Feel Well Again Blog

Depression is one of the leading causes of disability around the world. According to the World Health Organization, an estimated 12 billion work days are lost every year due to depression and anxiety, costing the global economy nearly $1 trillion.

Psychiatrists and other clinicians want to see these numbers reduced. However, useful, generalizable information from clinical trials is limited. Most randomized clinical trials (RCTs) recruit participants by advertisement, rather than from clinical settings. And eligibility requirements often exclude those with coexisting medical or psychiatric disorders, those who are taking medications other than antidepressants, those with chronic depression, and those with suicidal ideation.

As a result, the evidence from RCTs involves a largely “sanitized”, uncomplicated population of depressed patients that is not representative of the population of patients showing up in the offices of most practicing clinicians. 

To address these issues, in 2003 the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study set out to develop and analyze treatment strategies to care for more representative, “real-world” patients with one or more prior failed treatment attempts.

For an overview of the STAR*D study, read this previous blog post. Here, I discuss STAR*D’s major implications for clinical treatment and policy.  

Clinical Implications for Mental Health

STAR*D was a seminal study because of its inclusiveness and real-world design methodology. The racial-ethnic makeup of enrolled patients approximates that of the U.S. population and the range of severity of depression symptoms is consistent with what practitioners report. The study had all of the participants start in the first level, where they were given a single, commonly prescribed antidepressant (citalopram).  One third of the patients in level one had fully recovered from their depression, and exited the study as a result.  However, the other two thirds were allowed to progress to level 2, where they were given the option to augment their medication with a second treatment, or switch to an entirely different treatment.  There were four total levels in the study, with the most severe, treatment resistant patients ultimately reaching level four.  A visual representation for each level can be seen in the image below:

Consequently, STAR*D taught us a lot about how to treat people with depression in a clinical setting.

Here’s a summary of the key implications:

• Remission rates were lower than expected in level 1 (about one-third of participants became symptom free, compared with 35% to 40% typically reported in clinical settings), suggesting the need for several steps to achieve remission for most patients.
• There is no clear medication “winner” for patients with treatment-resistant depression (i.e., those whose depression does not remit after one or more aggressive medication trials).
• Both switching to another medication and augmenting the original medication with a second one are reasonable options for patients after an initial antidepressant treatment has failed. There was no clear “winner” here.
• It may take longer to reach remission than expected, and thus medication trials of at least eight weeks with at least moderately aggressive dosing may be necessary.
• Cognitive therapy is a well-tolerated treatment option for patients when an antidepressant alone fails, and the outcomes patients achieve appear equivalent to those they would have achieved with the trial of a new medication. At the same time, it should be noted that for patients taking citalopram (brand name: Celexa), adding on a new medication (e.g., bupropion-SR (Wellbutrin)) was more rapidly effective than augmentation with cognitive therapy.

• The previously common practice of selecting treatments based on symptom patterns (e.g., social anxiety vs. avoidance due to anxiety) was not backed up by this study. Neither socio-demographic measures nor symptom patterns measured by STAR*D predicted a benefit from the available medication options.
• The study found that likelihood of remission after two vigorous medication trials substantially decreases.  A vigorous medication trial was defined as at least eight weeks on a treatment with at least moderately aggressive dosing.  Remission for these patients required more complicated medication regimens, for which the existing evidence base is quite thin.  Thus, this study proposed a new empirically supported definition for treatment-resistant depression: two antidepressant treatment failures, with each previous trial lasting at least eight weeks on at least a moderately aggressive dosage.

• The finding that about two-thirds of patients may be expected to reach remission with up to four treatment attempts is encouraging. Continued treatment attempts, even beyond a second treatment failure, do yield results for some patients. 
• No statistically significant difference in outcome was found between patients treated in primary care and psychiatric settings. Thus, primary care physicians, who manage the majority of depressed patients, can be reasonable providers of depression care for at least the first two treatment trials.Outcomes supported remission (defined as the complete recovery from the depressive episode) as the preferred goal of treatment. During the follow-up phase, lower relapse rates were found among participants who entered follow-up in remission than for those who only had a “response” (defined as a greater than 50% reduction in depressive symptoms, but not complete recovery from those symptoms) or those who did not achieve a “response”.

• Outcomes supported remission (defined as the complete recovery from the depressive episode) as the preferred goal of treatment. During the follow-up phase, lower relapse rates were found among participants who entered follow-up in remission than for those who only had a “response” (defined as a greater than 50% reduction in depressive symptoms, but not complete recovery from those symptoms) or those who did not achieve a “response”.
• For those who achieved remission, relapse to depression was more likely in those who required more treatment steps (ie those had greater treatment resistance).

Policy Implications

In addition to the clinical implications, STAR*D has affected policy around clinical trials and treatment in the following ways:

• STAR*D shows that inclusion of more real-world patients in clinical trials is both feasible and informative. For example, of the group of participants enrolled as a result of the broadly inclusive selection criteria used by STAR*D, only one-fourth would have been enrolled in a standard clinical trial. Results of STAR*D suggest that broader inclusion criteria would increase generalizability of results to real-world practice. 
• The choice of medications must be carefully considered. Because there was no antidepressant “winner” and the chance of remission did not clearly differ by medication choice, some may argue that doctors could restrict the available antidepressants to try in the early stages of working with a patient. However, some findings would argue for a broader list of medications. For example, antidepressant medications differed in the likelihood of particular side effects, and at the time of this study, tolerance could not be readily predicted.

• Given the multiple treatment steps needed for most participants, availability of a large number of treatments seems prudent, especially given our inability to predict who will respond to each medication. Finally, given the similar likelihood of response to treatments at level 1 and 2 (some of which have generic formulations) and the inability to predict who will respond better to a particular treatment, available generic antidepressants seem reasonable choices for these first two medication trials.
• Measurement-based care—that is, using brief, easy-to-administer techniques to monitor depression severity and side effects, following an evidence-based treatment algorithm, making decisions at key time points, and having remission as a goal of treatment—is a feasible strategy that can be adapted in real-world practice settings.

• Referral guidelines can incorporate the findings that most patients with depressive illness can be adequately treated in primary care for at least two antidepressant trials, thereby reducing the rate of premature referral to psychiatric clinics.
• The large number of patients with either recurrent major depressive disorder (MDD) or with chronic major depressive episodes (more than 75% in this study), the fact that only about half the patients reached remission after two treatments, and the poor long-term outcomes for patients when two or more acute treatments failed all suggest the need for more evidence to guide the effective treatment of treatment-resistant depression.

For nearly twenty years, researchers, clinicians, and others have continued to discuss, analyze, and share the findings from STAR*D.  The methodical, thoughtful approach of taking various treatments with well documented efficacy, allocating those treatments into different “levels”, having patients who fail to remit enter into the next “level”, has provided tremendous educational value for those of us trying to help their patients relieve their depression.  It certainly helped give me a starting framework for helping relieve depression symptoms in my patients, not only as an intern and resident, but as a practicing psychiatrist as well.