title: Personalized medicine and opioid analgesic prescribing for chronic pain: opportunities and challenges.
abstract: Use of opioid analgesics for pain management has increased dramatically over the past decade, with corresponding increases in negative sequelae including overdose and death. There is currently no well-validated objective means of accurately identifying patients likely to experience good analgesia with low side effects and abuse risk prior to initiating opioid therapy. This paper discusses the concept of data-based personalized prescribing of opioid analgesics as a means to achieve this goal. Strengths, weaknesses, and potential synergism of traditional randomized placebo-controlled trial (RCT) and practice-based evidence (PBE) methodologies as means to acquire the clinical data necessary to develop validated personalized analgesic-prescribing algorithms are overviewed. Several predictive factors that might be incorporated into such algorithms are briefly discussed, including genetic factors, differences in brain structure and function, differences in neurotransmitter pathways, and patient phenotypic variables such as negative affect, sex, and pain sensitivity. Currently available research is insufficient to inform development of quantitative analgesic-prescribing algorithms. However, responder subtype analyses made practical by the large numbers of chronic pain patients in proposed collaborative PBE pain registries, in conjunction with follow-up validation RCTs, may eventually permit development of clinically useful analgesic-prescribing algorithms.
  
  
  CONCLUSIONS
  Current research is insufficient to base opioid analgesic prescribing on patient characteristics. Collaborative PBE studies in large, diverse pain patient samples in conjunction with follow-up RCTs may permit development of quantitative analgesic-prescribing algorithms that could optimize opioid analgesic effectiveness and mitigate risks of opioid-related abuse and mortality.
authors: Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. stephen.bruehl@vanderbilt.edu
authors: Stephen
authors: S
authors: Bruehl
authors: A Vania
authors: AV
authors: Apkarian
authors: Jane C
authors: JC
authors: Ballantyne
authors: Ann
authors: A
authors: Berger
authors: David
authors: D
authors: Borsook
authors: Wen G
authors: WG
authors: Chen
authors: John T
authors: JT
authors: Farrar
authors: Jennifer A
authors: JA
authors: Haythornthwaite
authors: Susan D
authors: SD
authors: Horn
authors: Michael J
authors: MJ
authors: Iadarola
authors: Charles E
authors: CE
authors: Inturrisi
authors: Lixing
authors: L
authors: Lao
authors: Sean
authors: S
authors: Mackey
authors: Jianren
authors: J
authors: Mao
authors: Andrea
authors: A
authors: Sawczuk
authors: George R
authors: GR
authors: Uhl
authors: James
authors: J
authors: Witter
authors: Clifford J
authors: CJ
authors: Woolf
authors: Jon-Kar
authors: JK
authors: Zubieta
authors: Yu
authors: Y
authors: Lin
mesh_terms: D000701:Analgesics, Opioid / Q000627:therapeutic use*; D015415:Biomarkers; D035843:Biomedical Research; D059350:Chronic Pain / Q000188:drug therapy* / Q000235:genetics / Q000523:psychology; D011307:Drug Prescriptions; D004357:Drug Synergism; D014644:Genetic Variation; D006801:Humans; D018377:Neurotransmitter Agents / Q000378:metabolism / Q000502:physiology; D057285:Precision Medicine / Q000379:methods*; D016032:Randomized Controlled Trials as Topic
chemical_list: D000701:Analgesics, Opioid; D015415:Biomarkers; D018377:Neurotransmitter Agents
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