Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)

Trends in co-prescribed opioids and benzodiazepines, non-prescribed opioids and benzodiazepines, and schedule-I drugs in the United States, 2013 to 2019

Concurrent opioid and benzodiazepine users are at increased risk of overdose death, compared to opioid-only users. The objective of this study was to understand recent time trends in opioid and benzodiazepine concurrent use, misuse, and schedule-I drug use, and how these differ by age, sex and geographic region. Commercial, United States medical insurance claims data and urine drug test results from 2013 to 2019 were used to study the outcomes of concurrent use (n = 756,258), schedule-I drug use (n = 746,672) and prescription misuse (n = 452,523). Drug use outcomes were studied at quarterly time points for each year. Data analysis included joinpoint regression models to estimate quarterly drug use rates, determined by positive urine tests for corresponding drug categories, and was conducted from November 2021 through January 2022. Concurrent use decreased from 19.3% to 9.8%, misuse generally decreased from 75.6% to 55.1%, and schedule-I use increased from 8.9% to 13.8%, from 2013 to 2019. Concurrent use decreased at greater rates after 2016, after the Centers for Disease Control and Food and Drug Administration guidelines against concurrent use were released, while schedule-I use increased, notably after the 2014 hydrocodone reschedule. This indicates a potential shift from prescription use to non-prescribed drug use, where most affected groups included males, younger individuals, and those residing in Northeastern regions. Study results support public health initiatives focused on policy that increases access to multimodal pain management and substance use disorder management programs-critical steps in preventing patients from seeking non-prescribed drugs for self- medicating due to pain or addiction.

Adverse Drug Reactions to Opioids: A Study in a National Pharmacovigilance Database

INTRODUCTION

Opioids are commonly used as analgesics; however, like any medicine, they can produce adverse drug reactions (ADRs), including nausea, constipation, dependence, and respiratory depression, that result in harmful and fatal events. Therefore, it is essential to monitor the safety of these drugs in clinical practice.

OBJECTIVE

This study aimed to characterize the safety profile of opioids by conducting a descriptive study based on a spontaneous reporting system (SRS) for ADRs in The Netherlands, focusing on abuse, misuse, medication errors, and differences between sexes.

METHODS

Reports submitted to the Netherlands Pharmacovigilance Centre Lareb from January 2003 to December 2021 with an opioid drug as the suspected/interacting medicine were analyzed. Reporting odds ratios (RORs) for drug-ADR combinations were calculated, analyzed, and corrected for sex and drug utilization (expenditure) for the Dutch population.

RESULTS

A total of 8769 reports were analyzed. Tramadol was the opioid with the most reports during the period (n = 2746), while oxycodone or tramadol had the highest number of reports per year in the study period. The most reported ADRs from opioid use were nausea, followed by dizziness and vomiting, independent of sex, and all of them were more often reported in women. Vomiting associated with tramadol (ROR females/males = 2.17) was significantly higher in women. Buprenorphine was responsible for most ADRs when corrected for expenditure, with high RORs observed with application site hypersensitivity, application site reaction, and application site rash. Fentanyl gave rise to most of the reports of ADRs concerning abuse, misuse, and medication errors.

CONCLUSION

Patients treated with opioids experienced ADRs, primarily nausea, dizziness, and vomiting. For those groups of drugs, no significant differences were found between the sexes, except for the vomiting associated with tramadol. In general, ADRs related to opioids presented higher RORs when uncorrected and corrected for sexes and expenditure than other drugs. There was more disproportionate reporting for ADRs concerning abuse, misuse, and medication errors for opioids than other drugs in the Dutch SRS.

Effect of oxycodone combined with ultrasound-guided thoracic paravertebral nerve block on postoperative analgesia in patients with lung cancer undergoing thoracoscopic surgery: protocol for a randomised controlled study

INTRODUCTION

Postoperative pain is a main component influencing the recovery of patients with lung cancer. The combination of patient-controlled intravenous analgesia (PCIA) and paravertebral nerve block for postoperative analgesia in patients undergoing thoracoscopic lobectomy for lung cancer can achieve a satisfactory analgesic effect and promote early rehabilitation of patients. The objective is to investigate the optimal dose of oxycodone for PCIA combined with paravertebral nerve block, to achieve effective multimodal analgesia management in patients undergoing thoracoscopic lung cancer lobectomy.

METHODS AND ANALYSIS

This prospective, double-blind, single-centre, parallel-group, superiority study from 7 April 2023 to 31 December 2024 will include 160 participants scheduled for thoracoscopic lobectomy for lung cancer. Participants will be randomly assigned to four groups in a 1:1:1:1 ratio: OCA group (oxycodone: 0.5 mg/kg), OCB group (oxycodone: 1.0 mg/kg), OCC group (oxycodone: 1.5 mg/kg) and one sufentanil group (sufentanil: 2 µg/kg). Flurbiprofen 50 mg and ondansetron 16 mg are added to each group. All the drugs are diluted with 0.9% saline in a 100 mL volume, with a background infusion rate of 2 mL/hour, a bolus dose of 0.5 mL and a lockout interval of 15 min. The primary outcome is pain scores at rest and dynamic at 24 hours after surgery using a Numeric Rating Scale (NRS). Dynamic NRS scores are defined as NRS when coughing. NRS scores will be assessed at 2, 4, 12, 24 and 48 hours postoperatively. The secondary outcomes include the following variables: (1) NRS score at rest and dynamic at 2, 4, 12 and 48 hours postoperatively; (2) total dose of sufentanil or oxycodone consumption in PCIA; (3) the times of patient-controlled analgesia; (4) Ramsay Sedation Score (RSS) at 2, 4, 12, 24 and 48 hours after the surgery; (5) extubation time; (6) serum C-reactive protein and interleukin six levels; (7) incidence of postoperative nausea and vomiting; (8) incidence of itching; (9) incidence of respiratory depression and (10) gastrointestinal recovery (exhaust time).

ETHICS AND DISSEMINATION

The First Affiliated Hospital of Shandong First Medical University's Ethics Committee granted consent for this study (approval number: YXLL-KY-2022(116)). To enable widespread use of the data gathered, we plan to publish the trial's findings in an appropriate scientific journal after it is complete.

TRIAL REGISTRATION NUMBER

NCT05742256.

Is There a Risk for Semaglutide Misuse? Focus on the Food and Drug Administration's FDA Adverse Events Reporting System (FAERS) Pharmacovigilance Dataset

Recent media reports commented about a possible issue of the misuse of antidiabetics related to molecules promoted as a weight-loss treatment in non-obese people. We evaluated here available pharmacovigilance misuse/abuse signals related to semaglutide, a glucagon-like peptide-1 (GLP-1) analogue, in comparison to other GLP-1 receptor agonists (albiglutide, dulaglutide, exenatide, liraglutide, lixisenatide, and tirzepatide) and the phentermine-topiramate combination. To acheieve that aim, we analyzed the Food and Drug Administration's FDA Adverse Events Reporting System (FAERS) dataset, performing a descriptive analysis of adverse event reports (AERs) and calculating related pharmacovigilance measures, including the reporting odds ratio (ROR) and the proportional reporting ratio (PRR). During January 2018-December 2022, a total of 31,542 AERs involving the selected molecules were submitted to FAERS; most involved dulaglutide (n = 11,858; 37.6%) and semaglutide (n = 8249; 26.1%). In comparing semaglutide vs. the remaining molecules, the respective PRR values of the AERs 'drug abuse', 'drug withdrawal syndrome', 'prescription drug used without a prescription', and 'intentional product use issue' were 4.05, 4.05, 3.60, and 1.80 (all < 0.01). The same comparisons of semaglutide vs. the phentermine-topiramate combination were not associated with any significant differences. To the best of our knowledge, this is the first study documenting the misuse/abuse potential of semaglutide in comparison with other GLP1 analogues and the phentermine-topiramate combination. The current findings will need to be confirmed by further empirical investigations to fully understand the safety profile of those molecules.

Using GPT-3 to Build a Lexicon of Drugs of Abuse Synonyms for Social Media Pharmacovigilance

Drug abuse is a serious problem in the United States, with over 90,000 drug overdose deaths nationally in 2020. A key step in combating drug abuse is detecting, monitoring, and characterizing its trends over time and location, also known as pharmacovigilance. While federal reporting systems accomplish this to a degree, they often have high latency and incomplete coverage. Social-media-based pharmacovigilance has zero latency, is easily accessible and unfiltered, and benefits from drug users being willing to share their experiences online pseudo-anonymously. However, unlike highly structured official data sources, social media text is rife with misspellings and slang, making automated analysis difficult. Generative Pretrained Transformer 3 (GPT-3) is a large autoregressive language model specialized for few-shot learning that was trained on text from the entire internet. We demonstrate that GPT-3 can be used to generate slang and common misspellings of terms for drugs of abuse. We repeatedly queried GPT-3 for synonyms of drugs of abuse and filtered the generated terms using automated Google searches and cross-references to known drug names. When generated terms for alprazolam were manually labeled, we found that our method produced 269 synonyms for alprazolam, 221 of which were new discoveries not included in an existing drug lexicon for social media. We repeated this process for 98 drugs of abuse, of which 22 are widely-discussed drugs of abuse, building a lexicon of colloquial drug synonyms that can be used for pharmacovigilance on social media.

Cardiovascular Adverse Events Associated with Monoclonal Antibody Products in Patients with COVID-19

Little is known about cardiovascular safety profiles for monoclonal antibody products that received the FDA Emergency Use Authorization for COVID-19. In this study, data from the FDA Adverse Event Reporting System from the first quarter of 2020 to the second quarter of 2022 were used to investigate cardiovascular safety signals associated with seven monoclonal antibody products (casirivimab + imdevimab, bamlanivimab, bamlanivimab + etesevimab, sotrovimab, tocilizumab, bebtelovimab, tixagevimab + cilgavimab) in COVID-19 patients. Disproportionality analyses were conducted using reporting odds ratio and information component to identify safety signals. About 10% of adverse events in COVID-19 patients were cardiovascular adverse events. Four monoclonal antibody products (casirivimab + imdevimab, bamlanivimab, bamlanivimab + etesevimab, and bebtelovimab) were associated with higher reporting of hypertension. Tocilizumab was associated with higher reporting of cardiac failure and embolic and thrombotic event. Casirivimab + imdevimab and bamlanivimab were also associated with higher reporting of ischemic heart disease. No cardiovascular safety signals were identified for sotrovimab and tixagevimab + cilgavimab. The results indicate differential cardiovascular safety profiles in monoclonal antibodies. Careful monitoring of cardiovascular events may be considered for certain COVID-19 patients at risk when they are treated with monoclonal antibodies.

Recreational Drug Misuse and Its Potential Contribution to Male Fertility Levels' Decline: A Narrative Review

Recreational drug intake may be associated with a range of medical untoward consequences, including male infertility. However, as the related evidence is still limited, the main outcome of this review is to provide a better understanding of the existence of any association between recreational drug misuse and male fertility levels' decline. Whilst searching the MEDLINE/PubMed, a comprehensive overview of the literature regarding male infertility and substances of abuse (e.g., phytocannabinoids, opiates/opioids, stimulants, 'herbal highs', psychedelics, and 'novel psychoactive substances) was here undertaken. Due to the paucity of robust, high-quality, empirical, human studies, a narrative strategy was here preferred over a systematic approach. Relevant data are qualitatively analyzed and presented in a table. Although most available evidence is in support of a detrimental role of cannabis on human spermatogenesis, a few remaining studies failed to document any effect of this drug on seminal quality, and it is not clear to which extent this drug impacts fertility rates/time to pregnancy. The current understanding of the impact of opiate-, cocaine- and amphetamine/stimulant-misuse on human reproduction is widely unknown, and most studies dealing with this matter represent only an extrapolation of data derived from specific clinical circumstances. Although the message of 'no smoking, no alcohol and no street drugs' should always be offered as good health advice to all patients seeking medical help for fertility issues, robust scientific clinical evidence in support of a direct detrimental impact of recreational drugs on spermatogenesis is scant to date.

Analysis of pharmacovigilance databases for spontaneous reports of adverse drug reactions related to substandard and falsified medical products: A descriptive study

Introduction: The public health threat of substandard and falsified medicines has been well known in the last two decades, and several studies focusing on the identification of products affected and preventing consumption have been published. However, the number of these products reaching patients and causing health consequences and adverse drug reactions is not a well-researched area.

Objectives: Our aim was to identify and describe the characteristics of cases that are related to adverse drug reactions potentially originating from counterfeit medication using publicly available pharmacovigilance data.

Methods: A descriptive study was performed based on pharmacovigilance data retrieved from Individual Case Safety Reports (ICSRs) identified in the European Medicines Agency’s EudraVigilance and FDA Adverse Event Reporting System (FAERS) databases in April 2022 using selected MedDRA preferred terms: counterfeit product administered, product counterfeit, product label counterfeit, product packaging counterfeit, suspected counterfeit product, adulterated product, product tampering, and suspected product tampering. ICSRs were analyzed by age and gender, by year of reporting, region of origin, reporter’s profession, and severity of the outcome. The disproportionality method was used to calculate pharmacovigilance signal measures.

Results: A total of 5,253 cases in the FAERS and 1,049 cases in the EudraVigilance database were identified, generally affecting middle-aged men with a mean age of 51.055 (±19.62) in the FAERS and 64.18% of the cases between 18 and 65 years, while the male to female ratios were 1.18 and 1.5. In the FAERS database, we identified 138 signals with 95% confidence interval including sildenafil (n = 314; PRR, 12.99; ROR, 13.04; RRR, 11.97), tadalafil (n = 200; PRR, 11.51; ROR, 11.55; RRR, 10.94), and oxycodone (n = 190; PRR, 2.47; ROR, 2.14; RRR, 2.47). While in the EV data 31, led by vardenafil (n = 16, PRR = 167.19; 101.71–274.84; 95% CI, RRR = 164.66; 100.17–270.66; 95% CI, ROR = 169.47; 103.09–278.60; 95% CI, p &lt; 0.001), entecavir (n = 46, PRR = 161.26, RRR = 154.24, ROR = 163.32, p &lt; 0.001), and tenofovir (n = 20, PRR = 142.10, RRR = 139.42, ROR = 143.74, p &lt; 0.001).

Conclusion: The application of pharmacovigilance datasets to identify potential counterfeit medicine ADRs can be a valuable tool in recognition of potential risk groups of consumers and the affected active pharmaceutical ingredients and products. However, the further development and standardization of ADR reporting, pharmacovigilance database analysis, and prospective and real-time collection of potential patients with health consequences are warranted in the future.