Canine Cutaneous Plasmacytosis: 21 Cases (2005–2015)
Bibliographic record
Abstract
BACKGROUND: Cutaneous plasmacytosis (CP) is a syndrome of multiple cutaneous plasma cell tumors, in the absence of multiple myeloma. Although rare in both humans and dogs, treatment recommendations are usually extrapolated from multiple myeloma protocols. To date, no case series of CP have been described in the veterinary literature. HYPOTHESIS/OBJECTIVES: To describe clinical presentation, determine treatment response rates and duration, and report overall survival of dogs with CP. ANIMALS: Twenty-one client-owned dogs with CP. METHODS: Medical records of 21 dogs with CP were reviewed. Diagnosis was based on histopathologic evaluation of at least 1 representative cutaneous or subcutaneous lesion in dogs with ≥3 lesions. Dogs with suspicion of multiple myeloma were excluded. RESULTS: The most commonly affected breeds were the golden (5/21) and Labrador retriever (3/21). Fourteen of 21 dogs had >10 lesions, with some having >100. Lesions commonly were described as round, raised, pink-to-red, and variably alopecic or ulcerated. The most commonly used drug protocol was combined melphalan and prednisone, with an overall response rate (ORR) of 73.7% (14/19 dogs). Single-agent lomustine was associated with a similar ORR of 71.4% (5/7 dogs). For all treatments combined, the median progression-free interval after the first treatment was 153 days. The median survival time from the first treatment was 542 days. CONCLUSIONS AND CLINICAL IMPORTANCE: Alkylating agents were effective in inducing remission of CP; corticosteroids, melphalan, and lomustine were the most commonly used drugs. Survival times were similar to those reported in dogs with multiple myeloma treated with alkylating agents.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".