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Psychol Med. 2012 Feb;42(2):309-16. doi: 10.1017/S0033291711001280. Epub 2011 Jul 25.

A practical approach to the early identification of antidepressant medication non-responders.

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Department of Statistics and Applied Probability, National University of Singapore, Singapore.
Duke-National University of Singapore, Graduate Medical School, Singapore.



The aim of the present study was to determine whether a combination of baseline features and early post-baseline depressive symptom changes have clinical value in predicting out-patient non-response in depressed out-patients after 8 weeks of medication treatment.


We analysed data from the Combining Medications to Enhance Depression Outcomes study for 447 participants with complete 16-item Quick Inventory of Depressive Symptomatology - Self-Report (QIDS-SR16) ratings at baseline and at treatment weeks 2, 4 and 8. We used a multi-time point, recursive subsetting approach that included baseline features and changes in QIDS-SR16 scores from baseline to weeks 2 and 4, to identify non-responders (<50% reduction in QIDS-SR16) at week 8 with a pre-specified accuracy level.


Pretreatment clinical features alone were not clinically useful predictors of non-response after 8 weeks of treatment. Baseline to week 2 symptom change identified 48 non-responders (of which 36 were true non-responders). This approach gave a clinically meaningful negative predictive value of 0.75. Symptom change from baseline to week 4 identified 79 non-responders (of which 60 were true non-responders), achieving the same accuracy. Symptom change at both weeks 2 and 4 identified 87 participants (almost 20% of the sample) as non-responders with the same accuracy. More participants with chronic than non-chronic index episodes could be accurately identified by week 4.


Specific baseline clinical features combined with symptom changes by weeks 2-4 can provide clinically actionable results, enhancing the efficiency of care by personalizing the treatment of depression.

[Indexed for MEDLINE]

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