Publications by authors named "C Blazquez-Goni"

Introduction: This systematic review, adhering to PRISMA guidelines, aimed to evaluate the efficacy and safety of antiemetic prophylaxis in haematological patients undergoing high-dose chemotherapy as part of their hematopoietic stem cell transplantation (HSCT) conditioning regimens.

Methods: We performed a comprehensive search in PubMed, EMBASE, ClinicalTrials.gov and the Cochrane database to identify randomised controlled trials (RCTs) and systematic reviews of antiemetic prophylaxis.

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Objective: Chemotherapy-induced nausea and vomiting continue to pose a significant challenge for patients undergoing hematopoietic stem cell transplantation. This study aims to synthesize available evidence on antiemetic prophylaxis regimens in patients with hematologic malignancies undergoing hematopoietic stem cell transplantation, in order to identify the best standard of care.

Methods: A systematic review will be conducted using MEDLINE via PubMed, EMBASE, ClinicalTrials.

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Background: Dyskeratosis congenita (DC) is a multisystem and ultra-rare hereditary disease characterized by somatic involvement, bone marrow failure, and predisposition to cancer. The main objective of this study is to describe the natural history of DC through a cohort of patients diagnosed in childhood and followed up for a long period of time.

Material And Methods: Multicenter, retrospective, longitudinal study conducted in patients followed up to 24 years since being diagnosed in childhood (between 1998 and 2020).

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Article Synopsis
  • Children with a type of cancer called acute lymphoblastic leukaemia (ALL) usually have good chances of survival, but some of them might get sick again (called relapse).
  • Researchers are using a special method called topological data analysis (TDA) to look at patient data and predict who is more likely to relapse, especially those who were thought to be low risk.
  • They suggest three ways to analyze data to help doctors understand the risks better, using things like visual checks or advanced math and machine learning with certain important markers (CD10, CD20, CD38, and CD45).
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