MétaCan
Menu
Back to cohort
Record W2995383111 · doi:10.1186/s12917-019-2189-x

RNA disruption indicates CHOP therapy efficacy in canine lymphoma

2019· article· en· W2995383111 on OpenAlexafffund
Amadeo M. Parissenti, Laura B. Pritzker, Baoqing Guo, Rashmi Narendrula, Shirly Xiaohui Wang, Lin Laura Lin, Jingchun Pei, Karolina Skowronski, Dorothee Bienzle, J. Paul Woods, K. P. H. Pritzker, Brenda L. Coomber

Bibliographic record

VenueBMC Veterinary Research · 2019
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversity of GuelphLaurentian UniversityHealth Sciences North
FundersOVC Pet TrustOntario Veterinary College, University of Guelph
KeywordsCanine LymphomaCHOPVincristineMedicineLymphomaInternal medicineOncologyCyclophosphamidePrednisoneRegimenChemotherapyLymph nodeLymphGastroenterologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Assessment of the efficacy of a multi-agent chemotherapy protocol in which cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) are administered in canine lymphoma is generally performed by physical measurement of lymph node diameter. However, no consistent correlation has been made with prognostic indicators and the length or absence of clinical remission based on lymph node size. RNA disruption measured mid-therapy has been correlated with increased disease-free survival in recent studies of human cancer and was assessed in this study of canine lymphoma patients. Fine needle aspirate samples were taken before treatment and at weeks 3, 6, and 11 of CHOP therapy. RNA was isolated from these samples and assessed using an Agilent Bioanalyzer. RNA disruption assay (RDA) analysis was performed on the data from the resulting electropherograms. RESULTS: An increased RNA disruption index (RDI) score was significantly associated with improved progression-free survival. CONCLUSIONS: Predicting the risk of early relapse during chemotherapy could benefit veterinary patients by reducing ineffective treatment and could allow veterinary oncologists to switch earlier to a more effective drug regimen.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.228
GPT teacher head0.474
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations12
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueBMC Veterinary ResearchSame topicVeterinary Oncology ResearchFrench-language works237,207