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Optimizing and Accelerating the Development of Precision Pain Treatments for Chronic Pain: IMMPACT Review and Recommendations.
Edwards, Robert R; Schreiber, Kristin L; Dworkin, Robert H; Turk, Dennis C; Baron, Ralf; Freeman, Roy; Jensen, Troels S; Latremoliere, Alban; Markman, John D; Rice, Andrew S C; Rowbotham, Michael; Staud, Roland; Tate, Simon; Woolf, Clifford J; Andrews, Nick A; Carr, Daniel B; Colloca, Luana; Cosma-Roman, Doina; Cowan, Penney; Diatchenko, Luda; Farrar, John; Gewandter, Jennifer S; Gilron, Ian; Kerns, Robert D; Marchand, Serge; Niebler, Gwendolyn; Patel, Kushang V; Simon, Lee S; Tockarshewsky, Tina; Vanhove, Geertrui F; Vardeh, Daniel; Walco, Gary A; Wasan, Ajay D; Wesselmann, Ursula.
Affiliation
  • Edwards RR; Harvard Medical School, Boston, Massachusetts. Electronic address: RREdwards@Partners.org.
  • Schreiber KL; Harvard Medical School, Boston, Massachusetts.
  • Dworkin RH; University of Rochester, Rochester, New York.
  • Turk DC; Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington.
  • Baron R; Division of Neurological Pain Research and Therapy, Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Straße 3, House D, 24105 Kiel, Germany.
  • Freeman R; Harvard Medical School, Boston, Massachusetts.
  • Jensen TS; Aarhus University, Aarhus, Denmark.
  • Latremoliere A; Johns Hopkins, Baltimore, Maryland.
  • Markman JD; University of Rochester, Rochester, New York.
  • Rice ASC; Imperial College, London, UK.
  • Rowbotham M; UCSF, San Francisco, California.
  • Staud R; University of Florida, Gainesville, Florida.
  • Tate S; ICG Life Sciences, London, UK.
  • Woolf CJ; Harvard Medical School, Boston, Massachusetts.
  • Andrews NA; Salk Institute for Biological Studies, San Diego, California.
  • Carr DB; Tufts University, Boston, Massachusetts.
  • Colloca L; University of Maryland, Maryland.
  • Cosma-Roman D; Abbvie Pharmaceuticals, Cambridge, Massachusetts.
  • Cowan P; American Chronic Pain Association, Rocklin, California.
  • Diatchenko L; Department of Anesthesia and Faculty of Dentistry, McGill University, Montreal, California.
  • Farrar J; University of Pennsylvania, Philadelphia, Pennsylvania.
  • Gewandter JS; University of Rochester, Rochester, New York.
  • Gilron I; Queen's University, Kingston ON, Canada.
  • Kerns RD; Yale University, Departments of Psychiatry, Neurology, and Psychology, New Haven, Connecticut.
  • Marchand S; Universite de Sherbrooke, Quebec, Canada.
  • Niebler G; Innocoll Biotherapeutics, Princeton, New Jersey.
  • Patel KV; Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington.
  • Simon LS; SDG LLC, Cambridge, Massachusetts.
  • Tockarshewsky T; Ceres Consulting, Poughkeepsie, New York.
  • Vanhove GF; Surrozen Inc., South San Francisco, California.
  • Vardeh D; Lahey Headache Center, Boston, Massachusetts.
  • Walco GA; Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington.
  • Wasan AD; University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Wesselmann U; Department of Anesthesiology/Division of Pain Medicine, Neurology and Psychology, The University of Alabama at Birmingham, Birmingham, Alabama.
J Pain ; 24(2): 204-225, 2023 02.
Article in En | MEDLINE | ID: mdl-36198371
ABSTRACT
Large variability in the individual response to even the most-efficacious pain treatments is observed clinically, which has led to calls for a more personalized, tailored approach to treating patients with pain (ie, "precision pain medicine"). Precision pain medicine, currently an aspirational goal, would consist of empirically based algorithms that determine the optimal treatments, or treatment combinations, for specific patients (ie, targeting the right treatment, in the right dose, to the right patient, at the right time). Answering this question of "what works for whom" will certainly improve the clinical care of patients with pain. It may also support the success of novel drug development in pain, making it easier to identify novel treatments that work for certain patients and more accurately identify the magnitude of the treatment effect for those subgroups. Significant preliminary work has been done in this area, and analgesic trials are beginning to utilize precision pain medicine approaches such as stratified allocation on the basis of prespecified patient phenotypes using assessment methodologies such as quantitative sensory testing. Current major challenges within the field include 1) identifying optimal measurement approaches to assessing patient characteristics that are most robustly and consistently predictive of inter-patient variation in specific analgesic treatment outcomes, 2) designing clinical trials that can identify treatment-by-phenotype interactions, and 3) selecting the most promising therapeutics to be tested in this way. This review surveys the current state of precision pain medicine, with a focus on drug treatments (which have been most-studied in a precision pain medicine context). It further presents a set of evidence-based recommendations for accelerating the application of precision pain methods in chronic pain research. PERSPECTIVE Given the considerable variability in treatment outcomes for chronic pain, progress in precision pain treatment is critical for the field. An array of phenotypes and mechanisms contribute to chronic pain; this review summarizes current knowledge regarding which treatments are most effective for patients with specific biopsychosocial characteristics.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Chronic Pain Type of study: Guideline / Prognostic_studies Limits: Humans Language: En Journal: J Pain Journal subject: NEUROLOGIA / PSICOFISIOLOGIA Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Chronic Pain Type of study: Guideline / Prognostic_studies Limits: Humans Language: En Journal: J Pain Journal subject: NEUROLOGIA / PSICOFISIOLOGIA Year: 2023 Document type: Article