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Effectiveness of Supportive Care Measurements to Reduce Infections During Induction for Children with Acute Myeloid Leukemia: A Report From the Children's Oncology Group

2012· article· en· W2592678340 on OpenAlexaff
Lillian Sung, Richard Aplenc, Todd A. Alonzo, Robert B. Gerbing, Thomas Lehrnbecher, Alan S. Gamis

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsGemtuzumab ozogamicinMedicineInduction chemotherapyCytarabineFebrile neutropeniaNeutropeniaInternal medicineEtoposideDaunorubicinChemotherapy regimenRandomized controlled trialIntensive careChemotherapyIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract Abstract 1478 Background: Current therapies for pediatric acute myeloid leukemia (AML) are intensive; infections are responsible for considerable morbidity and most non-relapse related mortality (NRM). Three supportive care strategies that have garnered much attention are prophylactic antibiotics, prophylactic granulocyte-colony stimulating factor (G-CSF) and hospitalization during profound neutropenia. The Children's Oncology Group (COG) trial AAML0531 was a phase 3 study that included children with de novo AML treated with intensive chemotherapy, and randomized them to standard chemotherapy ± gemtuzumab ozogamicin. We surveyed participating COG sites mid-way through the trial to measure the effect of institutional standards for antibiotic prophylaxis, G-CSF prophylaxis, and discharge policy on Induction I infection risk and NRM for children on study. Methods: AAML0531 used 5 courses of intensive chemotherapy with Induction I consisting of cytarabine 100 mg/m2/dose intravenous (IV) every 12 h on days 1–10; daunorubicin 50 mg/m2/dose IV on days 1,3 and 5; and etoposide 100 mg/m2/dose IV on days 1–5 (ADE 10+3+5). Infections were collected prospectively and monitored in real-time to optimize reporting accuracy. In this analysis, infectious events were limited to Induction I to reduce the chance that a patient's clinical course resulted in the patient receiving a supportive care practice different than the institutional standard. NRM was not limited to Induction I and NRM was defined as any induction death or deaths during intensification or within 30 days of being taken off study due to non-disease related causes. The survey included questions on institutional standards for antibacterial prophylaxis, antifungal prophylaxis, prophylactic G-CSF use and mandatory hospitalization until count recovery. Results: A total of 1024 patients were enrolled on AAML0531. The survey response rate from 216 COG sites was 180/216 (83.3%) and there were 897 non-Down syndrome patients treated at institutions responding to the survey. The use of any anti-bacterial prophylaxis was not associated with a reduction in sterile site bacterial infection and did not significantly alter the risk of Clostridium difficile or fungal infection. Penicillin or vancomycin prophylaxis was associated with an increased risk of any sterile site bacterial infection (odds ratio (OR) 1.96, 95% confidence interval (CI) 1.15 to 3.34; P=.014), Gram-negative infection specifically (OR 4.22, 95% CI 1.62 to 11.0; P=.003) and sterile site fungal infection (OR 3.67, 95% CI 1.31 to 10.3; P=.013). Anti-mold prophylaxis was associated with more sterile site bacterial infection (OR 1.87, 95% CI 1.06 to 3.29; P=.031) and a non-significant increase in Gram-negative infection (OR 2.95, 95% CI 0.97 to 8.95; P=.056). Anti-mold prophylaxis did not influence the rate of sterile site fungal infection. G-CSF prophylaxis and discharge policy did not impact on Induction I infections. None of these supportive care practices influenced NRM during induction or intensification. Conclusions: Penicillin or vancomycin prophylaxis was associated with more Gram-negative and fungal infections. These data do not support routine prophylaxis with these agents. Routine antibiotic prophylaxis, G-CSF prophylaxis, and discharge policy did not impact NRM. Disclosures: No relevant conflicts of interest to declare.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.018
GPT teacher head0.292
Teacher spread0.275 · 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 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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