A Pharmacokinetic Study of Plerixafor in Subjects with Varying Degrees of Renal Impairment
Bibliographic record
Abstract
Plerixafor is a selective antagonist of CXCR4 used for mobilization of hematopoietic stem cells (HSCs) for autologous stem cell transplantation (SCT) in patients with multiple myeloma (MM) and non-Hodgkin lymphoma (NHL). This Phase 1 open-label study in healthy subjects was conducted to evaluate the pharmacokinetic characteristics of plerixafor in subjects with renal impairment. All subjects received a single 0.24 mg/kg subcutaneous dose of plerixafor. Subjects were stratified into 4 cohorts based on creatinine clearance determined from a 24-hour urine collection: control (>90 mL/min), mild renal impairment (51-80 mL/min), moderate renal impairment (31-50 mL/min), and severe renal impairment (<31 mL/min, not requiring dialysis). Eleven female subjects (48%) and 12 male subjects (52%), ranging in age from 35 to 73 years, were enrolled. Plerixafor clearance was reduced in subjects with renal impairment and was positively correlated with creatinine clearance. The mean area under the concentration- versus-time curve from time 0 to 24 hours postdose of plerixafor in subjects with mild, moderate, and severe renal impairment was 7%, 32%, and 39% higher, respectively, than that in subjects with normal renal function. Renal impairment had no effect on maximal plasma concentrations. The safety profile was similar among subjects with renal impairment and controls. No renal impairment-related trends in the incidence of adverse events were apparent. A plerixaflor dose reduction to 160 microg/kg in patients with a creatinine clearance value
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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) | 0.001 | 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) | 0.001 | 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".