Adverse events related to drug-drug interactions in COVID-19 patients. A persistent concern in the post-pandemic era: a systematic review.

INTRODUCTION: Since COVID-19 patients are often polytreated, monitoring drug-drug interaction (DDIs) is necessary. We evaluated whether drugs used after the second COVID-19 pandemic wave were associated with DDI-related adverse events and the role of drug interaction checkers in identifying them. METHODS: The study (PROSPERO-ID: CRD42024507634) included: 1) consulting the drug interaction checkers Drugs.com, Liverpool COVID-19 Interactions, LexiComp, Medscape, and Micromedex; 2) systematic review; 3) reviewed studies analysis; 4) evaluating drug interaction checkers potential to anticipate DDI-related adverse events.The systematic review was performed searching PubMed, Scopus, ScienceDirect, and Cochrane databases from 1 March 2022 to 11 November 2023. Observational studies, and clinical trials were included. Article without reporting direct association between DDIs and adverse events were excluded. The risk of bias was assessed by Newcastle-Ottawa scale. RESULTS: The most frequent DDIs involved nirmatrelvir/ritonavir (N/R) and fluvoxamine. Fifteen studies, including 150 patients and 35 DDI-related outcomes, were analyzed. The most frequent DDIs involved tacrolimus with N/R, resulting in creatinine increase.Eighty percent of reported DDI-related adverse events would have been identified by all drug-interaction checkers, while the remaining 20% by at least 2 of them. CONCLUSIONS: Drug interaction checkers are useful but show inconsistencies. Multiple sources are needed to tailor treatment in the context of COVID-19.

Predictive significance of FGFR4 p.G388R polymorphism in metastatic colorectal cancer patients receiving trifluridine/tipiracil (TAS-102) treatment.

BACKGROUND: TAS-102 (Lonsurf®) is an oral fluoropyrimidine consisting of a combination of trifluridine (a thymidine analog) and tipiracil (a thymidine phosphorylation inhibitor). The drug is effective in metastatic colorectal cancer (mCRC) patients refractory to fluorouracil, irinotecan and oxaliplatin. This study is a real-world analysis, investigating the interplay of genotype/phenotype in relation to TAS-102 sensitivity. METHODS: Forty-seven consecutive mCRC patients were treated with TAS-102 at the National Cancer Institute of Naples from March 2019 to March 2021, at a dosage of 35 mg/m2, twice a day, in cycles of 28 days (from day 1 to 5 and from day 8 to 12). Clinical-pathological parameters were described. Activity was evaluated with RECIST criteria (v1.1) and toxicity with NCI-CTC (v5.0). Survival was depicted through the Kaplan-Meyer curves. Genetic features of patients were evaluated with Next Generation Sequencing (NGS) through the Illumina NovaSeq 6000 platform and TruSigt™Oncology 500 kit. RESULTS: Median age of patients was 65 years (range: 46-77). Forty-one patients had 2 or more metastatic sites and 38 patients underwent to more than 2 previous lines of therapies. ECOG (Eastern Cooperative Oncology Group) Performance Status (PS) was 2 in 19 patients. The median number of TAS-102 cycles was 4 (range: 2-12). The most frequent toxic event was neutropenia (G3/G4 in 16 patients). There were no severe (> 3) non-haematological toxicities or treatment-related deaths. Twenty-six patients experienced progressive disease (PD), 21 stable disease (SD). Three patients with long-lasting disease control (DC: complete, partial responses or stable disease) shared an FGFR4 (p.Gly388Arg) mutation. Patients experiencing DC had more frequently a low tumour growth rate (P = 0.0306) and an FGFR4 p.G388R variant (P < 0.0001). The FGFR4 Arg388 genotype was associated with better survival (median: 6.4 months) compared to the Gly388 genotype (median: 4 months); the HR was 0.25 (95% CI 0.12- 0.51; P = 0.0001 at Log-Rank test). CONCLUSIONS: This phenotype/genotype investigation suggests that the FGFR4 p.G388R variant may serve as a new marker for identifying patients who are responsive to TAS-102. A mechanistic hypothesis is proposed to interpret these findings.

Two-year Opioid Prescription Trends in Local Sanitary Agency Naples 3 South, Campania Region, Italy. Descriptive Analyses and AI-based Translational Perspectives.

Aims: This study delves into the two-year opioid prescription trends in the Local Sanitary Agency Naples 3 South, Campania Region, Italy. The research aims to elucidate prescribing patterns, demographics, and dosage categories within a population representing 1.7% of the national total. Perspectives on artificial intelligence research are discussed. Methods: From the original dataset, spanning from January 2022 to October 2023, we processed multiple variables including demographic data, medications, dosages, drug consumption, and administration routes. The dispensing quantity was calculated as defined daily doses (DDD). Results: The analysis reveals a conservative approach to opioid therapy. In subjects under the age of 20, prescriptions accounted for 2.1% in 2022 and declined to 1.4% in 2023. The drug combination paracetamol/codeine was the most frequently prescribed, followed by tapentadol. Approximately two-thirds of the consumption pertains to oral formulations. Transdermal formulations were 15% (fentanyl 9.8%, buprenorphine 5.1%) in 2022; and 16.6% (fentanyl 10%, buprenorphine 6.6%) in 2023. These data were confirmed by the DDD analysis. The trend analysis demonstrated a significant reduction ( p < 0.001) in the number of prescribed opioids from 2022 to 2023 in adults (40-69 years). The study of rapid-onset opioids (ROOs), drugs specifically used for breakthrough cancer pain, showed higher dosage (>267 mcg) consumption among women, whereas a lower dosage (<133 mcg) was calculated for men. Fentanyl pectin nasal spray accounted for approximately one-fifth of all ROOs. Conclusion: Despite limitations, the study provides valuable insights into prescribing practices involving an important study population. The findings underscore the need for tailored approaches to prescribing practices, recognizing the complexities of pain management in different contexts. This research can contribute to the ongoing discourse on opioid use, advocating for innovative strategies that optimize therapeutic outcomes while mitigating potential risks.

Algor-ethics: charting the ethical path for AI in critical care.

The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particularly in critical care, where physicians often deal with life-threating conditions requiring rapid actions and patients unable to participate in the decisional process. Moreover, development of AI-based CDSS is complex and should address different sources of bias, including data acquisition, health disparities, domain shifts during clinical use, and cognitive biases in decision-making. In this scenario algor-ethics is mandatory and emphasizes the integration of 'Human-in-the-Loop' and 'Algorithmic Stewardship' principles, and the benefits of advanced data engineering. The establishment of Clinical AI Departments (CAID) is necessary to lead AI innovation in healthcare, ensuring ethical integrity and human-centered development in this rapidly evolving field.

Translational Insights in the Landscape of Salivary Gland Cancers: Ready for a New Era?

Salivary gland carcinomas (SGCs) are rare neoplasms, representing less than 10% of all head and neck tumors, but they are extremely heterogeneous from the histological point of view, their clinical behavior, and their genetics. The guidelines regarding their treatment include surgery in most cases, which can also play an important role in oligometastatic disease. Where surgery cannot be used, systemic therapy comes into play. Systemic therapy for many years has been represented by polychemotherapy, but recently, with the affirmation of translational research, it can also count on targeted therapy, at least in some subtypes of SGCs. Interestingly, in some SGC histotypes, predominant mutations have been identified, which in some cases behave as "driver mutations", namely mutations capable of governing the carcinogenesis process. Targeting these driver mutations may be an effective therapeutic strategy. Nonetheless, it is not always possible to have drugs suitable for targeting driver mutations-and targeting driver mutations is not always accompanied by a clinical benefit. In this review, we will analyze the main mutations predominant in the various histotypes of SGCs.

rs822336 binding to C/EBPß and NFIC modulates induction of PD-L1 expression and predicts anti-PD-1/PD-L1 therapy in advanced NSCLC.

Efficient predictive biomarkers are needed for immune checkpoint inhibitor (ICI)-based immunotherapy in non-small cell lung cancer (NSCLC). Testing the predictive value of single nucleotide polymorphisms (SNPs) in programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown contrasting results. Here, we aim to validate the predictive value of PD-L1 SNPs in advanced NSCLC patients treated with ICIs as well as to define the molecular mechanisms underlying the role of the identified SNP candidate. rs822336 efficiently predicted response to anti-PD-1/PD-L1 immunotherapy in advanced non-oncogene addicted NSCLC patients as compared to rs2282055 and rs4143815. rs822336 mapped to the promoter/enhancer region of PD-L1, differentially affecting the induction of PD-L1 expression in human NSCLC cell lines as well as their susceptibility to HLA class I antigen matched PBMCs incubated with anti-PD-1 monoclonal antibody nivolumab. The induction of PD-L1 expression by rs822336 was mediated by a competitive allele-specificity binding of two identified transcription factors: C/EBPß and NFIC. As a result, silencing of C/EBPß and NFIC differentially regulated the induction of PD-L1 expression in human NSCLC cell lines carrying different rs822336 genotypes. Analysis by binding microarray further validated the competitive allele-specificity binding of C/EBPß and NFIC to PD-L1 promoter/enhancer region based on rs822336 genotype in human NSCLC cell lines. These findings have high clinical relevance since identify rs822336 and induction of PD-L1 expression as novel biomarkers for predicting anti-PD-1/PD-L1-based immunotherapy in advanced NSCLC patients.

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.

The Breakthrough of Large Language Models Release for Medical Applications: 1-Year Timeline and Perspectives.

Within the domain of Natural Language Processing (NLP), Large Language Models (LLMs) represent sophisticated models engineered to comprehend, generate, and manipulate text resembling human language on an extensive scale. They are transformer-based deep learning architectures, obtained through the scaling of model size, pretraining of corpora, and computational resources. The potential healthcare applications of these models primarily involve chatbots and interaction systems for clinical documentation management, and medical literature summarization (Biomedical NLP). The challenge in this field lies in the research for applications in diagnostic and clinical decision support, as well as patient triage. Therefore, LLMs can be used for multiple tasks within patient care, research, and education. Throughout 2023, there has been an escalation in the release of LLMs, some of which are applicable in the healthcare domain. This remarkable output is largely the effect of the customization of pre-trained models for applications like chatbots, virtual assistants, or any system requiring human-like conversational engagement. As healthcare professionals, we recognize the imperative to stay at the forefront of knowledge. However, keeping abreast of the rapid evolution of this technology is practically unattainable, and, above all, understanding its potential applications and limitations remains a subject of ongoing debate. Consequently, this article aims to provide a succinct overview of the recently released LLMs, emphasizing their potential use in the field of medicine. Perspectives for a more extensive range of safe and effective applications are also discussed. The upcoming evolutionary leap involves the transition from an AI-powered model primarily designed for answering medical questions to a more versatile and practical tool for healthcare providers such as generalist biomedical AI systems for multimodal-based calibrated decision-making processes. On the other hand, the development of more accurate virtual clinical partners could enhance patient engagement, offering personalized support, and improving chronic disease management.

Ethical issues in pain and palliation.

PURPOSE OF REVIEW: Increased public awareness of ethical issues in pain and palliative care, along with patient advocacy groups, put pressure on healthcare systems and professionals to address these concerns.Our aim is to review the ethics dilemmas concerning palliative care in ICU, artificial intelligence applications in pain therapy and palliative care, and the opioids epidemics. RECENT FINDINGS: In this focus review, we highlighted state of the art papers that were published in the last 18 months, on ethical issues in palliative care within the ICU, artificial intelligence trajectories, and how opioids epidemics has impacted pain management practices (see Visual Abstract). SUMMARY: Palliative care in the ICU should involve a multidisciplinary team, to mitigate patients suffering and futility. Providing spiritual support in the ICU is an important aspect of holistic patient care too.Increasingly sophisticated tools for diagnosing and treating pain, as those involving artificial intelligence, might favour disparities in access, cause informed consent problems, and surely, they need prudence and reproducibility.Pain clinicians worldwide continue to face the ethical dilemma of prescribing opioids for patients with chronic noncancer pain. Balancing the need for effective pain relief with the risk of opioid misuse, addiction, and overdose is a very controversial task.

Between human and AI: assessing the reliability of AI text detection tools.

OBJECTIVE: Large language models (LLMs) such as ChatGPT-4 have raised critical questions regarding their distinguishability from human-generated content. In this research, we evaluated the effectiveness of online detection tools in identifying ChatGPT-4 vs human-written text. METHODS: A two texts produced by ChatGPT-4 using differing prompts and one text created by a human author were analytically assessed using the following online detection tools: GPTZero, ZeroGPT, Writer ACD, and Originality. RESULTS: The findings revealed a notable variance in the detection capabilities of the employed detection tools. GPTZero and ZeroGPT exhibited inconsistent assessments regarding the AI-origin of the texts. Writer ACD predominantly identified texts as human-written, whereas Originality consistently recognized the AI-generated content in both samples from ChatGPT-4. This highlights Originality's enhanced sensitivity to patterns characteristic of AI-generated text. CONCLUSION: The study demonstrates that while automatic detection tools may discern texts generated by ChatGPT-4 significant variability exists in their accuracy. Undoubtedly, there is an urgent need for advanced detection tools to ensure the authenticity and integrity of content, especially in scientific and academic research. However, our findings underscore an urgent need for more refined detection methodologies to prevent the misdetection of human-written content as AI-generated and vice versa.

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.

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.

Emerging treatment approaches for triple-negative breast cancer.

Approximately, 15% of global breast cancer cases are diagnosed as triple-negative breast cancer (TNBC), identified as the most aggressive subtype due to the simultaneous absence of estrogen receptor, progesterone receptor, and HER2. This characteristic renders TNBC highly aggressive and challenging to treat, as it excludes the use of effective drugs such as hormone therapy and anti-HER2 agents. In this review, we explore standard therapies and recent emerging approaches for TNBC, including PARP inhibitors, immune checkpoint inhibitors, PI3K/AKT pathway inhibitors, and cytotoxin-conjugated antibodies. The mechanism of action of these drugs and their utilization in clinical practice is explained in a pragmatic and prospective manner, contextualized within the current landscape of standard therapies for this pathology. These advancements present a promising frontier for tailored interventions with the potential to significantly improve outcomes for TNBC patients. Interestingly, while TNBC poses a complex challenge, it also serves as a paradigm and an opportunity for translational research and innovative therapies in the field of oncology.

Evaluating Nutritional Risk Factors for Delirium in Intensive-Care-Unit Patients: Present Insights and Prospects for Future Research.

Malnutrition, hypercatabolism, and metabolic changes are well-established risk factors for delirium in critically ill patients. Although the exact mechanisms are not fully understood, there is mounting evidence suggesting that malnutrition can cause a variety of changes that contribute to delirium, such as electrolyte imbalances, immune dysfunction, and alterations in drug metabolism. Therefore, a comprehensive metabolic and malnutrition assessment, along with appropriate nutritional support, may help to prevent or ameliorate malnutrition, reduce hypercatabolism, and improve overall physiological function, ultimately lowering the risk of delirium. For this aim, bioelectrical impedance analysis can represent a valuable strategy. Further research into the underlying mechanisms and nutritional risk factors for delirium is crucial to developing more effective prevention strategies. Understanding these processes will allow clinicians to personalize treatment plans for individual patients, leading to improved outcomes and quality of life in the intensive-care-unit survivors.

Prior Anti-Angiogenic TKI-Based Treatment as Potential Predisposing Factor to Nivolumab-Mediated Recurrent Thyroid Disorder Adverse Events in mRCC Patients: A Case Series.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) have revolutionized the management of many types of solid tumors, including metastatic renal cell carcinoma (mRCC). Both sequential and combinatorial therapeutic strategies utilizing anti-PD-1 monoclonal antibodies (mAbs) and anti-angiogenic tyrosine kinase inhibitors (TKIs) have demonstrated to improve the survival of patients with mRCC as compared to standard therapies. On the other hand, both ICIs and TKIs are well known to potentially cause thyroid disorder adverse events (TDAEs). However, in the context of sequential therapeutic strategy, it is not clear whether prior anti-angiogenic TKI may increase the risk and/or the severity of ICI-related TDAEs. In this work, by describing and analyzing a case series of mRCC patients treated sequentially with prior TKIs and then with ICIs, we investigated the role of prior anti-angiogenic TKI-based treatment as a potential predisposing factor to anti-PD-1-mediated recurrent TDAEs, as well as its potential impact on the clinical characteristics of nivolumab-mediated recurrent TDAEs. Fifty mRCC patients were included in the analysis. TKI-mediated TDAEs were reported in ten out of fifty patients. TKI-mediated TDAEs were characterized by hypothyroidism in all ten patients. Specifically, 40%, 40% and 20% of patients presented grade 1, 2 and 3 hypothyroidisms, respectively. Following tumor progression and during anti-PD-1 nivolumab treatment, five out of ten patients developed anti-PD-1 nivolumab-mediated recurrent TDAEs. Anti-PD-1 nivolumab-mediated recurrent TDAEs were characterized by an early transient phase of thyrotoxicosis and a late phase of hypothyroidism in all five patients. The TDAEs were grade 1 and 2 in four and one patients, respectively. Prior anti-angiogenic TKI did not modify the clinical characteristics of nivolumab-mediated recurrent TDAEs. However, all five patients required an increased dosage of levothyroxine replacement therapy. In conclusion, our work suggests that prior anti-angiogenic TKI-based treatment significantly increases the risk of ICI-mediated recurrent TDAEs in patients with mRCC without modifying their clinical characteristics. The most relevant effect for these patients is the need to increase the dosage of lifelong levothyroxine replacement therapy.

Beyond Body Size: Adiponectin as a Key Player in Obesity-Driven Cancers.

Obesity, a complex and multifactorial disease influenced by genetic, environmental, and psychological factors, has reached epidemic proportions globally, posing a significant health challenge. In addition to its established association with cardiovascular disease and type II diabetes, obesity has been implicated as a risk factor for various cancers. However, the precise biological mechanisms linking obesity and cancer remain largely understood. Adipose tissue, an active endocrine organ, produces numerous hormones and bioactive molecules known as adipokines, which play a crucial role in metabolism, immune responses, and systemic inflammation. Notably, adiponectin (APN), the principal adipocyte secretory protein, exhibits reduced expression levels in obesity. In this scoping review, we explore and discuss the role of APN in influencing cancer in common malignancies, including lung, breast, colorectal, prostate, gastric, and endometrial cancers. Our review aims to emphasize the critical significance of investigating this field, as it holds great potential for the development of innovative treatment strategies that specifically target obesity-related malignancies. Furthermore, the implementation of more rigorous and comprehensive prevention and treatment policies for obesity is imperative in order to effectively mitigate the risk of associated diseases, such as cancer.