Evaluation of the role of <i>TAX</i>, <i>HBZ</i>, and HTLV-1 proviral load on the survival of ATLL patients

Akbarin, Mohammad Mehdi; Shirdel, Abbas; Bari, Alireza; Mohaddes, Seyedeh Tahereh; Rafatpanah, Houshang; Karimani, Ehsan Ghayour; Etminani, Kobra; Golabpour, Amin; Torshizi, Reza

doi:10.5045/br.2017.52.2.106

Cited by 11 publications

(12 citation statements)

References 23 publications

(27 reference statements)

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“…However Both the chronic and acute group, as for the PCT group, presented high levels of LDH, emphasizing that the last group had the highest level of LDH, when compared to the others. The high level of LDH may be linked to more aggressive symptoms and directly related with the evolution of the disease, which is consistent with the findings of the present assessment, thus proposing that high levels of LDH may be a good indicator evolution and clinical aggressiveness 6,18,19,20 . It is important to highlight that in ATLL there is skin involvement and that it can occur in any clinical condition, be it less or more aggressive.…”

Section: Flow Cytometric Analysissupporting

confidence: 90%

“…In all the cases studied the individuals had dermatological lesions and in half of the cases evaluated, they were associated with another clinical condition. These showed advanced and aggressive ATLL form, which indicates that the clinical condition is an indicator of death evolution, as was also observed in the study by Akbarin et al (2017).…”

Section: Flow Cytometric Analysissupporting

confidence: 82%

“…It was observed a distinct pattern in the expression of molecular markers among ALL clinical pictures, suggesting that such behavior may reflect the pathway of clinical pathogenesis. It is generally observed that the ATLL phenotype is known to present simultaneous positivity for CD4 + CD25 +, as observed in the present study 6,14 .…”

Section: Flow Cytometric Analysissupporting

confidence: 81%

“…This disease has an unpleasant prognosis, rapid clinical evolution and diverse manifestations, and is commonly characterized by short survival time and poor response to chemotherapy, important points that are distinguished from other types of leukemias 5 . Differentiation between anomalous and normal cells is based on phenotypic patterns that are distinct in these cell populations 6 . Therefore, most patients that develop ATLL exhibit the phenotype mature CD4 + T cell and express some surface markers, partial loss or complete absence of others 7,8 .…”

Section: Introductionmentioning

confidence: 99%

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Clinical and laboratory characterization of adult T-cell leukemia/lymphoma in patients from Salvador, Bahia

Bomfim¹,

Santos²,

Freire³

et al. 2021

BJOncology

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ATLL is a malignant and aggressive leukemia whose survival time is limited. It is known that 5% of individuals infected with HTLV-1, after many years of latency, may develop this disease. The mechanisms by which the evolution of clinical conditions occurs are unknown, and in Brazil there are few studies about ATLL, this some important themes will be addressed in this study. Thus, the objective of this study is to characterize the epidemiological and immunophenotypic profile of patients diagnosed with ATLL, attended at an oncohematological reference center in Salvador, Bahia, in the period between 2010-2018. The methodology consisted of a descriptive, retrospective of time series study, which cases of ATLL were collected from reports belonging a reference laboratory and of medical reports available from Com-HUPES. These data were treated and analyzed statistically, being observed that the majority of cases were female and that a large part have the most aggressive clinical condition Although the literature reports that ATLL clinical condition are always considered as severe, in this study it was observed that patients can achieve long survival in good clinical conditions, according to the treatment administered. In view of the available results, it is possible to conclude that exist a broad distinction between the clinical and molecular forms, being may be an important indicator of the evolution of ATLL.

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Section: Flow Cytometric Analysissupporting

confidence: 90%

Section: Flow Cytometric Analysissupporting

confidence: 82%

Section: Flow Cytometric Analysissupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Clinical and laboratory characterization of adult T-cell leukemia/lymphoma in patients from Salvador, Bahia

Bomfim¹,

Santos²,

Freire³

et al. 2021

BJOncology

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“…Algorithm. ATLL is an advanced malignancy of adults' T cells and is the result of HTLV-1 infection [25,26]. Twenty-five ATLL patients, who were admitted to Jahad Daneshgahi Research Center from 2016 to 2018, were included.…”

Section: Imputation Of Atll Data Based On the Proposedmentioning

confidence: 99%

A Dynamic Model for Imputing Missing Medical Data: A Multiobjective Particle Swarm Optimization Algorithm

Almasinejad

Golabpour

Meybodi

et al. 2021

Journal of Healthcare Engineering

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Missing data occurs in all research, especially in medical studies. Missing data is the situation in which a part of research data has not been reported. This will result in the incompatibility of the sample and the population and misguided conclusions. Missing data is usual in research, and the extent of it will determine how misinterpreted the conclusions will be. All methods of parameter estimation and prediction models are based on the assumption that the data are complete. Extensive missing data will result in false predictions and increased bias. In the present study, a novel method has been proposed for the imputation of medical missing data. The method determines what algorithm is suitable for the imputation of missing data. To do so, a multiobjective particle swarm optimization algorithm was used. The algorithm imputes the missing data in a way that if a prediction model is applied to the data, both specificity and sensitivity will be optimized. Our proposed model was evaluated using real data of gastric cancer and acute T-cell leukemia (ATLL). First, the model was then used to impute the missing data. Then, the missing data were imputed using deletion, average, expectation maximization, MICE, and missForest methods. Finally, the prediction model was applied for both imputed datasets. The accuracy of the prediction model for the first and the second imputation methods was 0.5 and 16.5, respectively. The novel imputation method was more accurate than similar algorithms like expectation maximization and MICE.

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Gene expression study of host-human T-cell leukaemia virus type 1 (HTLV-1) interactions: adult T-cell leukaemia/lymphoma (ATLL)

Rahimzada,

Nahavandi,

Saffari

et al. 2023

Mol Biol Rep

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Evaluation of the role of TAX, HBZ, and HTLV-1 proviral load on the survival of ATLL patients

Cited by 11 publications

References 23 publications

Clinical and laboratory characterization of adult T-cell leukemia/lymphoma in patients from Salvador, Bahia

Clinical and laboratory characterization of adult T-cell leukemia/lymphoma in patients from Salvador, Bahia

A Dynamic Model for Imputing Missing Medical Data: A Multiobjective Particle Swarm Optimization Algorithm

Gene expression study of host-human T-cell leukaemia virus type 1 (HTLV-1) interactions: adult T-cell leukaemia/lymphoma (ATLL)

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