Beneficial effects of eculizumab regardless of prior transfusions or bone marrow disease: Results of the International Paroxysmal Nocturnal Hemoglobinuria Registry
Bibliographic record
Abstract
OBJECTIVES: To evaluate the effects of eculizumab on transfusions and thrombotic events (TEs) in patients with and without prior history of transfusion in the International Paroxysmal Nocturnal Hemoglobinuria (PNH) Registry. METHODS: Registry patients enrolled on or before January 1, 2018, initiated on eculizumab no more than 12 months prior to enrollment, having known transfusion status for the 12 months before eculizumab initiation, and ≥12 months of Registry follow-up after eculizumab initiation, were included. RESULTS: Eculizumab treatment was associated with a 50% reduction in transfusions in patients with a transfusion history (10.6 units/patient-year before eculizumab vs 5.4 after; P < .0001), with greater reduction observed in those with no history of bone marrow disease vs those with bone marrow disease. Mean lactate dehydrogenase levels decreased from a mean of 6.7 to 1.4 times the upper limit of normal (ULN) in patients with transfusion history and from 5.1 to 1.2 times ULN in those with no transfusion history. TE and major adverse vascular event rates also decreased by 70% in patients with and without history of transfusion. CONCLUSIONS: The benefit of eculizumab therapy does not appear to be limited to any group defined by transfusion history or bone marrow disease history.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".