC (Mayberg et al., 2005) and (3) EEG
biofeedback / neurofeedback in order to train the frontal asymmetry
(Baehr, Rosenfeld, Baehr, & Earnest, 1998; 2001). The
application of neurofeedback for depression is still quite
experimental and considering the presence of better alternatives for
depression, they should be considered first. Neurofeedback for the treatment of ADHD and
epilepsy on the other hand is well-investigated and can be
regarded as an evidence-based treatment.
There is a large body of research on magnetic brain stimulation
or rTMS as treatment for depression. Given that the effect of this
treatment is very straightforward (excitation or inhibition of the
underlying cortex) the effectiveness of the treatment should be
easier to predict. Eschweiler et al (2000) have shown for instance
that patients with a left frontal hypo-activity responded better to
stimulation of the left DLPFC through rTMS. In our investigation –
in which we are personalizing the rTMS stimulation on the basis of
QEEG – we see comparable results. Our first preliminary results show
a more than 65% decrease of depressive complaints within 15
treatment sessions (see figure 3), whereas more than 90% of the
patients show a complete remission within 20 treatment sessions
(Spronk et al., 2008). It is important to note, however, that in
this study rTMS was complemented by psychotherapy in order to reach
a consistent long-term effect.
Figure 3: This figure shows the first preliminary results of
21 depressive clients treated with rTMS combined with
Psychotherapy. The progressive decline in depressive symptoms
over sessions can be clearly seen.
You can
download here a survey article about the predictive value of QEEG,
ERPs and neuropsychological tests for antidepressants as a treatment
of depressions.
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