Canine lymphoma in Croatia: a fourteen-year retrospective study
Bibliographic record
Abstract
BACKGROUND: Lymphoma is the most prevalent hematopoietic system tumor in dogs and holds significant clinical importance in veterinary medicine. However, the epidemiology of canine lymphoma in Croatia remains understudied. This retrospective study aims to describe the predominant lymphoma types in this population over 14 years and evaluate associations with sex, breed, and age. RESULTS: Among 28,681 canine cases referred to the Department of Veterinary Pathology, University of Zagreb, from 2009 to 2023, a total of 374 cases (1.30%) were diagnosed with lymphoma. Of these, 282 cases (75.40%) were purebred dogs, with the most affected breeds being Golden Retrievers (23, 6.15%), Labrador Retrievers (23, 6.15%), German Shepherds (14, 3.74%), and Boxers (14, 3.74%). Bullmastiffs (8.14%) had the highest number of lymphoma diagnoses among the referred breeds, followed by Airedale Terriers (6.67%) and German Shepherds (5.09%). The Maltese, though a popular breed, showed a low lymphoma rate of 0.40%, indicating no notable predisposition. Multicentric lymphoma (59, 53.64%) was the most common anatomical classification, followed by cutaneous (33, 30.00%) and alimentary lymphoma (13, 11.82%). The mean age at diagnosis was 8.27 ± 3.07 years, with most cases occurring between 5 and 10 years (207, 55.35%). Males (216, 57.75%) were more frequently affected than females (158, 42.24%), except among Golden Retrievers, where 69.56% of cases were female. CONCLUSION: Our study reveals that the distribution of dogs with lymphomas, including type and anatomical classification, in terms of breed, sex and age, is consistent with existing literature, except in the cases of Golden Retrievers, Basset Hounds, and Scottish Terriers. Further molecular and environmental studies are recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".