A retrospective analysis of 11 dogs with surface osteosarcoma
Bibliographic record
Abstract
While the majority of canine osteosarcomas (OSA) arise from the medullary cavity, a subset arises from the surface of bone. In humans, surface OSA often has a more indolent disease course with better outcomes than medullary OSA. The aim of this retrospective case series was to evaluate the clinical outcome and potential prognostic factors of dogs with surface OSA. Medical records from 11 dogs previously diagnosed with surface OSA were included. Histopathology of cases was evaluated during case review by two veterinary anatomic pathologists. Median progression free interval (PFI) and overall median survival time (OST) were estimated using Kaplan-Meier methods. Intergroup comparisons were performed using log-rank tests. Six dogs were diagnosed with periosteal OSA, 4 dogs with parosteal OSA, and one dog with an unclassified surface OSA. Two dogs were found to have metastatic disease at the time of diagnosis and four developed metastatic lesions after treatment. The median PFI and median OST for all dogs with surface OSA was 425 and 555 days, respectively. The 6 dogs diagnosed with periosteal OSA had a median PFI of 461 days and median OST of 555 days, while the 4 dogs with parosteal OSA had a PFI of 350 days and the OST could not be calculated. Multiple prognostic factors (surgery, systemic adjunctive therapy, elevated alkaline phosphatase at diagnosis, appendicular vs axial location, mitotic count, and tumour grade) were evaluated and none were prognostic for PFI or OST. Dogs with surface OSA appear to have prolonged PFI and OST, consistent with humans with surface OSA.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".