Conectar
by Yu Cui, Yuxuan Gao, Na Meng, Xiaojuan Li, Na Zhao, Lili Yu
Atezolizumab is a widely used immune checkpoint inhibitor (ICI) for cancer treatment, and postmarketing testing is important. This study aims to provide a reference for the safe and rational use of drugs in clinical practice by mining and analyzing the adverse event (AE) signals of atezolizumab on the basis of the FDA Adverse Event Reporting System (FAERS). This research extracted AE reports from the second quarter (Q2) of 2016 to Q2 of 2024 from the FAERS. AEs were standardized and classified on the basis of the System Organ Class (SOC) and Preferred Term (PT) from the Medical Dictionary for Regulatory Activities (MedDRA) version 23.0. This study utilized disproportionality analysis (DPA) for signal mining and analysis, including the reporting odds ratio (ROR) method, the Medicines and Healthcare Products Regulatory Agency (MHRA) method, and the Bayesian confidence propagation neural network (BCPNN) method. We obtained a total of 3,124 AE signals and identified 640 PTs and 21 SOCs for atezolizumab. The highest signal intensity was systemic immune activation (n = 15, ROR = 449.20, PRR = 449.07, IC = 8.06), and the most frequently reported AEs were death, pyrexia, infectious pneumonia, anaemia, and febrile neutropenia. The top 100 PTs in terms of signal intensity involved a total of 16 SOCs, including those associated with endocrine disorders; respiratory, thoracic and mediastinal disorders; and renal and urinary disorders. This study revealed that AEs in the endocrine, respiratory and urinary systems need to be monitored in clinical practice.by Linna Zhao, Juanjuan Zhang, Weizhe Liu, Cheng Dai, Aiying Li
Diabetes mellitus (DM) is identified as a potential modifier of clinical outcomes in acute heart failure (AHF), yet its prognostic impact is not fully determined. This systematic review and meta-analysis aimed to assess the prognostic impact of DM on survival outcomes in AHF patients by synthesizing evidence from 26 studies involving 326,928 subjects collected from Cochrane Library, PubMed, Web of Science, and Embase databases up to 1 June 2024. Both prospective/retrospective cohort and case-control studies published since 2000 were included, with outcomes evaluated through multivariate, univariate, and binary analyses using the Newcastle-Ottawa Scale for quality assessment. Multivariate analysis indicated that DM significantly increased the risk of all-cause mortality in AHF patients (cohort studies: HR = 1.21, 95%CI (1.13, 1.29), OR=1.15, 95%CI (1.05, 1.26); case-control studies: HR = 1.39, 95%CI (1.26, 1.53), OR=1.43, 95%CI (1.10, 1.84)]. Univariate analysis confirmed this finding in case-control studies [HR = 1.30, 95%CI (1.01, 1.67)], but not in cohort studies. In both cohort [RR = 1.27, 95%CI (1.12, 1.43)] and case-control [OR=1.21, 95%CI (1.08, 1.35)] studies, DM increased the risk of all-cause mortality. AHF patients with DM had a higher risk of cardiovascular mortality [cohort studies: HR = 1.85, 95%CI (1.46, 2.33); case-control: OR=1.70, 95%CI (1.17, 2.47)]. While multivariate analysis showed no association between DM and in-hospital mortality, case-control studies indicated an increased risk [OR=1.21, 95%CI (1.03, 1.42)]. DM also increased the risk of readmission [cohort studies: HR = 1.32, 95%CI (1.14, 1.53); case-control studies: HR = 1.44, 95%CI (1.23, 1.69); binary data: OR=1.19, 95%CI (1.07, 1.31)].This updated meta-analysis demonstrates that DM imposes significant adverse effects on all-cause mortality, cardiovascular-related mortality, and readmission risk in AHF patients. However, no significant connection was found between diabetes and survival outcomes with respect to the co-endpoint of death or readmission and the endpoint of in-hospital mortality. These findings underscore the necessity for implementing targeted diabetes management within AHF care protocols to enhance clinical outcomes, an essential consideration for future practice.
FreshRSS