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Record W4311610529 · doi:10.2196/38878

The Japan Registry for Adult Subjects of Spinal Muscular Atrophy (jREACT-SMA): Protocol for a Longitudinal Observational Study

2022· article· en· W4311610529 on OpenAlexvenueno aff
Kentaro Sahashi, Atsushi Hashizume, Yachiyo Kuwatsuka, Madoka Chinen, Ai Saotome-Nakamura, Masahiko Ando, Masahisa Katsuno

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsnot available
FundersBiogen
KeywordsSMA*Spinal muscular atrophyObservational studyMedicinePhysical medicine and rehabilitationPhysical therapyProtocol (science)PsychologyGerontologyComputer scienceInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Spinal muscular atrophy (SMA) is an autosomal recessive genetic neuromuscular disorder with progressive muscle weakness and atrophy, mainly caused by lower motor neuron degeneration resulting from decreased levels of the survival motor neuron protein. Recently, 3 disease-modifying therapies for SMA (nusinersen, onasemnogene abeparvovec, and risdiplam) were approved in Japan that are expected to improve the prognosis of patients with SMA. Long-term clinical follow-up of adult patients treated with disease-modifying therapies and the natural history of SMA are essential to assess the real-world effectiveness of available treatments. Until recently, nusinersen was the only treatment option for patients with SMA in Japan; however, because Japanese approval of nusinersen was based on global clinical trials in infants and children aged 0-15 years with SMA, the effectiveness of nusinersen in adult patients has not been fully assessed in Japan. In addition, longitudinal clinical data of adult patients have not been systematically collected in Japan. OBJECTIVE: This longitudinal observational study of adult patients with SMA who have been diagnosed with 5q-SMA in Japan aims to gain a better understanding of the natural history of SMA, as well as the long-term effectiveness of disease-modifying therapies. Here, we describe the protocol for the study. METHODS: The Japan Registry for Adult Subjects of Spinal Muscular Atrophy (jREACT-SMA) study is a longitudinal (prospective and retrospective) observational study with a 60-month prospective follow-up being conducted at 19 investigational sites using the newly established jREACT-SMA registry. Patients aged ≥18 years with genetically confirmed 5q-SMA were planned to be enrolled in the registry from December 2020 to May 2022. The planned enrollment was 100 patients. The protocol was approved on September 28, 2020 (approval 2020-0289) by the ethical review committee of Nagoya University. Registration, demographics, genetic diagnosis, motor functions, patient-reported outcomes/quality-of-life outcomes, and other clinical data have been or will be collected. RESULTS: As of May 2022, 113 patients had been enrolled, and the completion of patient registration has been extended from May 2022 to December 2022. Data at registration and during the follow-up period were and will be prospectively collected at least once a year until November 2025 (maximum 60 months). Data analyses will be conducted when all data have been collected. Results are expected to be available in 2026 and the study is expected to be completed by March 2027. CONCLUSIONS: This jREACT-SMA study will provide longitudinal prospective follow-up data in adult patients with SMA in Japan, including data on the natural history of the disease and data on the long-term effectiveness of disease-modifying therapies. TRIAL REGISTRATION: University Hospital Medical Information Network Center Clinical Trials Registry UMIN000042015; https://rctportal.niph.go.jp/en/detail?trial_id=UMIN000042015. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/38878.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.016
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0160.004

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 head0.483
GPT teacher head0.588
Teacher spread0.105 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations7
Published2022
Admission routes1
Has abstractyes

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