Defining Optimally Safe and Effective Blood Levels of Hydroxychloroquine in Lupus: An Important Step Toward Precision Drug Monitoring
Bibliographic record
Abstract
OBJECTIVE: Using a hydroxychloroquine (HCQ) dose of 5 mg/kg/day in systemic lupus erythematosus (SLE) is associated with a higher risk of flares; HCQ blood level monitoring could be a better way to adjust the HCQ dose. We studied the upper threshold for a reference range of HCQ levels to inform routine monitoring. METHODS: This observational study included patients (N = 2,010) across the Systemic Lupus International Collaborating Clinics, Wisconsin, international, and French studies who underwent HCQ blood level measurements. Using adjusted spline and logistic regression analyses on the cross-sectional data, we first identified an HCQ blood level associated with higher HCQ toxicity. Next, we tested if this upper threshold level was supratherapeutic (no further risk reduction for the Systemic Lupus Erythematosus Disease Activity Index 2000 [score ≥6]). Finally, we examined associations between chronic kidney disease (CKD) stage and supratherapeutic (toxic) HCQ blood levels. RESULTS: Among 1,842 patients (excluding 168 patients with very low HCQ blood levels), 4.9% had HCQ-related toxicity. Odds of toxicity were 2.1-fold higher with blood levels ≥1,150 ng/mL and 1.7-fold higher with the cumulative HCQ dose per 1,000-g increase. Blood levels ≥1,150 ng/mL were associated with a saturation in therapeutic effect, indicating supratherapeutic levels. Patients with CKD stage ≥3 had 2.3-fold higher odds of having supratherapeutic levels (≥1,150 ng/mL). CONCLUSION: The therapeutic reference range for HCQ blood level monitoring is 750 to <1,150 ng/mL. HCQ level monitoring could optimize HCQ use, particularly in patients with CKD stage ≥3. Future longitudinal studies are needed to validate the use of HCQ blood level monitoring in optimizing dosing.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".