Limited Sampling Strategy for Predicting Area Under the Concentration‐Time Curve of Mycophenolic Acid in Adult Lung Transplant Recipients
Bibliographic record
Abstract
STUDY OBJECTIVE: To develop limited sampling strategies for estimation of mycophenolic acid exposure (by determining area under the concentration-time curve [AUC]) in lung transplant recipients by using sampling times within 2 hours after drug administration and a maximum of three plasma samples. DESIGN: Prospective, open-label clinical study. SETTING: Lung transplant clinic in Vancouver, British Columbia, Canada. PATIENTS: Nineteen adult (mean age 48.3 yrs) lung transplant recipients who were receiving mycophenolate mofetil therapy along with cyclosporine (9 patients) or tacrolimus (10 patients). INTERVENTION: Eleven blood samples were collected from each of the 19 patients over 12 hours: immediately before (0 hr) and 0.3, 0.6, 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after administration of mycophenolate mofetil. MEASUREMENTS AND MAIN RESULTS: Mycophenolic acid levels in plasma were determined by a high-performance liquid chromatography-ultraviolet detection method. The 19 patients were randomly divided into index (10 patients) and validation (9 patients) groups. Limited sampling strategies were developed with multiple regression analysis by using data from the index group. Data from the validation group were used to test each strategy. Bias and precision of each limited sampling strategy were determined by calculating the mean prediction error and the root mean square error, respectively. The correlation between AUC and single concentrations was generally poor (r2= 0.18-0.73). Two single-concentration strategies, eight two-concentration strategies, and eight three-concentration strategies matched our criteria. However, the best overall limited sampling strategies (and their predictive performance) were the following: log AUC = 0.241 log C0 + 0.406 log C2 + 1.140 (bias -5.82%, precision 5.97%, r2= 0.828) and log AUC = 0.202 log C0 + 0.411 log C1.5 + 1.09 (bias -5.71%, precision 6.94%, r2= 0.791), where Cx is mycophenolic acid concentration at time x hours. CONCLUSION: Two-concentration limited sampling strategies provided minimally biased and highly precise estimation of mycophenolic acid AUC in lung transplant recipients. These optimal and most clinically feasible limited sampling strategies are based collectively on the number of blood samples required, r2 value, bias, and precision.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".