P.065 AVXS-101 gene-replacement therapy (GRT)) in presymptomatic spinal muscular atrophy (SMA): study update
Bibliographic record
Abstract
Background: SMA is a neurodegenerative disease caused by biallelic deletion/mutation of SMN1. Copies of a similar gene (SMN2) modify disease severity. In a phase 1 study, SMN GRT onasemnogene abeparvovec (AVXS-101) improved outcomes of symptomatic SMA patients with two SMN2 copies (2xSMN2) dosed ≤6 months. Because motor neuron loss can be insidious and disease progression is rapid, early intervention is critical. This study evaluates AVXS-101 in presymptomatic SMA newborns. Methods: SPR1NT is a multicenter, open-label, phase 3 study enrolling ≥27 SMA patients with 2–3xSMN2. Asymptomatic infants ≤6 weeks receive a one-time intravenous AVXS-101 infusion (1.1x1014 vg/kg). Safety and efficacy are assessed through study end (18 [2xSMN2] or 24 months [3xSMN2]). Primary outcomes: independent sitting for ≥30 seconds (18 months [2xSMN2]) or assisted standing (24 months [3xSMN2]). Results: From April–September 2018, 7 infants received AVXS-101 (4 female; 6 with 2xSMN2) at ages 8–37 days. Mean baseline CHOP-INTEND score was 41.7 (n=6), which increased by 6.8, 11.0, 18.0, and 22.5 points at day 14 (n=4), month 1 (n=3), 2 (n=3), and 3 (n=2). Updated data available at the time of the congress will be presented. Conclusions: Preliminary data from SPR1NT show rapid motor function improvements in presymptomatic SMA patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".