Parallel modeling of pain and depression in prediction of relapse during buprenorphine and naloxone treatment: A finite mixture model.

ABSTRACT:

Background

Relapse is common in treatment for opioid use disorders (OUDs). Pain and depression often co-occur during OUD treatment, yet little is known about how they influence relapse among patients with a primary diagnosis of prescription opioid use disorder (POUD). Advanced statistical analyses that can simultaneously model these two conditions may lead to targeted clinical interventions.

Method

The objective of this study was to utilize a discrete survival analysis with a growth mixture model to test time to prescription opioid relapse, predicted by parallel growth trajectories of depression and pain, in a clinical sample of patients in buprenorphine/naloxone treatment. The latent class analysis characterized heterogeneity with data collected from the National Institute

SUBMITTER: Vest NA 

PROVIDER: S-EPMC7173998 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature