{
  "abstract": "BackgroundNusinersen has substantially increased survival and improved disease progression in Spinal Muscular Atrophy (SMA) patients. However, treatment response is heterogeneous, with some patients gaining the ability to sit and walk whilst others display less obvious changes.MethodFrom the SMA Reach UK and the Italian Telethon Network, 124 non-sitter SMA patients treated with nusinersen under 4 years were included and randomly allocated to training and testing (80/20%). Tree and regression-based machine learning for survival outcomes were compared, and oblique random forests were selected, with a testing C-Index of 0.74. The features were selected from items of the CHOP-INTEND and HINE-2 motor function assessments, respiratory and swallowing status using mutual information.FindingsSixty-two patients (50%) achieved sitting, at a median age of 2.4 years. The predicted median time-to-sitting in those requiring tube feeding at treatment initiation was 4-months later than those without, and this was the most influential factor. Specific motor function features, including the ability to kick in supine, were strongly associated with a higher likelihood of sitting.InterpretationThis work provides a framework for predicting nusinersen-response and represents the first stage in personalised counselling on treatment plans for SMA.FundingSupport for SMA Reach is provided by Biogen, Roche and Novartis, and historically the NIHR BRC, SMA Trust, the MRC Translational Research Centre and MD UK. Support for the Italian network is provided by Famiglie SMA, Telethon (GSP 13002), and ASAMSI.",
  "abstract_shown": true,
  "affiliations": [
    "Dubowitz Neuromuscular Centre, UCL Great Ormond Street Institute of Child Health, London, UK.",
    "Health and Medical Science Programme, The Alan Turing Institute, London, UK.",
    "NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL Great Ormond Street Institute of Child Health, London, UK.",
    "Paediatric Neurology Unit, Catholic University, Rome, Italy.",
    "Centro Clinico Nemo, U.O.C. Neuropsichiatria Infantile Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.",
    "Population, Policy & Practice Department, UCL Great Ormond Street Institute of Child Health, London, UK.",
    "UCL Cancer Institute and Dept of Medical Physics & Biomedical Engineering, UCL, London, UK.",
    "Department of Statistical Science, UCL."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Georgia Stimpson",
      "orcid": "0000-0003-2795-9898"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Emer O'Reilly"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Giorgia Coratti"
    },
    {
      "affs": [
        5
      ],
      "name": "Deborah Ridout"
    },
    {
      "affs": [
        1,
        6
      ],
      "name": "Tapabrata Chakraborti"
    },
    {
      "affs": [
        1,
        7
      ],
      "name": "Robin Mitra"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Roberto de Sanctis"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Marika Pane"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Mariacristina Scoto"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Eugenio Mercuri"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Francesco Muntoni",
      "orcid": "0000-0002-9102-5232"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Giovanni Baranello"
    },
    {
      "name": "International SMA Consortium"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9fdt6sthr6jmf.bib",
  "cited_by": 0,
  "doi": "10.1177/22143602261496327",
  "fulltext_url": "https://europepmc.org/articles/PMC13683824",
  "id": "9fdt6sthr6jmf",
  "issns": [
    "2214-3599",
    "2214-3602"
  ],
  "landing_url": "https://europepmc.org/article/MED/42900957",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2716|Neurogenetic and Muscular Disorders Research"
    ]
  ],
  "openalex": "W7223022398",
  "pdf_url": "https://europepmc.org/articles/PMC13683824?pdf=render",
  "pmcid": "PMC13683824",
  "pmid": "42900957",
  "published": "2026-10-20",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9fdt6sthr6jmf.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:32Z",
      "native_id": "MED:42900957",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42900957"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2716|Neurogenetic and Muscular Disorders Research",
      "subfield": "human-genetics"
    }
  ],
  "title": "Machine learning predicts treatment response to nusinersen in non-sitter spinal muscular atrophy (SMA).",
  "title_text": "Machine learning predicts treatment response to nusinersen in non-sitter spinal muscular atrophy (SMA).",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:32Z",
  "url": "https://research.draconitic.com/paper/9fdt6sthr6jmf",
  "venue": "Journal of neuromuscular diseases",
  "versions": []
}