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Pain after cancer remains underestimated and undertreated. Precision medicine is a recent concept that refers to the ability to classify patients into subgroups that differ in their susceptibility to, biology, or prognosis of a particular disease, or in their response to a specific treatment, and thus to tailor treatment to the individual patient characteristics. Applying this to pain after cancer, the ability to classify post-cancer pain into the three major pain phenotypes (i.e. nociceptive, neuropathic, and nociplastic pain) and tailor pain treatment accordingly, is an emerging issue. This is especially relevant because available evidence suggests that nociplastic pain is present in an important subgroup of those patients experiencing post-cancer pain. The 2021 International Association for the Study of Pain (IASP) clinical criteria and grading system for nociplastic pain account for the need to identify and correctly classify patients according to the pain phenotype early in their treatment. These criteria are an important step towards precision pain medicine with great potential for the field of clinical oncology. Within this framework, the Cancer Pain Phenotyping (CANPPHE) Network, an international and interdisciplinary group of oncology clinicians and researchers from seven countries, applied the 2021 IASP clinical criteria for nociplastic pain to the growing population of those experiencing post-cancer pain. A manual is provided to allow clinicians to differentiate between predominant nociceptive, neuropathic, or nociplastic pain after cancer. A seven-step diagnostic approach is presented and illustrated using cases to enhance understanding and encourage effective implementation of this approach in clinical practice., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Pain after resolution of peripheral nerve block, known as 'rebound pain' (RP), is a major problem in outpatient surgery. The primary objective was to evaluate the benefit of intraoperative ketamine at an anti-hyperalgesic dose on the incidence of rebound pain after upper limb surgery under axillary plexus block in ambulatory patients. The secondary objective was to better understand the rebound pain phenomenon (individual risk factors)., Methods: In this prospective, double-blind study, patients were randomised to receive either a single dose of i.v. ketamine (0.3 mg kg -1 ) or a placebo. Preoperative mechanical temporal summation and central sensitization inventory were applied to question underlying central sensitisation. Pain catastrophising and Douleur Neuropathique 4 questionnaires were used. Rebound pain was defined as pain intensity score >7 (numeric rating scale, 0-10) after block resolution. Postoperative pain was recorded at Days 1, 4, and 30 after discharge., Results: A total of 109 subjects completed the study, and 40.4% presented with rebound pain. Ketamine administration did not reduce rebound pain incidence or intensity. Temporal summation and central sensitisation inventory scores did not differ between subjects with and without rebound pain. The predictive risk factors were bone surgery (odds ratio [OR]=5.2; confidence interval [CI], 1.9-14.6), severe preoperative pain (OR=4.2; CI, 1.5-11.7), and high pain catastrophising (OR=4.8; CI, 1.0-22.3). At Day 30, the average daily pain was higher in the rebound pain group involving neuropathic characteristics., Conclusion: Ketamine at an anti-hyperalgesic dose showed no benefit on rebound pain development. Although central sensitisation might not be involved, preoperative pain intensity, and catastrophising stand as risk factors. Because rebound pain remains frequent despite adequate procedure-specific postoperative analgesia, future studies should focus on patient-specific pain management., (Copyright © 2022 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.)

Background: Naloxone, an opioid receptor antagonist, is used as a pharmacological tool to detect tonic endogenous activation of opioid receptors in experimental pain models. We describe a pharmacokinetic model linking naloxone pharmacokinetics to its main metabolite after high-dose naloxone infusion., Methods: Eight healthy volunteers received a three-stage stepwise high-dose i.v. naloxone infusion (total dose 3.25 mg kg -1 ). Naloxone and naloxone-3-glucuronide (N3G) plasma concentrations were sampled from infusion onset to 334 min after infusion discontinuation. Pharmacokinetic analysis was performed using non-linear mixed effect models (NONMEM). The predictive performances of Dowling's and Yassen's models were evaluated, and target-controlled infusion simulations were performed., Results: Three- and two-compartment disposition models with linear elimination kinetics described the naloxone and N3G concentration time-courses, respectively. Two covariate models were developed: simple (weight proportional) and complex (with the shallow peripheral volume of distribution linearly increasing with body weight). The median prediction error (MDPE) and wobble for Dowling's model were -32.5% and 33.4%, respectively. For Yassen's model, the MDPE and wobble were 1.2% and 19.9%, respectively., Conclusions: A parent-metabolite pharmacokinetic model was developed for naloxone and N3G after high-dose naloxone infusion. No saturable pharmacokinetics were observed. Whereas Dowling's model was inaccurate and over-predicted naloxone concentrations, Yassen's model accurately predicted naloxone pharmacokinetics. The newly developed covariate models may be used for high-dose TCI-naloxone for experimental and clinical practice., Clinical Trials Registration: NCT01992146., (Copyright © 2018 British Journal of Anaesthesia. All rights reserved.)