Lingti Kong

Objective: To compare adverse event reporting patterns for seven Alzheimer’s disease (AD) drugs (aducanumab, donanemab, lecanemab, donepezil, galantamine, rivastigmine, and memantine) using the FDA Adverse Event Reporting System (FAERS), and to explore potential reporting signals. Methods: FAERS reports from the first quarter of 2004 to the second quarter of 2026 were retrospectively analyzed. Adverse events were coded using MedDRA version 28.1 preferred terms (PTs) and system organ classes (SOCs). Disproportionality signals were detected using the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma-Poisson shrinker (MGPS). PT-level signals were additionally controlled using Benjamini–Hochberg false discovery rate correction. Drug-level comparisons, sex- and age-stratified analyses, time-to-onset (TTO) analysis, and Weibull distribution fitting were performed. Results: A total of 39,301 valid reports involving the seven AD drugs were included. Reports were more frequent among women (52.3%, n = 20,537) and patients aged ≥65 years. Anti-Aβ monoclonal antibodies showed concentrated reporting signals in nervous system disorders, with amyloid related imaging abnormalities (ARIA) related events as the core PT-level signal. Donanemab and lecanemab were also associated with prominent infusion-related reaction signals. Conventional symptomatic drugs demonstrated broader multi-system reporting patterns: donepezil and galantamine were mainly associated with cholinergic cardiovascular and fall-related signals; rivastigmine with administration-site reactions and fall-related events; and memantine with confusional state, agitation, dizziness, and somnolence. Several PT-level signals were not listed in the reviewed prescribing information and were annotated as potential reporting signals. Sex- and age-stratified analyses showed broadly consistent PT-level spectra. TTO analyses revealed heterogeneous onset patterns among different drug and adverse events. Conclusion: This study utilized FAERS data to compare adverse event reporting signals for seven anti-AD drugs. Distinct reporting profiles were observed across drugs, and several potential ADE signals, including potential unlabeled reporting signals, were identified. These findings may support pharmacovigilance surveillance and hypothesis generation, but should be interpreted as reporting associations rather than evidence of causality.

Introduction: Male sexual dysfunction (MSD) can induce or exacerbate depressive symptoms, and MSD caused by antidepressants may further aggravate the depressive symptoms of patients. However, real-world evidence regarding the association between different antidepressants and MSD remains insufficient. This study aims to systematically analyze the differences in the association between antidepressants and MSD, by utilizing the U.S. Food and Drug Administration Adverse Event Reporting System. Methods: Adverse drug events (ADEs) for male patients using antidepressants were retrieved. Adverse drug events were classified using the Standardized MedDRA Query. Disproportionality analysis was performed using reporting odds ratio (ROR), proportional reporting ratio (PRR), multi-item gamma-Poisson shrinker, and Bayesian confidence propagation neural network. The time-to-onset of MSD for each drug and the inclusion of MSD information in the drug labels were also analyzed. Results: Among the 28 included drugs, 24 drugs reported MSD, 18 drugs simultaneously satisfied the positive signal criteria of all 4 algorithms. Sertraline had the highest number of MSD (988 cases), accounting for 6.22% of its total 15 875 cases. Escitalopram showed the strongest signal on all 4 algorithms [ROR: 13.67, PRR: 13.19, lower limit of 95% CI of empirical Bayes geometric mean (EBGM05): 12.19, lower limit of 95% CI of the information component (IC025): 3.59]. The time-to-onset of MSD for most antidepressant drugs followed an “Early failure” model. Conclusion: This study employed 4 algorithms to detect and evaluate potential association signals between antidepressants and MSD. Among the 28 antidepressants analyzed, 18 demonstrated significant associations with MSD. Beyond traditional selective serotonin reuptake inhibitors, the signal strength of MSD associated with other classes of antidepressants should not be overlooked.

Background: Linezolid is a cornerstone therapy for multidrug-resistant Gram-positive infections. While prolonged intermittent infusion (PII) or continuous infusion (CI) can optimize the efficacy of time-dependent antibiotics, their application to linezolid remains controversial. Specifically, it is debated whether the theoretical efficacy gains of CI are negated by the elimination of the concentration nadir, which may trigger accumulation-related toxicity. Quantitative evidence dissecting this delicate trade-off is currently absent. Objectives: This study aimed to quantify the interplay between infusion duration, efficacy, and toxicity. By developing a population pharmacokinetic (PopPK) model and employing a “composite efficacy-safety target”, we sought to identify precision dosing strategies for critically ill patients. Methods: Plasma concentration-time data obtained from 20 critically ill patients were used to develop a PopPK model using nonlinear mixed-effects modeling (NONMEM v7.5). Based on final model parameters, Monte Carlo simulations were performed for 1,000 virtual patients. A composite target was established comprising a pharmacodynamic efficacy threshold (AUC ₂₄ ,ss/minimum inhibitory concentration ≥100 and %T > MIC ≥85%) and a safety threshold (steady-state trough concentration, C _min,ss < 8 mg/L). Probability of Target Attainment (PTA) was evaluated across 7 dosing regimens (300, … , 900 mg q12 h) and 13 infusion durations (0.5, 1, 2, … , 12 h). Results: The pharmacokinetics were best described by a one-compartment model, with body weight (WT) and creatinine clearance (CLcr) identified as critical determinants of distribution volume (V) and clearance (CL), respectively. Simulations revealed a non-linear relationship between infusion duration and composite PTA. While prolonged intermittent infusion enhanced efficacy by improving % T > MIC, indiscriminate extension to CI, particularly at moderate-to-high doses, resulted in a systematic breach of the safety threshold (C _min,ss ≥ 8 mg/L). Consequently, composite PTA declined due to toxic over-exposure. Notably, for refractory pathogens (MIC ≥2 mg/L), traditional CI yielded near-zero success rates due to high toxicity risks. Conclusion: In critically ill patients, the optimal infusion duration for linezolid exhibits a non-linear dependency on dose and MIC. For high-MIC pathogens requiring intensified dosing (e.g., 900 mg q12 h), a prolonged infusion of 2–5 h optimizes the therapeutic index, synergizing maximal efficacy with a necessary elimination phase to mitigate toxicity.

Objective: The real-world cardiac safety profile of systemic antifungal agents has not been thoroughly investigated. Based on the US Food and Drug Administration Adverse Event Reporting System FDA Adverse Event Reporting System database, this study analyzed the arrhythmogenic toxicity of nine systemic antifungal drugs, aiming to provide references for clinical safe medication practices. Research design and methods: Adverse events were described and classified using arrhythmogenic toxicity-related Standardized MedDRA Queries (SMQs) from the MedDRA. To identify the association between systemic antifungal agents and arrhythmogenic toxicity, this study used four algorithms: Reporting odds ratio (ROR), Proportional reporting ratio (PRR), Multi-item gamma-poisson shrinker (MGPS), and Bayesian confidence propagation Neural Network (BCPNN). Results: A total of 42,393 reports were included. The ranking of the number of positive signals across four types of SMQs was as follows: Itraconazole (4), Fluconazole (3), Posaconazole (3), Voriconazole (2), Caspofungin (1), Amphotericin B (1), Flucytosine (0), Isavuconazole (0), Micafungin (0). Itraconazole demonstrated the strongest ROR value of 2.95 in “Cardiac arrhythmia terms, nonspecific”. The highest ROR values in “Bradyarrhythmias” were 5.53 for both posaconazole and fluconazole. Fluconazole exhibited higher ROR values than other drugs in both “Tachyarrhythmias” and “Torsade de pointes/QT prolongation”, with values of 3.53 and 14.55, respectively. Conclusion: This study employed four disproportionality analysis methods to analyze the association between systemic antifungal agents and arrhythmogenic toxicity signals. Itraconazole, fluconazole, and posaconazole demonstrated stronger arrhythmogenic risks, whereas micafungin, flucytosine, and isavuconazole showed negative signals across all four SMQs. In clinical practice, individual patient risk should be comprehensively assessed to guide personalized drug selection.

Objective: The potential drug-drug interactions (pDDIs) seriously affecting the prognosis of colorectal cancer (CRC) patients. This study aimed to identify the risk factors of pDDIs in hospitalized CRC patients and construct a risk prediction model to provide a reference for clinical rational drug use. Research design and methods: A retrospective cohort study was conducted, enrolling 2,868 patients from a tertiary hospital. Medscape was used to assess pDDIs, and a risk prediction model was constructed based on independent risk factors. Results: A total of 1,790 (62.41%) patients experienced at least one pDDIs, with 1,458 (50.84%) cases of severe pDDIs. The number of drug varieties, hypoalbuminemia, and treatment were independent risk factors. The area under the receiver operating characteristic curve (AUC) of the model in the training and validation sets were 0.826 and 0.824, respectively. The calibration curve showed a good agreement between the predicted probability and the actual occurrence probability. Decision curve analysis (DCA) demonstrated that the model had a positive net clinical benefit within a wide range of 10%–90%. Conclusion: The constructed model has good predictive performance and can be used to identify high-risk patients with pDDIs in clinical practice, thereby improving the safety of drug use.

Purpose Trastuzumab, the first anti-human epidermal growth factor receptor 2 (HER2)-targeted drug, is limited by adverse drug events (ADEs). The next-generation antibody–drug conjugates trastuzumab deruxtecan (T-DXd) and trastuzumab emtansine (T-DM1) exhibit enhanced efficacy and safety profiles compared with trastuzumab. In this study, we utilized US Food and Drug Administration Adverse Event Reporting System (FAERS) data to compare the ADEs of all three drugs, to facilitate personalized clinical decision-making and targeted monitoring. Methods ADE reports for patients with breast cancer using trastuzumab, T-DXd, or T-DM1 were retrieved. ADEs were classified using preferred terms (PT), standardized MedDRA queries (SMQs), and system organ classes (SOCs). Data mining using reported odds ratio (ROR), proportional reporting ratio, Bayesian confidence propagation neural network (BCPNN), and multi-item gamma-Poisson shrinker was conducted. Results Overall, 20,829 cases of trastuzumab, 4565 cases of T-DXd, and 2975 cases of T-DM1 were included. With regard to SMQ terms, trastuzumab had a higher signal intensity for cardiac toxicity, and the RORs for “cardiomyopathy” of trastuzumab, T-DXd and T-DM1 were 8.59, 1.33, and 1.84, respectively. Meanwhile, T-DXd showed stronger signals for lung toxicity and T-DM1 showed prominent hepatotoxicity signals. Based on the differences between trastuzumab, T-DXd and T-DM1, this study established an individualized medication selection flowchart. Conclusions This study applied four algorithms to analyze and compare ADEs associated with trastuzumab, T-DXd, or T-DM1. By integrating multi-level analysis including PT, SMQ, and SOC, this study provides a comprehensive safety perspective to guide clinical decision-making and medication monitoring for patients with breast cancer receiving HER2-targeted therapy.

Objective: Studies on anti-Aβ drugs for the treatment of Alzheimer’s disease (AD) have garnered significant attention; however, their safety still requires further research and monitoring. Although recent studies have analyzed the adverse drug events (ADEs) of lecanemab and aducanumab separately, there is a lack of comparison between these two drugs, and no exploration of gender differences. This study aims to compare the adverse reaction signals of lecanemab and aducanumab, also exploring the differences between genders.Research design and methods: We analyzed ADEs reported by patients using lecanemab and aducanumab, using the FDA adverse event reporting system (FAERS). The data was classified using the preferred terms (PTs) and systemic organ categories (SOCs). Four positive signal detection algorithms were used, namely, the Ratio-to-Ratio (ROR), proportional reporting ratio (PRR), multi item gamma poisson shrinker (MGPS), and bayesian belief propagation neural network (BCPNN). Additionally, the time-to-onset of ADEs was also compared between the two drugs and between male and female patients.Results: A total of 1,409 ADE reports in which an anti-Aβ antibody drug was primarily suspected were included in the study, comprising 892 cases (63.31%) of lecanemab and 517 cases (36.69%) of aducanumab. For both lecanemab and aducanumab, only the SOC ‘nervous system disorders’ met the criteria for positive signal for all four algorithms. The number of positive PT signals related to lecanemab and aducanumab was 40 and 33, respectively. Among them, “cerebral microbleeds,” “amyloid protein related imaging abnormalities (ARIA),” and “central nervous system superficial squamous cell hyperplasia” all exhibited strong signals, regardless of drug or sex of the patient. Additionally, there were some differences in PT signals between male and female patients, and some new PT signals that were not included in the drug labels were identified. The median time-to-onset of lecanemab was shorter than that of aducanumab (33 days vs. 146 days).Conclusion: Four signal calculation methods were used to assess potential adverse reaction signals of lecanemab and aducanumab. This study identified some new PT signals and some PT signals showed gender differences. The median time-to-onset of ADEs due to lecanemab is shorter than that due to aducanumab.

Background: Sintilimab, a programmed cell death protein-1 (PD-1) inhibitor, has shown efficacy in non-small cell lung cancer (NSCLC), though response heterogeneity persists. Previous studies suggest that the Lung Immune Prognostic Index (LIPI) may predict prognosis and immune-related adverse events (irAEs) in immunotherapy. This study aimed to develop and validate LIPI-based nomograms for predicting overall survival (OS) and irAEs in NSCLC patients treated with sintilimab.Methods: Multicenter data stratified 356 patients into training, internal validation, and external validation cohorts. Propensity score matching (PSM) balanced baseline characteristics. Multivariable Cox regression identified OS and irAEs predictors, and nomograms were constructed using significant variables. Model performance was evaluated via concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Kaplan-Meier analysis assessed risk stratification.Results: Independent prognostic factors for OS include clinical stage, treatment lines, LIPI scores and albumin level. Among them, stage IV (hazard ratio [HR]=1.725, 95% confidence interval [CI] 1.529-1.902), treatment line ≥2 (HR=1.302, 95%CI: 1.125-1.569), LIPI intermediate (HR=1.736, 95%CI: 1.586-1.925), LIPI poor (HR=1.568, 95% CI: 1.361-1.637) and albumin level≥35 (HR=1.802, 95%CI: 1.698-2.023) were risk factors for OS. The OS prediction model demonstrated excellent discrimination across all cohorts, with time-dependent AUCs maintaining 0.770-0.850 for 1–2 year predictions. Consistent calibration was observed (C-index: training=0.778, internal validation=0.793, external validation=0.790). For irAEs prediction, significant predictors included age, sex, Eastern Cooperative Oncology Group performance status (ECOG PS), and LIPI scores. Similarly, the irAEs model showed robust performance (AUCs 0.754-0.835 for 1–2 year predictions; C-index: training=0.805, internal validation=0.825, external validation=0.775). Both nomograms significantly outperformed single-variable predictions in Kaplan-Meier analyses. DCA confirmed superior net clinical benefit.Conclusion: LIPI-based nomograms effectively predicted OS and irAEs in sintilimab-treated NSCLC patients, offering valuable tools for personalized treatment and clinical decision-making.

Objective: Voriconazole is a broad-spectrum antifungal agent. It is used widely for the prevention and treatment of invasive fungal infections in patients with a hematological malignancy, but studies on its safety in this population are scarce. We assessed the adverse drug events (ADEs) of voriconazole in this population based on the US Food and Drug Administration Adverse Event Reporting System (FAERS) database to improve understanding of the safety of voriconazole.Research design and methods: ADE reports for patients with a hematological malignant tumor using voriconazole between the first quarter of 2004 to the first quarter of 2024 were retrieved. Then, they were classified using the preferred terminology (PT) and system organ category (SOC) in the Medical Dictionary for Regulatory Activities. Data mining was done using reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS).Results: A total of 605 ADEs were included: 116 (19.17%) in children and 489 (80.83%) in adults. The types of SOC involved in children and adults were 22 and 24, respectively. The only positive SOC signal that satisfied all four algorithms simultaneously in children was “psychiatric disorders”, whereas in adults they were “endocrine disorders” and “hepatobiliary disorders”. At the PT level, the types involved in children and adults were 28 and 74, respectively. The highest ROR signal intensities were found for “hallucinations, mixed” in children and “toxic optic neuropathy” in adults. The median time of onset of the ADE in children and adults was 11 and 8.5 days, respectively.Conclusion: We used four algorithms (ROR, PRR, BCPNN, MGPS) to mine the signals of voriconazole in patients with a hematological malignant tumor, and compared the differences between children and adults. This study is important for targeting the monitoring, and could help to improve the safety of voriconazole.

To promote the accurate administration of linezolid, this study aimed to evaluate its dosage regimens in critically ill patients with varying renal functions. This evaluation was based on a combined analysis of pharmacokinetic (PK), pharmacodynamic (PD), and toxicodynamic (TD) indices. The percentage of therapeutic target attainment (PTTA) was used as the index for PK/PD/TD, defined as simultaneously meeting two PK/PD criteria (AUC_0-24h/MIC ≥ 100 and C_ss between 2.6-7.8 mg/L) and adjusted for toxicity probability, with MICs ranging from 0.5 to 8 mg/L. The recommended doses of linezolid for patients: 600 mg every 12 h for normal renal function or mild renal impairment, 300 mg every 12 h for severe renal impairment, 450 mg every 12 h for moderate renal impairment, and 600 mg every 8 h for supra-normal renal function. In conclusion, specific dosing regimens should be adopted for patients with varying renal functions, combined with therapeutic drug monitoring, to ensure the safety and efficacy of linezolid.