United European Gastroenterol J
December 2024
Background: Eosinophilic esophagitis (EoE) predominantly affects males across all ages; however, little is known about sex differences for other aspects of EoE.
Objective: To investigate associations between sex and clinical presentation, endoscopic features, treatment choice and response in EoE patients in real-world practice.
Methods: Cross-sectional analysis of the multicenter EoE CONNECT registry.
Background: Metastatic breast cancer (MBC) is incurable. Systemic therapy is the standard treatment; however, an optimal sequence of chemotherapy has not been established.
Objective: Evaluating effectiveness and safety of eribulin in MBC treatment and comparing the results obtained with published literature.
Purpose: Lenalidomide remains an effective drug for multiple myeloma, but it is often associated with adverse events and requires dose adjustments. The objective of this study was to propose a model for predicting whether a patient would require dose adjustment.
Methods: This retrospective observational study included patients treated with lenalidomide and dexamethasone from June 2014 to September 2018 at a tertiary hospital.
Anticancer Res
April 2023
Background/aim: This study aimed to assess the effectiveness and safety of nivolumab versus cetuximab in patients with Recurrent/Metastatic Squamous Cell Carcinoma of the Head and Neck (R/M HNSCC), as well as to analyze possible prognostic factors for response to treatment with nivolumab.
Patients And Methods: We conducted an observational, retrospective, descriptive study of patients with R/M HNSCC who initiated treatment with nivolumab or cetuximab monotherapy in two periods of equivalent duration. Overall efficacy was measured in terms of progression-free survival (PFS) and overall survival (OS).
Introduction: Linezolid is an antimicrobial with broad activity against Gram-positive bacteria. Thrombocytopenia is one of its most common side effects often leading to severe complications. The aim of this study is to identify factors related with development of this condition in critically ill patients and to develop and evaluate a predictive machine learning-based model considering easy-to-obtain clinical variables.
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