Retrospective analysis of carboplatin-induced cumulative neutropenia in cancer-bearing dogs
Bibliographic record
Abstract
OBJECTIVE: To determine the clinical significance of performing repeated postchemotherapy CBC for cancer-bearing dogs receiving ≥ 4 carboplatin treatments. The secondary aim was to identify risk factors associated with cumulative carboplatin-induced neutropenia in those dogs. ANIMALS: 40 client-owned dogs diagnosed with cancer. METHODS: A retrospective study using medical records from a single academic institution during 2012 to 2023. Dogs that received ≥ 4 doses of carboplatin with pre- and postchemotherapy CBCs available were included. Signalment and possible risk factors were recorded. Veterinary Cooperative Oncology Group-Common Terminology Criteria for Adverse Events was used for neutropenia grading. RESULTS: 40 dogs met the inclusion criteria, with a total of 206 prechemotherapy and 188 postchemotherapy CBC results available. The median carboplatin dosage was 300 mg/m2 (range, 200 to 300 mg/m2). The median interval between carboplatin administration and the postchemotherapy CBC was 10 days (range, 6 to 38 days). Eleven dogs developed a grade 2 or higher neutropenia, with 5 dogs developing multiple neutropenic events, for a total of 18 separate events (18/394). Only 2 of 18 neutropenic events were recorded at the 10- to 14-day postchemotherapy CBC. The yield of detecting neutropenia at a postchemotherapy CBC at any carboplatin chemotherapy after the second dose was < 1% (1/149). Dogs that developed neutropenia at the pre-2nd chemotherapy CBC had a significantly higher risk of developing another neutropenic event at subsequent prechemotherapy CBC (P < .001). CLINICAL RELEVANCE: The incidence of cumulative neutropenia after 4 to 6 doses of carboplatin is low in cancer-bearing dogs. If a grade 2 or higher neutropenia is observed at or before the second prechemotherapy CBC, the dog is at a higher risk of developing neutropenia following future treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".