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Off-label ketamine treatment has shown acute antidepressant effects that offer hope for patients with therapy-resistant depression. However, its potential for integration into treatment algorithms is controversial, not least because the evidence base for maintenance treatment with repeated ketamine administration is currently weak. Ketamine is also a drug of misuse, which has raised concerns regarding the target population. Little is known about which patients would seek ketamine treatment if it were more widely available.
To explore some of the characteristics of the patients actively seeking ketamine treatment.
An online survey containing questions about duration of current depressive episode, number of antidepressants used and other comments was completed by patients who were exploring the internet regarding the possibility of ketamine for depression.
Of the 1088 people who registered their interest, 93.3% reported depression, 64.3% reported a chronic course of their symptoms and in the past 10 years, 86.3% had tried at least two antidepressants. Desperation was a common theme, but this appeared to be competently expressed. A small minority (<8%) reported experience of illegal ketamine use.
It cannot be ruled out that patients with different degrees of treatment resistance and comorbidities will seek treatment with ketamine. This stresses the urgency to perform larger randomised controlled trials as well as to systematically monitor outcomes and adverse effects of ketamine, that is currently prescribed off-label for patients in need.
Declaration of interest
R.M. is consulting and is Principal Investigator for Janssen trials of esketamine and is consulting for Eleusis.
Etiological research of depression and anxiety disorders has been hampered by diagnostic heterogeneity. In order to address this, researchers have tried to identify more homogeneous patient subgroups. This work has predominantly focused on explaining interpersonal heterogeneity based on clinical features (i.e. symptom profiles). However, to explain interpersonal variations in underlying pathophysiological mechanisms, it might be more effective to take biological heterogeneity as the point of departure when trying to identify subgroups. Therefore, this study aimed to identify data-driven subgroups of patients based on biomarker profiles.
Data of patients with a current depressive and/or anxiety disorder came from the Netherlands Study of Depression and Anxiety, a large, multi-site naturalistic cohort study (n = 1460). Thirty-six biomarkers (e.g. leptin, brain-derived neurotrophic factor, tryptophan) were measured, as well as sociodemographic and clinical characteristics. Latent class analysis of the discretized (lower 10%, middle, upper 10%) biomarkers were used to identify different patient clusters.
The analyses resulted in three classes, which were primarily characterized by different levels of metabolic health: ‘lean’ (21.6%), ‘average’ (62.2%) and ‘overweight’ (16.2%). Inspection of the classes’ clinical features showed the highest levels of psychopathology, severity and medication use in the overweight class.
The identified classes were strongly tied to general (metabolic) health, and did not reflect any natural cutoffs along the lines of the traditional diagnostic classifications. Our analyses suggested that especially poor metabolic health could be seen as a distal marker for depression and anxiety, suggesting a relationship between the ‘overweight’ subtype and internalizing psychopathology.
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