Real‐world effectiveness of antifungal prophylaxis with posaconazole as the primary agent in patients with haematological malignancies
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Patients undergoing induction/reinduction chemotherapy for haematologic malignancies (HM) are at risk for invasive fungal infections (IFIs). In 2015, Duke University Hospital (DUH) implemented a new standardised fungal prophylaxis protocol for adult patients undergoing induction chemotherapy for acute lymphocytic leukaemia, acute myelocytic leukaemia and myelodysplastic syndrome. This study assessed the impact of protocol implementation on (1) use of antifungal prophylaxis, throughout the at-risk period and (2) patient outcomes such as IFI and mortality. METHODS: Retrospective, observational study of adult HM patients admitted to DUH for induction/reinduction chemotherapy pre- (7/1/2013-12/31/2014) and post- (1/1/2015-10/31/2016) implementation of standardised antifungal prophylaxis protocol (which recommended posaconazole as the first-line agent). Patients were followed for up to 100 days after initiation of induction chemotherapy to evaluate use of antifungal prophylaxis and patient outcomes. RESULTS: 218 patients with haematologic malignancies were included (90 pre, 128 post). Use of antifungal prophylaxis increased from 81.1% (pre) to 97.7% (post) (p < .0001). Overall, 71% received posaconazole as initial antifungal prophylaxis (64.4% pre, 75.7% post). Approximately one-fourth of patients (25.6%, pre vs 26.6%, post) developed an IFI (proven/probable or possible using modified EORTC definitions) (p = .868); 100-day mortality remained stable (18.9% pre vs 18.8% post, respectively, p = .979). Lack of antifungal prophylaxis and older age (≥60 years) were associated with higher risk of IFI. CONCLUSION: Implementation of a standardised protocol with posaconazole as the primary agent was associated with increased use of antifungal prophylaxis among patients undergoing induction/reinduction chemotherapy for haematologic malignancies in our hospital. Lack of antifungal prophylaxis was an independent predictor of IFIs, underscoring the importance of prophylaxis in this at-risk population.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".