{
  "abstract": "In Parkinsons disease (PD), early phase clinical trials of disease-modifying agents generally use the MDS-UPDRS Part III as the primary outcome measure of motor function, which typically requires a large sample and/or a long (12- 18 months) treatment duration, even if a substantial treatment effect is assumed. This is due to the rather slow rate of early PD progression relative to the variability of the MDS-UPDRS Part III assessments. Using placebo-arm data from four recent large Phase 2 trials of early-stage PD (SPARK, PASADENA, PADOVA and LUMA), the sample size needed to detect a range of assumed treatment effects on MDS-UPDRS Part III progression was estimated. The trial sample size estimates obtained for MDS-UPDRS Part III and for smartphone-based sensor-derived motor functional composite (MFC) endpoints were compared using an approach based on relative responsiveness to disease progression. The calculations were also implemented in an interactive, publicly accessible application. Powering a one-year trial using the MFC1 endpoint, derived from three active assessments (6-minute walk, U-turn and Hand Pronation-Supination), or the MFC2, which adds 60-Second Typing, was projected to reduce the required sample size by more than half relative to the MDS-UPDRS Part III, assuming equivalent proportional treatment effects.",
  "abstract_shown": true,
  "affiliations": [
    "Indivi AG"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "M. Pedrera Gomez"
    },
    {
      "name": "C. Bernasconi"
    },
    {
      "name": "C. Mazza"
    },
    {
      "name": "S. Belachew"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8trr97q4n4w68.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.29.26363876",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363876v1.full",
  "id": "8trr97q4n4w68",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363876v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "neurology"
    ],
    [
      "openalex",
      "2613|Statistical Methods in Clinical Trials"
    ]
  ],
  "openalex": "W7220363497",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363876v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8trr97q4n4w68.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:10Z",
      "native_id": "10.64898/2026.09.29.26363876",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26363876v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:neurology",
      "subfield": "neurology"
    }
  ],
  "title": "Sample Size and Power Calculations Based on Endpoint Responsiveness: Applications to Trials of Disease-Modifying Therapies in Parkinson's Disease",
  "title_text": "Sample Size and Power Calculations Based on Endpoint Responsiveness: Applications to Trials of Disease-Modifying Therapies in Parkinson's Disease",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:10Z",
  "url": "https://research.draconitic.com/paper/8trr97q4n4w68",
  "venue": "medRxiv",
  "versions": []
}