How can we get even better at customizing treatment for our patients and thereby achieve improved outcomes? How do we avoid becoming relegated to mere brokers of psychopharmacologic commodities? A few thoughts in this brief communication.
[Editor's note: Dr Scheiderer will be speaking at this year's PsychCongress in a presentation titled "Psychoneuroimmunology: Clinical Application of an Emerging Field in Psychiatry with a Special Emphasis on Atypical Depression."
The more exciting the message about launches of new antidepressants with novel modes and mechanisms, the louder the punishing drumbeat of that old assertion: the clinical efficacy of antidepressants-both between and within different classes-is comparable. While this assertion may be true from a strictly statistical standpoint, it is clinically useless, maybe even harmful. It fosters the practice of differentiating treatments by cost alone. After all, if antidepressants are similarly efficacious, why not pick the cheapest, most widely available ones?
Such a one-size-fits-all approach, however, stands directly opposed to a core tenet of psychiatric practice: personalize the treatment to fit the patient. It is also likely a major cause of the poor antidepressant treatment response rates so often reported. For example, despite advances of psychopharmacologic treatment, more than one-third of patients do not respond to the first drug tried. Moreover, results of the well-known STAR*D study found that 2/3 of patients remained symptomatic following antidepressant treatment.
The numbers are irrefutable. At the same time, these same antidepressants perform better in the hands of savvy clinicians. That is because clinicians, whether or not we can precisely articulate the rationale, attempt to match medication and other treatments to specific attributes of our patients. For example, we are unlikely to prescribe paroxetine monotherapy for the same type of depression that we would treat first line with bupropion.
Melancholic vs Atypical Depression: Clinical Features
How, however, can we get even better at customizing treatment for our patients and thereby achieve improved outcomes? How do we avoid being hoisted with our own statistical petard, becoming relegated to mere brokers of psychopharmacologic commodities? Wouldn’t it be nice to stratify our depressed patients in such a way that we could more deliberately select from among various medications? Which of our depressed patients, for example, will best be served by a generic SSRI or SNRI? Who, on the other hand is the Brintellix or Fetzima or Viibryd patient? Where does bupropion fit in, who needs adjunctive therapy with a second medication, and who is most likely to respond to the addition of Deplin?
These are among the questions I will attempt to address at the upcoming 2014 US Psych Congress in my lecture entitled - Psychoneuroimmunology: Clinical Application of an Emerging Field in Psychiatry with a Special Emphasis on Atypical Depression.
The usual disclaimers will apply. I don’t intend to talk off label. This will be a discussion of people who suffer from depression. And, as depression is the most common psychiatric illness in the world; is a leading contributor to disability globally; is degenerative and systemic; and is associated with premature aging and death, that’s plenty to talk about.
Melancholic vs Atypical Depression: Biological Features
(Juruena MF, Cleare AJ. Rev Bras Psiquiatr. 2007 May;29 Suppl 1:S19-26.)
The remainder of this brief communication highlights some of the main points I hope to make.
1. Gili M, Roca M, Armengol S, et al. Clinical patterns and treatment outcome in patients with melancholic, atypical and non-melancholic depressions. PLoS One. 2012;7(10):e48200.
2. Lamers F, Vogelzangs N, Merikangas KR, et al. Evidence for a differential role of HPA-axis function, inflammation and metabolic syndrome in melancholic versus atypical depression. Mol Psychiatry. 2013;18:692-699.
3. Penninx BW, Milaneschi Y, Lamers F, Vogelzangs N. Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile. BMC Med. 2013;15:129.
4. Duval F, Mokrani MC, Ortiz JA, et al. Neuroendocrine predictors of the evolution of depression. Dialogues Clin Neurosci. 2005;7:273-282.