Clinical Core

Clinical Core:  

LEADS

Conor O’Neill, MD            Clinical Core Director, UCSF Director of the multidisciplinary spine service

Dennis Black, PhD          Co-Director, Epidemiologist/Biostatistician, UCSF Head of chronic diseases division

Patricia Zheng, MD         Co-Director, UCSF Specialist in physical medicine and rehabilitation

 

AIMS

To identify factors associated with response to cLBP treatment and heterogeneity of treatment effects.

  1. Design/perform a prospective, multicenter, longitudinal Clinical Cohort Study, n=400, capable of supporting deep phenotyping efforts of cLBP patients based on combined biopsychosocial variables.

  2. Design/perform a large site-less Digital eCohort Study, n=5000.  This data will allow for testing and adoption of machine learning techniques reliant on large datasets to generate novel cLBP phenotyping algorithms.

  3. Develop a large central cLBP Data Warehouse (DW) to organize, integrate, maintain, and archive REACH-related data; this DW will be a pivotal data resource for the REACH research project, other members of the BACPAC consortium, and future cLBP researchers.

APPROACH

ComeBACK Study

Longitudinal multicenter cohort

N=400

4 clinical sites

Visits every 6 mos with up to 3 yrs of follow-up

 

Measurements:

NIH Pain Consortium minimum dataset

PROMIS-29

MRI (quantitative, MRS)

Spine exam/Quantitative Sensory Testing (QST)

Physical function testing

Genetic/biomarker testing & biospecimen archive

 

BackHome Study

eCohort

N=5000

Site-less

Enrollment/eConsent & potential f/u online-only

Collection of self-reported data and EHR data

Measurements:

NIH Pain Consortium minimum dataset

PROMIS-29

eREACH Engagement Platform

© 2020 Core Center for Patient-centric, Mechanistic Phenotyping in Chronic Low Back Pain