Population scale data reveals the antidepressant effects of ketamine and other therapeutics approved for non-psychiatric indications

Introduction

Depression is a major global burden, with lifetime prevalence commonly estimated at 8–12% in many countries. Current first‑line pharmacotherapies, principally serotonin reuptake inhibitors, suffer from delayed onset of effect (initial benefit often 2–3 weeks, optimal response 6–10 weeks), incomplete efficacy for a substantial minority of patients, and poor long‑term adherence. These limitations are particularly problematic for patients with acute suicidal ideation, who cannot wait weeks for symptomatic relief. As a result, clinicians have explored alternative agents such as ketamine; small clinical trials (typically 20–57 participants) have reported rapid antidepressant effects, but larger randomised trials face financial and ethical obstacles. Cohen and colleagues therefore sought population‑scale statistical evidence for ketamine’s antidepressant action by analysing post‑marketing reports in the FDA Adverse Event Reporting System (FAERS) and its legacy AERS repository. Using a method the authors call Inverse‑Frequency Analysis (IFA) — which examines statistically significant negative log odds ratios (LogOR) as an indirect signal of reduced complaint frequency — they compared reports involving ketamine against those for other drug combinations used to treat pain. In the extracted text the authors report that ketamine‑containing records showed substantially lower frequencies of reported depression (LogOR −0.67 ± 0.034) and pain (LogOR −0.41 ± 0.019) relative to other pain treatments. They also note findings for other approved non‑psychiatric drugs (including minocycline and diclofenac) that emerged as associated with reduced depression reports. The authors present these population‑scale observations as complementary evidence to small clinical trials, arguing that the rapidity of ketamine’s effect could be clinically useful for acute and treatment‑resistant depression and that the IFA approach can help discover off‑label therapeutic effects of existing drugs without immediate recourse to large new trials.