Epoetin alpha decreases the number of erythrocyte transfusions in patients with acute lymphoblastic leukemia, lymphoblastic lymphoma, and Burkitt leukemia/lymphoma
Bibliographic record
Abstract
BACKGROUND: Anemia is an expected consequence of intensive chemotherapy regimens administered to patients with acute leukemia. This study was designed to determine whether epoetin alpha would decrease the number of transfusion events and units of packed erythrocytes (PRBCs) transfused, and the secondary objective was to study the effects of epoetin alpha on quality of life (QOL) and complete remission (CR) rates. METHODS: Patients with acute lymphoblastic leukemia (ALL), lymphoblastic lymphoma (LL), or Burkitt lymphoma (BL) who were receiving frontline myelosuppressive chemotherapy were randomized to receive epoetin alpha or no epoetin during the first 6 cycles of their planned chemotherapy. QOL was assessed by using the Edmonton Symptom Assessment Scale (ESAS) and the Functional Assessment of Cancer Therapy (FACT)-Anemia questionnaires. RESULTS: Fifty-five patients were randomized to receive epoetin alpha, and 54 patients received no epoetin. Transfusion data were available for 79 of 81 evaluable patients (98%) who completed the treatment/observation period. The trial was stopped early because of poor accrual before the target of 123 evaluable patients was met. A mean of 10.6 units of PRBCs over 5 months were administered to those who received epoetin alpha compared with 13 units for those who did not receive epoetin (P = .04). There was no significant difference in QOL as assessed by the FACT-Anemia or ESAS instruments. The CR rate and the 3-year CR duration were not affected adversely by use of epoetin alpha. CONCLUSIONS: Epoetin alpha decreased the number of PRBC transfusions and did not appear to have a negative impact on remission duration. No difference in QOL was observed.
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.
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) | 0.001 | 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 | 0.001 |
| 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".