Anti-Erythropoietin Antibody-Mediated Pure Red Cell Aplasia after Treatment with Recombinant Erythropoietin Products
Bibliographic record
Abstract
Since 1998, there has been a marked increase in incidence of pure red cell aplasia secondary to development of anti-erythropoietin antibodies (Ab+ PRCA) in patients who have chronic kidney disease (CKD) and receive recombinant erythropoietin. The relationship between incidence of Ab+ PRCA and specific erythropoietin products has not been examined rigorously. Manufacturers provided data regarding exposure to erythropoietin products and incidence of Ab+ PRCA between January 1998 and March 2003 in patients with CKD. Assuming a Poisson distribution, a maximum likelihood estimate for the Poisson rate parameter was calculated for each product. A test for homogeneity of Poisson rates was conducted to compare likelihood estimates between products. Global incidence of Ab+ PRCA was relatively low. Likelihood estimates were not significantly different for Epogen, Procrit, and Aranesp, independent of their formulation or route of administration. Eprex lacking human serum albumin (HSA) and administered subcutaneously was associated with the greatest risk of Ab+ PRCA. HSA-containing Eprex administered subcutaneously was associated with a lower risk than HSA-free Eprex administered subcutaneously, but this risk exceeded that of intravenous Epogen and intravenous HSA-free Eprex. NeoRecormon administered subcutaneously was associated with less risk than subcutaneous HSA-free Eprex but more risk than intravenous Epogen. HSA-free Eprex should not be administered subcutaneously to patients with CKD due to increased risk of Ab+ PRCA. Although the subcutaneous administration of HSA-containing Eprex is riskier than intravenous Epogen and intravenous HSA-free Eprex, and the use of subcutaneous NeoRecormon is riskier than intravenous Epogen, there is currently no evidence that other products are safer.
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 | 0.004 |
| 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".