Outcome and Prognostic Factors for Canine Splenic Lymphoma Treated by Splenectomy (1995–2011)
Bibliographic record
Abstract
OBJECTIVE: To assess the outcome of canine splenic lymphoma treated with splenectomy and to evaluate prognostic factors, including involvement of other sites, adjuvant chemotherapy, and the effect of World Health Organization (WHO) histological classification of canine malignant lymphoma. DESIGN: Multi-institutional, retrospective study. ANIMALS: Client-owned dogs (n = 28). METHODS: Medical records (1995-2011) of dogs with a histological diagnosis of splenic lymphoma and treated by splenectomy submitted by Veterinary Society of Surgical Oncology members were reviewed. Included were dogs treated with or without adjuvant therapy. Overall survival, disease-free interval, and cause of death were determined. Prognostic factors and the WHO histological classification of canine malignant lymphoma were evaluated with respect to outcome. RESULTS: Dogs with splenic lymphoma treated by splenectomy had a 1-year survival rate of 58.8%, after which no animals died of their disease. B cell lymphoma held a better prognosis for survival than other variants of splenic lymphoma. Marginal zone lymphoma and mantle cell lymphoma were the most common B cell lymphoma subtypes in our study. Hemoabdomen and clinical signs related to splenic lymphoma, including abdominal distention, lethargy, and anorexia, were poor prognostic indicators, whereas disease confined to the spleen was a positive prognostic indicator. Pre- or postoperative adjuvant chemotherapy did not provide a survival benefit. CONCLUSION: Based on our sample population, splenectomy alone was an effective treatment for splenic lymphoma in cases with disease confined to the spleen. Chemotherapy may not improve survival in cases of lymphoma restricted to the spleen.
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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".