Long‐term effectiveness of eculizumab: Data from the International <scp>PNH</scp> Registry
Bibliographic record
Abstract
Abstract Objectives Data from the International PNH Registry (NCT01374360) were used to estimate the overall survival and first occurrence of thromboembolic events/major adverse vascular events (TEs/MAVEs) for eculizumab‐treated patients with paroxysmal nocturnal hemoglobinuria (PNH) compared with a contemporaneous untreated cohort. Methods Patients enrolled in the Registry from March 16, 2007, to February 14, 2022, were included. Treated patients received eculizumab for >35 days; untreated patients did not receive eculizumab at any time. Univariable and multivariable analyses were performed using a Cox proportional hazards regression model comparing eculizumab treatment periods to untreated periods and were adjusted for baseline covariates (e.g., high disease activity [HDA], transfusion dependency, and eculizumab treatment status). Results The analysis included 4118 patients. The univariable hazard ratio (HR) (95% CI) for mortality in eculizumab‐treated time versus untreated time was 0.51 (0.41–0.64; p < 0.0001). Significant baseline covariates included age, sex, history of bone marrow failure, ≥4 erythrocyte transfusions within 12 months before baseline, and an estimated glomerular filtration rate ≤ 60 mL/min/1.73 m 2 (all p < 0.0001). In the adjusted analysis, patients with baseline HDA had the greatest reduction in mortality risk (HR [95% CI], 0.51 [0.36–0.72]). Treated patients had approximately 60% reduction in TE/MAVE risk during treated versus untreated time (HR [95% CI]: TE: 0.40 [0.26–0.62], MAVE: 0.37 [0.26–0.54]; p < 0.0001). Conclusion Using data from the largest Registry of patients with PNH, with ≥14 years of overall follow‐up, we demonstrate that treatment with eculizumab conferred a 49% relative benefit in survival and an approximately 60% reduction in TE/MAVE risk.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".