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Record W4366822278 · doi:10.1038/s41408-023-00823-9

Management of chronic myeloid leukemia in 2023 – common ground and common sense

2023· review· en· W4366822278 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

VenueBlood Cancer Journal · 2023
Typereview
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsBosutinibDasatinibNilotinibPonatinibMedicineImatinibOncologyImatinib mesylateInternal medicineMyeloid leukemiaIntensive care medicine

Abstract

fetched live from OpenAlex

With the improving knowledge of CML and its management, the goals of therapy need to be revisited to ensure an optimal use of the BCR::ABL1 TKIs in the frontline and later-line therapy of CML. In the frontline therapy of CML in the chronic phase (CML-CP), imatinib and the three second-generation TKIs (bosutinib, dasatinib and nilotinib) are associated with comparable survival results. The second-generation TKIs may produce earlier deep molecular responses, hence reducing the time to reaching a treatment-free remission (TFR). The choice of the second-generation TKI versus imatinib in frontline therapy is based on the treatment aims (survival, TFR), the CML risk, the drug cost, and the toxicity profile with respect to the patient's comorbidities. The TKI dosing is more flexible than has been described in the registration trials, and dose adjustments can be considered both in the frontline and later-line settings (e.g., dasatinib 50 mg frontline therapy; dose adjusted schedules of bosutinib and ponatinib), as well as during an ongoing TKI therapy to manage toxicities, before considering changing the TKI. In patients who are not candidates for TFR, BCR::ABL1 (International Scale) transcripts levels <1% are acceptable, result in virtually similar survival as with deeper molecular remissions, and need not warrant a change of TKI. For patients with true resistance to second-generation TKIs or with the T315I gatekeeper mutation, the third-generation TKIs are preferred. Ponatinib should be considered first because of the cumulative experience and results in the CML subsets, including in T315I-mutated CML. A response-based dosing of ponatinib is safe and leads to high TKI compliance. Asciminib is a third-generation TKI with possibly a better toxicity profile, but lesser activity in T315I-mutated CML. Olverembatinib is another potent third-generation TKI with early promising results.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.356
Teacher spread0.309 · 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