Large granular lymphocyte lymphoma in 65 dogs (2005–2023)
Bibliographic record
Abstract
Large granular lymphocyte lymphoma (LGLL) is a rare form of lymphoma in dogs. Limited information exists regarding presentation, treatment response, and outcome. The aim of this single-institute, retrospective study was to characterise clinical presentation, biologic behaviour, outcomes, and prognostic factors for dogs with LGLL. Cytologic review was also performed. Sixty-five dogs were included. The most common breed was the Labrador retriever (29.2%), and the most common presenting signs were lethargy (60.0%) and hyporexia (55.4%). The most common primary anatomic forms were hepatosplenic (32.8%) and gastrointestinal (20.7%). Twenty dogs (30.8%) had peripheral blood or bone marrow involvement. Thirty-two dogs were treated with maximum tolerated dose chemotherapy (MTDC) with a response documented in 74.1% of dogs. Dogs ≥7 years, and those with neutropenia or thrombocytopenia at diagnosis had the reduced likelihood of response to treatment. For dogs treated with MTDC median progression-free interval (PFI) was 17 days (range, 0-481), the median overall survival time (OST) 28 days (range, 3-421), and the 6-month and 1-year survival rates were 9.4% and 3.1%, respectively. On multivariable analysis, monocytosis and peripheral blood involvement were significantly associated with shorter PFI and OST. Long-term survival (≥100 days) was significantly associated with intermediate lymphocyte size on cytology. Dogs with LGLL have moderate response rates to chemotherapy but poor overall survival. Additional studies are needed to further evaluate prognostic factors and guide optimum treatment recommendations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".