Prior joint disease is associated with increased risk of periarticular histiocytic sarcoma in dogs
Bibliographic record
Abstract
Periarticular histiocytic sarcoma (PAHS) is the most common synovial tumour in dogs and is characterized by aggressive local disease with a high rate of distant metastasis. Previously, an association between PAHS and prior joint disease has been demonstrated in the Bernese Mountain Dog breed and suggested in the Rottweiler. We hypothesized that this association would be present in other breeds and investigated this via a retrospective, case-controlled analysis. Cases were dogs diagnosed with PAHS of the stifle or elbow. Controls were age, breed and sex-matched dogs without a diagnosis of histiocytic sarcoma. Diagnosis of prior joint disease was determined based on review of medical records and direct veterinarian and owner communications. Data were evaluated using logistic regression, 2-sampled t tests, and chi-squared analysis. Our study population consisted of 28 cases and 46 controls, including Flat-Coated, Golden and Labrador Retrievers, Rottweilers, English Bulldogs, Shih Tzus, Australian Shepherds, Staffordshire Terriers and mixed breed dogs. Dogs with PAHS were more likely to have prior joint disease in the tumour-affected joint compared with the control population (odds ratio [OR] = 13.42, P < .0001, 95% confidence interval [CI] = 4.33-48.63). A total of 88.2% of dogs with stifle PAHS had prior joint disease in their tumour-affected joint, most commonly cranial cruciate ligament rupture. This study confirms that the previously noted association between prior joint disease and PAHS in Bernese Mountain Dogs also applies to other breeds. Additional studies are needed to further investigate for a causal relationship.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".