Outcome and failure patterns of localized sinonasal lymphoma in cats treated with first‐line single‐modality radiation therapy: A retrospective study
Bibliographic record
Abstract
Failure rate and site are not well defined in localized sinonasal lymphoma in cats treated with radiotherapy. In this study, we describe (a) failure pattern, (b) outcome, (c) influence of previously reported prognostic variables on the outcome in cats with suspected localized sinonasal lymphoma. In this multi-institutional retrospective study, we included 51 cats treated with single-modality radiotherapy. Cats were irradiated using 10x4.2Gy (n = 32), 12x3Gy (n = 11) or 5x6Gy (n = 8). Regional lymph nodes were prophylactically irradiated in 24/51 cats (47.1%). Twenty-five cats (49.0%) developed progressive disease: progression was local (nasal) in five (9.8%), locoregional (nodal) in two (3.9%), local and locoregional in three (5.9%), systemic in nine (17.6%) and both local and systemic in six cats (11.8%). No cat receiving prophylactic nodal irradiation had progression in the locoregional lymph nodes. The median time to progression was 974 days (95%CI: 283;1666), with 58% and 53% of cats free of progression at 1 and 2 years, respectively. Median overall survival was 922 days (95%CI: 66;1779) with 61% and 49% alive at 1 and 2 years, respectively. Half of the cats that died of relapse/progression (13/26) died within 6 months of treatment, suggesting possible shortcomings of staging, rapid dissemination of disease or sequential lymphomagenesis. None of the prognostic factors evaluated were predictive of outcome (prednisolone use, anaemia, nasopharyngeal involvement, modified canine Adams tumour stage, protocol, total dose). Radiotherapy is an effective treatment for localized sinonasal lymphoma with a long time to progression. However, in one-third of the cats, systemic disease progression occurs soon after radiotherapy.
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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 | 0.001 | 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) | 0.001 | 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".