Phase II trial of sorafenib (S) and vinorelbine (V) in metastatic breast cancer (mBC) with pharmacokinetics (PK) analysis.
Bibliographic record
Abstract
1099 Background: S inhibits pathways involved in cancer resistance to treatments (Raf, VEGFR, PDGFR). This phase 2 trial aimed to define tolerability and efficacy of full doses of S and V in mBC. Toxicity data were previously reported: frequent dose reductions were noted, for which we investigated a possible PK interaction. Indeed, the metabolism of both S and V depends on hepatic CYP3A isoenzymes. Methods: Patients with measurable (RECIST), HER2 negative mBC received first-line therapy with V (30 mg/m2 days 1, 8 every 21) + S (400 mg bid). After 8 cycles patients could be switched to S alone. For PK analysis 6 patients started S on day 4 of cycle 1, to compare plasma levels of V, S and M2 (N-oxide active metabolite of S) when V and S were administered apart from each other versus concomitantly. Plasma samples were collected at time 0 (oral intake of S or right before V infusion), at completion of V infusion and after 0.5, 1, 2.5, 5, 7, 24, 48 and 72 hours from time 0 (cycle 1 day 1 for V and day 21 for S+M2; cycle 2 day 1 for both). Samples were analyzed using validated LC-MS/MS assays. Results: 27 patients (median age 57, 35-71) received a median of 8 cycles (1-28), with one patient still on treatment. With repeated cycles 48% of patients required at least 1 dose reduction and 3 patients discontinued therapy for toxicity. 30% of patients had a partial response, 85% had clinical benefit (including stable disease ≥ 4 cycles). Median progression-free survival was 5.7 months (95% CI 4.4-7.6). Plasma levels of V were influenced by S, with a mean Cmax right after the infusion of 1301 ng/mL for V administered alone (cycle 1 day 1) versus 2039 ng/mL with concomitant S (cycle 2 day 1; paired t-test, p=0.004). Plasma levels of S and M2 showed a greater degree of interpatient variability, with no significant difference observed in the presence or absence of concomitant V. Conclusions: Combining S with V at full doses is feasible, but not devoid of toxicity. A PK interaction may contribute to the frequent dose reductions. A reasonable option in clinical practice is to start therapy at lower doses of both agents, with a gradual dose increase if well tolerated. Promising efficacy of this combination is documented, with a very high rate of disease control.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".