There should be no ESKAPE for febrile neutropenic cancer patients: the dearth of effective antibacterial drugs threatens anticancer efficacy
Bibliographic record
Abstract
The success of modern anticancer treatment is a composite function of enhanced efficacy of surgical, radiation and systemic treatment strategies and of our collective clinical abilities in supporting patients through the perils of their cancer journeys. Despite the widespread availability of antibacterial therapies, the threat of community- or healthcare facility-acquired bacterial infection remains a constant risk to patients during this journey. The rising prevalence of colonization by multidrug-resistant (MDR) bacteria in the population, acquired through exposure from endemic environments, antimicrobial stewardship and infection prevention and control strategies notwithstanding, increases the likelihood that such organisms may be the cause of cancer treatment-related infection and the likelihood of antibacterial treatment failure. The high mortality associated with invasive MDR bacterial infection increases the likelihood that many patients may not survive long enough to reap the benefits of enhanced anticancer treatments, thus threatening the societal investment in the cancer journey. Since cancer care providers arguably no longer have, and are unlikely to have in the foreseeable future, the antibacterial tools to reliably rescue patients from harm's way, the difficult ethical debate over the risks and benefits of anticancer treatments must now be reopened.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".