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

doi: 10.3389/fmed.2022.849214. eCollection 2022.

Laura Frey-Law 1, Kathleen A Sluka 1, Emine O Bayman 2, Christopher S Coffey 2, Dixie Ecklund 2, Carol G T Vance 1, Dana L Dailey 3, John Burns 4, Asokumar Buvanendran 5, Robert J McCarthy 5, Joshua Jacobs 6, Xiaohong Joe Zhou 7, Richard Wixson 8, Tessa Balach 9, Chad M Brummett 10, Daniel Clauw 10 11 12, Douglas Colquhoun 10, Steven E Harte 10 11, Richard E Harris 10 11, David A Williams 10 11 12 13, Andrew C Chang 14, Jennifer Waljee 15, Kathleen M Fisch 16, Kristen Jepsen 17, Louise C Laurent 16, Michael Olivier 18, Carl D Langefeld 19, Timothy D Howard 20, Oliver Fiehn 21, Jon M Jacobs 22, Panshak Dakup 22, Wei-Jun Qian 22, Adam C Swensen 22, Anna Lokshin 23, Martin Lindquist 24, Brian S Caffo 24, Ciprian Crainiceanu 24, Scott Zeger 24, Ari Kahn 25, Tor Wager 26, Margaret Taub 24, James Ford 27, Stephani P Sutherland 24, Laura D Wandner 28

Affiliations

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

Giovanni Berardi et al. Front Med (Lausanne). 2022.

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.

Keywords: biomarker; knee arthroplasty; pain; postsurgical pain; protocol; risk factors; thoracic surgery.

Copyright © 2022 Berardi, Frey-Law, Sluka, Bayman, Coffey, Ecklund, Vance, Dailey, Burns, Buvanendran, McCarthy, Jacobs, Zhou, Wixson, Balach, Brummett, Clauw, Colquhoun, Harte, Harris, Williams, Chang, Waljee, Fisch, Jepsen, Laurent, Olivier, Langefeld, Howard, Fiehn, Jacobs, Dakup, Qian, Swensen, Lokshin, Lindquist, Caffo, Crainiceanu, Zeger, Kahn, Wager, Taub, Ford, Sutherland and Wandner.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1

Figure 1

A2CPS study timeline. The flow of assessments is indicated across the 12-month study timeline. Remote assessments consist of patient reported outcomes (PRO) while onsite assessments involve quantitative sensory testing (QST), a blood draw for high-throughput screening techniques (omics), physical function, and brain imaging.

Figure 2

Figure 2

A2CPS structure and data flow. The organization of the A2CPS Consortium includes oversight from the Clinical Coordinating Center, data collection from the Multisite Clinical Centers, data generation from the Omics Data Generation Centers and Data Integration and Resource Center and storing of data and biospecimens within a repository.

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