Auranofin improves overall survival when combined with standard of care in a pilot study involving dogs with osteosarcoma
Bibliographic record
Abstract
Osteosarcoma is the most common paediatric primary bone malignancy. The major cause of death in osteosarcoma is drug-resistant pulmonary metastasis. Previous studies have shown that thioredoxin reductase 2 is a driver of metastasis in osteosarcoma and can be inhibited by auranofin (AF). Moreover, studies have shown that AF significantly reduces pulmonary metastases in xenotransplant models. Here, we describe a phase I/II study of AF in canine osteosarcoma, a well-recognized spontaneous model of human osteosarcoma. We performed a single-arm multicentre pilot study of AF in combination with standard of care (SOC) (amputation + carboplatin). We recruited 40 dogs to the trial and used a historical SOC-only control group (n = 26). Dogs >15 kg received 9 mg AF q3d PO and dogs <15 kg received 6 mg q3d. Follow-up occurred over at least a 3-year period. Auranofin plus SOC improved overall survival (OS) (P = .036) in all dogs treated. The improved outcome was attributable entirely to improved OS in male dogs (P = .009). At the time of writing, 10 dogs (25%) survive without measurable disease in the treatment group with survival times ranging between 806 and 1525 days. Our study shows that AF improves OS in male dogs when combined with SOC. Our findings have translational relevance for the management of canine and human osteosarcoma. Our data justify a larger multicentre phase 2 trial in dogs and a phase I/II trial in human patients with refractory disease at the time of initial surgery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".