A Retrospective Study of Efficacy and Safety of Albumin-bound paclitaxel in Metastatic Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Nab-paclitaxel is a novel nanoparticle, albumin-bound, solvent-free, taxane-based chemotherapy approved for the treatment of metastatic breast cancer (MBC). This study reports clinical benefit and toxicities experienced by women with MBC treated with nab-paclitaxel. METHODS: Women with MBC treated with single-agent nab-paclitaxel between January 2012 and March 2014 were included in this analysis. Retrospective data obtained included demographics, disease characteristics, prior chemotherapy, nab-paclitaxel treatment, toxicity and survival. Clinical benefit was defined as partial or complete response or stable disease (by clinical or radiologic evaluation, or both) at 6 months or more. RESULTS: Overall response rates (complete or partial responses) were 43% (95% CI: 35.3 - 60.0) for all patients. Median time to disease progression was 26.6 weeks, and median survival was 63.6 weeks. No severe hypersensitivity reactions were reported despite the lack of premedication. Toxicities observed were typical of paclitaxel and included grade 3 sensory neuropathy (14.3%), grade 4 neutropenia (7.14%) and grade 4 febrile neutropenia (7.14%). Patients received a median of six treatment cycles; three patients had 25% dose reductions because of toxicities. CONCLUSIONS: Our clinical experience demonstrates that most women treated with nab-paclitaxel experienced some clinical benefit. Patients achieving clinical benefit lived significantly longer than those who did not. Nab-paclitaxel was well tolerated, with the primary toxicity being mild sensory neuropathy. Nab-paclitaxel represents another treatment option, with a favorable toxicity profile, for women with MBC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".