评估脊柱治疗生物标志物临床试验参与者的基线特征：一项针对慢性下腰痛的序贯多重分配随机试验†

Baseline characteristics of participants in the Biomarkers for Evaluating Spine Treatments clinical trial: a sequential multiple assignment randomized trial for chronic low back pain†.

作者信息

Rowland Bryce, Barth Kelly S, Bell Kevin M, Brooks Amber K, Chadwick Andrea L, Cleven Annika, Hurley Robert W, Mackey Sean, Patel Kushang V, Piva Sara R, Schneider Michael J, Al-Kadhi Fatima, Asante-Nketiah Bernice, Bagaason Sarah, Batorsky Anna, Borckardt Jeffrey J, Bowden Anton E, Carey Timothy S, Castellanos Joel, Chen Lucy, Chidgey Brooke, Dalton Diane, Dufour Jonathan S, Eberting Jaclyn L, Eller Seth M, Fields Aaron J, Fritz Julie M, Fu Amber, Ghulamhussain Inam, Goolsby Rachel West, Greco Carol M, Grim Sarah, Gunn Cameron A, Hanes Lindsay, Harris Richard E, Harte Steven E, Hassett Afton L, Helton Kinsey, Hoffmeyer Anna, Ivanova Anastasia, Jones Berkeley Sara, Kaplan Chelsea, Kidwell Kelley M, Knapik Gregory G, Kosorok Michael R, Kurillo Gregorij, Li David, Lobo Remy, Long Joseph, Lotz Jeffrey C, Mageswaran Prasath, Majumdar Sharmila, Mao Jianren, Marras William S, McCracken Lance M, McCumber Micah, McLean Samuel A, McMillan Miranda, Mehling Wolf, Mendoza Rafael, Mitchell Ulrike H, Napadow Vitaly, O'Neill Conor, Pearson Sydnee, Peltier Scott, Rundell Sean D, Ryser Sonja, Schrepf Andrew, Schulze Emily, Sperger John, Vo Nam, Wallace Mark S, Wampler Abigail M, Wasan Ajay D, Weaver Tristan E, Weber Kenneth A, Wilcox Lauren, Williams David A, Wilson Leslie, Woo Jacqueline E, Zeidan Fadel, Zhao Beibo, Zhou Brianna, Anstrom Kevin J, Clauw Daniel J, Sowa Gwendolyn A, Mauck Matthew C

机构信息

Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, United States.

Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC 29425, United States.

出版信息

Pain Med. 2025 Aug 5. doi: 10.1093/pm/pnaf073.

DOI:10.1093/pm/pnaf073

PMID:40794568

Abstract

OBJECTIVE

Chronic low back pain (cLBP) is a significant public health problem in the United States. A method to identify treatments that are most likely effective for an individual patient based on their unique characteristics is needed.

METHODS

The Biomarkers for Evaluating Spine Treatments (BEST) Trial is a sequential, multiple assignment, randomized trial designed to estimate an optimal treatment or combination of treatments to reduce pain intensity and interference at 24 weeks in individuals with cLBP.

RESULTS

We describe the patient-reported characteristics of the BEST Trial at the Baseline visit. Data collection for extensive required phenotyping is reported. We analyzed the run-in period of the BEST Trial to evaluate predictors of run-in failure. The BEST Trial enrolled 1019 participants and randomized 805 participants (61.6% female, mean age 50.4, 12.5% Black or African American) to the first stage of treatment. We collected extensive required phenotyping on all 805 randomized BEST Trial participants, and additional optional phenotyping on 510 (63.4%) participants.

CONCLUSIONS

The BEST Trial successfully enrolled a racially and geographically diverse sample of chronic low back pain patients and completed rich phenotypic assessments to inform our primary goal of identifying in whom different treatments show optimal response. We demonstrated the feasibility of collecting extensive phenotypic assessments in a multi-site clinical trial 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).

摘要

目的

慢性下腰痛（cLBP）在美国是一个重大的公共卫生问题。需要一种基于个体独特特征来识别对其最可能有效的治疗方法的手段。

方法

评估脊柱治疗生物标志物（BEST）试验是一项序贯、多重分配随机试验，旨在评估一种最佳治疗方法或联合治疗方法，以减轻cLBP患者在24周时的疼痛强度和干扰。

结果

我们描述了BEST试验在基线访视时患者报告的特征。报告了广泛所需表型分析的数据收集情况。我们分析了BEST试验的导入期，以评估导入失败的预测因素。BEST试验招募了1019名参与者，并将805名参与者（61.6%为女性，平均年龄50.4岁，12.5%为黑人或非裔美国人）随机分配到第一阶段治疗。我们对所有805名随机分组的BEST试验参与者进行了广泛所需的表型分析，并对510名（63.4%）参与者进行了额外的可选表型分析。