Mould-active compared with fluconazole prophylaxis to prevent invasive fungal diseases in cancer patients receiving chemotherapy or haematopoietic stem-cell transplantation: a systematic review and meta-analysis of randomised controlled trials
Bibliographic record
Abstract
BACKGROUND: Objectives were to compare systemic mould-active vs fluconazole prophylaxis in cancer patients receiving chemotherapy or haematopoietic stem cell transplantation (HSCT). METHODS: We searched OVID MEDLINE and the Cochrane Central Register of Controlled Trials (1948-August 2011) and EMBASE (1980-August 2011). Randomised controlled trials of mould-active vs fluconazole prophylaxis in cancer or HSCT patients were included. Primary outcome was proven/probable invasive fungal infections (IFI). Analysis was completed by computing relative risks (RRs) using a random-effects model and Mantel-Haenszel method. RESULTS: From 984 reviewed articles, 20 were included in this review. Mould-active compared with fluconazole prophylaxis significantly reduced the number of proven/probable IFI (RR 0.71, 95% CI 0.52 to 0.98; P=0.03). Mould-active prophylaxis also decreased the risk of invasive aspergillosis (IA; RR 0.53, 95% confidence interval (CI) 0.37-0.75; P=0.0004) and IFI-related mortality (RR 0.67, 95% CI 0.47-0.96; P=0.03) but is also associated with an increased risk of adverse events (AEs) leading to antifungal discontinuation (RR 1.95, 95% CI 1.24-3.07; P=0.004). There was no decrease in overall mortality (RR 1.0; 95% CI 0.88-1.13; P=0.96). CONCLUSION: Mould-active compared with fluconazole prophylaxis significantly reduces proven/probable IFI, IA, and IFI-related mortality in cancer patients receiving chemotherapy or HSCT, but increases AE and does not affect overall mortality. (PROSPERO Registration: CRD420111174).
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.030 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".