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Edwards RR, Schreiber KL, Dworkin RH, Turk DC, Baron R, Freeman R, Jensen TS, Latremoliere A, Markman JD, Rice ASC, Rowbotham M, Staud R, Tate S, Woolf CJ, Andrews NA, Carr DB, Colloca L, Cosma-Roman D, Cowan P, Diatchenko L, Farrar J, Gewandter JS, Gilron I, Kerns RD, Marchand S, Niebler G, Patel KV, Simon LS, Tockarshewsky T, Vanhove GF, Vardeh D, Walco GA, Wasan AD, Wesselmann U. Optimizing and Accelerating the Development of Precision Pain Treatments for Chronic Pain: IMMPACT Review and Recommendations. J Pain 2023; 24:204-225. [PMID: 36198371 PMCID: PMC10868532 DOI: 10.1016/j.jpain.2022.08.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 08/01/2022] [Accepted: 08/17/2022] [Indexed: 11/06/2022]
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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Affiliation(s)
| | | | | | - Dennis C Turk
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington
| | - Ralf Baron
- Division of Neurological Pain Research and Therapy, Department of Neurology, University Hospital Schleswig-Holstein, Arnold-Heller-Straße 3, House D, 24105 Kiel, Germany
| | - Roy Freeman
- Harvard Medical School, Boston, Massachusetts
| | | | | | | | | | | | | | | | | | - Nick A Andrews
- Salk Institute for Biological Studies, San Diego, California
| | | | | | | | - Penney Cowan
- American Chronic Pain Association, Rocklin, California
| | - Luda Diatchenko
- Department of Anesthesia and Faculty of Dentistry, McGill University, Montreal, California
| | - John Farrar
- University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | - Robert D Kerns
- Yale University, Departments of Psychiatry, Neurology, and Psychology, New Haven, Connecticut
| | | | | | - Kushang V Patel
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington
| | | | | | | | | | - Gary A Walco
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington
| | - Ajay D Wasan
- University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Ursula Wesselmann
- Department of Anesthesiology/Division of Pain Medicine, Neurology and Psychology, The University of Alabama at Birmingham, Birmingham, Alabama
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Gewandter JS, Dworkin RH, Turk DC, Devine EG, Hewitt D, Jensen MP, Katz NP, Kirkwood AA, Malamut R, Markman JD, Vrijens B, Burke L, Campbell JN, Carr DB, Conaghan PG, Cowan P, Doyle MK, Edwards RR, Evans SR, Farrar JT, Freeman R, Gilron I, Juge D, Kerns RD, Kopecky EA, McDermott MP, Niebler G, Patel KV, Rauck R, Rice ASC, Rowbotham M, Sessler NE, Simon LS, Singla N, Skljarevski V, Tockarshewsky T, Vanhove GF, Wasan AD, Witter J. Improving Study Conduct and Data Quality in Clinical Trials of Chronic Pain Treatments: IMMPACT Recommendations. J Pain 2019; 21:931-942. [PMID: 31843583 DOI: 10.1016/j.jpain.2019.12.003] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 10/30/2019] [Accepted: 12/11/2019] [Indexed: 11/30/2022]
Abstract
The estimated probability of progressing from phase 3 analgesic clinical trials to regulatory approval is approximately 57%, suggesting that a considerable number of treatments with phase 2 trial results deemed sufficiently successful to progress to phase 3 do not yield positive phase 3 results. Deficiencies in the quality of clinical trial conduct could account for some of this failure. An Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials meeting was convened to identify potential areas for improvement in trial conduct in order to improve assay sensitivity (ie, ability of trials to detect a true treatment effect). We present recommendations based on presentations and discussions at the meeting, literature reviews, and iterative revisions of this article. The recommendations relate to the following areas: 1) study design (ie, to promote feasibility), 2) site selection and staff training, 3) participant selection and training, 4) treatment adherence, 5) data collection, and 6) data and study monitoring. Implementation of these recommendations may improve the quality of clinical trial data and thus the validity and assay sensitivity of clinical trials. Future research regarding the effects of these strategies will help identify the most efficient use of resources for conducting high quality clinical trials. PERSPECTIVE: Every effort should be made to optimize the quality of clinical trial data. This manuscript discusses considerations to improve conduct of pain clinical trials based on research in multiple medical fields and the expert consensus of pain researchers and stakeholders from academia, regulatory agencies, and industry.
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Affiliation(s)
| | | | | | | | | | | | - Nathaniel P Katz
- Analgesic Solutions, Natick, Massachusetts; Tufts University, Boston, Massachusetts
| | - Amy A Kirkwood
- CR UK and UCL Cancer Trials Centre, UCL Cancer Institute, London, UK
| | | | - John D Markman
- University of Rochester Medical Center, Rochester, New York
| | | | | | | | - Daniel B Carr
- Tufts University School of Medicine, Boston, Massachusetts
| | - Philip G Conaghan
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, & NIHR Leeds Biomedical Research Centre, Leeds, UK
| | - Penney Cowan
- American Chronic Pain Association, Rocklin, California
| | | | | | - Scott R Evans
- George Washington University, Washington, District of Columbia
| | - John T Farrar
- University of Pennsylvania, Philadelphia, Pennsylvania
| | - Roy Freeman
- Brigham & Women's Hospital, Boston, Massachusetts
| | - Ian Gilron
- Queen's University, Kingston, Ontario, Canada
| | - Dean Juge
- Horizon Pharma, Lake Forest, Illinois
| | | | | | | | | | | | - Richard Rauck
- Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | | | | | | | | | - Neil Singla
- Lotus Clinical Research, Pasadena, California
| | | | | | | | - Ajay D Wasan
- University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - James Witter
- National Institutes of Health, Bethesda, Maryland
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