@article{APM32148,
author = {Cornelis Jan van Dam and Marijke Hyke Algera and Erik Olofsen and Leon Aarts and Terry Smith and Monique van Velzen and Elise Sarton and Marieke Niesters and Albert Dahan},
title = {Opioid utility function: methods and implications},
journal = {Annals of Palliative Medicine},
volume = {9},
number = {2},
year = {2019},
keywords = {},
abstract = {Opioids are complex drugs that produce profit (most importantly analgesia) as well as a myriad of adverse effects including gastrointestinal motility disturbances, abuse and addiction, sedation and potentially lethal respiratory depression (RD). Consequently, opioid treatment requires careful evaluation in terms of benefit on the one hand and harm on the other. Considering benefit and harm from an economic perspective, opioid treatment should lead to profit maximization with decision theory defining utility as (profit − loss). We here focus on the most devastating opioid adverse effect, RD and define opioid utility U = P(benefit) − P(harm), where P(benefit) is the probability of opioid-induced analgesia and P(harm) the probability of opioid-induced RD. Other utility functions are also discussed including the utility U = P(benefit AND NOT harm), the most wanted opioid effect, i.e., analgesia without RD, and utility surfaces, which depict the continuum of probabilities of presence or absence of analgesia in combination with the presence or absence of RD. Utility functions are constructed from pharmacokinetic and pharmacodynamic data sets, although pragmatic utility functions may be constructed when pharmacokinetic data are not available. We here discuss utilities of several opioids including the partial mu-opioid-receptor agonist buprenorphine, the full opioid receptor agonists fentanyl and alfentanil, and the bifunctional opioid cebranopadol, which acts at mu-opioid and nociception/orphanin FQ-receptors. We argue that utility functions give clinicians the opportunity to make an informed decision when opioid analgesics are needed for pain relief, in which opioids with a positive utility function are preferred over opioids with negative functions. Furthermore, utility functions of subpopulations will give an extra insight as a utility functions measured in one subgroup (e.g., patients with postoperative pain, good opioid responders) may not be mirrored in other patient subgroups (e.g., neuropathic pain patients, poor opioid responders).},
issn = {2224-5839}, url = {https://apm.amegroups.org/article/view/32148}
}