Predicting outcome with Intranasal Esketamine treatment - A machine-learning, three-month study in Treatment-Resistant Depression (ESK-LEARNING)

Aug 5, 2026

Treatment-resistant depression (TRD) is a severe condition with high social and economic impact. Esketamine nasal spray (ESK-NS) is approved by EMA and FDA, yet reliable predictors of individual response remain limited. A retrospective multicentric real-world study of 149 TRD patients used baseline and 1-month/T1 and 3-month/T2 psychometric data to train random forest classifiers for response and remission prediction, achieving moderate accuracies at T1 and T2. Severe anhedonia, anxious distress, mixed symptoms and bipolarity supported earlier response, while benzodiazepine use and higher depression severity delayed outcomes.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Background

Study Design and Data Collection

Psychometric Measures

Machine-Learning Methods

Random Forest Classifiers

Results and Predictors of Response

Response and Remission Accuracies

Psychiatry Research 327 (2023) 115378 Contents lists available at ScienceDirect Psychiatry Research journal [homepage:](homepage: www.elsevier.com/locate/psychres)[ www.elsevier.com/locate/psychres](homepage: www.elsevier.com/locate/psychres) Predicting outcome with Intranasal Esketamine treatment: A machine-learning, three-month study in Treatment-Resistant Depression (ESK-LEARNING) Mauro Pettorruso a, Roberto Guidotti a, Giacomo d’Andrea a, *, Luisa De Risiob, Antea D’Andrea a, Stefania Chiappini a, Rosalba Carullo a, Stefano Barlati c, d, Raffaella Zanardi e, f, Gianluca Rosso g, Sergio De Filippish, Marco Di Nicola i,j, Ileana Andriolak, Matteo Marcatilil, Giuseppe Nicol`ob, Vassilis Martiadis m, Roberta Bassetti n, Domenica Nucifora o, Pasquale De Fazio p, Joshua D. Rosenblat q, r, s, t, Massimo Clericil, u, Bernardo Maria Dell’Osso v, Antonio Vita c, d, Laura Marzetti a, Stefano L. Sensi a, Giorgio Di Lorenzo w, x, Roger S. McIntyre q, r, s, t, y, Giovanni Martinotti a, z, the REAL-ESK Study Group1 a Department of Neurosciences, Imaging and Clinical Sciences, Universit`a degli Studi G. D’Annunzio, Chieti, Italy b Department of Mental Health and Addiction, ASL Roma 5, Rome, Italy c Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy d Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Brescia, Italy e Mood Disorder Unit, Department of Clinical Neurosciences, IRCCS San Raffaele Scientific Institute, Milan, Italy f Department of Clinical Neurosciences, University Vita-Salute San Raffaele, Milan, Italy g Department of Neurosciences Rita Levi Montalcini, University of Torino, Turin, Italy h Neuropsychiatric Clinic, Villa Von Siebenthal, Genzano di Roma, Italy i Department of Neurosciences, Section of Psychiatry, Universit`a Cattolica del Sacro Cuore, Rome j Department of Psychiatry, Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome k Universit`a degli Studi di Bari Aldo Moro, Italy l Department of Mental Health and Addiction, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy m ASL Napoli 1 Centro, Department of Mental Health, Napoli, Italy n Department of Mental Health and Addiction Services, Niguarda Hospital, Milan, Italy o MDSMA Taormina-Messina Sud ASP di Messina, Italy p Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy q Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada r Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada s Department of Psychiatry, University of Toronto, Toronto, ON, Canada t Braxia Health, Canadian Centre for Rapid Treatment Excellence (CRTCE), Mississauga, ON, Canada u School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy v Department of Biomedical and Clinical Sciences Luigi Sacco and Aldo Ravelli Center for Neurotechnology and Brain Therapeutic, University of Milan, Milano, Italy w Chair of Psychiatry, Department of Systems Medicine, Tor Vergata University of Rome, Rome, Italy x IRCCS Fondazione Santa Lucia, Rome, Italy y Brain and Cognition Discovery Foundation, Toronto, ON, Canada z Psychopharmacology, Drug Misuse and Novel Psychoactive Substances Research Unit, School of Life and Medical Sciences, University of Hertfordshire, Hatfield AL10 9AB, UK A R T I C L E I N F O Keywords: TRDEsketamine A B S T R A C T Treatment-resistant depression (TRD) represents a severe clinical condition with high social and economic costs. Esketamine Nasal Spray (ESK-NS) has recently been approved for TRD by EMA and FDA, but data about * Corresponding author at: Department of Neurosciences, Imaging and Clinical Sciences, Universit`a degli Studi G. D’Annunzio, Via dei Vestini, 66100 Chieti, Italy. E-mail address: giacomo.dandrea1993@gmail.com (G. d’Andrea). 1 A list of authors of the consortia and their affiliations appears

FAQs

What is the main aim of the ESK-LEARNING study?

To build a machine-learning tool that predicts each TRD patient’s probability of response and remission to intranasal esketamine (ESK-NS).

What data were used to train the prediction models?

Sociodemographic and clinical features, including psychometric scores collected at baseline and at one month (T1) and three months (T2) after treatment initiation.

Which features were linked to better response or remission?

Severe anhedonia, anxious distress, mixed symptoms, and bipolarity were found to positively predict response and remission.

What factors were associated with delayed responses?

Benzodiazepine usage and greater depression severity were associated with delayed responses.

Aug 5, 2026

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