Do Antidepressants Increase Suicide Risk?

This is kind of an old story, I know.  Still, every once in a
while it is good to revisit these things.  When the topic
first came up in 2004, it was the subject of much newspaper space and
blog commentary.  But now, it has pretty much faded from the
national consciousness.  Has anything more come of it?

In a recent editorial in the American Journal of Psychiatry,
Gregory E. Simon, M.D., M.P.H., reviews the largest and most
informative studies on the subject:


Can We Know Whether Antidepressants Increase Suicide Risk?

Am J Psychiatry 163:1861-1863, November 2006

doi: 10.1176/appi.ajp.163.11.1861

© 2006 American Psychiatric Association

In this issue of the Journal, Gibbons and colleagues
use pharmacy records and mortality data to examine the association
between rates of antidepressant use and rates of suicide death in
children and younger adolescents. They find that U.S. counties with
higher rates of SSRI antidepressant use had lower rates of suicide
death, and that this relationship persisted after accounting for
potential confounding factors. This finding is consistent with two
other observational studies (1, 2) finding that increasing rates of
antidepressant use among adolescents were accompanied by stable or
declining suicide rates.

These findings seem to conflict with a meta-analysis of data from
randomized placebo-controlled trials (3) and with a recent case/control
study (4). Using data from all placebo-controlled antidepressant trials
in children and adolescents, Hammad and colleagues at the U.S. Food and
Drug Administration (FDA) found that risk of suicidal ideation and
suicidal behavior was nearly twice as high during treatment with
several newer antidepressants compared with placebo (3). It is
important to note that the number of actual suicide attempts in those
placebo-controlled trials was too small to compare and that the number
of suicide deaths was zero...

There is more, of course, so you really have to read the whole thing
(it is short).  Some studies suggest one conclusion, while
other sugget the opposite, and none is completely conclusive.
 He points out later in the article:

It is unlikely that additional randomized trials will
provide a final answer to this question, either for adolescents or
adults. A randomized trial to definitively determine whether a specific
antidepressant increases or decreases risk of suicide death would need
to include several hundred thousand patients. Such a study will never
occur. Observational studies using computerized pharmacy data can
include such large populations, but those studies are always subject to
confounding or other biases.

The fact is, there are limits to what studies can tell us.  It
simply is not possible to perform the study that would be required to
get a definitive answer.  

So if I cannot give a definitive answer, what is the point of this
post?  The point is twofold.  First, I think it is a
good idea to follow up on stories such as this, because you cannot rely
on the media to do the follow-up.  Second, I think this
illustrates how important it is to do a full review of the pertinent
literature before trying to formulate a conclusion that will impact
your behavior in any significant way.  

As href="">philosophers
of science like to point out, the key factor that
differentiates science from pseudoscience is not whether a given study
is correct or not.  Rather, the cornerstones of science are
the way that topics are selected (falsifiable hypotheses), information
is processed (publication and peer review), and the way that
conclusions are handled (all conclusions are tentative).  

If you are walking around with a preconceived notion about something,
and want to find support for it, there is a fair chance that you will
find a citation somewhere to support it, possibly even in a
peer-reviewed article.  But merely citing that one article
does not really support your position.  In order to be valid,
it has to be interpreted in the context of all that is known about the

As an illustrative aside, you may want to look at recent exchange in
the online journal, PLOS
, on the topic of antidepressants and
suicide.  The original article was href="">Modeling
of the Temporal Patterns of Fluoxetine Prescriptions and Suicide Rates
in the United States
.  It was accompanied
by an editorial ( href="">Suicide
Rates and Antidepressant Prescribing: A Casual or Causal Relationship?
then followed by a somewhat sarcastic rehash of the same data ( href="">Fluoxetine
and Suicide Rates: Suicide and the Economy
), which
was then followed by an " href="">author's
reply."  The gist of the exchange is this: the
authors of the original paper showed that there was an inverse
relationship between suicide and the rate of prescribing of fluoxetine.
 The editorial examined the omnipresent question of the
relationship between correlation and causation, something that the
authors of the original paper acknowledged fully.  In their
words, "While these types of data cannot lead to conclusions on
causality..."  The paper on suicide and the economy showed
that the inverse correlation between the (improving) economy and the
(declining) rate of suicide was strong that the correlation between
fluoxetine prescriptions and the decline in suicide rate.

The whole exchange is kind of amusing, but it is a good illustration of
how misleading any one article can be.  The point of the
original paper in the exchange was not to prove anything, but to show
an instance of the absence of falsification.  That is a
perfectly valid thing to do.  It is only a small contribution,
but it is meaningful.  The more different perspectives one
takes on a hypothesis, the more convincing it is when no falsification
is found.  

Of course, in the practice of medicine, we cannot just sit around and
pontificate on these things.  Sooner or later, we have to
actually use the information, and incorporate it into the clinical
decision-making process.  How did Dr. Simon formulate the
antidepressant and suicide risk data?  This is what he tells

The Food and Drug Administration requires a warning
that antidepressant medications can sometimes cause or increase
thoughts of suicide. Studies in children and adolescents have shown
that antidepressants can increase suicidal thoughts. However, other
studies have shown that the overall risk of attempting suicide goes
down after starting antidepressant medication. Even if antidepressants
help most people who take them, some people may have very negative
reactions. Thus, it is important that we have regular contact over the
next few weeks. If you have thoughts about suicide or about harming
yourself, please contact me right away.

Well said.

More like this

This is starting to look like a never-ending saga, and I have written about it extensively before.  But this latest update certainly deserves some attention. It comes from an article ( href=";164/7/1029">Suicide Attempts Among Patients…
In 2004, the FDA assigned a "black box" warning on prescription of antidepressants to patients under 25. This was because of a flurry of anecdotal evidence linking the beginning of treatment with SSRIs to increases in suicide risk and because of placebo vs. drug trials that showed these increases…
Being on vacation over the following two weeks, I've scheduled publication of some old posts. The formatting might be a little funny, but I can't really check that ahead of time. The preview function in MT is not perfect. This one is from June, 2004.... From the newsletter, Psychiatric Times,…
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Excellent post, Joseph. I agree that Dr. Simon really puts the issue of the use of antidepressants in children and adolescents in perspective. Careful and balanced scrutiny of studies as well as weighing risk-benefit are essential. I speak from the experience not only as a scientist, but as a parent who must weigh these factors.

I liked NAMI's well considered response to the FDA black box warning.

Excerpted from NAMI's statement, and pertinent to Simon's analysis of risk-benefit:

...NAMI is concerned that the "black box" warning may lead to primary care providers refusing to prescribe these medications out of fear of liability. Families are often forced to see a primary care provider because of the severe shortage of child psychiatrists. This could worsen the existing crisis in depression and suicide among youth. Therefore, the "black box" warning must be accompanied by increased training and better education for physicians treating children and adolescents with major depression.

The "black box" warning also fails to acknowledge that untreated depression in youth is directly linked to suicide and that antidepressant medications can be effective in treating many adolescents with depression. If families and providers are not warned about the real risk of untreated depression and suicide, they will be hampered in their ability to accurately understand all of the risks.

Thanks for bringing up the subject and adressing it so thoughtfully.

Is there any data comparing different classes of anti-depressants (I guess it would have to be a multimodal study of some sort) with regards to suicide risk and suicidal ideation?

I'm wondering if perhaps one might find that for patients where suicidal tendencies are suspected, an MAOI, SNRI, NRI, or tricyclic antidepressant might be preferred, whereas cases where suicide is not considered an immediate risk might be ones where the (relatively) safer SSRIs would be appropriate. Then again, I wouldn't be surprised if the classes that increase synaptic catecholamine levels would actually be worse with suicidal patients given the role dopamine and norepinephrine seem to play in decision-making, activation, and motivation.

I'm also not sure that there's really an ethical way to do a study where you give people different types of antidepressants and compare suicide rates.

There are data comparing several newer antidepressants, but I have not seen anything that includes TCAs and MAOIs. The usual caveats about comparing data from different drug trials applies: without head-to-head studies, it is hard to know if there is any real difference. Although it would be possible to design such a study, it would have to have so many participants that it would be impossible to do.

The clearest summary of the actual data is here.