Prophylactic Granulocyte Colony-Stimulating Factor and Granulocyte-Macrophage Colony-Stimulating Factor Decrease Febrile Neutropenia After Chemotherapy in Children With Cancer: A Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
PURPOSE: To determine whether prophylactic hematopoietic colony-stimulating factors (CSFs) used in children with cancer reduce the rate of febrile neutropenia, hospitalization duration, documented infection rate, parenteral antibiotic duration, amphotericin B use, or infection-related mortality. METHODS: We included studies in this meta-analysis if their populations consisted of children, if there was randomization between CSFs and placebo or no therapy, if CSFs were administered prophylactically (before neutropenia or febrile neutropenia), and if chemotherapy treatments preceding CSFs and placebo or no therapy were identical. From 971 reviewed study articles, 16 were included. RESULTS: The mean rate of febrile neutropenia in the control arms was 57% (range, 39% to 100%). Using a random effects model, CSFs were associated with a reduction in febrile neutropenia, with a rate ratio of 0.80 (95% CI, 0.67 to 0.95; P =.01), and a decrease in hospitalization length, with a weighted mean difference of -1.9 days (95% CI, -2.7 to -1.1 days; P <.00001). CSF use was also associated with reduction in documented infections (rate ratio, 0.78; 95% CI, 0.62 to 0.97; P =.02) and reduction in amphotericin B use (rate ratio, 0.50; 95% CI, 0.28 to 0.87; P =.02). There was no difference in duration of parenteral antibiotic therapy (weighted mean difference, -4.3; 95% CI, -10.6 to 2.0 days; P =.2) or infection-related mortality (rate ratio, 1.02; 95% CI, 0.34 to 3.06; P =.97). CONCLUSION: CSFs were associated with a 20% reduction in febrile neutropenia and shorter duration of hospitalization; however, CSFs did not reduce infection-related mortality.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.046 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".