Application of the Gradient Boosted method in randomised clinical trials: Participant variables that contribute to depression treatment efficacy of duloxetine, SSRIs or placebo
Seetal Dodd, Michael Berk, Katarina Kelin, Qianyi Zhang, Elias Eriksson, Walter Deberdt, J Craig Nelson
JOURNAL OF AFFECTIVE DISORDERS | ELSEVIER SCIENCE BV | Published : 2014
BACKGROUND: Randomised, placebo-controlled trials of treatments for depression typically collect outcomes data but traditionally only analyse data to demonstrate efficacy and safety. Additional post-hoc statistical techniques may reveal important insights about treatment variables useful when considering inter-individual differences amongst depressed patients. This paper aims to examine the Gradient Boosted Model (GBM), a statistical technique that uses regression tree analyses and can be applied to clinical trial data to identify and measure variables that may influence treatment outcomes. METHODS: GBM was applied to pooled data from 12 randomised clinical trials of 4987 participants experi..View full abstract
This manuscript was funded by Eli Lilly.