Epidemiology of Breed-Related Mast Cell Tumour Occurrence and Prognostic Significance of Clinical Features in a Defined Population of Dogs in West-Central Italy
Bibliographic record
Abstract
Canine mast cell tumours (MCTs) present a wide variety of challenging clinical behaviours in terms of predicting the prognosis and choosing appropriate treatment. This study investigated the frequency, risk, and prognostic factors of MCTs in dogs admitted to a single veterinary teaching hospital (VTH). Breed, age, sex, and sexual status in ninety-eight dogs with MCTs (MCT-group) were compared with a control group of 13,077 dogs (VTH-group) obtained from the VTH clinical database from January 2010 to January 2016. Within the MCT-group, signalment, location, size, mass number, ulceration, histopathological grading, presence of lymph node, or distant metastases were compared with each other and with the outcome. Boxers (OR 7.2), American Pit Bull Terriers (OR 5.4), French Bulldogs (OR 4.4) and Labrador Retrievers (OR 2.6) were overrepresented. The MCT-group was significantly older than the VTH-group (p < 0.0001). In comparison with the VTH group, in the MCT-group neutered dogs (OR 2.1) and spayed females (OR 2.3) were predominant compared to intact dogs and intact females, respectively. Ulceration (OR 5.2) and lymph node metastasis (OR 7.1) occurred more frequently in larger MCTs. Both ulceration and MCTs > 3 cm were highly associated with lymph node metastasis (OR 24.8). Recurrence was associated with MCT-related death (OR 10.50, p = 0.0040), and the latter was associated with shorter survival times (p = 0.0115). Dogs with MCTs > 3 cm (p = 0.0040), lymph node metastasis (p = 0.0234), or elevated WHO stage (p = 0.0158) had shorter survival times. A significantly higher frequency of MCTs was found in specific breeds, and in older and neutered dogs. MCTs > 3 cm and lymph node or distant metastases were associated with shorter survival times.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".