T‐cell large granular lymphocyte leukemia
Bibliographic record
Abstract
BACKGROUND: To the authors' knowledge, there is no standard treatment for patients with T-cell large granular lymphocyte (LGL) leukemia. Available data are limited by patient numbers and coexisting pathologies. METHODS: The authors report on the use of immunosuppressants (cyclosporin A [CSA] and low-dose oral methotrexate [MTX] given continuously) and cytotoxic agents in the treatment of 29 patients with T-cell LGL leukemia age over the past 20 years. RESULTS: The overall response rate (ORR) to MTX (n = 8 patients) was 85.7% (complete hematologic response [CHR] rate, 14.3%; partial response [PR] rate, 71.4%) with dose-dependent responses observed and safe usage of doses >10 mg/m2 per week in 2 patients. The ORR to CSA (n = 23 patients) was 78.2% (CHR rate, 30.4%; PR rate, 47.8%). The median time to response for both agents was 1 month. Toxicity, although it was minor in most patients and was more common in the CSA group, included second malignancies in 5 patients. An ORR of 67% (all CHR) was attained with pentostatin (n = 4 patients); recurrences developed after a median of 4.6 years. Successful retreatment with pentostatin was possible but with increasing drug resistance. Cyclophosphamide induced CHR that lasted >7 years with bone marrow clearance in 1 of 4 patients. Alemtuzumab induced a PR in 1 patient who had refractory disease. CONCLUSIONS: Both MTX and CSA were efficacious in the treatment of T-cell LGL leukemia but generally required long-term maintenance therapy. The authors highlight the risks of second malignancies and persistence of bone marrow disease. Although MTX and CSA were effective as first-line therapy, alemtuzumab and pentostatin merit further investigation, particularly for refractory disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".