Michael Browning
The Clinical Effectiveness of Using a Predictive Algorithm to Guide Antidepressant Treatment in Primary Care (PReDicT): an open-label, randomised controlled trial
Browning, Michael; Bilderbeck, Amy C.; Dias, Rebecca; Dourish, Colin T.; Kingslake, Jonathan; Deckert, Jurgen; Goodwin, Guy M.; Gorwood, Philip; Guo, Boliang; Harmer, Catherine J.; Morriss, Richard; Reif, Andreas; Ruhe, Henricus G.; Van Schaik, Anneke; Simon, Judit; Sola, Victor Perez; Veltman, Dick J.; Elices, Matilde; Lever, Anne G.; Menke, Andreas; Scanferla, Elisabetta; St�blein, Michael; Dawson, Gerard R.
Authors
Amy C. Bilderbeck
Rebecca Dias
Colin T. Dourish
Jonathan Kingslake
Jurgen Deckert
Guy M. Goodwin
Philip Gorwood
BOLIANG GUO BOLIANG.GUO@NOTTINGHAM.AC.UK
Associate Professor
Catherine J. Harmer
RICHARD MORRISS richard.morriss@nottingham.ac.uk
Professor of Psychiatry and Community Mental Health
Andreas Reif
Henricus G. Ruhe
Anneke Van Schaik
Judit Simon
Victor Perez Sola
Dick J. Veltman
Matilde Elices
Anne G. Lever
Andreas Menke
Elisabetta Scanferla
Michael St�blein
Gerard R. Dawson
Abstract
Depressed patients often do not respond to the first antidepressant prescribed, resulting in sequential trials of different medications. Personalised medicine offers a means of reducing this delay, however the clinical effectiveness of personalised approaches to antidepressant treatment has not previously been tested. We assessed the clinical effectiveness of using a predictive algorithm, based on behavioural tests of affective cognition and subjective symptoms, to guide antidepressant treatment. We conducted a multi-centre, open-label, randomised controlled trial in 913 medication-free depressed patients. Patients were randomly assigned to have their antidepressant treatment guided by a predictive algorithm or treatment as usual (TaU). The primary outcome was response of depression symptoms, defined as a 50% or greater reduction in baseline score of the QIDS-SR-16 scale, at week 8. Additional prespecified outcomes included symptoms of anxiety at week 8, and symptoms of depression and functional outcome at weeks 8, 24 and 48. The response rate of depressive symptoms at week 8 in the PReDicT (55.9% ) and TaU (51.8% ) arms did not differ significantly (odds ratio: 1.18 (95% CI: 0.89-1.56), p=0.25). However, there was a significantly greater reduction of anxiety at week 8 and a greater improvement in functional outcome at week 24 in the PReDicT arm. Use of the PReDicT test did not increase the rate of response to antidepressant treatment estimated by depressive symptoms, but did improve symptoms of anxiety at week 8 and functional outcome at week 24. Our findings indicate that personalisation of antidepressant treatment may improve outcomes in depressed patients.
Citation
Browning, M., Bilderbeck, A. C., Dias, R., Dourish, C. T., Kingslake, J., Deckert, J., …Dawson, G. R. (2021). The Clinical Effectiveness of Using a Predictive Algorithm to Guide Antidepressant Treatment in Primary Care (PReDicT): an open-label, randomised controlled trial. Neuropsychopharmacology, 46, 1307–1314. https://doi.org/10.1038/s41386-021-00981-z
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 27, 2021 |
Online Publication Date | Feb 26, 2021 |
Publication Date | Jun 1, 2021 |
Deposit Date | Jan 29, 2021 |
Publicly Available Date | Aug 27, 2021 |
Journal | Neuropsychopharmacology |
Print ISSN | 0893-133X |
Electronic ISSN | 1740-634X |
Publisher | Nature Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 46 |
Pages | 1307–1314 |
DOI | https://doi.org/10.1038/s41386-021-00981-z |
Public URL | https://nottingham-repository.worktribe.com/output/5274659 |
Publisher URL | https://www.nature.com/articles/s41386-021-00981-z |
Files
Supplementary materials
(688 Kb)
PDF
PReDicT Paper
(1.3 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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