A Systematic Review and Pooled Analysis of Studies of Oral Etoposide in Metastatic Breast Cancer
Bibliographic record
Abstract
OBJECTIVE: Oral etoposide has been used as a later line therapy for metastatic breast cancer for more than twenty years. Its efficacy and clinical usefulness has been suggested in small phase II studies in the metastatic breast cancer population and the drug has also the added advantage of convenient oral administration. Despite these advantages, the place of oral etoposide in treatment of metastatic breast cancer has been challenged in the last decade due to introduction of several other chemotherapeutics, including options available orally, as well as novel targeted therapies. This report pools the data on response rates and survival from all available oral etoposide studies in order to reach a more precise estimate of the clinical benefit of the drug. MATERIALS AND METHODS: A review of the literature was performed for studies of oral etoposide in metastatic breast cancer. Data were extracted from eligible studies and summary statistics derived. Calculations of pooled response rates and survival estimates were performed according to a random or fixed effect model as appropriate. RESULTS: The pooled estimate of Response Rate derived from twelve studies found in the English literature was 18.5% (95% CI 11.5-25.5%). The pooled estimate of Clinical Benefit Rate (CBR) was 45.8% (95% CI 38.6-53.0%) and median Overall Survival (OS) approached 1 year. Summarized adverse effects profile data show an overall manageable toxicity. CONCLUSION: This pooled analysis provides evidence of a moderate clinical effectiveness of oral etoposide in metastatic breast cancer that could be useful in situations that options are limited but active treatment still appropriate.
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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 | 0.022 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.021 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".