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

ABSTRACT:

Abstract

Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

SUBMITTER: Sluka KA

PROVIDER: S-EPMC10436361 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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

Sluka Kathleen A KA Wager Tor D TD Sutherland Stephani P SP Labosky Patricia A PA Balach Tessa T Bayman Emine O EO Berardi Giovanni G Brummett Chad M CM Burns John J Buvanendran Asokumar A Caffo Brian B Calhoun Vince D VD Clauw Daniel D Chang Andrew A Coffey Christopher S CS Dailey Dana L DL Ecklund Dixie D Fiehn Oliver O Fisch Kathleen M KM Frey Law Laura A LA Harris Richard E RE Harte Steven E SE Howard Timothy D TD Jacobs Joshua J Jacobs Jon M JM Jepsen Kristen K Johnston Nicolas N Langefeld Carl D CD Laurent Louise C LC Lenzi Rebecca R Lindquist Martin A MA Lokshin Anna A Kahn Ari A McCarthy Robert J RJ Olivier Michael M Porter Linda L Qian Wei-Jun WJ Sankar Cheryse A CA Satterlee John J Swensen Adam C AC Vance Carol G T CGT Waljee Jennifer J Wandner Laura D LD Williams David A DA Wixson Richard L RL Zhou Xiaohong Joe XJ

Pain 20230615 9

<h4>Abstract</h4>Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are ...[more]

PMID: 37326643

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Project description:BackgroundChronic postsurgical pain (CPSP) is a clinical problem, and large prospective studies are needed to determine its incidence, characteristics, and risk factors.ObjectiveTo find predictive factors for CPSP in an international survey.DesignObservational study.SettingMulticentre European prospective observational trial.PatientsPatients undergoing breast cancer surgery, sternotomy, endometriosis surgery, or total knee arthroplasty (TKA).MethodStandardised questionnaires were completed by the patients at 1, 3, and 7 days, and at 1, 3, and 6 months after surgery, with follow-up via E-mail, telephone, or interview.Main outcome measureThe primary goal of NIT-1 was to propose a scoring system to predict those patient likely to have CPSP at 6 months after surgery.ResultsA total of 3297 patients were included from 18 hospitals across Europe and 2494 patients were followed-up for 6 months. The mean incidence of CPSP at 6 months was 10.5%, with variations depending on the type of surgery: sternotomy 6.9%, breast surgery 7.4%, TKA 12.9%, endometriosis 16.2%. At 6 months, neuropathic characteristics were frequent for all types of surgery: sternotomy 33.3%, breast surgery 67.6%, TKA 42.4%, endometriosis 41.4%. One-third of patients experienced CPSP at both 3 and 6 months. Pre-operative pain was frequent for TKA (leg pain) and endometriosis (abdomen) and its frequency and intensity were reduced after surgery. Severe CPSP and a neuropathic pain component decreased psychological and functional wellbeing as well as quality of life. No overarching CPSP risk factors were identified.ConclusionUnfortunately, our findings do not offer a new CPSP predictive score. However, we present reliable new data on the incidence, characteristics, and consequences of CPSP from a large European survey. Interesting new data on the time course of CPSP, its neuropathic pain component, and CPSP after endometriosis surgery generate new hypotheses but need to be confirmed by further research.Trial registrationclinicaltrials.gov ID: NCT03834922.

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Dataset Information

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

Abstract

Publications

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

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