Van Dam et al. (
1
) took an innovative, data-driven (as opposed to top-down, diagnostically driven)
approach to elucidate psychiatric phenotypes and related differences in functional
brain connectivity in a large sample of adults. This work attempted to clarify one
of the major problems in both clinical practice and research—namely, high comorbidity
of DSM diagnoses. The authors’ intention was to move away from DSM-5 labels, and their
results using a hierarchical clustering approach showed distinctions between individuals
with internalizing and externalizing symptoms, similar to the approach advocated by
the Hierarchical Taxonomy of Psychopathology consortium (R. Kotov, M.D., et al., The Hierarchical Taxonomy of Psychopathology [HiTOP]: A dimensional alternative
to traditional nosologies [unpublished data], 2016). The hierarchical clustering approach
used by Van Dam et al. (
1
) illuminated groups and subgroups (referred to as “clusters”) comprising typically
and atypically functioning individuals that cut across DSM-5 disorders, as well as
several functional connectivity differences between the two largest groups. It is
important to recognize that the authors could have chosen other data-driven statistical
approaches. The hierarchical clustering approach that was used relied on the assumption
of an underlying “hierarchy,” and also assumed that individuals fit into specific
clusters based on their phenotype profile. Essentially, the approach still categorized
individuals using phenotype profile instead of DSM diagnosis. In using such an approach,
the authors lost the ability to determine whether a categorical, dimensional, or true
hybrid structure best fit the data. We describe several benefits of alternative data-driven
modeling strategies below.To read this article in full you will need to make a payment
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References
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Article Info
Publication History
Accepted:
December 19,
2016
Received:
December 16,
2016
Identification
Copyright
© Society of Biological Psychiatry, 2016.
ScienceDirect
Access this article on ScienceDirectLinked Article
- Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 LabelsBiological PsychiatryVol. 81Issue 6Open Access