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Record W2161794113 · doi:10.3109/10428194.2011.652108

Long-term follow-up of patients with chronic myeloid leukemia in chronic phase developing sudden blast phase on imatinib therapy

2011· article· en· W2161794113 on OpenAlexaff
Adisak Tantiworawit, Maryse Power, Michael J. Barnett, Donna E. Hogge, Stephen H. Nantel, Thomas J. Nevill, John D. Shepherd, Kevin Song, Heather J. Sutherland, Cynthia L. Toze, Yasser Abou-Mourad, Sujaatha Narayanan, Raewyn Broady, Donna L. Forrest

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2011
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineImatinibCumulative incidenceInternal medicineImatinib mesylateMyeloid leukemiaIncidence (geometry)OncologyDasatinibTyrosine-kinase inhibitorNilotinibPediatricsTransplantationCancer

Abstract

fetched live from OpenAlex

Sudden blast phase (SBP) is a rare event that occurs in an unpredictable fashion amongst patients with chronic myeloid leukemia (CML) who otherwise appear to be responding satisfactorily to imatinib (IM) treatment. We investigated the incidence, clinical characteristics, treatment outcome and long-term follow-up of 213 patients with chronic phase CML treated with IM according to the European LeukemiaNet guidelines. Nine patients, eight of whom received IM as first-line therapy, developed SBP (4.2% of the total). They tended to have low or intermediate risk Sokal scores at diagnosis, a predominance of the lymphoid phenotype and a short interval from "optimal" response to the development of BP. Five of the nine patients with SBP are alive in complete molecular remission; however, all of them underwent allogeneic hematopoietic stem cell transplant. The cumulative incidence of SBP for the patients who received IM as first-line therapy was 5.9% and the 2-year overall survival of the nine patients who developed SBP was 56%. Despite the improved outcome for patients with SBP receiving tyrosine kinase inhibitors (TKIs) and transplant, many of these patients are not salvaged with these therapies. This illustrates the need to develop predictive models to identify patients early whose response to TKI therapy will not be durable and hopefully prevent the transformation to advanced disease.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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
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

Citations19
Published2011
Admission routes1
Has abstractyes

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