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
{"title":"评估脊柱治疗的生物标志物的设计和基本原理（BEST）试验：一项连续的多重分配随机试验。","authors":"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","doi":"10.1093/pm/pnaf032","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Chronic low back pain (cLBP) is a common condition that impacts quality of life and function. There are many evidence-based treatments to address cLBP; however, treatment effects are modest, perhaps in part due to individual variation in treatment response. The Biomarkers for Evaluating Spine Treatments (BEST) trial was designed as the collaborative centerpiece of the Back Pain Consortium (BACPAC) research program. This consortium was sponsored by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) as part of the Helping to End Addiction Long-term (HEAL) Initiative.</p><p><strong>Design: </strong>The BEST trial was a sequential multiple assignment randomized trial (SMART) designed with the primary goal of identifying in whom different treatments show optimal response. The primary focus of the study was to use patient features, including biomarkers and phenotypic measures, to identify subsets of persons with cLBP who respond best to specific common treatments.</p><p><strong>Methods: </strong>Four interventions were chosen for the trial: Enhanced Self-Care, Acceptance and Commitment Therapy, Duloxetine, and Evidence-Based Exercise and Manual Therapy. Following a run-in period and baseline assessment, participants were randomized to 1 of the 4 treatments for the first 12-week intervention period. Participants were reassessed and based on their self-reported response to initial treatment, continued that initial treatment, were augmented with an additional randomly assigned treatment, or were switched to a new treatment.</p><p><strong>Conclusion: </strong>This trial was designed to deliver rich phenotypic data that will both potentially aid in the discovery of phenotypic characteristics that predict treatment response and provide a greater mechanistic understanding of cLBP.</p><p><strong>Clinical trial registration number: </strong>The Biomarkers for Evaluating Spine Treatments (BEST) trial is registered on ClinicalTrials.gov (Registration number: NCT05396014; https://clinicaltrials.gov/study/NCT05396014).</p>","PeriodicalId":19744,"journal":{"name":"Pain Medicine","volume":" ","pages":"538-553"},"PeriodicalIF":3.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12405758/pdf/","citationCount":"0","resultStr":"{\"title\":\"The design and rationale of the Biomarkers for Evaluating Spine Treatments trial: a sequential multiple assignment randomized trial.\",\"authors\":\"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\",\"doi\":\"10.1093/pm/pnaf032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Chronic low back pain (cLBP) is a common condition that impacts quality of life and function. There are many evidence-based treatments to address cLBP; however, treatment effects are modest, perhaps in part due to individual variation in treatment response. The Biomarkers for Evaluating Spine Treatments (BEST) trial was designed as the collaborative centerpiece of the Back Pain Consortium (BACPAC) research program. This consortium was sponsored by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) as part of the Helping to End Addiction Long-term (HEAL) Initiative.</p><p><strong>Design: </strong>The BEST trial was a sequential multiple assignment randomized trial (SMART) designed with the primary goal of identifying in whom different treatments show optimal response. The primary focus of the study was to use patient features, including biomarkers and phenotypic measures, to identify subsets of persons with cLBP who respond best to specific common treatments.</p><p><strong>Methods: </strong>Four interventions were chosen for the trial: Enhanced Self-Care, Acceptance and Commitment Therapy, Duloxetine, and Evidence-Based Exercise and Manual Therapy. Following a run-in period and baseline assessment, participants were randomized to 1 of the 4 treatments for the first 12-week intervention period. 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The design and rationale of the Biomarkers for Evaluating Spine Treatments trial: a sequential multiple assignment randomized trial.
Objective: Chronic low back pain (cLBP) is a common condition that impacts quality of life and function. There are many evidence-based treatments to address cLBP; however, treatment effects are modest, perhaps in part due to individual variation in treatment response. The Biomarkers for Evaluating Spine Treatments (BEST) trial was designed as the collaborative centerpiece of the Back Pain Consortium (BACPAC) research program. This consortium was sponsored by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) as part of the Helping to End Addiction Long-term (HEAL) Initiative.
Design: The BEST trial was a sequential multiple assignment randomized trial (SMART) designed with the primary goal of identifying in whom different treatments show optimal response. The primary focus of the study was to use patient features, including biomarkers and phenotypic measures, to identify subsets of persons with cLBP who respond best to specific common treatments.
Methods: Four interventions were chosen for the trial: Enhanced Self-Care, Acceptance and Commitment Therapy, Duloxetine, and Evidence-Based Exercise and Manual Therapy. Following a run-in period and baseline assessment, participants were randomized to 1 of the 4 treatments for the first 12-week intervention period. Participants were reassessed and based on their self-reported response to initial treatment, continued that initial treatment, were augmented with an additional randomly assigned treatment, or were switched to a new treatment.
Conclusion: This trial was designed to deliver rich phenotypic data that will both potentially aid in the discovery of phenotypic characteristics that predict treatment response and provide a greater mechanistic understanding of cLBP.
Clinical trial registration number: The Biomarkers for Evaluating Spine Treatments (BEST) trial is registered on ClinicalTrials.gov (Registration number: NCT05396014; https://clinicaltrials.gov/study/NCT05396014).
期刊介绍：
Pain Medicine is a multi-disciplinary journal dedicated to pain clinicians, educators and researchers with an interest in pain from various medical specialties such as pain medicine, anaesthesiology, family practice, internal medicine, neurology, neurological surgery, orthopaedic spine surgery, psychiatry, and rehabilitation medicine as well as related health disciplines such as psychology, neuroscience, nursing, nurse practitioner, physical therapy, and integrative health.
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