Improved Outcome With Dose-Dense Chemotherapy
Bibliographic record
Abstract
TO THE EDITOR: Citron et al [1] have tested the hypoth-esis that outcome is improved with increased dose density of chemotherapy. Although it is not stated, it is likely that the dose-dense arms received considerably more granulo-cyte colony-stimulating factor (G-CSF) than the conven-tionally scheduled arms. An assumption is that G-CSF had no effect other than increasing neutrophil count and activ-ity against infection. However, G-CSF has been found to stimulate other potentially antitumor immune functions, including chemotaxis [2], adhesion [3], pre–B cells [4], and T helper cell type 2–inducing dendritic cells [5]. G-CSF can also have an anti-inflammatory effect [6]. Inflammation is thought to play an important role in cancer, and an anti-inflammatory approach to cancer treatment has been proposed [7]. Is the improved outcome due to increased dose density of chemotherapy, to increased G-CSF use, or both? To answer that question, an appropriate trial would be “dose-dense ” adjuvant chemotherapy (with scheduled G-CSF) versus “standard ” adjuvant chemo-therapy (with scheduled G-CSF in the same dose) versus “standard ” adjuvant chemotherapy (with G-CSF as clin-ically indicated).
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 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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".