Publications by authors named "L Guarnera"
Acute promyelocytic leukemia (APL) is a rare type of AML, characterized by the t(15;17) translocation and accounting for 8-15% of cases. The introduction of target therapies, such as all-trans retinoic acid (ATRA) and arsenic trioxide (ATO), radically changed the management of APL, making it the most curable AML subtype. However, a small percentage (estimated to be 2%) of AML presenting with APL-like morphology and/or immunophenotype lacks t(15;17).
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- Artificial intelligence, particularly machine learning, is transforming biomedical research, especially in hematologic malignancies and myeloid neoplasia, through improved diagnostics and predictions.
- Despite promising results from ML applications, none have yet been fully adopted in clinical practice due to challenges like limited familiarity among hematologists and patient concerns over privacy and reliability.
- The review discusses the mechanisms and applications of machine learning, focusing on hematologic conditions, and aims to highlight both the strengths and limitations for future clinical use.
Past studies described occasional patients with myeloid neoplasms (MN) and coexistent large granular lymphocytic leukemia (LGLL) or T-cell clonopathy of unknown significance (TCUS), which may represent expansion of myeloid clonal hematopoiesis (CH) as triggers or targets of clonal cytotoxic T cell reactions. We retrospectively analyzed 349 LGLL/TCUS patients, 672 MN patients, and 1443 CH individuals to establish the incidence, genetic landscape, and clinical phenotypes of CH in LGLL. We identified 8% of cases overlapping with MN, while CH was found in an additional 19% of cases (CH + /LGLL) of which TET2 (23%) and DNMT3A (14%) were the most common.
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