Adverse drug events (ADEs) risk signal mining related to eculizumab based on the FARES database.

Introduction: Eculizumab is a C5 complement inhibitor approved by the FDA for the targeted treatment of four rare diseases, paroxysmal nocturnal hemoglobinuria (PNH), atypical hemolytic uremic syndrome (aHUS), generalized myasthenia gravis (gMG), and aquaporin-4 immunoglobulin G-positive optic neuromyelitis optica spectrum disorders (AQP4-IgG+NMOSD). The current study was conducted to assess real-world adverse events (AEs) associated with eculizumab through data mining of the FDA Adverse Event Reporting System (FAERS).

Methods: Disproportionality analyses, including Reporting Ratio Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms were used to quantify the signals of eculizumab-associated AEs.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma.

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC.