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Personalising Antidepressant Treatment for Unipolar Depression Combining Individual Choices, Risks and big Data: The PETRUSHKA Tool: Personnalisation du traitement antidépresseur de la dépression unipolaire associant choix individuels, risques et mégadonnées: l'outil PETRUSHKA

delete2025-03-01
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PRE
AI
E
Edoardo G. Ostinelli
M
Matt Jaquiery
Q
Qiang Liu
R
Rania Elgarf
N
Nyla Haque
Z
Zhenpeng Li
O
Orestis Efthimiou
S
Sarah Markham
R
Roger Ede
L
Laurence Wainwright
K
Karen Barros Parron Fernandes
B
Bianca Barros Parron Fernandes
P
Paulo Victor Carpaneze Dalaqua
A
Anneka Tomlinson
K
Katharine Smith
C
Caroline Zangani
F
Franco De Crescenzo
M
Marcos Liboni
B
Benoit H. Mulsant
A
Andrea Cipriani *
P
PETRUSHKA Team
DOI:10.1177/07067437251322399delete
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Abstract

Abstract

En 中文
Objective We summarize the key steps to develop and assess an innovative online, evidence-based tool that supports shared decision-making in routine care to personalize antidepressant treatment in adults with depression. This PETRUSHKA tool is part of the PETRUSHKA trial (Personalize antidEpressant Treatment foR Unipolar depreSsion combining individual cHoices, risKs, and big datA).Methods The PETRUSHKA tool: (a) is based on prediction models, which use a combination of advanced analytics, i.e., traditional statistics, and machine learning methods; (b) utilizes electronic health records from primary care patients with depressive disorder in England and data from randomized controlled trials on antidepressants in depression, both at aggregate and individual patient level; (c) incorporates preferences from patients and clinicians (especially about adverse events); (d) generates a ranked list of personalized treatment recommendations to inform the discussion between clinicians and patients, and facilitates the final treatment choice. The PETRUSHKA tool is implemented as a web-based application, accessible from any computer, smartphone or tablet.Results We employed a bespoke algorithm to identify the best antidepressant for each individual patient, using patients' clinical and demographic characteristics and harnessing the power of innovations in digital technology, large datasets and machine learning. We established a dedicated group of patient representatives that were involved in the co-production of the tool, to maximize its impact in real-world clinical practice across the world. To test the tool, we designed an international multi-site, randomized trial (target sample: 504 participants), comparing the PETRUSHKA tool with usual care to personalize pharmacological treatment in patients with depressive disorder across Brazil, Canada and the UK.Conclusions Using evidence-based patient decision aids has been recommended to support shared decision-making when quality is assured. Future studies in precision mental health should develop multimodal web tools, incorporating patients' preferences and their individual demographic, cultural, clinical, and genetic characteristics.
Keywords:
adult psychiatry
antidepressants
caregivers
clinical trials
depressive disorders
evidence-based medicine
pharmacotherapy

Journal

C
Canadian Journal of Psychiatry and Revue Canadienne de Psychiatrie
IF:
3.8
Papers:
7.3K
Citations:
7.6K

Organization

P
pontificia universidade catolica do parana
Scholars:
3.0K
Papers: 1.9K
Citations: 1
O
Oxford Health NHS Foundation Trust
Scholars:
149
Papers: 90
Citations: 1.1K
U
Universidade Estadual de Londrina
Scholars:
5.7K
Papers: 3.0K
Citations: 2.6K
U
university of london
Scholars:
21.3W
Papers: 19.6W
Citations: 302
U
university of oxford
Scholars:
9.6W
Papers: 8.5W
Citations: 137
U
University of Bern
Scholars:
3.9W
Papers: 3.1W
Citations: 4.8W
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