Role of a Therapeutic Drug Monitoring-Guided Strategy of Isavuconazole for Optimizing Efficacy/Safety Outcomes in Onco-Hematological Pediatric Patients: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Evidence concerning the implementation of a therapeutic drug monitoring (TDM)-guided approach for optimizing isavuconazole exposure in onco-hematological pediatric patients is limited. The aim of this systematic review was to summarize the current evidence about the role that a TDM-guided strategy of isavuconazole may have in optimizing efficacy/safety outcomes of invasive fungal infection (IFI) treatment/prophylaxis among onco-hematological pediatric patients. METHODS: Two authors independently searched the PubMed-MEDLINE and Scopus databases up to 25 April 2025, to retrieve randomized controlled trials or observational studies providing real-life data assessing isavuconazole exposure according to a TDM-guided approach in pediatric patients, and evaluating the relationship between isavuconazole exposure and efficacy/safety outcomes. Data were independently extracted by the two authors, and the quality of the included studies was independently assessed by means of the Cochrane Risk of Bias Tool (RoB 2.0) in case of randomized controlled trials, and by means of the Newcastle-Ottawa scale in case of observational studies and case series. Mortality attributable to IFI and hepatotoxicity occurrence were selected as primary outcomes. Descriptive statistics were used for summarizing the retrieved data. RESULTS: After screening 577 articles, eight studies were included in the systematic review (five retrospective observational cohort studies and 3 case series; n = 116). Attainment of optimal isavuconazole exposure at first TDM assessment ranged from 36.7% to 83.3% of included patients, being underexposure reported in up to 40.0% of cases. Overall, mortality attributable to IFI occurred in 10 out of 59 patients (16.9%) in which this outcome was evaluated, being associated with isavuconazole underexposure only in 30.0% of cases. Hepatotoxicity occurred in 14 out of 78 included patients (17.9%), being related to isavuconazole overexposure in 50.0% of cases. CONCLUSION: Despite limited findings, our systematic review may support a potential role for a TDM-guided strategy in optimizing isavuconazole exposure among onco-hematological pediatric patients, particularly considering both the non-negligible proportion of cases who failed in attaining optimal exposure with standard dosing regimens.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".