Machine learning in paediatric haematological malignancies: a systematic review of prognosis, toxicity and treatment response models.

Background: Machine Learning (ML) has demonstrated potential in enhancing care in adult oncology. However, its application in paediatric haematological malignancies is still emerging, necessitating a comprehensive review of its capabilities and limitations in this area.

Methods: A literature search was conducted through Ovid.

Role of thrombopoietin receptor agonists in chemotherapy-induced thrombocytopenia: A meta-analysis.

Introduction: Chemotherapy-induced thrombocytopenia (CIT) is a significant challenge in cancer treatment, often leading to dose reductions and reduced number of cycles. The limited effectiveness of platelet transfusions in managing CIT highlights the need for alternative treatments. Thrombopoietin receptor agonists (TPO-RA), including romiplostim, eltrombopag and avatrombopag, have shown potential in increasing platelet counts in CIT patients, necessitating a comprehensive analysis of their efficacy.