Appendicular osteosarcoma in small-breed dogs: 51 cases (1986–2011)
Bibliographic record
Abstract
OBJECTIVE: To describe outcomes for small-breed dogs with appendicular osteosarcoma. DESIGN: Multi-institutional retrospective case series. ANIMALS: 51 small-breed dogs. PROCEDURES: Records from participating Veterinary Society of Surgical Oncology members were searched for dogs that weighed ≤ 15 kg (33 lb) with a histologic diagnosis of appendicular osteosarcoma. The Kaplan-Meier method was used to determine median survival times (MSTs), and Cox regression was performed to identify variables associated with survival time. RESULTS: Tumors were most commonly located on the humerus (n = 15) and femur (14). Of the 51 study dogs, 9 were treated nonsurgically, 16 underwent amputation of the affected limb only, and 26 underwent curative-intent treatment, with MSTs of 112, 257, and 415 days, respectively. The MST did not differ significantly between dogs in the amputation-only and curative-intent groups. For dogs in the nonsurgical group, MST decreased significantly as the tumor histologic score increased. For dogs in the amputation-only group, MST decreased as body weight increased. CONCLUSIONS AND CLINICAL RELEVANCE: For the small-breed dogs with appendicular osteosarcoma of the present study, tumor histologic grade and mitotic index were subjectively lower and MST following amputation of the affected limb without adjuvant chemotherapy was longer, compared with those for similarly affected larger dogs. Results indicated no significant advantage in MST for dogs that underwent curative-intent treatment versus dogs that underwent amputation only, and further investigation of the importance of adjuvant chemotherapy is warranted.
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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) | 0.002 | 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".