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Record W2139097830 · doi:10.1586/14737140.3.3.295

Advances in targeted therapy for chronic myeloid leukemia

2003· review· en· W2139097830 on OpenAlexaff
Karen Yee, Armand Keating

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2003
Typereview
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsOntario Institute for Cancer ResearchPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMyeloid leukemiaMedicineImatinib mesylateImatinibLeukemiaTargeted therapyImmunologyMyeloidCancer researchOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Despite the lack of long-term survival data, the impressive results obtained with imatinib mesylate (Gleevec) therapy and the lack of serious adverse events have significantly altered the management of patients with chronic myeloid leukemia. Nevertheless, a large proportion of patients with more advanced disease will develop resistance to imatinib mesylate monotherapy. To prevent the development of resistance, an understanding of the pathophysiology of chronic myeloid leukemia, including the signaling pathways that are activated by the BCR-ABL fusion protein, and the mechanisms of resistance to imatinib are required. This review summarizes the pathogenesis of chronic myeloid leukemia and the potential therapeutic impact of small molecule inhibitors that target pathways critical to the growth or survival of the leukemic cells in patients with chronic myeloid leukemia.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.401
Teacher spread0.362 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations15
Published2003
Admission routes1
Has abstractyes

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