Is there a common resilience mechanism underlying antidepressant drug response? Evidence from 2848 patients

Timing issues of antidepressant drug response are of major clinical relevance, given our current inability to predict when a particular patient will respond to a particular treatment.

We detailed the time characteristics of recovery in a study of 2848 patients (diagnosed according to DSM-III-R/DSM-IV criteria as having major depressive disorder or major depressive episode) who were treated with 7 different anti-depressants and placebo. A 2-dimensional cure model was used to disentangle the 2 central aspects of psychotropic drug response: the proportion of patients in whom a therapeutic response is induced ( incidence) and the time to onset of improvement ( latency). Random-effects models were applied to quantify unexplained heterogeneity. Patients were recruited between June 1982 and May 1998.

Our analyses yielded no indication for a delayed onset of antidepressant drug response. Rather, we found highly individual time characteristics of recovery along with a continuous distribution of the time spans to onset of improvement under treatment with all active compounds and placebo. The mean +/- SD time to onset of improvement was 13 +/- 1 days and to response was 19 +/- 1 days. Effective antidepressants appeared to trigger and maintain conditions necessary for recovery from the disorder. Odds-ratio analysis based on a random-effects model revealed that early improvers were at least 3 times more likely to become sustained responders with a pooled OR of 9.25, 95% CI = 7.79 to 10.98.

Affectively ill patients are likely to possess a common, biological, "resilience"-like component that largely controls recovery from depression. Once triggered, recovery appears to follow a pattern similar to the course observed with placebo, despite marked pharmacologic differences of the triggers. These findings may pave the way for new classes of psychotropic drugs specifically designed to support health-oriented processes underlying the natural resilience of patients.