Systematic review and mixed treatment comparison meta-analysis of randomized clinical trials of primary oral antifungal prophylaxis in allogeneic hematopoietic cell transplant recipients
Bibliographic record
Abstract
BACKGROUND: Antifungal prophylaxis is a promising strategy for reducing invasive fungal infections (IFIs) in allogeneic hematopoietic cell transplant (alloHCT) recipients, but the optimum prophylactic agent is unknown. We used mixed treatment comparison (MTC) meta-analysis to compare clinical trials examining the use of oral antifungals for prophylaxis in alloHCT recipients, with the goal of informing medical decision-making. METHODS: Randomized controlled trials (RCTs) of fluconazole, itraconazole, posaconazole, and voriconazole for primary antifungal prophylaxis were identified through a systematic literature review. Outcomes of interest (incidence of IFI/invasive aspergillosis/invasive candidiasis, all-cause mortality, and use of other antifungals) were extracted from eligible RCTs and incorporated into a Bayesian hierarchical random-effects MTC. RESULTS: Five eligible RCTs, randomizing 2147 patients in total, were included. Relative to fluconazole, prophylaxis with itraconazole (odds ratio [OR]: 0.52; interquartile range [IQR]: 0.35-0.76), posaconazole (OR: 0.56; IQR: 0.32-0.99), and voriconazole (OR: 0.46; IQR: 0.28-0.73) reduced incidence of overall proven/probable IFI. Posaconazole (OR: 0.31; IQR: 0.17-0.58) and voriconazole (OR: 0.33; IQR: 0.17-0.58) prophylaxis reduced proven/probable invasive aspergillosis more than itraconazole (OR: 0.68; IQR: 0.42-1.12). All-cause mortality was similar across all mould-active agents. CONCLUSION: As expected, mould-active azoles prevented IFIs, particularly invasive aspergillosis, more effectively than fluconazole in alloHCT recipients. The paucity of comparative efficacy data suggests that other factors such as long-term tolerability, availability of intravenous formulations, local IFI epidemiology, and drug costs may need to form the basis for selection among the mould-active azoles.
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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 | 0.036 | 0.088 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.049 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".