Accepted

Personalised and targeted interventions have revolutionised cancer treatment and dramatically improved survival rates in recent decades. Nonetheless, effective pain management remains a problem for patients diagnosed with cancer, who continue to suffer from the painful side effects of cancer itself, as well as treatments for the disease. This problem of cancer pain will continue to grow with an ageing population and the rapid advent of more effective therapeutics to treat the disease. Current pain management guidelines from the World Health Organisation are generalised for different pain severities, but fail to address the heterogeneity of mechanisms in patients with varying cancer types, stages of disease and treatment plans. Pain is the most common complaint leading to emergency unit visits by patients with cancer and over one-third of patients that have been diagnosed with cancer will experience under-treated pain. This review summarises preclinical models of cancer pain states, with a particular focus on cancer-induced bone pain and chemotherapy-associated pain. We provide an overview of how preclinical models can recapitulate aspects of pain and sensory dysfunction that is observed in patients with persistent cancer-induced bone pain or neuropathic pain following chemotherapy. Peripheral and central nervous system mechanisms of cancer pain are discussed, along with key cellular and molecular mediators that have been highlighted in animal models of cancer pain. These include interactions between neuronal cells, cancer cells and non-neuronal cells in the tumour microenvironment. Therapeutic targets beyond opioid-based management are reviewed for the treatment of cancer pain.

The mechanisms of neuropathic pain after spinal cord injury (SCI) are not fully understood. In addition to the plasticity that occurs within the injured spinal cord, peripheral processes, such as hyperactivity of primary nociceptors, are critical to the expression of pain after SCI. In adult rats, truncal stimulation within the tuning range of C-low threshold mechanoreceptors (C-LTMRs) contributes to pain hypersensitivity and elevates respiratory rates (RRs) after SCI. This suggests that C-LTMRs, which normally encode pleasant, affiliative touch, undergo plasticity to transmit pain sensation following injury. Because tyrosine hydroxylase (TH) expression is a specific marker of C-LTMRs, in the periphery, here we used TH-Cre adult mice to investigate more specifically the involvement of C-LTMRs in at-level pain after thoracic contusion SCI. Using a modified light-dark chamber conditioned place aversion (CPA) paradigm, we assessed chamber preferences and transitions between chambers at baseline, and in response to mechanical and optogenetic stimulation of C-LTMRs. In parallel, at baseline and select post-surgical timepoints, mice underwent non-contact RR recordings and von Frey assessment of mechanical hypersensitivity. The results showed that SCI mice avoided the chamber associated with C-LTMR stimulation, an effect that was more pronounced with optical stimulation. They also displayed elevated RRs at rest and during CPA training sessions. Importantly, these changes were restricted to chronic post-surgery timepoints, when hindpaw mechanical hypersensitivity was also evident. Together, these results suggest that C-LTMR afferent plasticity, coexisting with potentially facilitatory changes in breathing, drives at-level affective pain following SCI in adult mice.

Besides the established role of dopamine neurons and projections in nociceptive stimuli, the involvement of ventral tegmental area (VTA) glutamatergic projections to nucleus accumbens (NAc) in pain remains unknown. In the present study, we aimed to examine the role of VTA glutamatergic projections to NAc in painful stimuli and its related behavioral changes.

People with chronic low back pain experience myriads of problems from living with their condition. This study aimed to explore the lived experience of people with chronic low back pain in Ethiopia.

The opioid crisis brought scrutiny to opioid prescribing. Understanding how opioid prescribing patterns and corresponding patient outcomes changed during the epidemic is essential for future targeted policies. Many studies attempt to model trends in opioid prescriptions therefore understanding the temporal shift in opioid prescribing patterns across populations is necessary. This study characterized postoperative opioid prescribing patterns across different populations, 2010-2020.

The selection strategy of non-steroidal anti-inflammatory drugs (NSAIDs) for migraine is hard to judge whether it is effective, leading to unnecessary exposure to insufficient or lengthy treatment trials. The goal of the study was to investigate potential predictors of NSAIDs efficacy in migraine therapy and to explore their influence on efficacy. 610 migraine patients were recruited and assigned into responders and non-responders. Potential predictors among demographic and clinical characteristics for NSAIDs efficacy were extracted using multivariable logistic regression (LR) analysis, and were applied to construct prediction models machine learning (ML) algorithms. Finally, Cochran-Mantel-Haenszel tests were used to examine the impact of each predictor on drug efficacy. Multivariate LR analysis revealed migraine-related (disease duration, headache intensity and frequency) and psychiatric (anxiety, depression and sleep disorder) characteristics were predictive of NSAIDs efficacy. The accuracies of ML models using support vector machine, decision tree and multilayer perceptron were 0.712, 0.741, and 0.715, respectively. Cochran-Mantel-Haenszel test showed that, for variables with homogeneity of odds ratio, disease duration, frequency, anxiety, and depression and sleep disorder were associated with decreased likelihood of response to all NSAIDs. However, the variabilities in the efficacy of acetaminophen and celecoxib between patients with mild and severe headache intensity were not confirmed. Migraine-related and psychiatric parameters play a critical role in predicting the outcomes of acute migraine treatment. These models based on predictors could optimize drug selection and improve benefits from the start of treatment.

Trauma- and emotion-focused chronic pain interventions, particularly Emotional Awareness and Expression Therapy (EAET), show much promise for reducing pain and improving functioning. We developed a novel, single-session, telehealth-delivered EAET class ("Pain, Stress, and Emotions"; PSE) and tested it on adults with chronic pain of mixed etiology.