Multi-Site Observational Study to Assess Biomarkers for Susceptibility or Resilience to Chronic Pain: The Acute to Chronic Pain Signatures (A2CPS) Study Protocol

Abstract

Chronic pain has become a global health problem contributing to years lived with disability and reduced quality of life. Advances in the clinical management of chronic pain have been limited due to incomplete understanding of the multiple risk factors and molecular mechanisms that contribute to the development of chronic pain. The Acute to Chronic Pain Signatures (A2CPS) Program aims to characterize the predictive nature of biomarkers (brain imaging, high-throughput molecular screening techniques, or “omics,” quantitative sensory testing, patient-reported outcome assessments and functional assessments) to identify individuals who will develop chronic pain following surgical intervention. The A2CPS is a multisite observational study investigating biomarkers and collective biosignatures (a combination of several individual biomarkers) that predict susceptibility or resilience to the development of chronic pain following knee arthroplasty and thoracic surgery. This manuscript provides an overview of data collection methods and procedures designed to standardize data collection across multiple clinical sites and institutions. Pain-related biomarkers are evaluated before surgery and up to 3 months after surgery for use as predictors of patient reported outcomes 6 months after surgery. The dataset from this prospective observational study will be available for researchers internal and external to the A2CPS Consortium to advance understanding of the transition from acute to chronic postsurgical pain.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

“…Working in collaboration with NIH and diverse team members (Fig. 3), A2CPS developed a protocol to examine biomarkers in 2 different surgical populations: (1) KA and (2) thoracic surgery 10 (Fig. 4).…”

“…Goal 1 will use a candidate approach to examine whether putative biomarkers across multiple domains-clinical, biospecimen, patient-reported outcomes, and brain structure/ function-individually predict susceptibility or resilience to the development of chronic pain at 6 mo after surgery Goal 2 will develop biosignature(s) using the candidate biomarkers, evaluated in isolation for goal 1, to determine if combinations of biomarkers improve the prediction from acute to chronic pain after surgery Goal 3 is exploratory and will use a discovery-validation approach to define novel putative biomarkers and biosignatures across multiple domains-clinical, biospecimen, psychosocial, and brain structure/function-that predict the susceptibility and resilience to the development of chronic pain at 6 mo. The approach will include biomarkers (1) defined from prior basic work using a targeted approach and (2) identified using a discovery approach September 2023 • Volume 164 • Number 9 www.painjournalonline.com different surgical populations: (1) KA and (2) thoracic surgery 10 (Fig. 4).…”

Introduction to Bayesian Analyses for Clinical Research

“…Introduction to Bayesian Analyses explored as proposed by the Acute to Chronic Pain Signatures (A2CPS). 40 For such models, incorporating prior information in the statistical analyses allows researchers to reach conclusions with more effective sample sizes.…”

“…For example, when assessing the predictors of chronic postsurgical pain, not only the association between acute and chronic pain, but also demographic, psychosocial, quantitative sensory testing, omics and neuroimaging predictors may be explored as proposed by the Acute to Chronic Pain Signatures (A2CPS). 40 For such models, incorporating prior information in the statistical analyses allows researchers to reach conclusions with more effective sample sizes.…”