Weekly Epoetin Alfa Maintains Hemoglobin, Improves Quality of Life, and Reduces Transfusion in Breast Cancer Patients Receiving Chemotherapy
Bibliographic record
Abstract
PURPOSE: Epoetin alfa administered at 40,000 U once weekly (qw) to anemic cancer patients receiving chemotherapy increases hemoglobin levels, improves quality of life (QOL), and reduces transfusions. The benefit of epoetin alfa in maintaining hemoglobin levels in cancer patients with hemoglobin less than 12 g/dL has not been evaluated. METHODS: Breast cancer patients (N = 354) receiving chemotherapy were randomly assigned in 1:1 ratio to epoetin alfa (40,000 U qw) or standard of care (SOC). QOL was assessed at baseline and week 12. Hemoglobin responses, transfusion requirements, and prognostic factors for responses were measured. RESULTS: At week 12, Functional Assessment of Cancer Therapy-Anemia (FACT-An; mean, 2.16 +/- 12.84 for epoetin alfa v -4.43 +/- 13.42 for SOC) and FACT-An fatigue (mean, 1.85 +/- 10.52 for epoetin alfa v -3.55 +/- 11.14 for SOC) change scores were significantly higher in the epoetin alfa group (P < .0001). Hemoglobin responses defined as mean hemoglobin > or = 12 g/dL or a > or = 2 g/dL increase compared with baseline were significantly higher in the epoetin alfa group versus SOC: 52.0% v 5.1% and 65.7% v 6.3%, respectively (P < .0001 for both comparisons). Percentage transfused was significantly lower in the epoetin alfa group compared with SOC (8.6% v 22.9%). More than 90% of patients did not require a dose increase and 28.7% had a dose reduction. CONCLUSION: Epoetin alfa administered at 40,000 U qw is effective in improving QOL, maintaining hemoglobin level, and reducing transfusion requirements in breast cancer patients. The high effectiveness observed could be attributed in part to early treatment with epoetin alfa.
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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) | 0.001 | 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".