A Systematic Review and Meta-analysis of the Combination of Vinorelbine and Lapatinib in Patients With Her2-positive Metastatic Breast Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The development of effective human epidermal growth factor receptor 2 (HER2)-targeted therapies has been heralded as a significant milestone in breast cancer treatment, resulting in improvement of the outcome for those with HER2-positive metastatic breast cancer. Despite these advantages, metastatic breast cancer is still regarded as an incurable disease. In heavily pretreated patients with increasingly limited options for palliative management, ensuring control of disease and maintenance of quality of life is an important goal. Vinorelbine and lapatinib is a combination used in later-line treatment of metastatic HER2-positive breast cancer. The current article presents a systematic review and meta-analysis of prospective series of the vinorelbine/lapatinib doublet for efficacy and toxicity in metastatic HER2-positive breast cancer. Altogether seven prospective trials involving 235 evaluable patients were retrieved for analysis. Pooled estimates of response rate and disease control rate were 24.4% and 63.3% respectively. Furthermore, overall survival was 20.1 months and progression-free survival was 5.44 months. The most common grade 3 and 4 toxicities were seen in fewer than 10% of cases. Vinorelbine/ lapatinib combination regimen may serve as an option for pre-treated patients with metastatic HER2-positive breast cancer.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 it