Publications by authors named "E K Minga"
Article Synopsis
- The study focuses on chronic diseases like Chronic Lymphocytic Leukemia (CLL), which exhibit diverse outcomes, highlighting the need for better predictive models.
- A machine learning approach is used to forecast patient outcomes, aiming to enhance the reliability of these predictions in treating complex conditions.
- Conformal Prediction is integrated into the model to measure uncertainty and deliver personalized predictions, making the results more applicable in clinical settings.
Relying on our experience on the development of data registration and management systems for clinical and biological data coming from patients with hematological malignancies, as well as on the design of strategies for data collection and analysis to support multi-center, clinical association studies, we designed a framework for the standardized collection and transformation of clinically relevant real-world data into evidence, to meet the challenges of gathering biomedical data collected during daily clinical practice in order to promote basic and clinical research.
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- Patients with chronic lymphocytic leukemia (CLL) have a significantly heightened risk of developing other malignancies (OMs), with a study tracking nearly 20,000 CLL patients revealing 3,513 OMs diagnosed over 129,254 years of follow-up.
- The study found that treatment with fludarabine and cyclophosphamide increased the likelihood of developing myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), while non-melanoma skin cancer (NMSC) and prostate cancer were common solid tumors in treated patients.
- Importantly, patients with CLL who developed OMs had lower overall survival rates, especially those diagnosed with AML and MDS, highlighting that C
In this retrospective international multicenter study, we describe the clinical characteristics and outcomes of patients with chronic lymphocytic leukemia (CLL) and related disorders (small lymphocytic lymphoma and high-count monoclonal B lymphocytosis) infected by SARS-CoV-2, including the development of post-COVID condition. Data from 1540 patients with CLL infected by SARS-CoV-2 from January 2020 to May 2022 were included in the analysis and assigned to four phases based on cases disposition and SARS-CoV-2 variants emergence. Post-COVID condition was defined according to the WHO criteria.
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