Can we predict the antidepressant response? (Human Psychopharmacology:July 2012)


Baldwin and Balognesi in their July 2012 editorial  ask this key question.

They describe three categories of potential markers that needs consideration.

1.Predictor: Typically measured at baseline,its presence being correlated to outcome, for example, longer duration of untreated illness prior to starting treatment .

2.Moderator:  Could only derive from comparator studies; two medications would have similar overall efficacy, but the marker confers a superior outcome with one treatment;  (example:   presence of ‘atypical’ depressive symptoms and a greater likelihood of responding to phenelzine than imipramine)

3.Mediator:  could derive from any type of investigation, but the ‘marker’ is a change in value over time. ( example: evidence of onset of antidepressant effects (a drop in symptom severity by 20% or more over the first 2 weeks) as an indicator of the likelihood of response after 2 months of treatment)

Authors express disappointment at lack of research in this important area given the frequency of poor response to antidepressants.

Clinical assessment still provides indicators like the following

1.Greater depressive symptom severity may modify the response to treatment, with the more severely depressed having a greater likelihood of responding to escitalopram or venlafaxine, than to conventional selective serotonin reuptake inhibitors (Kennedy et al., 2009; Schmitt et al., 2009)

2.Greater severity of coexisting anxiety symptoms may predict a lower chance of responding o treatment (Fava et al., 2008)

3.Presence of co-morbid physical ill-health predicts a poorer outcome with selective serotonin reuptake inhibitor treatment (Papakostas, 2011).

Genetic evidence can help in predicting response/tolerability: examples:

1.Serotonin transporter gene promoter polymorphism (5-HTTLPR) status may predict response and symptom remission in Caucasians (though not Asians; Porcelli et al., 2012

2. Cytochrome CYP2C19 genotype may predict steady state serum concentrations of escitalopram (Huezo-Diaz et al., 2012 ).

Only a small  proportion of variance is explained by single gene polymorphisms. Predictive power can be increased if it is combined with neuro imaging findings.

Authors suggest areas of new lines of enquiry.

1. Serial measure of neuro inflammatory markers 2.Immunological function could also be studies in similar fashion. Emotion information processing. 3. Alterations in emotion information processing after repeated dosing.

Conclusions: It remains hard to predict antidepressant response.

This is the summary of the article :

On predicting the response to antidepressant treatment. Baldwin DS, Bolognesi F.Hum Psychopharmacol. 2012 Jul;27(4):343-4. doi: 10.1002/hup.2232.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s