Bibliometric Network Analysis on Rapid-Onset Opioids for Breakthrough Cancer Pain Treatment

Incorporation of "Artificial Intelligence" for Objective Pain Assessment: A Comprehensive Review

Pain is a significant health issue, and pain assessment is essential for proper diagnosis, follow-up, and effective management of pain. The conventional methods of pain assessment often suffer from subjectivity and variability. The main issue is to understand better how people experience pain. In recent years, artificial intelligence (AI) has been playing a growing role in improving clinical diagnosis and decision-making. The application of AI offers promising opportunities to improve the accuracy and efficiency of pain assessment. This review article provides an overview of the current state of AI in pain assessment and explores its potential for improving accuracy, efficiency, and personalized care. By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.

Bridging knowledge gaps: a bibliometric analysis of non-invasive ventilation in palliative care studies

BACKGROUND

Despite being a useful strategy for providing respiratory support to patients with advanced or terminal illnesses, non-invasive ventilation (NIV) requires in-depth investigation in several key aspects.

OBJECTIVES

This bibliometric analysis seeks to comprehensively examine the existing research on the subject. Its goal is to uncover valuable insights that can inform the prediction trajectory of studies, guide the implementation of corrective measures, and contribute to the improvement of research networks.

METHODS

A comprehensive review of literature on NIV in the context of palliative care was conducted using the Web of Science core collection online database. The search utilized the key terms "non-invasive ventilation" and "palliative care" to identify the most relevant articles. All data were gathered on November 7, 2023. Relevant information from documents meeting the specified criteria was extracted, and Journal Citation Reports™ 2022 (Clarivate Analytics) served as the data source. The analysis employed literature analysis and knowledge visualization tools, specifically CiteScope (version 6.2.R4) and VOSviewer (version 1.6.20).

RESULTS

A dataset with bibliometric findings from 192 items was analyzed. We found a consistent upward of the scientific output trend over time. Guidelines on amyotrophic lateral sclerosis management received the highest number of citations. Most documents were published in top-ranked journals. Less than one-third of the documents pertain to clinical studies, especially retrospective analyses (25%). Key topics such as "decision making", and "communication" were less addressed.

CONCLUSIONS

Given the substantial clinical implications, further high-quality studies on this subject are recommended. Encouraging international collaborations is needed. Despite the growing volume of documents in the field, this bibliometric analysis indicates a decline in collaborative networks.

Cost-Effectiveness and Cost-Utility Analyses in Thailand of Continuous Intrathecal Morphine Infusion Compared with Conventional Therapy in Cancer Pain: A 10-year Multicenter Retrospective Study

Background

Because of the high initial cost of intrathecal drug delivery (ITDD) therapy, this study investigated the cost-effectiveness and cost-utility of ITDD therapy in refractory cancer pain management in Thailand over the past 10 years.

Methods

The retrospective study was conducted in patients with cancer pain who underwent ITDD therapy from January 2011 to 2021 at three university hospitals. Clinical outcomes included the numerical rating scale (NRS), Palliative Performance Scale, and the EQ-5D. The direct medical and nonmedical as well as indirect costs were also recorded. Cost-effectiveness and cost-utility analyses were performed comparing ITDD therapy with conventional therapy (extrapolated from costs of the same patient before ITDD therapy) from a societally oriented economic evaluation.

Results

Twenty patients (F:M: 10:10) aged 60 ± 15 years who underwent implantation of an intrathecal percutaneous port (IT port; n = 15) or programmable intrathecal pump (IT pump; n = 5) were included. The median survival time was 78 (interquartile range = 121-54) days after ITDD therapy. At 2-month follow-up, the incremental cost-effectiveness ratio (ICER)/pain reduction of an IT port (US$2065.36 (CA$2829.54)/2-point NRS reduction/lifetime) was lower than for patients with an IT pump (US$5479.26 (CA$7506.58)/2-point NRS reduction/lifetime) compared with continued conventional therapy. The ICER/quality-adjusted life years (QALYs) gained for an IT port compared with conventional treatment was US$93,999.31(CA$128,799.06)/QALY gained, which is above the cost-effectiveness threshold for Thailand.

Conclusion

The cost-effectiveness and cost-utility of IT port therapy for cancer pain was high relative to the cost of living in Thailand, above the cost-effectiveness threshold. Prospective cost analysis studies enrolling more patients with diverse cancers that investigate the benefit of early ITDD therapy with devices over a range of prices are warranted.

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.

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.

The Clinical Researcher Journey in the Artificial Intelligence Era: The PAC-MAN’s Challenge

Artificial intelligence (AI) is a powerful tool that can assist researchers and clinicians in various settings. However, like any technology, it must be used with caution and awareness as there are numerous potential pitfalls. To provide a creative analogy, we have likened research to the PAC-MAN classic arcade video game. Just as the protagonist of the game is constantly seeking data, researchers are constantly seeking information that must be acquired and managed within the constraints of the research rules. In our analogy, the obstacles that researchers face are represented by “ghosts”, which symbolize major ethical concerns, low-quality data, legal issues, and educational challenges. In short, clinical researchers need to meticulously collect and analyze data from various sources, often navigating through intricate and nuanced challenges to ensure that the data they obtain are both precise and pertinent to their research inquiry. Reflecting on this analogy can foster a deeper comprehension of the significance of employing AI and other powerful technologies with heightened awareness and attentiveness.

Thirty-year survey of bibliometrics used in the research literature of pain: Analysis, evolution, and pitfalls

During the last decades, the emergence of Bibliometrics and the progress in Pain research have led to a proliferation of bibliometric studies on the medical and scientific literature of pain (B/P). This study charts the evolution of the B/P literature published during the last 30 years. Using various searching techniques, 189 B/P studies published from 1993 to August 2022 were collected for analysis-half were published since 2018. Most of the selected B/P publications use classic bibliometric analysis of Pain in toto, while some focus on specific types of Pain with Headache/Migraine, Low Back Pain, Chronic Pain, and Cancer Pain dominating. Each study is characterized by the origin (geographical, economical, institutional, …) and the medical/scientific context over a specified time span to provide a detailed landscape of the Pain research literature. Some B/P studies have been developed to pinpoint difficulties in appropriately identifying the Pain literature or to highlight some general publishing pitfalls. Having observed that most of the recent B/P studies have integrated newly emergent software visualization tools (SVTs), we found an increase of anomalies and suggest that readers exercise caution when interpreting results in the B/P literature details.

Bibliometric and Visual Analysis of the Scientific Literature on Percutaneous Electrical Nerve Stimulation (PENS) for Pain Treatment

Background: Percutaneous electrical nerve stimulation (PENS) is a minimally invasive peripheral neuromodulation approach implemented against chronic neuropathic and mixed pain. This bibliometric study aims to quantitatively evaluate the output of PENS for pain treatment in the scientific literature. The main purpose is to stimulate research in the field and bridge potential scientific gaps. Methods: Articles were retrieved from the Web of Science (WOS) database. The search key term was “percutaneous electrical nerve stimulation (All Fields) and pain (All Fields)”. Year of publication, journal metrics (impact factor and quartile, Q), title, document type, topic, and citations were extracted. The join-point regression was implemented to assess differences in time points for the publication output. The software tool VOSviewer (version 1.6.17) was used for the visual analysis. Results: One thousand three hundred and eighteen articles were included in the knowledge visualization process. A linear upward trend for annual new publications was found. Almost two-thirds of the documents were published in top-ranked journals (Q1 and Q2). The topic “efficacy” was prevalent (12.81%). Concerning article type, the search strategy yielded 307 clinical investigations (23.3%). Articles were cited 36,610 times with a mean of 42.4 citations per article. Approximately one-half of the articles were cited less than 23 times in a range of 21 years. The semantic network analysis for keywords found eight clusters. The analysis of collaborative efforts among researchers showed five thematic clusters including 102 authors with a minimum of five documents produced in collaborations. Most partnerships involved the United States, England, and Germany. Conclusions: despite the upward trend in the number of publications on the subject and the publication of articles in top-ranked journals, there is a need to increase scientific collaborations between researchers and institutions from different countries.

Multidisciplinary approach, continuous care and opioid management in cancer pain: case series and review of the literature

Underlying cancer pain has heterogenous aetiologies and mechanisms. It requires detailed and comprehensive pain assessment, combined with personalized treatment. A multidisciplinary team is essential to providing the best management of cancer pain at every disease stage, improving the quality of life and outcomes in patients with cancer. This narrative literature review emphasizes the value of providing all patients with multidisciplinary pain management in their preferred care setting. Real-life experiences are also reported to witness the efforts of physicians to properly manage cancer pain. This article is part of the Management of breakthrough cancer pain Special Issue: https://www.drugsincontext.com/special_issues/management-of-breakthrough-cancer-pain.

Current status of cervical cancer brachytherapy technologies: scientometric analysis

Background. Brachytherapy is an important component of cervical cancer (CC) treatment paradigm, so scientometric studies in this area are very relevant. Purpose – to assess the current state and development trends of cervical cancer brachytherapy te chnologies through a scientometric analysis of scientific publications. Materials and methods. Uses the scientometric method of document analysis. The analysis was carried out using the Scopus digital resource for the period 2012–2022. Evaluation of the found documents was carried out according to the following indicators: dynamics of publications, country, author of the publication, publication institution, source and sponsor who financed the work. Results. Based on the results of the study, 694 documents were found, the distribution of which determines the growth of publications in 2016 (71 documents), 2018 (84 documents), and 2021 (86 documents). The distribution by country made it possible to establish the United States as the leader, followed by India, Japan, France, China. Over the past 5 years, China has moved from fifth place to second, which it shares with India. Among the institutions involved in the development of cervical cancer brachytherapy technologies, Med. University Wien, Austria, Tata Memorial Hospital, India, Institut de Cacy Cackologie Gustave Roussy, France. The most active scientists were singled out: Pötter R., Haie-Meder C., Mahantshetty U., and Tanderup K. Mahantshetty U., Tanderup K. International scientific communications of scientists have been established to address issues of improving the methods of gynecological brachytherapy, in particular cervical cancer, as well as active sponsors. The main scientific sources on the subject of cervical cancer brachytherapy are the journal «Brachytherapy». Conclusion. An assessment of the current state and development trends of cervical cancer brachytherapy technologies is given, leading countries, organizations, and scientists involved in the development of new most effective brachytherapy technologies are identified, 20 most cited publications and 5 most cited scientists involved in the development of cervical cancer brachytherapy issues are revealed.

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.

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.