A novel differential diagnosis algorithm for chronic lymphocytic leukemia using immunophenotyping with flow cytometry

Abstract Introduction The availability of a clinical decision algorithm for diagnosis of chronic lymphocytic leukemia (CLL) may greatly contribute to the diagnosis of CLL, particularly in cases with ambiguous immunophenotypes. Herein we propose a novel differential diagnosis algorithm for the CLL diagnosis using immunophenotyping with flow cytometry. Methods The hierarchical logistic regression model (Backward LR) was used to build a predictive algorithm for the diagnosis of CLL, differentiated from other lymphoproliferative disorders (LPDs). Results A total of 302 patients, of whom 220 (72.8%) had CLL and 82 (27.2%), B-cell lymphoproliferative disorders other than CLL, were included in the study. The Backward LR model comprised the variables CD5, CD43, CD81, ROR1, CD23, CD79b, FMC7, sIg and CD200 in the model development process. The weak expression of CD81 and increased intensity of expression in markers CD5, CD23 and CD200 increased the probability of CLL diagnosis, (p < 0.05). The odd ratio for CD5, C23, CD200 and CD81 was 1.088 (1.050 - 1.126), 1.044 (1.012 - 1.077), 1.039 (1.007 - 1.072) and 0.946 (0.921 - 0.970) [95% C.I.], respectively. Our model provided a novel diagnostic algorithm with 95.27% of sensitivity and 91.46% of specificity. The model prediction for 97.3% (214) of 220 patients diagnosed with CLL, was CLL and for 91.5% (75) of 82 patients diagnosed with an LPD other than CLL, was others. The cases were correctly classified as CLL and others with a 95.7% correctness rate. Conclusions Our model highlighting 4 markers (CD81, CD5, CD23 and CD200) provided high sensitivity and specificity in the CLL diagnosis and in distinguishing of CLL among other LPDs.

Comparative evaluation of memory T cells in COVID-19 patients and the predictive role of CD4+CD8+ double positive T lymphocytes as a new marker

SUMMARY BACKGROUND: The COVID-19 pandemic has affected the entire world, posing a serious threat to human health. T cells play a critical role in the cellular immune response against viral infections. We aimed to reveal the relationship between T cell subsets and disease severity. METHODS: 40 COVID-19 patients were randomly recruited in this cross-sectional study. All cases were confirmed by quantitative RT-PCR. Patients were divided into two equivalent groups, one severe and one nonsevere. Clinical, laboratory and flow cytometric data were obtained from both clinical groups and compared. RESULTS: Lymphocyte subsets, CD4+ and CD8+ T cells, memory CD4+ T cells, memory CD8+ T cells, naive CD4+ T cells, effector memory CD4+ T cells, central memory CD4+ T cells, and CD3+CD4+ CD25+ T cells were significantly lower in severe patients. The naive T cell/CD4 + EM T cell ratio, which is an indicator of the differentiation from naive T cells to memory cells, was relatively reduced in severe disease. Peripheral CD4+CD8+ double-positive T cells were notably lower in severe presentations of the disease (median DP T cells 11.12 µL vs 1.95 µL; p< 0.001). CONCLUSIONS: As disease severity increases in COVID-19 infection, the number of T cell subsets decreases significantly. Suppression of differentiation from naive T cells to effector memory T cells is the result of severe impairment in adaptive immune functions. Peripheral CD4+CD8+ double-positive T cells were significantly reduced in severe disease presentations and may be a useful marker to predict disease severity.

RESUMO OBJETIVO: A pandemia de COVID-19 tem afetado o mundo todo, constituindo uma ameaça grave para a saúde humana. As células T desempenham um papel crítico na imunidade celular contra infecções virais. Procuramos desvendar a relação entre sub grupos de células T e a severidade da doença. MÉTODOS: Um total de 40 pacientes com COVID-19 foram aleatoriamente recrutados para o presente estudo transversal. Todos os casos foram confirmados por RT-PCR quantitativo. Os pacientes foram divididos em dois grupos equivalentes, um grave e um não-grave. Os dados da avaliação clínica, laboratorial e da citometria de fluxo foram obtidos para ambos os grupos e comparados. RESULTADOS: Os subconjuntos de linfócitos, células T CD4+ e CD8+, células T de memória CD4+, células T de memória CD8+, células T CD4+ virgens, células T efetoras CD4+, células T de memória central CD4+ e células T CD3+ CD4+ CD25+ estavam significativamente mais baixas nos pacientes graves. A razão células T virgens/células T efetoras TCD4+, que é um indicador da diferenciação entre células T virgens e células de memória, estava relativamente reduzida em casos graves da doença. As células T duplo-positivas CD4+CD8+ periféricas estavam notavelmente mais baixas em casos graves da doença (mediana das células T DP: 11,12 µL vs. 1,95 µL; p< 0,001). CONCLUSÃO: Conforme aumenta a gravidade da doença nos casos de COVID-19, o número de subconjuntos de células T diminui significativamente. A supressão da diferenciação de células T virgens para células T efetoras é o resultado do comprometimento grave das funções imunológicas adaptativas. As células T duplo-positivas CD4+CD8+ periféricas estavam notavelmente mais baixas em casos graves da doença e podem ser um marcador útil para predizer a severidade da doença.