Is Routine Therapeutic Drug Monitoring of Antiretroviral Agents Warranted in Human Immunodeficiency Virus-Infected Children?
Bibliographic record
Abstract
Background. There have been no studies directly assessing the utility of therapeutic drug monitoring (TDM) in the pediatric human immunodeficiency virus (HIV) population. Current US Department of Health and Human Services (DHHS) guidelines do not recommend routine TDM. Routine TDM was implemented on a trial basis in the HIV Clinic at the Hospital for Sick Children in March 2014. The purpose of this project was to assess the utility of this strategy. Methods. This was a prospective observational study of routine TDM for protease inhibitors (PIs), nonnucleoside reverse transcriptase inhibitors (NNRTIs), and integrase inhibitors (IIs) in combination antiretroviral therapy (cART)-treated HIV-infected children. Voluntary informed consent was required. Outcome measures included the proportion of serum antiretroviral medication (ARV) levels in the therapeutic range and correlation of levels with virologic control, adherence, and toxicity. Results. Forty-eight of 64 cART-treated children in the clinic were recruited (75%). Their median age, viral load (VL), and CD4 percentage were 13 (3–18) years, <40 (<40–124) copies/mL, and 37.4% (8.4–47.9%), respectively; 45.8% were female. Viral load was <40 copies/mL in 91.7%. Adherence was assessed as excellent (>95%) in 95.8%. Fifty baseline trough serum levels were taken, including 19 (38%) for PIs, 27 (54%) for NNRTIs, and 4 (8%) for IIs. Sixty-eight percent (n = 34) of levels were within the therapeutic range, 10% (n = 5) were subtherapeutic, and 22% (n = 11) were supratherapeutic. The highest proportion of therapeutic levels were within the NNRTI class (77.8%) followed by PIs (52.6%) and IIs (50%) (P = 0.047). There was no statistically significant correlation between serum ARV levels and demographic data, VL, CD4%, adverse-event scores, or adherence. Only 1 dose adjustment was made for subtherapeutic raltegravir levels due to a presumed interaction with ritonavir. Conclusion. This study does not support routine use of TDM in generally healthy, well controlled cART-treated HIV-infected children, which is consistent with current DHHS guidelines. A more targeted strategy, such as when adherence is questioned or when there are suspected drug interactions, may be more appropriate. Disclosures. All authors: No reported disclosures.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".