Examining factors related to low performance of predicting remission in participants with major depressive disorder using neuroimaging data and other clinical features

Junying Wang, David D Wu, Christine DeLorenzo and Jie Yang

PLOS ONE, 2024, vol. 19, issue 3, 1-26

Abstract: Major depressive disorder (MDD), a prevalent mental health issue, affects more than 8% of the US population, and almost 17% in the young group of 18–25 years old. Since Covid-19, its prevalence has become even more significant. However, the remission (being free of depression) rates of first-line antidepressant treatments on MDD are only about 30%. To improve treatment outcomes, researchers have built various predictive models for treatment responses and yet none of them have been adopted in clinical use. One reason is that most predictive models are based on data from subjective questionnaires, which are less reliable. Neuroimaging data are promising objective prognostic factors, but they are expensive to obtain and hence predictive models using neuroimaging data are limited and such studies were usually in small scale (N

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0299625

DOI: 10.1371/journal.pone.0299625

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