Patient predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH Treatment of Depression Collaborative Research Program

OBJECTIVE: The authors investigated patient characteristics predictive of treatment response in the National Institute of Mental Health (NIMH) Treatment of Depression Collaborative Research Program. METHOD: Two hundred thirty-nine outpatients with major depressive disorder according to the Research Diagnostic Criteria entered a 16-week multicenter clinical trial and were randomly assigned to interpersonal psychotherapy, cognitive-behavior therapy, imipramine with clinical management, or placebo with clinical management. Pretreatment sociodemographic features, diagnosis, course of illness, function, personality, and symptoms were studied to identify patient predictors of depression severity (measured with the Hamilton Rating Scale for Depression) and complete response (measured with the Hamilton scale and the Beck Depression Inventory). RESULTS: One hundred sixty-two patients completed the entire 16-week trial. Six patient characteristics, in addition to depression severity previously reported, predicted outcome across all treatments: social dysfunction, cognitive dysfunction, expectation of improvement, endogenous depression, double depression, and duration of current episode. Significant patient predictors of differential treatment outcome were identified. 1) Low social dysfunction predicted superior response to interpersonal psychotherapy. 2) Low cognitive dysfunction predicted superior response to cognitive-behavior therapy and to imipramine. 3) High work dysfunction predicted superior response to imipramine. 4) High depression severity and impairment of function predicted superior response to imipramine and to interpersonal psychotherapy. CONCLUSIONS: The results demonstrate the relevance of patient characteristics, including social, cognitive, and work function, for prediction of the outcome of major depressive disorder. They provide indirect evidence of treatment specificity by identifying characteristics responsive to different modalities, which may be of value in the selection of patients for alternative treatments.