Elsevier

Biological Psychiatry

Volume 91, Issue 7, 1 April 2022, Pages 647-657
Biological Psychiatry

Archival Report
Mining Clinical Data for Novel Posttraumatic Stress Disorder Medications

https://doi.org/10.1016/j.biopsych.2021.10.008Get rights and content

Abstract

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Section snippets

Study Sample and Data Sources

We conducted a nested case-control study within a previously established retrospective cohort that included all VA users with a clinical diagnosis of PTSD (ICD-9 code: 309.81; ICD-10 code: F43.1x) from October 1, 1999, through September 30, 2019 (11). The data source contains information on services use, clinical diagnoses, filled prescriptions, and patient-reported outcome measures (PROMs) for PTSD using the PTSD Checklist (PCL) for these patients. This study was approved by the Veterans

Results

There were 192,912 PCL pairs that met our inclusion criteria, representing 168,941 patients (Table 1). There was a median of 89 days between the baseline and follow-up PCL, with 25% of intervals spanning less than 79 days and 25% of intervals spanning more than 141 days. Cases and controls were similar in terms of demographic and diagnostic characteristics with standardized mean differences of well below 0.1 (Table 2). Cases were more likely to have received EBT and had higher baseline PCL

Discussion

This study is the first large-scale exploration of existing medications that may have potential efficacy for the treatment of PTSD using a population-based sample. There has been limited advancement in the pharmacologic treatment options for PTSD over the last 2 decades, and the findings from this study are an initial step toward future critical innovation in this area. To address this issue, we used a novel exploratory method called TreeScan. Although the application of any novel exploratory

Acknowledgments and Disclosures

This work was supported by the National Institute of Mental Health (Grant No. R01MH121397 [to JLG and BS]). The cohort used for this study was developed through support from the Department of Defense (Grant No. PR160206 [to BS]). The sponsors had no role in the study design, methods, analysis, and interpretation of results or in the preparation of the manuscript and the decision to submit it for publication.

BS was the principal investigator on a Cooperative Research and Development Agreement

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