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Record W2102353693

Chemotherapy in canine acute megakaryoblastic leukemia: a case report and review of the literature.

2010· article· en· W2102353693 on OpenAlexaboutno aff
Michael Willmann, Leonhard Müllauer, Ilse Schwendenwein, Birgitt Wolfesberger, Miriam Kleiter, Maximilian Pagitz, Emir Hadzijusufovic, S. Shibly, M. Reifinger, Johann G. Thalhammer, Peter Valent

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsDaunorubicinEtoposideMedicineVincristinePrednisoloneChemotherapyCytarabineInternal medicineMyeloid leukemiaGastroenterologySurgeryCyclophosphamideOncology
DOInot available

Abstract

fetched live from OpenAlex

Acute myeloid leukemia (AML) in dogs is a rare disease with poor prognosis. In most subjects, palliative treatment or euthanasia is performed. A 3.5-year-old male castrated labrador with AML-M7, which was treated with induction polychemotherapy (8 cycles) using vincristine (0.5 mg/m(2)/cycle), daunorubicin (20 mg/m(2)/cycle), cytosine arabinoside (ARA-C, 100 mg/m(2)/cycle) and prednisolone (1 mg/kg/day) is reported. Treatment was well tolerated and complete remission was achieved. Postinduction chemotherapy consisted of ARA-C, daunorubicin and prednisolone. After 3, 5 and 18 months, the subject relapsed. Each relapse was treated with ARA-C (up to 1,000 mg/m(2)) and etoposide or daunorubicin. Again, no severe side-effects occurred and the disease was controlled, with 37 chemotherapy-cycles (ARA-C, 3 x 1,000 mg/m(2)/cycle), for 24 months. Based on a literature-search, this is the first report documenting a long-term response of canine AML, probably resulting from the high-dose ARA-C. Clinical trials using high-dose ARA-C are now required to confirm antileukemic efficacy in canine leukemias.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.314
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2010
Admission routes1
Has abstractyes

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