Design of the COMEBACK and BACKHOME Studies, Longitudinal Cohorts for Comprehensive Deep Phenotyping of Adults with Chronic Low-Back Pain (cLBP): a part of the BACPAC Research Program

Abstract

ABSTRACTObjectiveThe University of California, San Francisco (UCSF) Core Center for Patient-centric, Mechanistic Phenotyping in Chronic Low Back Pain (REACH) is one of the three NIH Back Pain Consortium (BACPAC) Research Programs Mechanistic Research Centers (MRCs). The goal of UCSF REACH is to define cLBP phenotypes and pain mechanisms that can lead to effective, personalized treatments for patients across the population. The primary objective of this research project is to address the critical need for new diagnostic and prognostic markers, and associated patient classification protocols for chronic low back pain (cLBP) treatment.DesignTo meet this objective, REACH is conducting two large investigator-initiated translational research cohort studies called: The Longitudinal Clinical Cohort for Comprehensive Deep Phenotyping of Chronic Low-Back Pain (cLBP) Adults Study (comeBACK) and the Chronic Low-Back Pain (cLBP) in Adults Study (BACKHOME).SettingcomeBACK is a longitudinal multicenter in-person observational study of 450 adults with chronic low back pain designed to perform comprehensive deep phenotyping. While, the BACKHOME study is a site-less longitudinal observational e-cohort of approximately 3000 U.S. adults with cLBP. To our knowledge, BACKHOME is the largest prospective remote registry of nationwide adults with cLBP.MethodsBoth the comeBACK and BACKHOME studies are collecting a robust and comprehensive set of risk factors, outcomes, and covariates in order to perform deep phenotyping of cLBP patients based on combined biopsychosocial variables to: define cLBP subtypes, establish phenotyping tools for routine clinical evaluation, and lead to improved cLBP outcomes in the future. The data from both studies will be used to establish techniques to develop a patient-centric definition of treatment success and to analyze cLBP patient traits to define clinically useful cLBP phenotypes, using a combination of traditional data analyses and deep learning methods.ConclusionsThese 2 pivotal studies, in conjunction with the ancillary studies being performed in both comeBACK and BACKHOME, and the other BACPAC-consortium research projects, we will be able to address a number of diagnostic and therapeutic issues in this complex and diverse patient population with cLBP. These studies will help clarify biopsychosocial mechanisms of cLBP with the aim to provide a foundation to improve the evaluation of treatment effectiveness and to spur new avenues of therapeutic research, including personalized outcome measures that constitute a clinically meaningful treatment effect for individual cLBP patients.