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.
Perspective
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.
Key words
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Article info
Footnotes
Supported in part by grants R01-DA031726 (S.B.); RC2 DA028928 (S.D.H. and C.E.I.); R01 NS058870, R01 NS038253, and R37NS039518 (C.J.W.); P01 AT006651, K24 DA029262, and R01 NS053961 (S.C.M.), and the NIDA-Intramural Research Program (G.R.U.).
The authors do not have any conflicts of interest.
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© 2013 American Pain Society. Published by Elsevier Inc. All rights reserved.
