{
  "abstract": "BackgroundComprehensive genomic reports in oncology contain complex molecular information that must be translated into concise summaries for treating clinicians. Manual summarisation is time-intensive, and robust evidence supporting AI-assisted summarisation systems remains limited. We evaluated whether AI-generated summaries were non-inferior to manually produced summaries in faithfully representing information from tertiary paediatric cancer genomics reports.\n\nMethodsQNOMX-VHIR-CPSP-001 Phase 1 was a single-site, non-interventional clinical performance study conducted at Vall dHebron Institut de Recerca under ISO 20916:2019. De-identified tertiary paediatric cancer genomics reports were summarised using both the AI-assisted system under evaluation and the standard manual workflow. Three qualified raters assessed both summary types against the source reports using the six-domain, five-point Quality Summary Index (QSI) in a blinded, counterbalanced crossover design with a minimum fourteen-day washout. Co-primary endpoints were composite content and presentation scores. Non-inferiority was assessed using a pre-specified Bayesian hierarchical model with a margin of 0.5 points and confirmed using a frequentist linear mixed model.\n\nResultsThirty-seven of 38 planned cases contributed 74 paired evaluations. Mean content scores were similar between AI-generated and manual summaries (4.01 vs 3.97), whereas AI-generated summaries achieved higher presentation scores (4.39 vs 4.12). Non-inferiority was demonstrated for both co-primary endpoints: content +0.05 (95% CrI -0.18 to +0.28), presentation +0.28 (+0.10 to +0.47). Frequentist analyses were concordant. Accuracy was the only QSI dimension for which Bayesian non-inferiority was not concluded. Inter-rater reliability was low across all QSI domains.\n\nConclusionsAI-generated summaries were non-inferior to manually produced summaries for both content and presentation endpoints in tertiary paediatric oncology genomics reports. Presentation scores were higher for AI-generated summaries, whereas content scores were comparable between approaches. Low inter-rater reliability limits confidence in the dimension-level estimates and is the main constraint on future validation studies. Clinical validity and workflow effect were not assessed.",
  "abstract_shown": true,
  "affiliations": [
    "Qnomx AG"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "J. Creeden"
    },
    {
      "name": "M. Olivecrona"
    },
    {
      "name": "N. Benavent"
    },
    {
      "name": "R. Hladun Alvaro"
    },
    {
      "name": "L. Valero-Arrese"
    },
    {
      "name": "A. Carolina Torres"
    },
    {
      "name": "A. Soriano"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3dh2bkp6chr5p.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.10.26362656",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362656v1.full",
  "id": "3dh2bkp6chr5p",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362656v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "genetic and genomic medicine"
    ],
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7212353400",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362656v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-10",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3dh2bkp6chr5p.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:21Z",
      "native_id": "10.64898/2026.09.10.26362656",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.09.10.26362656v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:genetic and genomic medicine",
      "subfield": "human-genetics"
    }
  ],
  "title": "Evaluation of AI-assisted summarisation of tertiary clinical genomics reports: results of the QNOMX-VHIR-CPSP-001 Phase 1 study",
  "title_text": "Evaluation of AI-assisted summarisation of tertiary clinical genomics reports: results of the QNOMX-VHIR-CPSP-001 Phase 1 study",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:21Z",
  "url": "https://research.draconitic.com/paper/3dh2bkp6chr5p",
  "venue": "medRxiv",
  "versions": []
}