Agalsidase alfa versus agalsidase beta for the treatment of Fabry disease: an international cohort study
Bibliographic record
Abstract
BACKGROUND: Two recombinant enzymes (agalsidase alfa 0.2 mg/kg/every other week and agalsidase beta 1.0 mg/kg/every other week) have been registered for the treatment of Fabry disease (FD), at equal high costs. An independent international initiative compared clinical and biochemical outcomes of the two enzymes. METHODS: In this multicentre retrospective cohort study, clinical event rate, left ventricular mass index (LVMI), estimated glomerular filtration rate (eGFR), antibody formation and globotriaosylsphingosine (lysoGb3) levels were compared between patients with FD treated with agalsidase alfa and beta at their registered dose after correction for phenotype and sex. RESULTS: 387 patients (192 women) were included, 248 patients received agalsidase alfa. Mean age at start of enzyme replacement therapy was 46 (±15) years. Propensity score matched analysis revealed a similar event rate for both enzymes (HR 0.96, P=0.87). The decrease in plasma lysoGb3 was more robust following treatment with agalsidase beta, specifically in men with classical FD (β: -18 nmol/L, P<0.001), persisting in the presence of antibodies. The risk to develop antibodies was higher for patients treated with agalsidase beta (OR 2.8, P=0.04). LVMI decreased in a higher proportion following the first year of agalsidase beta treatment (OR 2.27, P=0.03), while eGFR slopes were similar. CONCLUSIONS: Treatment with agalsidase beta at higher dose compared with agalsidase alfa does not result in a difference in clinical events, which occurred especially in those with more advanced disease. A greater biochemical response, also in the presence of antibodies, and better reduction in left ventricular mass was observed with agalsidase beta.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".