Efficacy of the pharmacologic chaperone migalastat in a subset of male patients with the classic phenotype of Fabry disease and migalastat-amenable variants: data from the phase 3 randomized, multicenter, double-blind clinical trial and extension study
Bibliographic record
Abstract
Purpose Outcomes in patients with Fabry disease receiving migalastat during the phase 3 FACETS trial (NCT00925301) were evaluated by phenotype. Methods Data were evaluated in two subgroups of patients with migalastat-amenable GLA variants: "classic phenotype" ( n =14; males with residual peripheral blood mononuclear cell α-galactosidase A <3% normal and multiorgan system involvement) and "other patients" ( n =36; males not meeting classic phenotype criteria and all females). Endpoints included estimated glomerular filtration rate (eGFR), left ventricular mass index (LVMi), Gastrointestinal Symptoms Rating Scale diarrhea subscale (GSRS-D), renal peritubular capillary (PTC) globotriaosylceramide (GL-3) inclusions, and plasma globotriaosylsphingosine (lyso-Gb 3 ). Results Baseline measures in the classic phenotype patients suggested a more severe phenotype. At month 24, mean (SD) annualized change in eGFR CKD-EPI with migalastat was −0.3 (3.76) mL/min/1.73m 2 in the classic phenotype subgroup; changes in LVMi, GSRS-D, and lyso-Gb 3 were −16.7 (18.64) g/m 2 , −0.9 (1.66), and −36.8 (35.78) nmol/L, respectively. At month 6, mean PTC GL-3 inclusions decreased with migalastat (−0.8) and increased with placebo (0.3); switching from placebo to migalastat, PTC inclusions decreased by −0.7. Numerically smaller changes in these endpoints were observed in the other patients. Conclusion Migalastat provided clinical benefit to patients with Fabry disease and amenable variants, regardless of disease severity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".