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Record W4389150857 · doi:10.1136/jnnp-2023-abn.179

SUNFISH: 4-year efficacy and safety data of risdiplam in types 2 and 3 SMA

2023· article· en· W4389150857 on OpenAlexaff
Servais Laurent, Day John, Mazzone Elena, Nascimento Andres, Maryam Oskoui, Giovanni Baranello, Gerber Marianne, Martin Carmen, Yeung Wai Yin, Mercuri Eugenio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsSMA*PlaceboMedicineSpinal muscular atrophyClinical endpointMotor functionPhysical therapyInternal medicinePhysical medicine and rehabilitationRandomized controlled trial

Abstract

fetched live from OpenAlex

<h3></h3> Risdiplam (EVRYSDI®) is an oral survival of motor neuron (<i>SMN2</i>) pre-mRNA splicing modifier approved by the EMA and MHRA for the treatment of patients aged ≥2 months with Type 1, 2 or 3 spinal muscular atrophy (SMA) or 1–4 <i>SMN2</i> copies. SUNFISH (NCT02908685) is a two-part, randomised, placebo-controlled, double-blind study in patients with Types 2/3 SMA aged 2–25 years at enrolment. Part 2 (N=180) assessed efficacy and safety of the Part 1-selected dose of risdiplam versus placebo in Type 2 and non-ambulant Type 3 SMA. Participants were treated with risdiplam or placebo for 12 months, then received risdiplam in a blinded manner until Month 24, when they entered the open-label extension. The primary endpoint (Part 2) of change from baseline in the 32-item Motor Function Measure (MFM32) total score in patients receiving risdiplam (n=120) versus placebo (n=60) was met at Month 12. Motor function increases were sustained in the second and third year after risdiplam treatment (assessed by the MFM32, Hammersmith Functional Motor Scale – Expanded and Revised Upper Limb Module). At Month 36, no safety findings led to treatment withdrawal in SUNFISH Part 1 or 2. Here we present 4-year efficacy and safety data from SUNFISH.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.144

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.064
GPT teacher head0.357
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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