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Record W2427148223 · doi:10.1002/ijc.30236

Association between prolonged neutropenia and reduced relapse risk in pediatric AML: A report from the children's oncology group

2016· article· en· W2427148223 on OpenAlexaff
Lillian Sung, Richard Aplenc, Todd A. Alonzo, Robert B. Gerbing, Yi‐Cheng Wang, Soheil Meshinchi, Alan S. Gamis

Bibliographic record

VenueInternational Journal of Cancer · 2016
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsHospital for Sick Children
FundersNational Cancer InstituteNational Institutes of Health
KeywordsNeutropeniaMedicineInternal medicineHazard ratioChemotherapyHematopoietic stem cell transplantationTransplantationSurgeryOncologyConfidence interval

Abstract

fetched live from OpenAlex

Objective was to describe the relationship between the number of sterile site infections and duration of neutropenia during the first four cycles of chemotherapy and the risk of recurrence and overall survival in children with newly diagnosed acute myeloid leukemia (AML). AAML0531 was a Children's Oncology Group randomized phase 3 clinical trial that included 1022 children with de novo AML. For this analysis, we focused on non-Down syndrome favorable and standard risk patients who completed at least 4 cycles of chemotherapy without recurrence or withdrawal during protocol therapy. Those receiving hematopoietic stem cell transplantation in first remission were excluded. Five hundred and sixty-nine patients were included; 274 (48.2%) were favorable risk. The median cumulative time with neutropenia between Induction II to completion of Intensification II was 96 (range 54-204) days. Number of sterile site infections did not influence the risk of relapse or overall survival. However, longer duration of neutropenia was associated with a lower risk of relapse (hazard ratio 0.81 per 20 days neutropenia, p = 0.007). Longer duration of neutropenia was associated with a reduced risk of relapse for children with favorable and standard risk AML. Toxicity may be influenced by pharmacogenomics suggesting that individualized chemotherapy dosing may be an effective strategy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.314
Teacher spread0.303 · 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.

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

Citations8
Published2016
Admission routes1
Has abstractyes

Explore more

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