Quantification of circulating tumour cells over time in dogs with appendicular osteosarcoma
Bibliographic record
Abstract
Abstract Enumeration of circulating tumour cells (CTC) has shown promise for prognostication and guidance of therapeutic decisions in human cancers. The objective of this study was to enumerate CTC over time in dogs with naturally occurring osteosarcoma (OSA), and to determine correlation with patient outcome. Twenty‐six dogs with OSA and no evidence of metastatic disease at the time of amputation were enrolled. Dogs were assessed for lung metastases and CTC prior to and following amputation, and at each chemotherapy visit. Twenty‐one dogs completed the study. Nineteen dogs were euthanized and two were alive and free of metastases. Overall survival time ranged from 88 to 1058 days (median survival time (MST) 374 days). Increased serum alkaline phosphatase activity, advanced age, and higher body weight were significantly associated with lower MST. Dogs with OSA had a mean of 356 (0 to 4443) CTC/106leukocytes. In 12 of 15 dogs that developed radiographic evidence of metastasis, a pre‐metastatic CTC spike was retrospectively detectable on average 36.5 (1–100 days) days prior to metastasis and was associated with significantly shorter MST (301 ± 64 vs. 626 ± 55 days;p = .0107). In a multivariable analysis, dogs with a CTC spike were 10× more likely to die compared with those without. These results suggest that a spike in CTC frequency precedes detection of metastasis in dogs with OSA and is associated with shorter survival. More frequent enumeration of CTC in a larger cohort of dogs with OSA may be 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 | 0.000 |
| 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".