Pharmacological Treatments and Therapeutic Drug Monitoring in Patients with Chronic Pain

Opioid Monitoring in Clinical Settings: Strategies and Implications of Tailored Approaches for Therapy

This review emphasises the importance of opioid monitoring in clinical practice and advocates for a personalised approach based on pharmacogenetics. Beyond effectively managing pain, meticulous oversight is required to address concerns about side effects, specially due to opioid-crisis-related abuse and dependence. Various monitoring techniques, along with pharmacogenetic considerations, are critical for personalising treatment and optimising pain relief while reducing misuse and addiction risks. Future perspectives reveal both opportunities and challenges, with advances in analytical technologies holding promise for increasing monitoring efficiency. The integration of pharmacogenetics has the potential to transform pain management by allowing for a precise prediction of drug responses. Nevertheless, challenges such as prominent pharmacogenetic testing and guideline standardisation persist. Collaborative efforts are critical for transforming scientific advances into tangible improvements in patient care. Standardised protocols and interdisciplinary collaboration are required to ensure consistent and evidence-based opioid monitoring. Future research should look into the long-term effects of opioid therapy, as well as the impact of genetic factors on individual responses, to help guide personalised treatment plans and reduce adverse events. Lastly, embracing innovation and collaboration can improve the standard of care in chronic pain management by striking a balance between pain relief and patient safety.

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.

Causal effects and immune cell mediators between prescription analgesic use and risk of infectious diseases: a Mendelian randomization study

Introduction

Clinical observations have found that prolonged use of analgesics increases the incidence of infection. However, the direct causal relationship between prescription analgesic use (PAU) and risk of infection (ROI) remains unclear.

Methods

This study used Mendelian randomization (MR) design to estimate the causal effect of PAU on ROI, as well as their mediating factors. Genetic data on prescription analgesics use and immune cells were obtained from published GWAS. Additionally, data on ROI were extracted from the FinnGen database. Two-sample MR analysis and multivariate MR (MVMR) analysis were performed using inverse variance weighting (IVW) to ascertain the causal association between PAU and ROI. Finally, 731 immune cell phenotypes were analyzed for their mediating role between analgesics and infection.

Results

Using two-sample MR, IVW modeling showed that genetically predicted opioid use was associated with increased risk of pulmonary infection (PI) (OR = 1.13, 95% CI: 1.05-1.21, p< 0.001) and upper respiratory infection (URI) (OR = 1.18, 95% CI: 1.08-1.30, p< 0.001); non-steroidal anti-inflammatory drugs (NSAIDs) were related to increased risk of skin and subcutaneous tissue infection (OR = 1.21, 95% CI: 1.05-1.39, p = 0.007), and antimigraine preparations were linked to a reduced risk of virus hepatitis (OR = 0.79, 95% CI: 0.69-0.91, p< 0.001). In MVMR, the association of opioids with URI and PI remained after accounting for cancer conditions. Even with a stricter threshold (p< 0.05/30), we found a significant causal association between opioids and respiratory infections (URI/PI). Finally, mediation analyses found that analgesics influence the ROI through different phenotypes of immune cells as mediators.

Conclusion

This MR study provides new genetic evidence for the causal relationship between PAU and ROI, and the mediating role of immune cells was demonstrated.