CPX-351 Pharmacokinetics and Safety in Adults with Hematologic Malignancies and Renal Function Impairment: Phase 1 Trial
Bibliographic record
Abstract
This open-label phase 1 study (clinicaltrials.gov, NCT03555955) assessed CPX-351 pharmacokinetics (PK) and safety in patients with hematologic malignancies with normal or impaired renal function. Patients were enrolled into three cohorts based on their creatinine clearance (CrCl): ≥90 mL/min (Cohort 1, normal renal function, n = 7), 30 to <59 mL/min (Cohort 2, moderate renal impairment, n = 8), or <30 mL/min (Cohort 3, severe renal impairment, n = 6). Patients received intravenous CPX-351 for initial induction; blood and urine samples were collected for PK analysis. The primary objective was to assess the PK parameters for cytarabine, daunorubicin, and their respective metabolites, arabinosyluracil (Ara-U) and daunorubicinol. Renal impairment did not significantly impact the cytarabine, daunorubicin, or daunorubicinol exposure, but it caused a slight increase in the Ara-U exposure. The CPX-351 side effect profile was similar in patients with impaired renal function compared to those with normal renal function. All the patients reported ≥1 treatment-emergent adverse event (TEAE), most commonly febrile neutropenia and nausea (57% each) and hyperglycemia (43%); no patients discontinued treatment due to TEAEs. These data suggest that CPX-351 dose adjustment is not required for patients with hematologic malignancies with moderate or severe renal impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".