Meta-Analysis of Impact of Epoetin Alfa Versus Darbepoetin Alfa on Blood Transfusion Requirements.
Bibliographic record
Abstract
Abstract Background: Epoetin alfa (EPO) and darbepoetin alfa (DARB) are commonly used for the treatment of chemotherapy-induced anemia (CIA). To date, three randomized head-to-head studies have compared EPO dosed 40,000 Units once weekly (QW) and DARB dosed 200mcg once every two weeks (Q2W). As transfusion results across these studies were inconsistent a meta-analysis was undertaken to provide a pooled estimate of the comparative difference in red blood cell transfusion rates between DARB and EPO treatment groups. Methods: Demographic and transfusion rate data were extracted from the three publicly available head-to-head comparison studies (pooled N=940 for DARB and N=933 for EPO). Odds ratios, risk ratios and risk differences of transfusion rates from week 1 to the end of treatment between DARB and EPO groups were analyzed using both fixed- and random-effects meta-analysis methods; the latter incorporated between-study variation in addition to within-study variation. A multivariate logistic regression model weighted by the number of patients in each study arm and including population-level characteristics from each study arm, was conducted to isolate the treatment effect on the risk of transfusion after controlling for differences in baseline characteristics between DARB and EPO patients. Results: Fixed- and random-effects models generated similar results (p>0.42 for homogeneity test across studies), both demonstrating that the DARB Q2W group had a statistically significantly higher transfusion rate than the EPO QW group. Using the random-effects model, the odds ratio of transfusion in the DARB group was 1.28 of that in the EPO group (95%CI: 1.03– 1.59). The corresponding risk ratio and risk difference were 1.21 (95%CI: 1.02–1.43) and 4% (95%CI: 0.3%–8%), respectively. Multivariate regression analysis further confirmed DARB Q2W had a higher transfusion rate compared to EPO QW, after controlling for age, baseline hemoglobin and the proportion of breast cancer patients (adjusted odds ratio=1.45, 95%CI: 1.10–1.91). Conclusion: This meta-analysis demonstrates that, in patients with CIA, EPO 40,000 units QW is more effective at reducing RBC transfusion requirements than DARB 200 mcg Q2W.
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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 | 0.028 | 0.044 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.073 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".