Metronomic Dosing of Chemotherapy: Applications in Pediatric Oncology
Bibliographic record
Abstract
Pediatric cancer has a better outcome profile than adult cancers. However, refractory disease and the potential for long-term morbidity resulting from the use of conventional therapies necessitate the development of novel treatments for this population. Recent advances in oncology include the use of low dose metronomic (LDM) chemotherapy. The promise of this novel therapeutic approach includes reduced toxicity and the potential for efficacy predominantly through an antiangiogenic effect. The clinical benefit may be realized especially when combined with other antiangiogenic agents and/or conventional maximally tolerated doses of chemotherapy. In this article, we review the evidence for the use of LDM chemotherapy with a focus on pediatric cancer. Included are some of the possible risks attributable to this therapy in a pediatric setting and some of the hurdles to overcome in order to conduct good clinical research. Emphasis is placed on the development of proper surrogate markers to monitor antiangiogenic therapy in order to both optimize the dosing schedule for LDM chemotherapy and to provide a way of tracking therapeutic efficacy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".