Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

ABSTRACT:

Objectives

Fibromyalgia is frequently treated with opioids due to limited therapeutic options. Long-term opioid use is associated with several adverse outcomes. Identifying factors associated with long-term opioid use is the first step in developing targeted interventions. The aim of this study was to evaluate risk factors in fibromyalgia patients newly initiated on opioids using machine learning.

Methods

A retrospective cohort study was conducted using a nationally representative primary care dataset from the UK, from the Clinical Research Practice Datalink. Fibromyalgia patients without prior cancer who were new opioid users were included. Logistic regression, a random forest model and Boruta feature selection were used to identify risk factors related to long-term opioid

SUBMITTER: Ramirez Medina CR 

PROVIDER: S-EPMC11308899 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature