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The Painful Truth of Antidepressants

April 25, 2011

In a study published today, scientists at Rockefeller University proclaim that SSRI antidepressants (like Prozac and Celexa) may lose their efficacy when given with anti-inflammatory drugs like ibuprofen and aspirin.  Considering the high prevalence of depression and the widespread use of both SSRIs and anti-inflammatory medications, this result is bound to receive much attention.  As a matter of fact, it’s tantalizing to jump to the conclusion (as has been done in the Fox News and WSJ reports on this study) that the reason SSRIs may be so ineffective is because so many people with depression also use non-steroidal anti-inflammatory drugs (NSAIDs).

By my read of the data, it may be a bit too early to draw this conclusion.  Nevertheless, the study, by Paul Greengard, Jennifer Warner-Schmidt, and their colleagues, and published online in the Proceedings of the National Academy of Sciences, does propose some interesting mechanisms by which anti-inflammatory agents may affect antidepressant action.

The majority of the work was performed in mice, for which there are valid “models” of depression that are routinely used in preclinical studies.  In past work, Greengard’s group has shown that the expression of a small protein called p11 (which is associated with the localization and function of serotonin receptors) is correlated with “antidepressant-like” responses in mice, and probably in humans, too.  In the present study, they demonstrate that the antidepressants Prozac and Celexa cause an increase in expression of p11 in the frontal cortex of mice, and, moreover, that p11 expression is mediated by the ability of these antidepressants to cause elevations in interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α).  In other words, antidepressants enhance neural expression of these cytokines, which, in turn, increases p11 activity.

However, when mice are given NSAIDs or an analgesic (i.e., ibuprofen, naproxen, aspirin, or Tylenol), this prevents the increase in p11, as well as the increase in IFN-γ and TNF-α.  NSAIDs also prevent the “antidepressant-like” behavioral responses elicited by Celexa (as well as other antidepressants like Wellbutrin, Parnate, and TCAs) in mouse models of depression.

The group went one step further and even created a p11 “knockout” mouse.  These mice had no response to Celexa, nor did they have antidepressant-like responses to injections of IFN-γ or TNF-α.  However, the p11 knockout mice did respond to desipramine, an antidepressant that works mainly on norepinephrine, thus emphasizing the significance of serotonin in the p11-mediated response.

What does this mean for humans?  To answer this question, the group analyzed data from STAR*D, a huge multicenter antidepressant trial.  In the first stage of STAR*D, all patients (total of approximately 1500 individuals) took Celexa for a 12-week period.  The remission rate for patients who took an NSAID at any time during this 12-week period was only 45%, while those who took no NSAID remitted at a rate of 55%.

So does this mean that people taking antidepressants should avoid NSAIDs, and just deal with their pain?  Probably not. (In fact, one might ask the opposite question:  should people with chronic pain avoid SSRIs?  Unfortunately, the study did not look at whether SSRIs inhibited the pain-relieving effects of NSAIDs.)

In my opinion, some of the mouse data need to be interpreted carefully.  For instance, the mice received extremely high doses of NSAIDs (e.g., ibuprofen at 70 mg/kg/d, which corresponds to 4200 mg/d for a 60-kg man, or 21 Advil pills per day; similarly, the mice drinking aspirin received 210 mg/kg/d, or 12,600 mg = ~39 pills of regular-strength aspirin per day for a typical human).  Also, in the behavioral studies the mice received NSAIDs for an entire week but received only a single injection of Celexa (20 mg/kg, or about 1200 mg, 60 pills) immediately before the behavioral experiments.

The human data, of course, are equally suspect.  Patients in the STAR*D study were counted as “NSAID users” if they described using NSAIDs even once in the first 12 weeks of the study.  It’s hard to see how the use of ibuprofen once or twice in a three-month period might interfere with someone’s daily Celexa.  (Not to mention the fact that the “remission” data from STAR*D have come under some scrutiny themselves – see here and here).  Moreover, as the authors point out, it’s quite likely that patients with more severe forms of depression also had concurrent pain syndromes and used NSAIDs more frequently.  In other words, NSAID use might not attenuate SSRI activity, but may be a sign of depression that is more resistant to SSRIs.

In the end, however, I find the study to be quite provocative.  Certainly the correlation of antidepressant effect with expression of the p11 protein and with TNF-α and IFN-γ activity suggests a novel mechanism of antidepressant action—as well as new markers for antidepressant activity.  Moreover, the potential roles of NSAIDs in reducing antidepressant effects (or, in some cases, enhancing these effects), need to be explored.

But it raises even more unanswered questions.  For one, how do we reconcile the fact that antidepressant effects are associated with increased TNF-α and IFN-γ activity in the brain, while increases in these cytokines in the periphery are thought to cause depression?  Also, how can we explain the fact that other analgesic compounds, such as tramadol and buprenorphine, might actually have an antidepressant effect?  Finally, what does this mean for our treatment of pain symptoms in depression?  Should we avoid SSRIs and use other types of antidepressants instead?  Do NSAIDs inhibit the effects of SNRIs like Cymbalta, which has recently been FDA-approved for the treatment of chronic musculoskeletal pain (and whose users are most certainly also taking medications like NSAIDs)?

It’s great that the interface between mental illness and physical syndromes is receiving some well-deserved attention.  It’s also exciting to see that the neuroscience and pharmacology of depression and pain may overlap in critical ways that influence how we will treat these disorders in the future.  Perhaps it may also explain our failures up to now.  With future work in this area, studies like these will help us develop more appropriate antidepressant strategies for the “real world.”

[Finally, a “hat tip,” of sorts, to Fox News, which first alerted me to this article.  Unfortunately, the story, written by Dr. Manny Alvarez, was fairly low on substance but high on the “wow” factor.  It drew some broad conclusions and—my biggest pet peeve—did not refer the reader to any site or source to get more detailed information.  Alas, such is the case with much public science and medicine reporting: Alarm first, ask questions later.]

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Antidepressants and “Stress” Revisited

April 13, 2011

If you have even the slightest interest in the biology of depression (or if you’ve spent any time treating depression), you’ve heard about the connection between stress and depressive illness.  There does seem to be a biological—maybe even a causative—link, and in many ways, this seems intuitive:  Stressful situations make us feel sad, hopeless, helpless, etc—many of the features of major depression—and the physiological changes associated with stress probably increase the likelihood that we will, in fact, become clinically depressed.

To cite a specific example, a steroid hormone called cortisol is elevated during stress, and—probably not coincidentally—is also usually elevated in depression.  Some researchers have attempted to treat depression by blocking the effects of cortisol in the brain.  Although we don’t (yet) treat depression this way, it is a tantalizing hypothesis, if for no reason other than the fact that it makes more intuitive sense than the “serotonin hypothesis” of depression, which has little evidence to back it up.

A recent article in Molecular Psychiatry (pdf here) adds another wrinkle to the stress hormone/depression story.  Researchers from King’s College London, led by Christoph Anacker, show that antidepressants actually promote the growth and development of new nerve cells in the hippocampus, and both processes depend on the stress hormone receptor (also known as the glucocorticoid receptor or GR).

Specifically, the group performed their experiments in a cell culture system using human hippocampal progenitor cells (this avoids some of the complications of doing such experiments in animals or humans).  They found that neither sertraline (Zoloft) alone, nor stress steroids (in this case, dexamethasone or DEX) alone, caused cells to proliferate, but when given together, proliferation occurred—in other words, the hippocampal progenitor cells started to divide rapidly.  [see figure above]

Furthermore, when they continued to incubate the cells with Zoloft, the cells “differentiated”—i.e., they turned into cells with all the characteristics of mature nerve cells.  But in this case, differentiation was inhibited by dexamethasone. [see figure at right]

To make matters more complicated, the differentiation process was also inhibited by RU486, a blocker of the receptor for dexamethasone (and other stress hormones).  What’s amazing is that RU486 prevented Zoloft-induced cell differentiation even in the absence of stress hormones.  (However, it did prevent the damaging effects of dexamethasone, consistent with what we might predict.) [see figure at left]

The take-home message here is that antidepressants and dexamethasone (i.e., stress hormones) are required for cell proliferation (first figure), but only antidepressants cause cell differentiation and maturation (second figure).  Furthermore, both processes can be inhibited by RU486, a stress hormone antagonist (third figure).

All in all, this research makes antidepressants look “good.”  (Incidentally, the researchers also got the same results with amitripytline and clomipramine, two tricyclic antidepressants, so the effect is not unique to SSRIs like Zoloft.)  However, it raises serious questions about the relationship between stress hormones and depression.  If antidepressants work by promoting the growth and development of hippocampal neurons, then this research also says that stress hormones (like dexamethasone) might be required, too—at least for part of this process (i.e., they’re required for growth/proliferation, but not for differentiation).

This also raises questions about the effects of RU486.  Readers may recall the enthusiasm surrounding RU486 a few years ago as a potential treatment for psychotic depression, promoted by Alan Schatzberg and his colleagues at Corcept Pharmaceuticals.  Their argument (a convincing one, at the time) was that if we could block the unusually high levels of cortisol seen in severe, psychotic depression, we might treat the disease more effectively.  However, clinical trials of their drug Corlux (= RU486) were unsuccessful.  The experiments in this paper show one possible explanation why:   Instead of simply blocking stress hormones, RU486 blocks the stress hormone receptor, which seems to be the key intermediary for the positive effects of antidepressants (see the third figure).

The Big Picture:   I’m well aware that this is how science progresses:  we continually refine our hypotheses as we collect new data, and sometimes we learn how medications work only after we’ve been using them successfully for many years.  (How long did it take to learn the precise mechanism of salicylic acid, also known as aspirin?  More than two millennia, at least.)  But here we have a case in which antidepressants seem to work in a fashion that is so different from what we originally thought (incidentally, the word “serotonin” is used only three times in their 13-page article!!).  Moreover, the new mechanism (making new brain cells!!) is quite significant.  And the involvement of stress hormones in this new mechanism doesn’t seem very intuitive or “clean” either.

It makes me wonder (yet again) what the heck these drugs are doing.  I’m not suggesting we call a moratorium on the further use of antidepressants until we learn exactly how they work, but I do suggest that we practice a bit of caution when using them.  At the very least, we need to change our “models” of depression.  Fast.

Overall, I’m glad this research is being done so that we can learn more about the mechanisms of antidepressant action (and develop new, more specific ones… maybe ones that target the glucocorticoid receptor).  In the meantime, we ought to pause and recognize that what we think we’re doing may be entirely wrong.  Practicing a little humility is good every once in a while, even especially for a psychopharmacologist.


The Mythology of “Treatment-Resistant” Depression

February 27, 2011

“Treatment-resistant depression” is one of those clinical terms that has always been a bit unsettling to me.  Maybe I’m a pessimist, but when I hear this phrase, it reminds me that despite all the time, energy, and expense we have invested in understanding this all-too-common disease, we still have a long way to go.  Perhaps more troubling, the phrase also suggests an air of resignation or abandonment:  “We’ve tried everything, but you’re resistant to treatment, and there’s not much more we can do for you.”

But “everything” is a loaded term, and “treatment” takes many forms.  The term “treatment-resistant depression” first appeared in the literature in 1974 and has been used widely in the literature.  (Incidentally, despite appearing over 20 times in the APA’s 2010 revised treatment guidelines for major depression, it is never actually defined.)  The phrase is often used to describe patients who have failed to respond to a certain number of antidepressant trials (typically two, each from a different class), each of a reasonable (6-12 week) duration, although many other definitions have emerged over the years.

Failure to respond to “adequate” trials of appropriate antidepressant medications does indeed suggest that a patient is resistant to those treatments, and the clinician should think of other ways to approach that patient’s condition.  In today’s psychiatric practice, however, “treatment-resistant” is often a code word for simply adding another medication (like an atypical antipsychotic) or to consider somatic treatment options (such as electroconvulsive therapy, ECT, or transcranial magnetic stimulation, TMS).

Seen this way, it’s a fairly narrow view of “treatment.”  The psychiatric literature—not to mention years and years of anecdotal data—suggests that a broad range of interventions can be helpful in the management of depression, such as exercise, dietary supplements, mindfulness meditation, acupuncture, light therapy, and literally dozens of different psychotherapeutic approaches.  Call me obsessive, or pedantic, but to label someone’s depression as “treatment resistant” without an adequate trial of all of these approaches, seems premature at best, and fatalistic at worst.

What if we referred to someone’s weight problem as “diet-resistant obesity”?  Sure, there are myriad “diets” out there, and some obese individuals have tried several and simply don’t lose weight.  But perhaps these patients simply haven’t found the right one for their psychological/endocrine makeup and motivational level; there are also some genetic and biochemical causes of obesity that prevent weight loss regardless of diet.  If we label someone as “diet-resistant” it means that we may overlook some diets that would work, or ignore other ways of managing this condition.

Back to depression.   I recognize there’s not much of an evidence base for many of the potentially hundreds of different “cures” for depression in the popular and scientific literature.  And it would take far too much time to try them all.  Experienced clinicians will have seen plenty of examples of good antidepressant response to lithium, thyroid hormone, antipsychotics (such as Abilify), and somatic interventions like ECT.  But they have also seen failures with the exact same agents.

Unfortunately, our “decision tree” for assigning patients to different treatments is more like a dartboard than an evidence-based flowchart.  “Well, you’ve failed an SSRI and an SNRI, so let’s try an atypical,” goes the typical dialogue (not to mention the typical TV commercial or magazine ad), when we really should be trying to understand our patients at a deeper level in order to determine the ideal therapy for them.

Nevertheless, the “step therapy” requirements of insurance companies, as well as the large multicenter NIH-sponsored trials (like the STAR*D trial) which primarily focus on medications (yes, I am aware that STAR*D had a cognitive therapy component, although this has received little attention and was not widely chosen by study participants), continue to bias the clinician and patient in the direction of looking for the next pill or the next biological intervention, instead of thinking about patients as individuals with biological, genetic, psychological, and social determinants of their conditions.

Because in the long run, nobody is “treatment resistant,” they’re just resistant to what we’re currently offering them.


To Treat Depression, Just Give ‘Em What They Want

February 23, 2011

A doctor’s chief task is to determine the cause of a patient’s suffering and to develop a course of treatment.  In psychiatry, the task is no different: examine the patient, determine a diagnosis, and initiate treatment.  However, “treatment” comes in many forms, and what works for one patient may not work for another.  A good psychiatrist tries to figure out which approach is ideal for the patient in his office, rather than reflexively reaching for the prescription pad and the latest drug option.

How to determine what’s the best course of action for a patient?  Recent research suggests one potentially foolproof way:  Ask him.

A paper in this month’s Psychotherapy and Psychosomatics by Mergl and colleagues shows that patient preference (that is, whether the patient prefers medications or psychotherapy) predicts how effective a treatment will be.  In their study, patients who expressed a preference for medications at the beginning of treatment had a better response to Zoloft than to group therapy, while patients who preferred therapy showed the exact opposite response.

In an even larger study published in 2009 by James Kocsis and colleagues at Weill-Cornell in New York (comparing nefazodone, an antidepressant, with a cognitive therapy approach called CBASP), a similar result was obtained:  patients with chronic major depression who entered the study expressing a preference for drug treatment had higher remission rates when receiving medication than when receiving psychotherapy, and vice versa.

The numbers were quite shocking:

Patients who preferred medication:

Treatment received Remission rate Avg. depression score (HAM-D) at end of study (high score = more depressed)
Meds 45.5% 11.6
Therapy 22.2% 21.0

Patients who preferred therapy:

Treatment received Remission rate Avg. depression score (HAM-D) at end of study
Meds 7.7% 18.3
Therapy 50.0% 12.1

(original HAM-D scores were approximately 26-27 for all patients, constituting major depression, and patients in this study had been depressed for over two years)

Thus, if a depressed patient wanted therapy but got medications instead, their chances of “remitting” (ie, having a fully therapeutic response to nefazodone) were less than 1 in 12.  But if they did get therapy, those chances improved to 1 in 2.  Interestingly, patients who preferred therapy and got combination treatment (meds and therapy) actually did worse than with therapy alone (remission rate was only 38.9%), leading the authors to conclude that “few patients who stated a preference for psychotherapy benefited much from the addition of medication.”

It’s not surprising, at first glance, that people who “get what they want” do better.  After all, a depressed patient who insists on taking meds probably won’t get much better if he’s dragged into psychotherapy against his will, and the patient who believes that a weekly session with a therapist is exactly what she needs, will probably have some resistance to just getting a pill.

But then again, isn’t depression supposed to be a hard-wired biological illness?  Shouldn’t a medication have a more profound effect, regardless of whether the patient “wants” it or not?

Apparently not.  The fact that people responded to the treatment they preferred means one of two things.  There may be two different types of depression, one that’s biological and one that’s more behavioral or “exogenous,” and people just happen to choose the appropriate treatment for their type due to some predisposition or innate tendency (self-knowledge?).  Alternatively, the “biological” basis of depression is not all it’s cracked up to be.

One question raised by these results is, why don’t we listen more to our patients and give them what they say they want?  If half the people who want therapy actually get better with therapy, doesn’t that make it hard to justify meds for this population?  Conversely, when we talk about “treatment-resistant depression,” or “depression that doesn’t respond to antidepressants alone,” could it be that the people who don’t respond to pills are simply those who would rather engage in psychotherapy instead?

I believe the implications of these findings may be significant.  For one thing, insurers are becoming less likely to pay for therapy, while they spend more and more money on antidepressant medications.  These studies say that this is exactly what we don’t want to do for a large number of patients (and these patients are easy to identify—they’re the ones who tell us they don’t want meds!).  Furthermore, trials of new antidepressant treatments should separate out the self-described “medication responders” and “therapy responders” and determine how each group responds.  [Note:  in the large STAR*D trial, which evaluated “switching” strategies, patients were given the opportunity to switch from meds to therapy or from one med to a different one of their choosing, but there was no group of patients who didn’t have the option to switch.]  If the “therapy responders” routinely fail to respond to drugs, we need to seriously revamp our biological theories of depression.  Its chemical basis may be something entirely different from how our current drugs are thought to work, or maybe depression isn’t “biological” at all in some people.  This will also keep us from wasting money and resources on treatments that are less likely to work.

While it’s often risky to ask a patient what he or she wants (and to give it to them), depression may be just the opportunity to engage the patient in a way that respects their desires.  These data show that the patient may know more than the doctor what “works” and what doesn’t, and maybe it’s time we pay closer attention.


“Decision Support” in Psychiatry

January 28, 2011

I’ve long believed that, just as no two psychiatric patients are identical, there is– and never will be– a “one size fits all” approach to psychiatric care.  However, much work has been done in the last several years to develop “algorithms” to guide treatment and standardize care. At the same time, the adoption of electronic health record (EHR) systems– which are emphasized in the new U.S. health care legislation– has introduced the possibility that computerized decision-support systems will help guide practitioners to make the right choices for their patients.  It is my opinion that such approaches will not improve psychiatric care, and, in fact, will interfere with the human aspect that is the essence of good psychiatric practice.

Clinical decision support,” or CDS, is the idea that an algorithm can help a provider to give the right kind of care.  For a busy doctor, it makes sense that getting a quick reminder to prescribe aspirin to patients with coronary artery disease, or to give diet and exercise recommendations to patients at risk for obesity or diabetes, helps to ensure good care.  Several years ago, I actually helped to develop a CDS system designed to remind primary care doctors to avoid opiate painkillers (or use them with caution) in patients who had a history of substance abuse or other relative contraindications to narcotics.  At the time, I thought this was a great idea.  Why not harness the ability of a computer to gather all the data on a given patient– something that even the best doctor cannot do with absolute accuracy– and suggest the most advisable plan of action?

Now that I spend most of my time actually practicing medicine, and using two different EHR systems, I’m having second thoughts.  While I appreciate the ability to enter patient data (and my notes) into a system that is instantly accessible by any provider in my office at any time, and write prescriptions with a few clicks of my mouse, I’ve begun to resent the ways in which EHRs tell me how to practice, particularly when (a) they give recommendations that I would employ anyway (thereby wasting my time), or (b) they give recommendations that deviate from what I believe is right for the patient.

Obviously, the latter complaint is particualrly relevant in psychiatry, where each patient presents a different background of symptoms, stressors, preferences, and personal history.  When anyone asks me “who is your ideal patient for drug X?” or “what is your first choice of drug for depression?” I find it hard to give an answer.  Treatment choices come down to a feeling, a gestalt, incorporating both observable data and intuition; it’s hard to describe and impossible to quantify.

One example of a psychiatric CDS is based on the Texas Medication Algorithm Project (TMAP).  The TMAP was developed to help providers determine what medications to use in the treatment of mood disorders; the first version of TMAP for depression was designed in 1999 and implemented in a computerized CDS in 2004.  A pilot study involving four primary care providers, published in 2009, showed that depression outcomes were slightly better (i.e., scores in the HAM-D were lower) in the group using the CDS.  (This may have been due to the setting; in a busy primary care clinic, any guidance to address depression symptoms may improve outcomes relative to no guidance at all.)  However, a follow-up study by the same group found that it was much harder to implement the CDS on a more widespread scale in mental health clinics, due to technical problems, poor IT support, billing & coding problems, formulary issues, recommendations that providers disagreed with, lack of time, and impact on workflow.

That may have been for the better.  A new study in this month’s Archives of Internal Medicine by Romano and Stafford shows that CDSs may just be a waste of time and money.  They evaluated over 330 million ambulatory care patient visits using EHRs over 2005-2007, 57% of which involved at least one CDS, and found that, on 20 quality-of-care indicators, using a CDS contributed to improvements in treatment (i.e., treatment concordant with established guidelines) on only one measure.  (Two measures involved psychiatric conditions– one was for the treamtent of depression, and the other was to remind providers not to use benzodiazepines alone for depression treatment.  Neither of these measures showed improvement when a CDS was used, relative to no CDS.)

So despite all the resources devoted to electronic medical records and clinical decision support systems to improve care, the evidence seems to indicate that they don’t.  Either doctors ignore CDSs and provide “practice as usual” anyway, or the CDSs give recommendations that doctors already follow.

This may be good news for psychiatry, where treatment guidelines (thankfully) offer a great deal of latitude, but CDSs, by their very nature, may restrict our options.  In the future, then, when we believe that the patient sitting in front of us is a good candidate for Effexor, or Seroquel, or interpersonal therapy with no meds at all, we may no longer need to explain to a computer program why we’re ignoring its recommendation to try Prozac or Haldol first.

In my opinion, anything that preserves the integrity of the physician-patient interaction– and prevents the practice of medicine from turning into a checklist-and-formula-based recipe– preserves the identity of the patient, and improves the quality of care.

Addendum:  See also a related post today on 1boringoldman.com.


Viva Viibryd ?

January 25, 2011

Well, what do you know… I turn my back for one second and now the FDA has gone ahead and approved another antidepressant.

This new one is vilazodone, made by Massachusetts-based company Clinical Data, Inc., and will be sold under the name Viibryd (which I have absolutely no idea how to pronounce, but I’m sure someone will tell me soon).

At first glance, vilazodone seems promising. It’s not exactly a “me-too” drug, a molecule similar in structure and function to something that already exists. Instead, it’s a “dual-action” antidepressant, a selective serotonin reuptake inhibitor and partial agonist at serotonin 1A receptors. In other words, it does two things: it blocks the reuptake of serotonin into neurons (much like the existing SSRIs like Prozac, Zoloft, and Lexapro) and it acts as a partial agonist at a particular type of serotonin receptor called “1A.” A partial agonist is a molecule that binds to a receptor on a target cell and does not activate that cell fully but doesn’t entirely prevent its response, either.

(Note: don’t let the name fool you. “Dual-action” agents are not “twice as effective” as other agents, and sometimes work just the same.)

If you buy the serotonin hypothesis of depression (closely derived from the “monoamine hypothesis“), then depression is caused by a deficiency in serotonin. SSRIs cause an increase in serotonin between two cells. However, the higher levels of serotonin serve as “negative feedback” to the first-order cell in order to keep the system in balance. (Our bodies do this all the time. If I keep yelling at you for no clear reason, you’ll rapidly “downregulate” your attention so that you don’t listen to me anymore. Neurons work this way, too.) The idea behind a partial agonist is that it will only do “part” of the work that serotonin will do (actually, it will effectively block the negative feedback of serotonin) to increase serotonin release even more.

Remember– that’s only if you agree that low serotonin is responsible for depression. And there are plenty of respectable people who just don’t buy this. After all, no one has convincingly shown a serotonin deficit in depression, and when SSRIs do work (which they do, remarkably well sometimes), they may be acting by a totally different mechanism we just don’t understand yet. Nevertheless, vilazodone did show a significant effect as early as the first week, an effect that lasted for eight weeks.

Specifically, a phase III trial of 410 adults with depression showed decreases in MADRS and HAM-D scales relative to placebo, as well as on the CGI-I, CGI-S, and HAM-A scales, with a decrease in MADRS score from a mean of 30.8 at baseline to about 18 at the 8-week timepoint (the placebo group showed a decrease of about 10 points). A similar decrease was seen in the HAM-D. As is typical with these studies, the phase III trial did not compare vilazodone to an existing drug. However, unpublished phase II trials did compare it to fluoxetine (Prozac) and citalopram (Celexa), and to placebo, and results show that the drugs were comparable (and placebo response rates were high, as high as 40% in some trials). Incidentally, 9.3% of patients in the phase III trial dropped out due to adverse effects, mainly diarrhea.

So is a blockbuster in the works? Well, it’s not quite as “new” as one would think. SSRIs have been in widespread use for years, and there’s already a serotonin 1A partial agonist available called BuSpar (generic = buspirone) which is sort of a “ho-hum” drug– effective for some, but nothing to get too excited about. It seems that one could make “homemade” vilazodone by combining buspirone with an SSRI. (Kids, don’t try this at home. Please consult an expert.) This is a fairly common combination, although most psychiatrists have been underwhelmed by buspirone’s efficacy (one of my teachers called it “holy water”). Maybe vilazodone will convince me otherwise.

To go back to my original question, do we really need this? My gut reaction is no, as it seems too similar to what we already have available. There may be a small group of treatment-resistant depressed patients for whom vilazodone will be a wonder drug, a true lifesaver. In an attempt to discover this small group, the manufacturer is simultaneously studying “biomarkers that may predict treatment response.” In other words, they’re looking for genetic “fingerprints” that might predict patients who will respond to their drug (or who will get side effects). They have no “hits” yet (one of the markers they studied in phase III proved to have no predictive value in a follow-up trial), but it’s appealing to think that we might get more data on how to use– or avoid– this new drug more wisely.

While it’s good to have more tools in our toolkit, I sincerely hope this doesn’t turn into yet another in a long line of medications that we give to depressed patients in the trial-and-error process that unfortunately characterizes a lot of depression management. What’s truly needed is not just another serotonin agent, but a guideline (like a genetic test) to predict who’s likely to respond, or, better yet, a more sophisticated understanding of what’s happening in the minds of “depressed” patients. (And the differences among depressed patients far outweigh their similarities.) Until then, we’ll just be making incremental progress toward an elusive goal.


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