Brain Imaging Study on Biomarkers for Chronic Back Pain
Status:
Enrolling by invitation
Trial end date:
2035-01-01
Target enrollment:
Participant gender:
Summary
Drugs used for managing chronic pain have not proven to be effective and chronic pain
continues to cost Canadians $60 billion a year without truly helping those who suffer. The
study proposes to investigate the factors related to a person that can enhance or reduce the
effectiveness of pain treatments in people suffering with chronic pain. Treatment response to
pain killers in a person may be related to their brain, genetics, social, and psychological
makeup. The investigators aim to study these factors to identify and develop feasible and
robust indicators based on a person's biological makeup (also called biomarkers). These
biomarkers will allow doctors and researchers to predict more accurately which treatment and
prevention strategies for a particular disease will work in which groups of people. These
measures will offer new opportunities for improving treatment such as by tailoring treatment
to meet the specific needs of each patient based on his/her biological and psychological
makeup. Towards the specific aim, data will first be collected in several experimental
domains for studying treatment expectations (cognitive, psychosocial, brain-related,
genetic). These 'experimental' data will be compared between chronic back pain (CBP) and
healthy participants to yield new understanding of the factors that govern treatment
response. At the end of experimental data collection, the investigators will collect data in
the 'clinical' domain. Hence, at the end of the experimental sessions, a subset of CBP
participants will receive a mock drug (placebo disguised as an approved pain treatment) and
another subset will provide pain ratings only and hence serve as a waiting list control for
the placebo trial. Data will be studied in steps to understand factors that mediate treatment
outcomes and finally the investigators will use advanced computational tools used for big
data analysis and aim to identify factors that can be used as biomarkers and precision
medicine tools.