Utility of voriconazole therapeutic drug monitoring: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Voriconazole therapeutic drug monitoring (TDM) is increasingly used in clinical practice. However, the utility of voriconazole TDM to guide therapy remains uncertain and controversial. We conducted a meta-analysis of studies assessing the relationship between voriconazole serum concentration and clinical outcomes of success and toxicity. METHODS: We searched bibliographic databases for studies on voriconazole serum concentrations and clinical outcomes. We compared success outcomes between patients with therapeutic and subtherapeutic voriconazole serum concentrations, and toxicity outcomes between patients with and without supratherapeutic serum concentrations. RESULTS: Twenty-four studies were analysed. Pooled analysis for efficacy endpoint demonstrated that patients with therapeutic voriconazole serum concentrations (1.0-2.2 mg/L) were more likely to have successful outcomes compared with those with subtherapeutic voriconazole serum concentrations (OR 2.30; 95% CI 1.39-3.81). A therapeutic threshold of 1.0 mg/L was most predictive of successful outcome (OR 1.94; 95% CI 1.04-3.62). Patients with therapeutic concentrations did not have better survival rates. Pooled analysis for toxicity endpoint demonstrated that patients with supratherapeutic voriconazole serum concentrations (4.0-6.0 mg/L) were at increased risk of toxicity (OR 4.17; 95% CI 2.08-8.36). A supratherapeutic threshold of 6.0 mg/L was most predictive of toxicity (OR 4.60; 95% CI 1.49-14.16). CONCLUSIONS: Patients with therapeutic voriconazole serum concentrations were twice as likely to achieve successful outcomes. The likelihood of toxicity associated with supratherapeutic voriconazole serum concentrations was 4-fold that of therapeutic concentrations. Our findings suggest that the use of voriconazole TDM to aim for serum concentrations between 1.0 and 6.0 mg/L during therapy may be warranted to optimize clinical success and minimize toxicity.
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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 | 0.024 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.078 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".