Association of opioid use with survival in patients with cancer treated with immune checkpoint inhibitors: it is time for evidence-based behaviors.

Cancer is a leading cause of morbidity and mortality worldwide, with pain experienced by most patients undergoing cancer treatment. Opioids are the recommended treatment for cancer pain management, but recent studies suggest a negative association between opioid use and survival rates among patients undergoing immunotherapy. However, conclusions cannot be drawn regarding causality from these observational data. Immunotherapy, which boosts the body's immune system to fight cancer cells, has emerged as a promising treatment option for all types of cancer. Immune checkpoint inhibitors (ICIs) can activate the anticancer function of exhausted T cells and have shown remarkable survival benefits in patients with multiple malignancies. However, a recent systematic review and meta-analysis suggested that the use of opioids during ICI treatment has an adverse effect on patient prognosis, while the use of NSAIDs is not significantly associated with the prognosis in patients treated with ICIs. These reviews have major limitations due to the retrospective nature of the studies and the multiple factors that can influence the phenomenon. Therefore, caution is required when interpreting results from retrospective data on drug interactions. The findings of this study are alarming and potentially harmful to patients with cancer suffering from pain or other symptoms requiring opioid drugs.

Cannabinoids for Cancer-related Pain Management: An Update on Therapeutic Applications and Future Perspectives.

Pain is a debilitating phenomenon that dramatically impairs the quality of life of patients. Many chronic conditions, including cancer, are associated with chronic pain. Despite pharmacological efforts that have been conducted, many patients suffering from cancer pain remain without treatment. To date, opioids are considered the preferred therapeutic choice for cancer-related pain management. Unfortunately, opioid treatment causes side effects and inefficiently relieves patients from pain, therefore alternative therapies have been considered, including Cannabis Sativa and cannabinoids. Accumulating evidence has highlighted that an increasing number of patients are choosing to use cannabis and cannabinoids for the management of their soothing and non-palliative cancer pain and other cancer-related symptoms. However, their clinical application must be supported by convincing and reproducible clinical trials. In this review, we provide an update on cannabinoid use for cancer pain management. Moreover, we tried to turn a light on the potential use of cannabis as a possible therapeutic option for cancer-related pain relief.

Medicinal Cannabis: Extended Stability of Cannabis Extracts Produced Using a New Ethanol-based Extraction Method.

Cannabis as a therapeutic agent is increasing in popularity all around the globe, particularly in Western countries, and its potential is now well assessed. On the other hand, each country has its own regulation for the preparation of cannabis macerated oils; in Italy, there are only a few preparation methods allowed. With this work, we aim to perform a stability study of cannabis oils produced with a novel method for the extraction of cannabinoids from cannabis inflorescence. Three different varieties of cannabis were used, with and without the adding of tocopherol acetate as an antioxidant. Cannabinoids were extracted using ethanol at room temperature; then, the solvent was evaporated under reduced pressure and the preparations reconstituted with olive oil. In this work, we assessed the stability of both cannabinoids and terpenes in these formulas over 8 months. Cannabinoid stability was assessed by monitoring the concentrations of THC and CBD, while terpene stability was assessed by monitoring ß-Caryophyllene and α-Humulene concentrations. Stability of the extracts was not influenced by the presence of tocopherol acetate, though refrigeration seems to be detrimental for a long storage of products, especially regarding THC concentrations. The improvements offered by this method reside in the flexibility in controlling the concentration of the extract and the ability to produce highly concentrated oils, alongside the possibility to produce standardized oils despite the variability of the starting plant material.

Fentanyl in cancer pain management: avoiding hasty judgments and discerning its potential benefits.

Cancer pain is an important challenge in treatment and requires a rapid onset of action for its control. In particular, breakthrough cancer pain (BTcP) should be adequately controlled with a stable dose of a short-acting oral opioid. Fentanyl is a synthetic, highly selective opioid with many advantageous chemical properties, including high lipophilicity and distinct pharmacokinetic properties. It is recommended for pain management in a variety of settings, including acute pain, chronic pain and BTcP. To date, its variously designed formulations allow non-invasive administration; amongst others, sublingual fentanyl has proven useful in the management of BTcP and in improving the quality of life of patients with cancer. This review provides an update on the management of BTcP with fentanyl, with consideration of safety, as it remains an important tool in the treatment of cancer pain.

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives.

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be addressed. For narrative purposes, AI-based methods are grouped into behavioral-based approaches and neurophysiology-based pain detection methods. Since pain is generally accompanied by spontaneous facial behaviors, several approaches for APA are based on image classification and feature extraction. Language features through natural language strategies, body postures, and respiratory-derived elements are other investigated behavioral-based approaches. Neurophysiology-based pain detection is obtained through electroencephalography, electromyography, electrodermal activity, and other biosignals. Recent approaches involve multimode strategies by combining behaviors with neurophysiological findings. Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. Collaboration programs involving clinicians and computer scientists must be aimed at structuring and processing robust datasets that can be used in various settings, from acute to different chronic pain conditions. Finally, it is crucial to apply the concepts of explainability and ethics when examining AI applications for pain research and management.

Utilizing an artificial intelligence framework (conditional generative adversarial network) to enhance telemedicine strategies for cancer pain management.

BACKGROUND: The utilization of artificial intelligence (AI) in healthcare has significant potential to revolutionize the delivery of medical services, particularly in the field of telemedicine. In this article, we investigate the capabilities of a specific deep learning model, a generative adversarial network (GAN), and explore its potential for enhancing the telemedicine approach to cancer pain management. MATERIALS AND METHODS: We implemented a structured dataset comprising demographic and clinical variables from 226 patients and 489 telemedicine visits for cancer pain management. The deep learning model, specifically a conditional GAN, was employed to generate synthetic samples that closely resemble real individuals in terms of their characteristics. Subsequently, four machine learning (ML) algorithms were used to assess the variables associated with a higher number of remote visits. RESULTS: The generated dataset exhibits a distribution comparable to the reference dataset for all considered variables, including age, number of visits, tumor type, performance status, characteristics of metastasis, opioid dosage, and type of pain. Among the algorithms tested, random forest demonstrated the highest performance in predicting a higher number of remote visits, achieving an accuracy of 0.8 on the test data. The simulations based on ML indicated that individuals who are younger than 45 years old, and those experiencing breakthrough cancer pain, may require an increased number of telemedicine-based clinical evaluations. CONCLUSION: As the advancement of healthcare processes relies on scientific evidence, AI techniques such as GANs can play a vital role in bridging knowledge gaps and accelerating the integration of telemedicine into clinical practice. Nonetheless, it is crucial to carefully address the limitations of these approaches.

Investigating Functional Impairment in Chronic Low Back Pain: A Qualitative Study from the Patients and Specialists' Perspectives.

Prompt and appropriate treatment of chronic low back pain (cLBP) is of the utmost importance for preventing relevant disability, high burden of disease, and increasing costs for the healthcare system. Recently, the concept of functional impairment has been associated with any type of chronic pain, and mounting attention has been paid to extending the aims of treatment beyond mere pain remission, including restoration of working capacity, everyday functioning, mobility, and quality of life. Nevertheless, a shared definition of functionality is still lacking. Notably, different specialists involved in the treatment of cLBP such as general practitioners, orthopedists, pain therapists, and physiatrists, and patients themselves have different opinions on what "functional impairment" actually means. On these premises, a qualitative interview study was performed to investigate how the concept of "functionality" is interpreted by different specialists involved in the management of cLBP, and by patients. Overall, all different specialists agreed that functionality should be assessed in clinical practice. However, in spite of several instruments available for evaluating functionality, no homogeneity of behavior is observable.

High-rate breakthrough cancer pain and tumour characteristics - literature review and case series.

Cancer pain requires careful comprehensive patient evaluation and an appropriate and personalized clinical approach by a trained multidisciplinary team. The proper assessment of breakthrough cancer pain (BTcP) is part of an all-inclusive multidimensional evaluation of the patient. The aim of this narrative review is to explore the relationship between high-rate BTcP, which strongly impacts health- related quality of life and tumour characteristics, in the face of novel approaches that should provide guidance for future clinical practice. The presentation of short, emblematic clinical reports also promotes knowledge of BTcP, which, despite the availability of numerous therapeutic approaches, remains underdiagnosed and undertreated. This article is part of the Management of breakthrough cancer pain Special Issue: https://www.drugsincontext.com/special_issues/management-of-breakthrough-cancer-pain.

Phytocannabinoids in Triple Negative Breast Cancer Treatment: Current Knowledge and Future Insights.

Triple negative breast cancer (TNBC) represents an aggressive subtype of breast cancer, which is deficient in estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression. Thus, TNBC cells are unable to respond to the conventional hormonal therapies, making chemotherapy the only therapeutic choice. Patients with TNBC develop metastasis and recurrence over time and have reduced survival compared to patients with other subtypes of breast cancer. Therefore, there is a need for innovative therapies. Data emerged from pre-clinical studies, highlighted various antitumor activities of plant-derived Cannabis sativa and synthetic cannabinoids (CBs), including delta-9-tetrahydrocannabinol (THC) and non-psychoactive cannabidiol (CBD). On the contrary, some studies indicated that CBs might also promote tumor progression. At present, clinical studies on the effects of CBs from Cannabis sativa in cancer patients are few. In the present study, we reviewed known and possible interactions between cannabinoids and TNBC therapies.

Strategies to build and maintain competence in pain management: Insights from a SIAARTI survey on educational needs among Italian anesthesiologists.

PURPOSE: Fulfilling educational needs in pain management should be a lifelong process, even involving physicians board certified in pain medicine such as the anesthesiologists/pain therapists. The aim of the study was to investigate Italian anesthesiologists' self-perceived competency, confidence, and interest to attend educational programs in relation to their seniority in pain management. METHODS: SIAARTI members were sent an online questionnaire addressing the following items: education, skills (both soft and hard skills), technical expertise and engaged to participate between December 2020 and January 2021. Participants rated their competence based on the following range (no knowledge, knowledge, competence) while their agreement to attend educational courses was assessed using a 5-point Likert-type scale. RESULTS: Less than one in four participants declare to be dedicated to pain medicine activity with greater proportion among older (over 61 years) compared to younger ones (31-40 years). Regarding cancer and chronic noncancer pain a positive gradient of self-perceived competence has been observed in relation to seniority. In contrast, no gradient of self-perceived competence was reported about musculoskeletal and low back pain. Participants self-perceived competent in both opioid use and prevention of opioid-related adverse event while feeling less competent when managing drugs with abuse potential. The lowest competence has been observed in pediatric pain along with the lowest interest to attend educational courses. Participants were much and very much interested to education regarding cancer, noncancer, musculoskeletal, and low back pain, invasive analgesic procedures but less regarding items for which they declared less competence, such as use of pain scales, pain management in children, and use of drugs with abuse potential. CONCLUSION: This work provides first evidence of a summative assessment of competency and related educational needs' profile of anesthesiologists/pain therapists thus paving the way for developing a nationwide educational program to improve chronic pain care in Italy.

Implementation of a Hybrid Care Model for Telemedicine-based Cancer Pain Management at the Cancer Center of Naples, Italy: A Cohort Study.

BACKGROUND/AIM: Telemedicine, the remote delivery of healthcare services, represents a great opportunity for cancer pain management. A care model of telemedicine that combines remote visits and hospital access could be an effective and safe strategy for pain management of cancer patients. PATIENTS AND METHODS: A retrospective study was conducted using the dataset of the telemedicine program at the Istituto Nazionale Tumori of Naples, Italy for assessing the efficacy of a telehealth-based model of care. Demographic, clinical, and process variables were investigated. RESULTS: A total of 226 cases and 489 visits were included in the analysis. The mean age of patients was 63.4 years (SD=12.4 years), and no sex differences were observed. Approximately 55% of patients were ECOG-PS ≤2 and 87% suffered from metastatic disease. More than half of the patients were treated with high doses of opioids. Each patient had a mean of 2 remote visits and half of the patients had more than 1 telehealth consultation. The dropout ratio was 5.3%. Most visits (n=472) were conducted on patients in the Campania Region, Italy. The maximum covered distance from the Cancer Center and the patients' location was 555.22 Km. A significant difference in the overall number of visits (p=0.006) and the number of pro-capita remote visits (p=0.010) was found, in favor of the group of patients treated before the end of the Covid-19 emergency in Italy, compared to those treated after the pandemic. CONCLUSION: Despite various positive outcomes, the analysis highlights several weaknesses, such as the need to assist patients with advanced and non-advanced disease located outside the regional territory. Overall, the telehealth processes should be adapted to post-pandemic scenarios towards their implementation in routine clinical practice.

Pathophysiology and Therapeutic Perspectives for Chemotherapy-induced Peripheral Neuropathy.

Chemotherapy-induced peripheral neuropathy (CIPN) develops as a challenging nerve-damaging adverse effect of anticancer drugs used in chemotherapy. The disorder may require a chemotherapy dose reduction and a cessation of administration of chemotherapeutic drugs. Its principal sensory symptoms include, tingling, and numbness in the hands and feet. Severe pain can be encompassed among clinical manifestations. CIPN affects dramatically the patient's quality of life (QoL). Pain and sensory symptoms may occur for months, or even years after the termination of chemotherapeutic drugs. Although many pharmacological and non-pharmacological therapeutic approaches have been tested to overcome these symptoms, there is currently no standardized treatment for CIPN. According to current guidelines, Duloxetine is the only recommended agent for painful neuropathic symptoms. Therefore, finding effective therapies for CIPN is mandatory. The aim of this review was to dissect CIPN, the target and immunotherapy-based approaches to this disorder, as well as to offer new insights for new therapeutic perspectives.

Bayesian Network Analysis for Prediction of Unplanned Hospital Readmissions of Cancer Patients with Breakthrough Cancer Pain and Complex Care Needs.

BACKGROUND: Unplanned hospital readmissions (HRAs) are very common in cancer patients. These events can potentially impair the patients' health-related quality of life and increase cancer care costs. In this study, data-driven prediction models were developed for identifying patients at a higher risk for HRA. METHODS: A large dataset on cancer pain and additional data from clinical registries were used for conducting a Bayesian network analysis. A cohort of gastrointestinal cancer patients was selected. Logical and clinical relationships were a priori established to define and associate the considered variables including cancer type, body mass index (BMI), bone metastasis, serum albumin, nutritional support, breakthrough cancer pain (BTcP), and radiotherapy. RESULTS: The best model (Bayesian Information Criterion) demonstrated that, in the investigated setting, unplanned HRAs are directly related to nutritional support (p = 0.05) and radiotherapy. On the contrary, BTcP did not significantly affect HRAs. Nevertheless, the correlation between variables showed that when BMI ≥ 25 kg/m2, the spontaneous BTcP is more predictive for HRAs. CONCLUSIONS: Whilst not without limitations, a Bayesian model, combined with a careful selection of clinical variables, can represent a valid strategy for predicting unexpected HRA events in cancer patients. These findings could be useful for calibrating care interventions and implementing processes of resource allocation.

Opioid Misuse: A Review of the Main Issues, Challenges, and Strategies.

In the United States, from 1999 to 2019, opioid overdose, either regularly prescribed or illegally acquired, was the cause of death for nearly 500,000 people. In addition to this pronounced mortality burden that has increased gradually over time, opioid overdose has significant morbidity with severe risks and side effects. As a result, opioid misuse is a cause for concern and is considered an epidemic. This article examines the trends and consequences of the opioid epidemic presented in recent international literature, reflecting on the causes of this phenomenon and the possible strategies to address it. The detailed analysis of 33 international articles highlights numerous impacts in the social, public health, economic, and political spheres. The prescription opioid epidemic is an almost exclusively North American problem. This phenomenon should be carefully evaluated from a healthcare systems perspective, for consequential risks and harms of aggressive opioid prescription practices for pain management. Appropriate policies are required to manage opioid use and prevent abuse efficiently. Examples of proper policies vary, such as the use of validated questionnaires for the early identification of patients at risk of addiction, the effective use of regional and national prescription monitoring programs, and the proper dissemination and translation of knowledge to highlight the risks of prescription opioid abuse.

Different Machine Learning Approaches for Implementing Telehealth-Based Cancer Pain Management Strategies.

Background: The most effective strategy for managing cancer pain remotely should be better defined. There is a need to identify those patients who require increased attention and calibrated follow-up programs. Methods: Machine learning (ML) models were developed using the data prospectively obtained from a single-center program of telemedicine-based cancer pain management. These models included random forest (RF), gradient boosting machine (GBM), artificial neural network (ANN), and the LASSO−RIDGE algorithm. Thirteen demographic, social, clinical, and therapeutic variables were adopted to define the conditions that can affect the number of teleconsultations. After ML validation, the risk analysis for more than one remote consultation was assessed in target individuals. Results: The data from 158 patients were collected. In the training set, the accuracy was about 95% and 98% for ANN and RF, respectively. Nevertheless, the best accuracy on the test set was obtained with RF (70%). The ML-based simulations showed that young age (<55 years), lung cancer, and occurrence of breakthrough cancer pain help to predict the number of remote consultations. Elderly patients (>75 years) with bone metastases may require more telemedicine-based clinical evaluations. Conclusion: ML-based analyses may enable clinicians to identify the best model for predicting the need for more remote consultations. It could be useful for calibrating care interventions and resource allocation.

Satisfaction with Telemedicine for Cancer Pain Management: A Model of Care and Cross-Sectional Patient Satisfaction Study.

Background: Since cancer pain requires complex modalities of care, the proper strategy for addressing its telemedicine-based management should be better defined. This study aimed to trace a pathway for a progressive implementation of the telemedicine process for the treatment of pain in the setting of cancer patients. Methods: The features of the model were investigated to dissect the dropout from the telemedicine pathway. A cross-sectional patient satisfaction study was conducted. The degree of satisfaction was evaluated through a developed 22-item questionnaire (Likert scale 0−7). Results: A total of 375 video consultations for 164 patients (mean age 62.9 years) were performed through remote consultations for cancer pain management between March 2021 and February 2022. After the exclusion of 72 patients, 92 (56.1%) were included in the analysis. The dropout ratio was 8.7%. The number of visits and pharmacological therapies for neuropathic pain correlated with the risk for readmission (p < 0.05). Overall, the satisfaction was very high (mean > 5.5 for all items). Conclusion: Feedback from patients reflected high satisfaction rates with the care provided. A methodological approach based on the degree of satisfaction combined with the analysis of the pathways can help to implement the quality of a service provided through telemedicine. While not without limitations, our hybrid protocol can be useful for addressing cancer pain through a patient-centered approach.

VOSviewer-Based Bibliometric Network Analysis for Evaluating Research on Juvenile Primary Fibromyalgia Syndrome (JPFS).

BACKGROUND: Juvenile primary fibromyalgia syndrome (JPFS) is a chronic musculoskeletal pain syndrome that affects children and adolescents. METHODS: A VOSviewer-based bibliometric network analysis was performed by scanning the global literature on JPFS in the Web of Science (WOS) online database. The search string applied to identify the closest matching articles was "juvenile primary fibromyalgia syndrome (all field)". RESULTS: A total of 67 articles on JPFS were published from 1985 to March 2022, in the WOS. Regarding article types, 39 were research manuscripts, 16 reviews, 8 meeting abstracts, 2 letters, 1 book chapter, 1 correction, and 1 proceeding paper. The Quartile analysis demonstrated that 44% of papers were published in Q1, 37% in Q2, 8% in Q3, and 11% in Q4. CONCLUSIONS: Our analysis highlights that more efforts are warranted to increase the production of quality papers and enhance the connections between the various research groups. JFPS represents a research field still to be explored and which deserves greater investments to obtain quality scientific evidence.

Management of Metastatic Disease in Campania (MAMETIC): An Observational Multicenter Retrospective and Prospective Trial on Palliative Radiotherapy in an Italian Region. Study Protocol.

Background: In the Italian Campania Region, 30.517 new cases of solid cancer have been diagnosed, in 2019. Of those, patients with metastatic disease are up to 20%. This class of patients is extremely diversified and copious, and the offer of radiotherapy may vary in different geographical areas within the same region. The aim of this observational multicenter retrospective and prospective trial is to evaluate the occurrence of metastatic metastatic cancer patients candidates for palliative radiotherapy in several areas of a great Italian region, the management of the disease through RT approaches, and its impact on cancer-related pain and overall HRQoL. Methods: This is a multicenter, retrospective and prospective observational investigation. The retrospective part of the study concerns all patients enrolled with a diagnosis of metastatic disease and treated in RT centers within the Campania Region between January 2019 and July 2020. The prospective phase is going to involve all the metastatic patients with an indication of palliative RT. Considering regional epidemiological data, we expect an enrollment of 12.500-21.000 patients in 5 years. Conclusion: The MAMETIC Trial in an observational study designed for investigating on the use of radiotherapy in patients with advanced disease within a regional area, and for evaluating the local response to the patient's request. It can be a unique opportunity, not only to highlight possible geographic differences but also to regularly collect and share data to standardize the therapeutic offer within the regional area. ClinicalTrials.gov ID NCT04595032, retrospectively registered.