Therapeutic Advances in Drug Safety最新文献

Background: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy but are linked with immune-related adverse events (irAEs), including cardiac events.

Objective: This study aims to assess the reporting frequency of atrial fibrillation with ICIs using data from the Food and Drug Administration Adverse Event Reporting System (FAERS).

Design: It is an observational, retrospective, pharmacovigilance study.

Methods: Individual Case Safety Reports (ICSRs) were retrieved from FAERS up to September 24, 2024. Cases reporting one or more ICIs (atezolizumab, avelumab, cemiplimab, dostarlimab, durvalumab, ipilimumab, nivolumab, pembrolizumab, and tremelimumab) and atrial fibrillation were selected. Disproportionality analyses were performed by applying the reporting odds ratio (ROR) and the Informational Component (IC) with a 95% confidence interval (95% CI).

Results: A total of 1228 ICSRs were retrieved, of which 218 (17.75%) were related to combinations of ICIs. Most ICSRs (N = 812; 66.1%) referred to male patients and the age group most represented was ⩾65 years (N = 772; 62.9%). Atrial fibrillation was serious in 99.3% (N = 1220) of cases and had a fatal outcome (N = 248; 20.3%). Atezolizumab, avelumab, durvalumab, nivolumab, and pembrolizumab were associated with a statistically significant higher reporting frequency of atrial fibrillation compared to all other drugs (ROR: 1.90, IC: 0.91; ROR: 1.94, IC: 0.92; ROR: 1.52, IC: 0.60; ROR: 1.30, IC: 0.38; ROR: 1.66, IC: 0.72, respectively). The anti-CTLA-4 ipilimumab showed a statistically significant lower reporting frequency of atrial fibrillation compared to all other drugs (ROR: 0.69, IC: -0.53) and to all other ICIs (ROR: 0.45, IC: -1.02). Moreover, anti-PD-L1 (ROR: 2.60, IC: 0.47) and anti-PD-1 (ROR: 2.12, IC: 0.16) were associated with a higher reporting of atrial fibrillation compared to anti-CTLA-4.

Conclusion: ICI-induced atrial fibrillation was serious and had severe outcomes. The anti-CTLA-4 showed a lower likelihood of reporting atrial fibrillation, while higher reporting was found with anti-PD-1 and anti-PD-L1. Further studies are needed to confirm this safety aspect.

Integrating real-world healthcare data is challenging due to diverse formats and terminologies, making standardization resource-intensive. While Common Data Models (CDMs) facilitate interoperability, they often cause information loss, exhibit semantic inconsistencies, and are labor-intensive to implement and update. We explore how generative artificial intelligence (GenAI), especially large language models (LLMs), could make CDMs obsolete in quantitative healthcare data analysis by interpreting natural language queries and generating code, enabling direct interaction with raw data. Knowledge graphs (KGs) standardize relationships and semantics across heterogeneous data, preserving integrity. This perspective review proposes a fourth generation of distributed data network analysis, building on previous generations categorized by their approach to data standardization and utilization. It emphasizes the potential of GenAI to overcome the limitations CDMs with GenAI-enabled access, KGs, and automatic code generation. A data commons may further enhance this capability, and KGs may well be needed to enable effective GenAI. Addressing privacy, security, and governance is critical; any new method must ensure protections comparable to CDM-based models. Our approach would aim to enable efficient, real-time analyses across diverse datasets and enhance patient safety. We recommend prioritizing research to assess how GenAI can transform quantitative healthcare data analysis by overcoming current limitations.

The increasing off-label use of medications needs a robust pharmacovigilance system. This is particularly crucial given the abundance of scientific data that can be harnessed to ensure a product's safety. Our review focuses on the off-label use of local anesthetics, a common practice in topical and intracameral applications. However, the occurrence of mydriasis, as indicated in the monographs/summaries of product characteristics, is an unexpected adverse event. Our aim is to provide a comprehensive understanding of mydriasis caused by local anesthetics, both as an unexpected adverse event and as an off-label use, to reinforce the importance of pharmacovigilance practices. We conducted a comprehensive search in Medline/PubMed and Google Scholar from two distinct perspectives: examining the occurrence of mydriasis with the use of local anesthetic as an adverse event and as an off-label use. Our search yielded 14 articles that reported mydriasis as an unexpected adverse event with the use of anesthetics, with dental procedures being a significant contributor to this type of event. Also, we identified eight articles that explored the off-label use of local anesthetics to induce mydriasis, with the most common method of drug administration being intracameral injection. These findings underscore the importance of our research in understanding the unexpected adverse event of mydriasis and the potential for off-label use of local anesthetics. They also highlight the need for continued involvement and vigilance in this area, as our understanding of these phenomena continues to evolve and further investigation is crucial. The use of local anesthetics for mydriasis holds significant promise, particularly in ophthalmological surgeries. This approach could potentially mitigate the adverse events associated with conventional mydriatics, offering a more efficient and safer alternative. Furthermore, using a single medication for akinesia, anesthesia, and mydriasis could significantly enhance the efficiency and convenience of surgical procedures. On the other hand, it is crucial to extend the knowledge of the mydriasis-anesthesia association through risk minimization activities (e.g., the inclusion of monographs/summary of product characteristics) to communicate the risk of mydriasis with the use of local anesthetics.

Background: Novel antidiabetic medications (SGLT-2 inhibitors, DPP-4 inhibitors, and GLP-1 agonists) are commonly used worldwide; however, the available research lacks definitive conclusions on their protective effects or potential risks on cancer.

Objectives: Compared to other antidiabetics, our systematic review and network meta-analysis (NMA) aims to use real-world studies to assess the potential cancer risks or protective effects of these novel antidiabetics.

Methods: We comprehensively searched PubMed, CINAHL, and Web of Science from their inception until November 30, 2023. We included observational studies examining at least one novel antidiabetics in the systematic review. The novel antidiabetics include sodium-glucose cotransporter-2 inhibitors (SGLT-2i), dipeptidyl peptidase-4 inhibitors (DPP-4i), and glucagon-like peptide-1 agonists (GLP-1a).

Design: We focused on cohort studies that provided data on cancer incidence and sample size in the NMA. Using NetMetaXL^®, the random effects model with informative priors was used in the NMA to estimate the pooled odds ratio (OR) with 95% credible intervals (CrI).

Results: The systematic review included 62 studies, of which 22 met the inclusion criteria for the NMA. SGLT-2i users had lower overall cancer risk compared to sulfonylureas (OR: 0.54; 95% CrI: 0.40-0.74, low certainty), GLP-1a (OR: 0.70; 95% CrI: 0.53-0.92, low certainty), and DPP-4i users (OR: 0.72; 95% CrI: 0.57-0.92, very low certainty). DPP-4i users also had a lower cancer risk than sulfonylureas users (OR: 0.76; 95% CrI: 0.60-0.96, low certainty). No other statistically significant ORs were found in other direct comparisons.

Conclusion: SGLT-2i users have a lower risk of developing cancers than sulfonylureas, GLP-1a, and DPP-4i users. These results may improve patient safety by guiding future clinical practice and medication choices. Future studies should investigate the mechanisms behind these observed associations.

Trial registration: This NMA was registered in PROSPERO (CRD42023469941).

Background: Unlike the propofol-opioids combination, a single dose of S-ketamine with propofol achieves the same anesthetic effects while effectively minimizing adverse reactions in painless abortion. Ciprofol, a novel analog of propofol, has distinct advantages, its application in painless abortion is underexplored.

Objectives: To investigate a 90% effective dose (ED₉₀) of ciprofol and propofol with S-ketamine for painless abortion.

Design: This prospective biased coin up-and-down (BCUD) sequential dose-finding study aimed to estimate the ED₉₀ of ciprofol when administered with 0.15 mg/kg S-ketamine in painless abortion while comparing adverse effects incidence with the ED₉₀ of propofol when combined with the same dose of S-ketamine.

Methods: Eighty patients were recruited and randomly allocated to either ciprofol or propofol groups, with initial doses of 0.375 mg/kg and 1.5 mg/kg, respectively. The dose for the subsequent patient in the study was based on the response of the preceding patient, following the BCUD design. The study estimated the ED₉₀ using isotonic regression. Secondary outcomes, including the incidence of injection pain, vital signs, and adverse events, were recorded and compared between the two groups.

Results: The ED₉₀ of ciprofol with 0.15 mg/kg S-ketamine was 0.498 mg/kg (95% confidence interval: 0.498-0.510), while the ED₉₀ of propofol with 0.15 mg/kg S-ketamine was 1.99 mg/kg (95% confidence interval: 1.98-2.16). Patients in the ciprofol group had a lower incidence of respiratory pause (7.5% vs 52.5%; p < 0.001). Other adverse events and recovery time were comparable between groups.

Conclusion: Compared to propofol and S-ketamine combination, ciprofol and S-ketamine are equally effective with reduced respiratory depression. Thus, clinicians should consider a dose of 0.5 mg/kg ciprofol with 0.15 mg/kg S-ketamine for painless abortion.

Trial registration: http://www.chictr.org.cn; ChiCTR2400086522; July 5, 2024.

Background: The risk factors related to the adverse drug reactions (ADRs) of anlotinib have been rarely investigated. In addition, a corresponding risk prediction model has not been established in China pertaining to anlotinib-related ADRs.

Objectives: To manage ADRs more efficiently and improve the prognosis of patients administered anlotinib.

Design: A retrospective analysis was conducted using the medical records of patients diagnosed with cancer who were administered anlotinib after hospitalization between January 1, 2020, and December 31, 2023.

Methods: We performed a combination of univariate analysis and multivariate binary logistic regression analysis to identify significant factors that can accurately predict ADRs. Model fitting was performed using forward selection. The accuracy of the prediction model was expressed as the area under the receiver operating characteristic curve (AUC). The final ADR risk model was validated.

Results: In this study, 300 patients who were administered anlotinib were included. Among them, 238 (79.33%) patients experienced at least one ADR. Diagnosis, combination treatment, distant metastasis, treatment lines, and cumulative dose were independent risk factors for the ADRs of anlotinib. The AUC and the concordance index of the nomogram constructed from the above five factors were 0.790 and 0.789, respectively. The results of the Hosmer-Lemeshow test showed that the model was a good fit (p = 0.811). In addition, the decision curve analysis demonstrated a significantly higher net benefit of the model. The external validation indicated that the prediction nomogram was reliable.

Conclusion: We developed and validated a simple model to use the ADR risk score in patients who were administered anlotinib. This risk prediction model was well-calibrated and discriminative. It can be used as a reference for clinical decision-making. It has clinical significance for preventing ADRs, improving the prognosis of patients, and providing support for the rational use of drugs.

Local anesthetics have a broad application for minor and major surgeries, in outpatient and inpatient settings. Drug dosing, frequency, duration of action, and coadministration with other drugs, are some of many factors that must be considered for each patient, before drug administration. Like other medical treatments, the use of local anesthetics has potential complications, such as local anesthetic systemic toxicity (LAST). LAST primarily affects the cardiac and central nervous systems (CNS), seizures and cardiac arrest being some of the more time-sensitive symptoms requiring immediate treatment. Patients should be briefed on potential symptoms if LAST occurs and physicians should be aware of the warning signs, treatment, and prevention. In our case study, a 40-year-old, 51 kg woman was administered a lidocaine dosage of 760 mg in an outpatient setting. She presented to the emergency department with diffuse tremors, paresthesias of the mouth and face, spasticity, irritability, and a single generalized tonic-clonic seizure. The patient was successfully treated with Ativan along with lipid emulsion. We review this case and perform a literature review to identify key points in the use of local anesthetics. Healthcare providers should be trained in LAST treatment and prevention. Our case study therefore serves to reduce the frequency of LAST and other adverse outcomes associated with local anesthetic administration.

Background: Although there are reports of adverse events (AEs) of cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors, the safety of ribociclib alone has not yet been comprehensively evaluated in real-world clinical practice.

Objectives: To investigate the overall real-world safety profile of ribociclib by mining data from the FDA Adverse Event Reporting System (FAERS).

Design: A retrospective disproportionality analysis was conducted based on the FAERS database.

Methods: We processed reports from the first quarter of 2017 to the second quarter of 2023 and applied disproportionality analysis using four different methods: reporting odds ratio, Medicines and Healthcare Products Regulatory Agency, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker.

Results: A total of 12,885 AE reports of ribociclib as the primary suspect were enrolled. 48.81% of AEs occur within 60 days of ribociclib administration. Blood and lymphatic system disorders and abnormalities in investigation at the system organ class level showed statistically significant signals in all four methods. Nausea (n = 1426), neutropenia (n = 940), vomiting (n = 863), white blood cell count decreased (n = 812), and alopecia (n = 536) turned out to be the five most frequent AEs at the preferred term level. Twenty-eight AEs undiscovered in the label were newly identified. Neutropenia, as a widely recognized AE, was observed to potentially result in more serious outcomes than previously anticipated (p < 0.001).

Conclusion: This study utilized the FAERS database to analyze real-world AE signals associated with ribociclib following its market approval. We characterized the clinical profiles of reported AEs and found some significant signals consistent with previous clinical trials. In addition, several AEs not included in the drug label or exhibiting unexpected severity were detected. These findings provide valuable insights for clinicians and highlight directions for further causality-focused research to validate the observed results.

Artificial intelligence (AI) is transforming medication research and development, giving clinicians new treatment options. Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. Furthermore, generative AI is accelerating the development and re-engineering of medicinal molecules to cater to both common and rare diseases. Although, to date, no AI-generated medicinal drug has been FDA-approved, HLX-0201 for fragile X syndrome and new molecules for idiopathic pulmonary fibrosis have entered clinical trials. However, AI models are generally considered "black boxes," making their conclusions challenging to understand and limiting the potential due to a lack of model transparency and algorithmic bias. Despite these obstacles, AI-driven drug discovery has substantially reduced development times and costs, expediting the process and financial risks of bringing new medicines to market. In the future, AI is expected to continue to impact pharmaceutical innovation positively, making life-saving drug discoveries faster, more efficient, and more widespread.

Background: The association between dipeptidyl peptidase-4 inhibitors (DPP-4i) exposure and the risk of colorectal cancer (CRC) in patients with type 2 diabetes mellitus (T2DM) is unclear.

Objectives: This meta-analysis aims to investigate the relationship between DPP-4i exposure and the incidence of CRC in patients with T2DM.

Design: A systematic review and meta-analysis.

Methods: A comprehensive search of electronic databases, including PubMed, Web of Science, EMBASE, and ScienceDirect, was conducted up to March 2024. The studies including randomized clinical trials (RCTs), cohort studies, and case-control studies were retrieved. The odds ratio (OR) was calculated using Stata 12.0 statistical software. The primary outcome assessed was the incidence of CRC.

Results: This meta-analysis incorporated six retrospective cohort studies and two case-control studies. The findings indicate that the incidence of CRC in the DPP-4i exposure group was significantly higher than that in the control group (OR = 1.11, 95% CI: 1.02-1.21, p = 0.013). Subgroup analysis revealed that both male (OR = 2.07, p < 0.001) and female participants (OR = 1.49, p = 0.05) in the DPP-4i exposure group exhibited a significantly higher incidence of CRC compared to the control group. Among participants younger than 65 years, the incidence of CRC was markedly elevated in the exposure group (OR = 2.81, p < 0.001). Furthermore, when the exposure duration was less than 1 year, the CRC incidence in the exposure group surpassed that of the control group (OR = 1.24, p = 0.005). When sulfonylureas (SU) were used as control drugs, the incidence of CRC was higher in the exposure group (OR = 1.10, p = 0.017).

Conclusion: There is a potential correlation between DPP-4i exposure and increased incidence of CRC in T2DM patients. This association appears to be influenced by gender, age, duration of exposure, and the choice of control medications. Therefore, attention should be paid to colorectal diseases when DPP-4i is employed in the clinic.

Trial registration: The meta-analysis has been registered with the International Prospective Register of Systematic Reviews (PROSPERO). The registration number is CRD42024535292.