Predicting non-response to ketamine for depression: An exploratory symptom-level analysis of real-world data among military veterans.
Eric A. Miller, Houtan Totonchi Afshar, Jyoti Mishra, Roger S McIntyre, Dhakshin Ramanathan
Psychiatry Research May 1, 2024 DOI: 10.1016/j.psychres.2024.115858 (opens in new tab)
The journal has published a correction to this paper. Read the correction (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Retrospective analysis Peer reviewed |
|---|---|
| Sample size | 120 |
| Population | Adults with treatment-resistant depression who received intravenous racemic ketamine or intranasal esketamine in a real-world clinic |
| Intervention | intravenous racemic ketamine |
| Topics | Esketamine Ketamine Depression |
| Keywords | Predictive modeling Symptom trajectories Treatment resistant depression Treatment-resistant depression trd Refractory depression Predictive analytics Medical forecasting Veterans mental health |
| Citations | 12 |
| Key points | Using baseline symptoms alone, a logistic regression classifier identified 22% of patients who would not respond to ketamine or esketamine with a negative predictive value over 96%. |
Abstract
Ketamine helps some patients with treatment resistant depression (TRD), but reliable methods for predicting which patients will, or will not, respond to treatment are lacking. Herein, we aim to inform prediction models of non-response to ketamine/esketamine in adults with TRD. This is a retrospective analysis of PHQ-9 item response data from 120 patients with TRD who received repeated doses of intravenous racemic ketamine or intranasal eskatamine in a real-world clinic. Regression models were fit to patients' symptom trajectories, showing that all symptoms improved on average, but depressed mood improved relatively faster than low energy. Principal component analysis revealed a first principal component (PC) representing overall treatment response, and a second PC that reflects variance across affective versus somatic symptom subdomains. We then trained logistic regression classifiers to predict overall response (improvement on PC1) better than chance using patients' baseline symptoms alone. Finally, by parametrically adjusting the classifier decision thresholds, we identified optimal models for predicting non-response with a negative predictive value of over 96 %, while retaining a specificity of 22 %. Thus, we could identify 22 % of patients who would not respond based purely on their baseline symptoms. This approach could inform rational treatment recommendations to avoid additional treatment failures.
Comparable studies
Other observational and cohort studies on esketamine for depression, most cited first.
Citations in the library
Cited by 9
- Psychedelics and psychoanalysis: The journey from talking cure to transformation Journal of Psychedelic Studies August 21, 2024
- Utilizing depression symptom-based phenotypes to explore ketamine treatment response in major depression: The Bio-K multicenter trial. Journal of Affective Disorders September 15, 2025
- Nonresponse to Ketamine in Treatment‐Resistant Bipolar Depression Neuropsychopharmacology Reports July 20, 2025
- Effects of ketamine on individual symptoms and symptom networks of depression in a randomised controlled trial of ketamine for treatment-resistant depression. The British Journal of Psychiatry May 13, 2025
- Non-response to short-term ketamine use for treatment-resistant depression. Pharmacological Reports April 30, 2025
and 4 more in the library
Cites 15
- Single-Dose Psilocybin for a Treatment-Resistant Episode of Major Depression. New England Journal of Medicine November 3, 2022
- Synthesizing the Evidence for Ketamine and Esketamine in Treatment-Resistant Depression: An International Expert Opinion on the Available Evidence and Implementation American Journal of Psychiatry March 17, 2021
- Clinical Predictors of Ketamine Response in Treatment-Resistant Major Depression The Journal of Clinical Psychiatry May 15, 2014
- International pooled patient-level meta-analysis of ketamine infusion for depression: In search of clinical moderators Molecular Psychiatry September 7, 2022
- Predicting outcome with Intranasal Esketamine treatment: A machine-learning, three-month study in Treatment-Resistant Depression (ESK-LEARNING) Psychiatry Research July 29, 2023
and 10 more in the library