Characteristics, clinical outcomes, and risk factors of SARS-COV-2 infection in adult acute myeloid leukemia patients: experience of the PETHEMA group.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection produces higher morbidity and mortality in hematological malignancies, but evidence in acute myeloid leukemia (AML) is scarce. A multicenter observational study was conducted to determine the clinical outcomes and assess the impact of therapeutic approaches in adult AML patients with SARS-CoV-2 infection in the first wave (March-May 2020). Overall, 108 patients were included: 51.9% with active leukemia and 70.4% under therapeutic schedules for AML. Signs and symptoms of SARS-CoV-2 were present in 96.3% of patients and 82.4% received specific treatment for SARS-CoV-2. The mortality rate was 43.5% and was correlated with age, gender, active leukemia, dyspnea, severe SARS-CoV-2, intensive care measures, neutrophil count, and D-dimer levels. A protective effect was found with azithromycin, lopinavir/ritonavir, and normal liver enzyme levels. During the SARS-CoV-2 first wave, our findings suggested an increased mortality in AML in a short period. SARS-CoV-2 management could be guided by risk factors in AML patients.

High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia.

Artificial intelligence methods may help in unveiling information that is hidden in high-dimensional oncological data. Flow cytometry studies of haematological malignancies provide quantitative data with the potential to be used for the construction of response biomarkers. Many computational methods from the bioinformatics toolbox can be applied to these data, but they have not been exploited in their full potential in leukaemias, specifically for the case of childhood B-cell Acute Lymphoblastic Leukaemia. In this paper, we analysed flow cytometry data that were obtained at diagnosis from 56 paediatric B-cell Acute Lymphoblastic Leukaemia patients from two local institutions. Our aim was to assess the prognostic potential of immunophenotypical marker expression intensity. We constructed classifiers that are based on the Fisher's Ratio to quantify differences between patients with relapsing and non-relapsing disease. We also correlated this with genetic information. The main result that arises from the data was the association between subexpression of marker CD38 and the probability of relapse.