Additional Local Therapy With Primary Re‐Excision or Radiation Therapy Improves Survival and Local Control After Incomplete or Close Surgical Excision of Mast Cell Tumors in Dogs
Bibliographic record
Abstract
OBJECTIVE: To compare survival and local recurrence outcomes in dogs with mast cell tumors with incomplete or close margins treated with primary re-excision or radiation therapy of the primary site versus no additional local therapy. STUDY DESIGN: Retrospective case series. ANIMALS: Dogs (n = 64). METHODS: Outcomes of canine mast cell tumor cases that had incomplete or close surgical resection and presented to the Ontario Veterinary College Health Sciences Centre (2001-2010) were evaluated after additional local therapy (primary re-excision or radiation therapy) or no additional local therapy (comparison). Follow-up was performed through evaluation of medical records and telephone contact with referring veterinarians and owners. RESULTS: Tumors (n = 70) in 64 dogs were studied. Median survival times for the primary re-excision (2930 days) and radiation therapy (2194 days) groups were significantly longer than for the comparison (710 days) group. Local recurrence occurred in 13% of the re-excision group, 8% of the radiation therapy group, and 38% of the comparison group. Although local recurrence rate was not statistically significant for the re-excision group, time to local recurrence was statistically longer for both the re-excision and radiation groups. Adjunctive chemotherapy was not associated with improved survival or local control. CONCLUSION/CLINICAL RELEVANCE: There is significant improvement in survival and duration of local control when additional local therapy is performed after incomplete or close resection of mast cell tumors. These follow-up therapies should be recommended to owners when mast cell tumors are incompletely or closely resected.
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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) | 0.001 | 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".