Compare the efficacy of antifungal agents as primary therapy for invasive aspergillosis: a network meta-analysis
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Bibliographic record
Abstract
Abstract Background Several antifungal agents are available for primary therapy in patients with invasive aspergillosis (IA). Although a few studies have compared the effectiveness of different antifungal agents in treating IA, there has yet to be a definitive agreement on the best choice. Herein, we perform a network meta-analysis comparing the efficacy of different antifungal agents in IA. Methods We searched PubMed, Embase, and the Cochrane Central Register of Controlled Clinical Trials databases to find studies (both randomized controlled trials [RCTs] and observational) that reported on treatment outcomes with antifungal agents for patients with IA. The study quality was assessed using the revised tool for risk of bias and the Newcastle Ottawa scale, respectively. We performed a network meta-analysis (NMA) to summarize the evidence on antifungal agents’ efficacy (favourable response and mortality). Results We found 12 studies (2428 patients) investigating 11 antifungal agents in the primary therapy of IA. There were 5 RCTs and 7 observational studies. When treated with monotherapy, isavuconazole was associated with the best probability of favourable response (SUCRA, 77.9%; mean rank, 3.2) and the best reduction mortality against IA (SUCRA, 69.1%; mean rank, 4.1), followed by voriconazole and posaconazole. When treated with combination therapy, Liposomal amphotericin B plus caspofungin was the therapy associated with the best probability of favourable response (SUCRA, 84.1%; mean rank, 2.6) and the best reduction mortality (SUCRA, 88.2%; mean rank, 2.2) against IA. Conclusion These findings suggest that isavuconazole, voriconazole, and posaconazole may be the best antifungal agents as the primary therapy for IA. Liposomal amphotericin B plus caspofungin could be an alternative option.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.844 | 0.008 |
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 it