Predictors of outcome in dogs treated with adjuvant carboplatin for appendicular osteosarcoma: 65 cases (1996–2006)
Bibliographic record
Abstract
OBJECTIVE: To determine outcomes and prognostic factors for those outcomes in dogs with appendicular osteosarcoma treated with curative-intent surgery and adjuvant carboplatin. DESIGN: Retrospective case series. ANIMALS: 65 client-owned dogs with appendicular osteosarcoma and no evidence of gross metastatic disease at the time of diagnosis. PROCEDURES: Medical records of dogs that underwent limb amputation or distal ulnectomy and adjuvant carboplatin treatment for appendicular osteosarcoma were reviewed. Adverse effects of chemotherapy and findings regarding preoperative biopsy specimens and postoperative diagnostic imaging were recorded. Signalment, clinical history, and chemotherapy variables were evaluated for associations with outcome. Histologic grade and other variables were evaluated for association with outcome for 38 tumors that were retrospectively graded. RESULTS: The median disease-free interval was 137 days (95% confidence interval [CI], 112 to 177 days). Median survival time was 277 days (95% CI, 203 to 355 days). The 1-, 2-, and 3-year survival rates were 36%, 22%, and 19%, respectively. None of the chemotherapy variables were associated with outcome. Preoperative proteinuria was the only clinical variable associated with poor outcome. Histologic features of tumors associated with a poor outcome were intravascular invasion, mitotic index > 5 in 3 microscopic hpfs, and grade III classification. CONCLUSIONS AND CLINICAL RELEVANCE: Carboplatin administration was well tolerated and resulted in a disease-free interval and median survival time similar to those of other published protocols.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".