Impact of Age and Gender on the Pharmacokinetics of Gemtuzumab Ozogamicin
Bibliographic record
Abstract
STUDY OBJECTIVE: To determine the pharmacokinetic parameters of the components of gemtuzumab ozogamicin and to assess the possible influence of age and gender on the values. DESIGN: Phase II, multicenter, open-label, nonrandomized, parallel study SETTING: Hospitals and outpatient oncology clinics. PATIENTS: Fifty-eight patients with acute myeloid leukemia in first relapse participated. Demographic data included 29 men and 29 women; 34 were younger than 60 years of age (mean age 53+/-16 yrs). INTERVENTION: Patients received gemtuzumab ozogamicin as a single 2-hour infusion of 9 mg/m2. Serial plasma samples were collected over 10 days after the beginning of the infusion. MEASUREMENTS AND MAIN RESULTS: Plasma concentrations of components of gemtuzumab ozogamicin (hP67.6 antibody, total and unconjugated calicheamicin derivatives) were measured by validated enzyme-linked immunosorbent assays. Pharmacokinetic parameters were determined by noncompartmental methods and comparisons between groups were made by analysis of variance. No significant differences were seen between men and women or between those over 60 and those less than 60 years of age in maximum concentration, time to maximum concentration, area under the curve, clearance, or volume of distribution for components of gemtuzumab ozogamicin. CONCLUSION: No differences occur in the pharmacokinetics of the components of gemtuzumab ozogamicin (hP67.6 or calicheamicin) based on gender or age.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".