Our previous work indicates a new period of opioid analgesic use (OAU) lasting beyond 30 days, is associated with increased risk for new onset depression, depression recurrence and transition to treatment resistant depression compared to 1-30 OAU days. In multiple studies with robust control for confounding, including pain severity, longer OAU predicted new onset depression in middle-aged patients (substantially older than the age of risk for new onset depression in the population) with no recent history of depression, no evidence of opioid misuse and no recent history of OAU. Our research utilized electronic medical record (EMR) data from large samples of Veterans Administration (VA) and private sector patients. Compared to patients who discontinued OAU within 30 days, patients with 31-90 day OAU were 18% (VA) to 33% (private sector) more likely to have new onset depression. In patients with >90 day OAU, the likelihood increased to 35% in VA and 105% in private sector data. In patients with recent depression and in remission, initiation of OAU, compared to no OAU, was associated with depression recurrence in VA (HR=2.2, 95% CI = 2.0-2.3) and private sector data (HR=1.8, 95% CI = 1.4-2.2). We found that patients with depression were 22% more likely to develop treatment resistant depression with OAU of 31-90 days and 49% more likely with OAU of >90 days. The consistency of findings, replication in VA and private sector patients, and rigorous control for pain support the hypothesis that OAU is likely a risk factor for depression, as well as its recurrence and severity. A prospective study is needed to confirm and advance this line of research, in part because medical record data lack lifetime histories of mood disorders and other risk factors such as substance use disorder, trauma exposure, as well as good measures of functional impairment, sleep quality and social support. Also, EMR data do not contain prospective data on the sequence of pain, OAU and depression symptom development. In the proposed research, we hypothesize that events prior to OAU, such as history of depression, will increase risk of post- OAU new onset major depressive episode. Second, we hypothesize that OAU-related adverse outcomes, such as opioid misuse, sleep apnea, occur after long term OAU and subsequently contribute to new onset depression. Third, we hypothesize that OAU leads to worse depression that in turn contributes to higher OAU and still worsening depression, independent of longitudinal pain measures. Fourth, we focus on depression phenotypes (anhedonia, vital exhaustion, dysthymia, comorbid substance use disorder) to elucidate the new onset depression phenotypes most strongly associated with chronic OAU. Fifth, we determine which depression phenotypes are risk factors for incident opioid misuse and abuse.Data is obtained at baseline, 6 month and 12 month follow-up with monthly brief assessments for trajectory analysis. Our innovative research has great potential to advance understanding of depression in OAU and opioid misuse, abuse/use disorder. Results will inform pain management and safe opioid prescribing for patients with chronic non-cancer pain.

Public Health Relevance

In several studies controlling for pain, we found long term, >90 day opioid analgesic use (OAU) is associated with increased risk for depression and impairs depression treatment and recovery. This project collects data from 1,500 patients using prescription opioids to determine the risk factors, (e.g. lifetime history of depression, substance use disorder, poor functioning), that may increase risk of OAU related depression. We characterize the type of depression most strongly associated with OAU and determine depression subtypes associated with incident opioid misuse and abuse. Our results will help clinicians educate patients and provide evidence to further encourage pain patients to limit OAU as much as possible to improve their mood and quality of life.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
1R01DA043811-01A1
Application #
9736889
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Schulden, Jeffrey D
Project Start
2019-04-15
Project End
2024-01-31
Budget Start
2019-04-15
Budget End
2020-01-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Saint Louis University
Department
Family Medicine
Type
Schools of Medicine
DUNS #
050220722
City
Saint Louis
State
MO
Country
United States
Zip Code
63103