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

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.

%d bloggers like this: