Empirical versus Preemptive Antifungal Therapy for Fever during Neutropenia
Bibliographic record
Abstract
To the Editor—We congratulate Cordonnier et al [1] on successful completion of a trial that addresses a very complicated issue: the relative utility of antifungal therapy administered “empirically” for fever during neutropenia, compared with a “preemptive” approach that relies on diagnostic monitoring. As mentioned in the accompanying editorial by de Pauw and Donnelly [2], a challenge to the paradigm of treating fever with antifungals is long overdue, with little supporting evidence generated in the most contemporaneous cohorts of patients. However, there are issues with the design and interpretation of the study that we think deserve further attention. First, we are concerned that the results of the trial, which measured overall survival as a primary end point and invasive fungal infection (IFI) as a secondary end point, were biased by the institutionally driven rather than protocol-driven administration of effective anti-Candida prophylaxis. Antifungal prophylaxis was particularly uncommon in the group of patients undergoing induction therapy, which is the group in which most of the IFIs occurred. Thus, absence of prophylaxis could have resulted in more breakthrough infection due to Candida species in the preemptive treatment arm, because the preemptive “comprehensive” diagnostic approach relied largely on radiographic abnormalities and use of galactomannan antigen screening, which are more suitable for detection of aspergillosis. Although the monitoring also incorporated sepsis and mucositis as indicators for preemptive therapy, these would occur relatively late or would be poor predictors for driving preemptive therapy. Indeed, the 5 cases of candidemia that occurred in the preemptive treatment arm developed in patients who were not receiving antifungal prophylaxis, supporting the thesis that the secondary end point of IFI may have been driven by lack of effective prophylaxis, not the intervention. If candidiasis was excluded to account for lack of standardization in azole prophylaxis, it appears that IFI in the preemptive therapy arm would be no different than that in the empirical therapy arm, with 7 versus 3 cases of aspergillosis (or 5 vs 3 cases of aspergillosis that would be potentially detected using the lower galactomannan cutoff value of 0.5). Have the investigators analyzed the results on the basis of receipt of antifungal prophylaxis? Also, considering that the definition of “breakthrough infection” only required administration of the study drug for 24 h, the timing of infection onset relative to the start of drug treatment would provide more indication of the impact of prior antifungal therapies. What was the timing of IFI relative to start of amphotericin-based therapy?
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.001 |
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".