{
  "abstract": "To develop and validate a machine-learning–based prediction model for overall survival (OS) in locally advanced head and neck squamous cell carcinoma (LA-HNSCC) that integrates both surgery-based and chemoradiotherapy (CRT) cohorts within a single framework. A total of 1,005 LA-HNSCC patients receiving curative-intent surgery-based treatment or CRT were retrospectively assembled from a domestic multicenter cohort ( n = 678) and publicly available datasets from The Cancer Imaging Archive ( n = 327). Candidate predictors were pre-specified from routinely available clinical variables. Elastic net regularization with 10-fold cross-validation was applied for variable selection and weighting, followed by a multivariable Cox proportional hazards model. Elastic net selected 12 variables, of which p16 status, performance status, nodal stage, serum albumin, T stage, and age were most influential. The model showed good discrimination (C-index 0.73), with time-dependent AUCs of 0.78–0.73 across 1–5 years and good calibration at 1 and 3 years. Decision curve analysis confirmed clinical utility across relevant threshold probabilities in both cohorts. By relying on prognostic factors common to both surgery-based treatment and CRT, this interpretable model demonstrated stable performance and may support prognostic risk stratification applicable across treatment modalities in LA-HNSCC.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "name": "Yutaro Koide"
    },
    {
      "name": "Shunichi Ishihara"
    },
    {
      "name": "Kohei Wakabayashi",
      "orcid": "0000-0003-4833-8660"
    },
    {
      "name": "Souichiro Abe"
    },
    {
      "name": "Nobuhiro Hanai"
    },
    {
      "name": "Taijiro Ozawa"
    },
    {
      "name": "Makoto Ito",
      "orcid": "0000-0001-7733-1594"
    },
    {
      "name": "Hidetoshi Shimizu"
    },
    {
      "name": "Takahiro Aoyama",
      "orcid": "0000-0002-8423-6509"
    },
    {
      "name": "Masamune Noguchi"
    },
    {
      "name": "Hiroyuki Tachibana"
    },
    {
      "name": "Takeshi Kodaira",
      "orcid": "0000-0002-7075-8488"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/btp538xngb9qh.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-74101-6",
  "fulltext_url": null,
  "id": "btp538xngb9qh",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-74101-6",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2733|Head and Neck Cancer Studies"
    ]
  ],
  "openalex": "W7223185907",
  "pdf_url": "https://www.nature.com/articles/s41598-026-74101-6_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-22",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/btp538xngb9qh.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:33Z",
      "native_id": "10.1038/s41598-026-74101-6",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-74101-6"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2733|Head and Neck Cancer Studies",
      "subfield": "general"
    }
  ],
  "title": "Development of a clinical prediction model for overall survival in locally advanced head and neck squamous cell carcinoma",
  "title_text": "Development of a clinical prediction model for overall survival in locally advanced head and neck squamous cell carcinoma",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:33Z",
  "url": "https://research.draconitic.com/paper/btp538xngb9qh",
  "venue": "Scientific Reports",
  "versions": []
}