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Abstract

In major depression, a very common disorder, the prediction of treatment
effects is an area of  intense study. Of special interest is the question
whether stable, latent treatment subtypes can be detected and predicted.
Using mixed model-based clustering on longitudinal Hamilton Disease Rating
Scale measures revealed seven distinct treatment response dynamics clusters
in a discovery sample (N=834) that were confirmed in a replication sample
(N=237). Clusters could be predicted from 50 clinical baseline variables,
particularly personality items, life events, duration of the episode, and
specific psycho­pathological features, with cluster-derived features
performing better than individual-level features, hinting at validity
of the cluster solution.b-it-programmes/lecture-series-talks-and-events/b-it-lecture-series-summer-semester-2018/abstract-deciphering-subtypes-in-response-to-treatment-in-major-depression-a-longitudinal-approach/#

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