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Case Report of Aggressive T-Cell Large Granular Lymphocytic Leukemia

2017· article· en· W2943086918 on OpenAlexaff
Vanessa Brunet, Michel Pavic, Isabelle Fleury, Jean‐François Castilloux, Sofia Marouan

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-RosemontUniversité de Sherbrooke
Fundersnot available
KeywordsPancytopeniaLymphocytosisMedicineCytopeniaLeukemiaPathologySplenectomyBone marrowProlymphocytic leukemiaImmunologyGastroenterologyChronic lymphocytic leukemiaSpleen

Abstract

fetched live from OpenAlex

Abstract Large granular lymphocyte (LGL) leukemia is a spectrum of rare lymphoproliferative disorders. Two entities are reported: indolent T-cell LGL leukemia and aggressive NK cell leukemia. However, a review of the literature identified cases of aggressive T-cell LGL. Considering this unusual and rare clinical presentation, we are reporting a case of aggressive T-cell LGL leukemia. A 53-yo man presented in May 2014 with a one year history of constitutional symptoms, splenomegaly, mild lymphocytosis and a pancytopenia (hemoglobin 105 g/L, neutrophils 0,5 x 109 /L and platelets 80 x 109 /L). He had similar symptoms at the age of 24 that resolved without further investigation. Bone marrow evaluation revealed a massive infiltration by small to medium sized lymphocytes with irregular nucleus CD3 +, CD4 -, CD7 -, CD8 +, CD25 -, CD33 -, CD34 -, CD56 -, CD57 -, TCRαβ+. HTLV-1 serology was negative. His pancytopenia did not improve with 3 cycles of CHOP followed by 4 cycles of ESHAP. In January 2015, indolent T LGL was finally retained. The patient was observed up to July 2015 where methotrexate was begun because of frequent infections and symptomatic splenomegaly. A splenectomy was performed in January 2016 due to a toxicity to methotrexate and persistent symptoms from splenomegaly. Pathology report showed a splenic and lymph node infiltration by mature T CD8+ lymphocytes supporting the T LGL diagnosis. Post splenectomy, cytopenia improved and progressed in June 2016 with a lymphocytosis (82 x 109/L), new lung infiltrates and acute renal insufficiency. The lung biopsy revealed an infiltration by the T-cell LGL and renal imaging suggested infiltration by this T-cell LGL as well. Based on the weak expression of CD20+ on the splenic pathology, rituximab was attempted in August 2016. The patient rapidly progressed fatally with systemic involvement of T-cell LGL (skin, lungs, liver, kidney, facial cranial nerves, conus medullaris and bone marrow). This case therefore depicts a very aggressive case of T-cell LGL with an atypical clinical presentation. In contrast to the indolent variant and as seen in the few similar cases retrieved in literature, the clinical presentation of the aggressive T-cell LGL leukemia is characterized by constitutional symptoms, rapidly progressive hepatosplenomegaly, cytopenia with/without organic infiltration and an important resistance to treatment. Moreover, concerning the pathological findings, the medullary involvement of our patient was massive without real images of intra-sinusal lymphocytosis and the T-cell of this T-cell LGL were atypical because of their small-medium size with slightly irregular nuclei and the lack of expression of CD56 and CD57. However, the few studies on aggressive T-cell LGL leukemia retrieved similar findings. Even though there is no consensus on the optimal therapeutic management of this disease, we believe that the treatments given to our patient were consistent with literature and did not add an additional mortality risk. To conclude, LGL cell leukemia represent a spectrum of indolent and aggressive diseases, whereby an indolent form can evolve into an aggressive form. Aggressive T-cell LGL leukemia are characterized by a multisystem disease, an atypical immunophenotype (CD56-, CD57-) and are associated with an uncertainty regarding therapeutics. Download : Download high-res image (70KB) Download : Download full-size image Figure 1 . Disclosures Fleury: Gilead: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.307
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2017
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