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Pediatric Treatment Guidelines for Philadelphia Positive (Ph+) Chronic Myelogenous Leukemia (CML): What Are They in Today’s Imatinib Era?

2008· article· en· W2550517509 on OpenAlexaffabout
Michael J. Burke, Jennifer Willert, Sunil Desai, Richard Kadota

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsStollery Children's Hospital
Fundersnot available
KeywordsMedicineChronic myelogenous leukemiaImatinibImatinib mesylatePhiladelphia chromosomeInternal medicineTransplantationOncologyLeukemiaPediatricsMyeloid leukemiaChromosomal translocation

Abstract

fetched live from OpenAlex

Abstract Background: The treatment of pediatric Philadelphia positive (Ph+) chronic myelogenous leukemia (CML) in the era of the tyrosine kinase inhibitors (TKI) continues to evolve with the role of allogeneic hematopoietic cell transplantation (allo-HCT) in these patients becoming more controversial. Imatinib has completely replaced allo-HCT for adult CML patients presenting in first chronic phase, reserving HCT for TKI resistant and/or advanced stage patients (accelerated phase and blast crisis). Whether treatment strategies in 2008 have changed for CML in pediatrics, from heavily allo-HCT based to TKI based medical therapy, is presently unclear. Methods: Thirty-two pediatric centers across the United States and Canada were surveyed regarding current treatment practices for CML in order to explore treatment practices in 2008. The survey targeted primary pediatric oncologists and bone marrow transplant physicians regarding their treatment approach for CML in terms of upfront therapy, utility of allo-HCT, use of TKI (including their role in the post-HCT setting) and how response to therapy was monitored. Results: Twenty-three of the thirty-two centers completed the survey to provide a completion rate of 72% (Table 1). Sixty-three percent of survey responders recommended allo-HCT, when a matched sibling donor was available, for patients with CML in first chronic phase. Regarding the use of TKI in the post-HCT setting, 9 of 27 (33%) physicians reported using imatinib as maintenance therapy post-HCT as a means to prevent relapse. All physicians reported using PCR techniques for bcr-abl of either bone marrow, peripheral blood or both to monitor treatment response with frequencies ranging from monthly to every six months. Conclusion: Treatment of pediatric CML appears variable and center dependent. This survey identified a trend toward less allo-HCT for CML in 2008 compared to years past. Despite the trend toward less HCT, the pediatric treatment consensus in 2008 for CML remains MSD allo-HCT when available. Use of imatinib was recognized by all survey responders as standard of care in upfront therapy, but the use of imatinib or other TKI in the post-HCT setting as maintenance therapy remains in question. Prospective pediatric clinical trials will be necessary to determine the optimal strategy for CML in children. Table 1. Pediatric Centers British Columbia’s Children’s Hospital Children’s Hospital of Pittsburgh Children’s Memorial Medical Center–Northwestern Cincinnati Children’s Hospital Medical Center City of Hope Columbia Presbyterian College of Phys & Surgeons Doernbecher Children’s Hospital-OHSU Duke University Medical Center Mayo Clinic Medical College of Wisconsin Nationwide Children’s Hospital Schneider Children’s Hospital St. Jude Children’s Research Hospital Stollery Children’s Hospital–Edmonton Texas Children’s Cancer Center at Baylor College of Medicine The Children’s Hospital of Philadelphia The University of Chicago Comer Children’s Hospital University of California at San Diego/Rady Children’s Hospital San Diego UCSF School of Medicine University of Florida University of Michigan–C.S. Mott Children’s Hospital University of Minnesota Children’s Hospital, Fairview Washington University–St. Louis

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.053
GPT teacher head0.309
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2008
Admission routes2
Has abstractyes

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