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Despite the prevalence and negative impact of posttraumatic stress disorder (PTSD), there are few medications approved by the U.S. Food and Drug Administration for treatment, and approved medications do not work well enough. We leveraged large-scale electronic health record data to identify existing medications that may be repurposed as PTSD treatments. We constructed a mechanistic tree of all Food and Drug Administration-approved medications and used the tree-based scan statistic to identify medications associated with greater than expected levels of clinically meaningful improvement in PTSD symptoms using electronic health record data from the U.S. Department of Veterans Affairs. Our cohort included patients with a diagnosis of PTSD who had repeated symptom measurements using the PTSD Checklist over a 20-year period (N = 168,941). We calculated observed numbers based on patients taking each drug or mechanistically related class of drugs and the expected numbers based on the tree as a whole. Medications typically used to treat PTSD, such as the Food and Drug Administration-approved agent sertraline, were associated with improvement in PTSD symptoms, but the effects were small. Several, but not all, direct-acting antivirals used in the treatment of hepatitis C virus demonstrated a strong association with PTSD improvement. The finding was robust to a sensitivity analysis excluding patients who received established PTSD treatments, including trauma-focused psychotherapy, concurrent with hepatitis treatment. Our exploratory approach both demonstrated findings that are consistent with what is known about pharmacotherapy for PTSD and uncovered a novel class of medications that may improve PTSD symptoms. Published by Elsevier Inc.


Brian Shiner, Jenna A Forehand, Luke Rozema, Martin Kulldorff, Bradley V Watts, Marina Trefethen, Tammy Jiang, Krista F Huybrechts, Paula P Schnurr, Matthew Vincenti, Jiang Gui, Jaimie L Gradus. Mining Clinical Data for Novel Posttraumatic Stress Disorder Medications. Biological psychiatry. 2022 Apr 01;91(7):647-657

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PMID: 34952698

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