Relationship between posaconazole concentrations and clinical outcomes in paediatric cancer and haematopoietic stem cell transplant recipients
Bibliographic record
Abstract
BACKGROUND: Posaconazole is used to prevent and treat invasive fungal infections (IFIs) in immunocompromised children, including those undergoing cancer treatment or HSCT. Despite differences in pharmacokinetics and IFI epidemiology between children and adults, therapeutic targets established in adult studies are often applied to children. OBJECTIVES: This systematic review evaluated the correlation between serum posaconazole concentrations and clinical outcomes of IFI prophylaxis and treatment in children with malignancies or HSCT recipients. METHODS: Four databases (Cochrane, Embase, MEDLINE and PubMed) were searched for studies involving children (≤18 years old) receiving cancer treatment or HSCT that reported posaconazole serum concentrations and treatment outcomes. Animal studies, those primarily in adult (>18 years old) populations, non-malignant conditions (excluding HSCT), case reports, letters, editorials, conference abstracts and narrative reviews were excluded. Bias was assessed using the Newcastle-Ottawa scale. RESULTS: Nineteen studies were included: 12 reported outcomes of posaconazole prophylaxis; two of treatment; and five of both. For prophylaxis, breakthrough IFIs occurred in 1%-12% of children. All but one occurred with serum concentrations of ≤0.7 mg/L. For treatment, no clear association was observed between a trough concentration of >1.0 mg/L and treatment efficacy, with poor outcomes reported for serum concentrations ranging between 0.2 and 4.8 mg/L. Overall, quality of evidence was poor (medium to high risk of bias for 18 papers, low risk for 1 paper) and there was variation in IFI definitions across studies. CONCLUSIONS: This review supports current recommendations for posaconazole prophylaxis in paediatric oncology and HSCT recipients. The absence of a clear correlation found between serum trough concentrations and treatment efficacy highlights the need for further studies to determine optimal therapeutic targets for treatment.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".