The Impact of Pamidronate and Chemotherapy on Survival Times in Dogs with Appendicular Primary Bone Tumors Treated with Palliative Radiation Therapy
Bibliographic record
Abstract
OBJECTIVE: To assess survival times in dogs that received palliative radiation therapy (RT) alone, and in combination with chemotherapy, pamidronate, or both for primary appendicular bone tumors and determine whether the addition of these adjunctive therapies affects survival. STUDY DESIGN: Retrospective case series. ANIMALS: Dogs (n = 50) with primary appendicular bone tumors. METHODS: Dogs were divided into the following treatment groups: RT alone, RT + chemotherapy, RT+ pamidronate, and RT+ chemotherapy + pamidronate. Dogs were considered for analysis if they had a known euthanasia date or follow-up data were available for at least 120 days from the time of diagnosis. Survival time was defined as the time from admission to euthanasia. Cox proportional hazard models and Kaplan-Meier survival functions were used. A P value of less than .05 was considered significant. RESULTS: Fifty dogs were considered for survival analysis. Median survival times (MSTs) were longest for dogs receiving RT and chemotherapy (307 days; 95% CI: 279, 831) and shortest in dogs receiving RT and pamidronate (69 days; 95% CI: 47, 112 days). The difference in MST between dogs who received pamidronate and those who did not in this population was statistically significant in a univariate (P = .039) and multivariate analysis (P = .0015). The addition of chemotherapy into any protocol improved survival (P < .001). CONCLUSIONS: Chemotherapy should be recommended in addition to a palliative RT protocol to improve survival of dogs with primary appendicular bone tumors. When combined with RT ± chemotherapy, pamidronate decreased MST and should not be included in a standard protocol.
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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 | 0.000 | 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".