Uridine glucuronosyltransferase 2B7 polymorphisms and epirubicin pharmacokinetics
Bibliographic record
Abstract
13071 Background: Epirubicin (epi) is a widely used anthracycline for the treatment of breast cancer. In contrast to its optical isomer doxorubicin, epi is predominantly glucuronidated by uridine glucuronosyltransferase 2B7 (UGT2B7). UGT2B7 has a T to C polymorphism at position -161 in the enhancer region which correlated with efficacy of morphine glucuronidation (Sawyer et al. Clin Pharmcol Ther 2003). Methods: We performed a prospective pharmacogenetic study of FEC100 (5-fluorouracil 500 mg/m2, Epi 100 mg/m2 and cyclophosphamide 500 mg/m2) given every 3 wks in early stage breast cancer pts. Drug levels were drawn at 1 and 24 hrs. We have determined levels of epi, epi-glucuronide (epiG), epirubicinol (epiol), and epiol-glucuronide (epiolG) in 78 of the 120 pts. The levels of epi and its metabolites were measured using an HPLC with fluorescence detection using the method of Fogli et al with modifications. Patient characteristics-median (range): age 50 (28 - 67), sex 77 F/ 1 M, baseline AST 22 U/L (13–66), ALT 20 U/L (5–90), bilirubin 7 umol/L (2–24), creatinine 73 umol/L (51–126). Results: 14 pts were TT homozygotes, 45 were CT heterozygotes, and 19 were CC homozygotes. Concentrations (ng/ml, median (range)) of epi, epiG, epiol, and epiolG at 1 hr respectively were 91 (39–481), 280 (0–981) 76 (14–212) 76 (0–276). There was no relationship between epiG concentration and genotype: 315 (median) TT, 263 CT, 288 CC. Patients with a TT genotype had a lower epiol concentrations (median, ng/ml) at 24 hr: 12 TT, 23 CT, 25 CC; p = 0.04. Conclusions: This analysis shows a relationship between UGT2B7 genotype and epi pharmacokinetics. We are completing analysis of all 120 samples and plan to perform a formal NONMEM analysis. No significant financial relationships to disclose.
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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 | 0.000 | 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) | 0.003 | 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".