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Record W2095357289 · doi:10.3109/10428190903370387

State-of-the-art in the management of chronic myelogenous leukemia in the era of the tyrosine kinase inhibitors: evolutionary trends in diagnosis, monitoring and treatment

2009· review· en· W2095357289 on OpenAlexaff
Álvaro Aguayo, Stephen Couban

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2009
Typereview
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNilotinibDasatinibImatinibMedicineChronic myelogenous leukemiaMyeloid leukemiaTyrosine kinaseTyrosine-kinase inhibitorDiseaseImatinib mesylateIntensive care medicineOncologyInternal medicineLeukemia

Abstract

fetched live from OpenAlex

The treatment of patients with chronic myeloid leukemia (CML) continues to evolve rapidly as we gain better insights into the best monitoring strategies and as there is experience with the second generation tyrosine kinase inhibitors (TKI). Certain observations about CML and its clinical course remain relevant, such at its triphasic course and the prognostic value of the Sokal and Hasford scores. Other aspects of the disease including the most appropriate clinical monitoring and follow-up strategies and indications for changing therapy are evolving more rapidly. Best practice recommendations for monitoring of response have not only evolved over time but also affected by the availability and reliability of standard cytogenetics, FISH and molecular monitoring. Standard dose imatinib remains the best first-line therapy for most patients with first chronic phase CML. Patient and disease-related factors to evaluate when considering alternatives such as higher doses of imatinib, dasatinib, nilotinib and allogeneic transplant are discussed.

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)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.020
GPT teacher head0.279
Teacher spread0.260 · 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 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

Citations23
Published2009
Admission routes1
Has abstractyes

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