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Record W2220816567 · doi:10.3109/10428194.2015.1091929

Major arterial events in patients with chronic myeloid leukemia treated with tyrosine kinase inhibitors: a meta-analysis

2015· review· en· W2220816567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2015
Typereview
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsUniversity of CalgaryMcMaster University
Fundersnot available
KeywordsNilotinibBosutinibDasatinibMedicinePonatinibImatinibInternal medicineTyrosine kinaseMyeloid leukemiaTyrosine-kinase inhibitorImatinib mesylateIncidence (geometry)OncologyCancer

Abstract

fetched live from OpenAlex

There is growing evidence that tyrosine kinase inhibitors (TKIs) may be associated with an increased risk of arterial events. We performed a meta-analysis to estimate the incidence of arterial events in patients with CML treated with TKIs. We identified 29 studies enrolling 15,706 patients. The incidence rates of composite of major arterial events were 0.8 per 100 patient-years for non-TKI treatments, 1.1 per 100 patient-years for dasatinib, 0.1 per 100 patient-years for imatinib, 0.4 per 100 patient-years for bosutinib, 2.8 per 100 patient-years for nilotinib and 10.6 per 100 patient-years for ponatinib. The relative risk (RR) for nilotinib compared with imatinib suggests a significantly increased risk of the composite of major arterial events with nilotinib treatment (RR 5.3; 95%CI 3.0-9.3, p < 0.001). This study demonstrates that, patients who received nilotinib or ponatinib had a greater number of major arterial events when compared to non-TKI-, imatinib-, dasatinib- and bosutinib-treated patients.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0160.004
Bibliometrics0.0030.006
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.025
GPT teacher head0.269
Teacher spread0.244 · 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