Toceranib phosphate-associated nephrotic syndrome in a dog: a case report
Bibliographic record
Abstract
BACKGROUND: Nephrotic syndrome (NS) is rare in dogs and is characterized by concurrent clinical findings of proteinuria, hyperlipidemia, hypoalbuminemia, and edema. NS has been reported in humans receiving tyrosine kinase inhibitors (TKI) and in dogs receiving masitinib. This is the first report of NS in a dog receiving toceranib phosphate. CASE PRESENTATION: An 8-year-old, female, spayed Labrador retriever was diagnosed with a 10 cm mast cell tumor on the left lateral abdomen. After completion of a 12-week vinblastine and prednisone protocol, she began treatment with toceranib phosphate (2.6 mg/kg by mouth, every other day). Proteinuria was documented prior to starting toceranib. On day 426 after diagnosis (day 328 of toceranib phosphate treatment), the dog was evaluated for diarrhea, lethargy and anorexia. On physical examination, dependent edema was noted on the ventral chest and abdomen, and sterile neutrophilic inflammation was aspirated from a 2.3 cm splenic nodule. The following laboratory values were reported: albumin < 1.5 g/dL; cholesterol 378 mg/dl and urine protein to creatinine ratio of 3.79. The patient was diagnosed with NS, and treatment with toceranib phosphate was discontinued. Low-dose aspirin was started in addition to an increased dosage of enalapril (0.47 mg/kg q12hr). No other therapy was instituted. The dog improved clinically, and laboratory values returned to near normal over the 8-week follow-up. She was euthanized 1399 days after discontinuing toceranib phosphate with progressive disease. CONCLUSIONS: Nephrotic syndrome is a potential adverse event associated with the drug toceranib phosphate which may be reversible with discontinuation of treatment. Careful monitoring of urine protein, serum biochemistry, blood pressure and patient weight is advisable during treatment with toceranib phosphate.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".