Hepatosplenic Alpha-Beta T-Cell Lymphoma: A Challenging Diagnostic Entity
Bibliographic record
Abstract
Hepatosplenic T-cell lymphoma (HSTCL) is rare and clinically very aggressive T-cell lymphoma. The majority of cases harbor GAMMA DELTA T-cell receptors (TCRs); however, in some even rarer cases, tumor cells harbor αβ TCR. Recent studies suggest that αβ cases may have distinct morphological characteristics and demonstrate an even more aggressive course. In this case report, we demonstrated that in line with previous findings, αβ case of HSTCL had hemolytic presentation, demonstrated a very aggressive clinical course, and was unrelated to immunosuppression. Morphologically, tumor cells demonstrated diffuse growth pattern, blastoid morphology, and were CD8 + positive on the background of CD4 + small to medium reactive T cells. Additionally, the liver tumor cells demonstrated periportal localization, and in bone marrow, evidence of emperipolesis was noted. The latter finding may significantly contribute to pancytopenia characteristic, all types of HSTCL. Those unusual morphologic and clinical characteristics make diagnosis of this rare subtype of rare disease very challenging. More case analysis is required to establish whether αβ/γδ HSTCL are prognostically or morphologically significantly distinct entities. J Hematol. 2024;13(1-2):29-33 doi: https://doi.org/10.14740/jh1203
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".