Predicting non-response to ketamine for depression: An exploratory symptom-level analysis of real-world data among military veterans.
Psychiatry research May 1, 2024 Eric A Miller, Houtan Totonchi Afshar, Jyoti Mishra et al. 12 citations
Ketamine helps some patients with treatment-resistant depression, but predicting who will respond is difficult. Analyzing symptom trajectories from 120 patients treated with ketamine or esketamine in a real-world clinic, all symptoms improved on average, with depressed mood improving faster than low energy. A principal component analysis identified overall treatment response and a second component reflecting differences between affective and somatic symptoms. Logistic regression classifiers predicted overall response better than chance using baseline symptoms alone. By adjusting decision thresholds, models identified 22% of patients who would not respond with over 96% negative predictive value, potentially guiding treatment recommendations to avoid ineffective treatments.