Recombinant Myeloid Hematopoietic Growth Factors and Clinical Stimulation of Acute Myeloid Leukemia Cells: A Narrative Review
Bibliographic record
Abstract
BACKGROUND: The advent of molecularly cloned hematopoietic growth factors (rhuG-CSF and rhuGM-CSF) enhanced the safety in treating acute myeloid leukemia (AML) by reducing the duration of neutropenia and thus decreasing the risks for infection. However, early in vitro studies demonstrated leukemia cell proliferation in response to these agents, raising reasonable concerns related to whether these factors can cause or contribute to relapse or progression of AML. SUMMARY: Clinical studies using recombinant myeloid hematopoietic growth factors have supported their safety, as there is little or no clear evidence for an association with an increased risk of relapse in AML in patients, regardless of the hematopoietic growth factor used, or whether the setting of AML is newly diagnosed or relapsed/refractory. One exception may be in the pediatric population, though this effect might reflect a different isoform of the G-CSF receptor expressed on the AML cells, as this truncated receptor is also seen in severe congenital neutropenia and aplastic anemia and underlies the increased myeloid malignancies that develop in these diseases after long-term exposure to growth factors. KEY MESSAGES: The current data support the use of rhuG-CSF and rhuGM-CSF in most patient populations with AML. Future studies should explore the factors influencing hematopoietic growth factor sensitivity in AML subpopulations to guide therapeutic decisions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".