The design and rationale of the Biomarkers for Evaluating Spine Treatments trial: a sequential multiple assignment randomized trial - Report - MDSpire

The design and rationale of the Biomarkers for Evaluating Spine Treatments trial: a sequential multiple assignment randomized trial

  • By

  • Matthew C Mauck

  • Kelly S Barth

  • Kevin M Bell

  • Amber K Brooks

  • Andrea L Chadwick

  • Cameron A Gunn

  • Robert W Hurley

  • Anastasia Ivanova

  • Sara R Piva

  • Michael J Schneider

  • Jeannie F Bailey

  • Sarah Bagaason

  • Anna Batorsky

  • Jeffrey J Borckardt

  • Anton E Bowden

  • Timothy S Carey

  • Joel Castellanos

  • Lucy Chen

  • Brooke Chidgey

  • Diane Dalton

  • Jonathan S Dufour

  • Aaron J Fields

  • Julie M Fritz

  • Rachel West Goolsby

  • Carol M Greco

  • Richard E Harris

  • Steven Harte

  • Afton L Hassett

  • Anna Hoffmeyer

  • Sara Jones Berkeley

  • Chelsea Kaplan

  • Kelley M Kidwell

  • Gregory G Knapik

  • Michael R Kosorok

  • Gregorij Kurillo

  • Remy Lobo

  • Jeffrey C Lotz

  • Sean Mackey

  • Prasath Mageswaran

  • Sharmila Majumdar

  • Jianren Mao

  • William S Marras

  • Micah McCumber

  • Samuel A McLean

  • Wolf Mehling

  • Ulrike H Mitchell

  • Vitaly J Napadow

  • Conor O'Neill

  • Kushang V Patel

  • Scott Peltier

  • Matthew Psioda

  • Bryce Rowland

  • Sean D Rundell

  • Andrew Schrepf

  • John Sperger

  • Nam Vo

  • Mark S Wallace

  • Ajay D Wasan

  • Tristan E Weaver

  • Kenneth A Weber

  • David A Williams

  • Leslie Wilson

  • Fadel Zeidan

  • Beibo Zhao

  • Kevin J Anstrom

  • Daniel J Clauw

  • Gwendolyn A Sowa

  • April 9, 2025

  • 0 min

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Clinical Report: Biomarkers for Assessing Spine Interventions in Chronic Low Back Pain

Overview

The Biomarkers for Evaluating Spine Treatments (BEST) trial is a large sequential multiple assignment randomized trial (SMART) designed to identify patient phenotypes and biomarkers that predict optimal treatment response in chronic low back pain (cLBP). Four non-surgical interventions were tested, with treatment adjustments based on individual response, aiming to personalize cLBP management.

Background

Chronic low back pain affects over 13% of adults aged 20-69 in the U.S. and is the leading cause of disability. Despite multiple evidence-based treatments, average patient improvement remains modest, partly due to variability in individual treatment response. There are currently no validated biomarkers or phenotypic characteristics to guide personalized treatment selection. The NIH HEAL Initiative and its Back Pain Consortium (BACPAC) developed the BEST trial to address this gap by integrating biomarker and phenotypic data to optimize treatment sequencing.

Data Highlights

The BEST trial enrolled participants with cLBP who were randomized to one of four treatments: Enhanced Self-Care, Acceptance and Commitment Therapy, Duloxetine, or Evidence-Based Exercise and Manual Therapy. After 12 weeks, treatment response was assessed, and participants either continued, augmented, or switched treatments based on their self-reported outcomes. The trial collected extensive phenotypic and biomarker data to identify predictors of treatment response. Enrollment is complete, and primary analyses are underway.

Key Findings

  • The BEST trial uses a SMART design to tailor cLBP treatment based on individual response and phenotypic features.
  • Four evidence-based non-surgical interventions were selected to represent common treatment modalities for cLBP.
  • Biomarkers and phenotypic measures were comprehensively collected to enable precision medicine approaches.
  • The trial aims to identify patient subgroups that respond optimally to specific treatments or treatment sequences.
  • This approach addresses the current lack of tools to guide personalized treatment selection in cLBP.
  • The study is part of the NIH HEAL Initiative’s effort to improve pain management and reduce opioid reliance.

Clinical Implications

Clinicians may soon have validated biomarkers and phenotypic profiles to guide personalized treatment selection for cLBP, improving patient outcomes. The BEST trial’s SMART design reflects real-world clinical decision-making by adapting treatments based on individual response. This precision medicine approach has the potential to reduce trial-and-error prescribing and enhance non-opioid pain management strategies.

Conclusion

The BEST trial represents a significant advancement in cLBP research by integrating biomarker and phenotypic data within a dynamic treatment framework. Its findings are expected to inform precision medicine strategies that optimize treatment effectiveness for individual patients.

References

  1. BEST Trial ClinicalTrials.gov NCT05396014 -- Biomarkers for Evaluating Spine Treatments

Original Source(s)

The design and rationale of the Biomarkers for Evaluating Spine Treatments trial: a sequential multiple assignment randomized trial

  • by Matthew C Mauck, Kelly S Barth, Kevin M Bell, Amber K Brooks, Andrea L Chadwick, Cameron A Gunn, Robert W Hurley, Anastasia Ivanova, Sara R Piva, Michael J Schneider, Jeannie F Bailey, Sarah Bagaason, Anna Batorsky, Jeffrey J Borckardt, Anton E Bowden, Timothy S Carey, Joel Castellanos, Lucy Chen, Brooke Chidgey, Diane Dalton, Jonathan S Dufour, Aaron J Fields, Julie M Fritz, Rachel West Goolsby, Carol M Greco, Richard E Harris, Steven Harte, Afton L Hassett, Anna Hoffmeyer, Sara Jones Berkeley, Chelsea Kaplan, Kelley M Kidwell, Gregory G Knapik, Michael R Kosorok, Gregorij Kurillo, Remy Lobo, Jeffrey C Lotz, Sean Mackey, Prasath Mageswaran, Sharmila Majumdar, Jianren Mao, William S Marras, Micah McCumber, Samuel A McLean, Wolf Mehling, Ulrike H Mitchell, Vitaly J Napadow, Conor O'Neill, Kushang V Patel, Scott Peltier, Matthew Psioda, Bryce Rowland, Sean D Rundell, Andrew Schrepf, John Sperger, Nam Vo, Mark S Wallace, Ajay D Wasan, Tristan E Weaver, Kenneth A Weber, David A Williams, Leslie Wilson, Fadel Zeidan, Beibo Zhao, Kevin J Anstrom, Daniel J Clauw, Gwendolyn A Sowa

  • April 9, 2025

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