Effectiveness of supportive care measures to reduce infections in pediatric AML: a report from the Children’s Oncology Group
Bibliographic record
Abstract
Objective was to describe the effect of antibiotic and granulocyte colony-stimulating factor (G-CSF) prophylaxis and discharge policy on infection risk and nonrelapse-related mortality (NRM) during chemotherapy for children with acute myeloid leukemia. Patients were non-Down syndrome children enrolled on Children's Oncology Group (COG) trial AAML0531. We surveyed sites to determine institutional standards for systemic antibacterial, antifungal, and G-CSF prophylaxis, and mandatory hospitalization during neutropenia. COG institution survey response rate was 180 of 216 (83.3%). Of 1024 patients enrolled on AAML0531, 897 were non-Down patients from survey-responding institutions. In multiple regression, antibacterial prophylaxis reduced any sterile-site bacterial infection (incidence rate ratio [IRR] 0.85; 95% confidence interval [CI], 0.72-1.01; P = .058) and Gram-positive sterile-site infection (IRR 0.71; 95% CI, 0.57-0.90; P = .004). Prophylactic G-CSF reduced bacterial (IRR 0.79; 95% CI, 0.67-0.92; P = .004) and Clostridium difficile infections (CDIs; IRR 0.46; 95% CI, 0.25-0.84; P = .012). Mandatory hospitalization did not reduce bacterial/fungal infection or significantly reduce NRM but did increase CDI (IRR 1.96; 95% CI, 1.34-2.87; P < .001). Antibacterial and G-CSF prophylaxis reduced infection rates while mandatory hospitalization did not reduce infection or significantly affect NRM. This trial was registered at www.clinicaltrials.gov as #AAML0531.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".