An Interventional Response Phenotyping Study in Chronic Low Back Pain: Protocol for a Mechanistic Randomized Controlled Trial

Autor: Afton L Hassett, David A Williams, Richard E Harris, Steven E Harte, Chelsea M Kaplan, Andrew Schrepf, Anna L Kratz, Chad M Brummett, Kelley M Kidwell, Alexander Tsodikov, Sana Shaikh, Susan L Murphy, Remy Lobo, Anthony King, Todd Favorite, Laura Fisher, Goodarz M Golmirzaie, Jill R Schneiderhan, Ishtiaq Mawla, Eric Ichesco, Jenna McAfee, Ronald A Wasserman, Elizabeth Banner, Kathy A Scott, Courtney Cole, Daniel J Clauw
Rok vydání: 2023
Předmět:
Zdroj: Pain Medicine.
ISSN: 1526-4637
1526-2375
DOI: 10.1093/pm/pnad005
Popis: Evidence-based treatments for chronic low back pain (cLBP) typically work well in only a fraction of patients, and at present there is little guidance regarding what treatment should be used in which patients. Our central hypothesis is that an interventional response phenotyping study can identify individuals with different underlying mechanisms for their pain who thus respond differentially to evidence-based treatments for cLBP. Thus, we will conduct a randomized controlled Sequential, Multiple Assessment, Randomized Trial (SMART) design study in cLBP with the following three aims. Aim 1: Perform an interventional response phenotyping study in a cohort of cLBP patients (n = 400), who will receive a sequence of interventions known to be effective in cLBP. For 4 weeks, all cLBP participants will receive a web-based pain self-management program as part of a run-in period, then individuals who report no or minimal improvement will be randomized to: a) mindfulness-based stress reduction, b) physical therapy and exercise, c) acupressure self-management, and d) duloxetine. After 8 weeks, individuals who remain symptomatic will be re-randomized to a different treatment for an additional 8 weeks. Using those data, we will identify the subsets of participants that respond to each treatment. In Aim 2, we will show that currently available, clinically derived measures, can predict differential responsiveness to the treatments. In Aim 3, a subset of participants will receive deeper phenotyping (n = 160), to identify new experimental measures that predict differential responsiveness to the treatments, as well as to infer mechanisms of action. Deep phenotyping will include functional neuroimaging, quantitative sensory testing, measures of inflammation, and measures of autonomic tone.
Databáze: OpenAIRE
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