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Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations
- Source :
- PAIN Reports, Vol 6, Iss 1, p e899 (2021), Edwards, R R, Dworkin, R H, Turk, D C, Angst, M S, Dionne, R, Freeman, R, Hansson, P, Haroutounian, S, Arendt-Nielsen, L, Attal, N, Baron, R, Brell, J, Bujanover, S, Burke, L B, Carr, D, Chappell, A S, Cowan, P, Etropolski, M, Fillingim, R B, Gewandter, J S, Katz, N P, Kopecky, E A, Markman, J D, Nomikos, G, Porter, L, Rappaport, B A, Rice, A S C, Scavone, J M, Scholz, J, Simon, L S, Smith, S M, Tobias, J, Tockarshewsky, T, Veasley, C, Versavel, M, Wasan, A D, Wen, W & Yarnitsky, D 2016, ' Patient phenotyping in clinical trials of chronic pain treatments : IMMPACT recommendations ', Pain, vol. 157, no. 9, pp. 1851-1871 . https://doi.org/10.1097/j.pain.0000000000000602, Edwards, R R, Dworkin, R H, Turk, D C, Angst, M S, Dionne, R, Freeman, R, Hansson, P, Haroutounian, S, Arendt-Nielsen, L, Attal, N, Baron, R, Brell, J, Bujanover, S, Burke, L B, Carr, D, Chappell, A S, Cowan, P, Etropolski, M, Fillingim, R B, Gewandter, J S, Katz, N P, Kopecky, E A, Markman, J D, Nomikos, G, Porter, L, Rappaport, B A, Rice, A S C, Scavone, J M, Scholz, J, Simon, L S, Smith, S M, Tobias, J, Tockarshewsky, T, Veasley, C, Versavel, M, Wasan, A D, Wen, W & Yarnitsky, D 2021, ' Patient phenotyping in clinical trials of chronic pain treatments : IMMPACT recommendations ', Pain Reports, vol. 6, no. 1, e896 . https://doi.org/10.1097/pr9.0000000000000896
- Publication Year :
- 2021
- Publisher :
- Wolters Kluwer, 2021.
-
Abstract
- There is tremendous interpatient variability in the response to analgesic therapy (even for efficacious treatments), which can be the source of great frustration in clinical practice. This has led to calls for “precision medicine” or personalized pain therapeutics (ie, empirically based algorithms that determine the optimal treatments, or treatment combinations, for individual patients) that would presumably improve both the clinical care of patients with pain and the success rates for putative analgesic drugs in phase 2 and 3 clinical trials. However, before implementing this approach, the characteristics of individual patients or subgroups of patients that increase or decrease the response to a specific treatment need to be identified. The challenge is to identify the measurable phenotypic characteristics of patients that are most predictive of individual variation in analgesic treatment outcomes, and the measurement tools that are best suited to evaluate these characteristics. In this article, we present evidence on the most promising of these phenotypic characteristics for use in future research, including psychosocial factors, symptom characteristics, sleep patterns, responses to noxious stimulation, endogenous pain-modulatory processes, and response to pharmacologic challenge. We provide evidence-based recommendations for core phenotyping domains and recommend measures of each domain.
- Subjects :
- medicine.medical_specialty
Treatment outcome
Analgesic
Alternative medicine
02 engineering and technology
01 natural sciences
Article
03 medical and health sciences
0302 clinical medicine
Analgesic therapy
030202 anesthesiology
Anesthesiology
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
medicine
Noxious stimulus
Humans
RD78.3-87.3
Psychiatry
010306 general physics
Intensive care medicine
Pain Measurement
Analgesics
Clinical Trials as Topic
business.industry
Chronic pain
Precision medicine
medicine.disease
Clinical trial
Phenotype
Treatment Outcome
Anesthesiology and Pain Medicine
Neurology
020201 artificial intelligence & image processing
Neurology (clinical)
Chronic Pain
business
Psychosocial
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 24712531
- Volume :
- 6
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- PAIN Reports
- Accession number :
- edsair.doi.dedup.....abd9ba5c6f5ac347f31b08f2ced337c8