{
  "abstract": "Lung cancer screening (LCS) participants have a high competing risk of non-lung cancer related death, which limits screening benefit. We hypothesized that imaging-based biological age can identify individuals at higher risk of non-lung cancer mortality. Low dose computed tomography scans from a large LCS trial were retrospectively analyzed. Bone density loss, muscular fat infiltration, vascular calcification, and visceral fat mass were calculated using segmentations from a nnU-Net based deep learning segmentation model. Each participant’s age gap, defined as the difference between their estimated biological age and chronological age, was estimated with disease course mapping using a Bayesian mixed-effects model. Disease course map construction used all available longitudinal scan data, whilst individual biological age prediction used baseline scan data only. The performance of age gap as a parameter in competing risk models for non-lung cancer related death versus lung cancer diagnosis was evaluated, following the TRIPOD + AI reporting guideline. We included 29,745 scans from 12,478 participants in the final analysis. Median follow-up was 5 years, representing 58,284 person-years at risk. Multivariable survival models of competing risks were constructed, including the estimated age gap. The subdistribution hazard ratio (sHR) for each decade of age gap for non-lung cancer related death was higher (sHR = 2.0, 95% CI 1.8–2.3), compared to lung cancer diagnosis (sHR = 1.3, 95% CI 1.2–1.5). Addition of age gap improved model concordance of non-lung cancer death compared to a model with clinical variables alone (pooled C-index = 0.69 vs 0.73, difference + 0.04, 95% CI 0.03–0.04, p < 0.001). Biological age estimation using an imaging-based disease progression model improves prediction of non-lung cancer related death in lung cancer screening.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 159,
  "authors": [
    {
      "name": "Daryl O. Cheng",
      "orcid": "0000-0001-9906-4298"
    },
    {
      "name": "John McCabe"
    },
    {
      "name": "Tanya Patrick"
    },
    {
      "name": "Robert Chapman"
    },
    {
      "name": "Shanshan Wang"
    },
    {
      "name": "Tianqi Yang"
    },
    {
      "name": "Adam Szmul"
    },
    {
      "name": "Mehran Azimbagirad"
    },
    {
      "name": "Shahab Aslani"
    },
    {
      "name": "Monica L. Mullin"
    },
    {
      "name": "Sindhu Bhaarrati Naidu"
    },
    {
      "name": "Chuen Ryan Khaw"
    },
    {
      "name": "Alfred C. P. So"
    },
    {
      "name": "SUMMIT consortium"
    },
    {
      "name": "Aashna Samson"
    },
    {
      "name": "Adefiola Olabode"
    },
    {
      "name": "Alberto Villanueva"
    },
    {
      "name": "Ali Mohammed"
    },
    {
      "name": "Alice Cotton"
    },
    {
      "name": "Andrew Crossingham"
    },
    {
      "name": "Andrew Perugia"
    },
    {
      "name": "Anjeli Ketkar"
    },
    {
      "name": "Anna Sikorska"
    },
    {
      "name": "Anthony Edey"
    },
    {
      "name": "Antonette Andrews"
    },
    {
      "name": "April Neville"
    },
    {
      "name": "Burcu Ozaltin"
    },
    {
      "name": "Camilla Mitchell"
    },
    {
      "name": "Catherine Nestor"
    },
    {
      "name": "Celia Snell"
    },
    {
      "name": "Charlie Sayer"
    },
    {
      "name": "Charlotte Cash"
    },
    {
      "name": "Chimtom Nwaosu"
    },
    {
      "name": "Christine Hosein"
    },
    {
      "name": "Claire Levermore"
    },
    {
      "name": "Columbus Ife"
    },
    {
      "name": "Derya Ovayolu"
    },
    {
      "name": "Dominique Arancon"
    },
    {
      "name": "Domminique Arancon"
    },
    {
      "name": "Eleanor Hellier"
    },
    {
      "name": "Elena Stefan"
    },
    {
      "name": "Elodie Murali"
    },
    {
      "name": "Esther Arthur-Darkwa"
    },
    {
      "name": "Ethaar El-Emir"
    },
    {
      "name": "Fabia Ruggiero"
    },
    {
      "name": "Fahiza Chowdhury"
    },
    {
      "name": "Fahmida Hoque"
    },
    {
      "name": "Fanta Bojang"
    },
    {
      "name": "Farhida Begum"
    },
    {
      "name": "Geoff Bellingan"
    },
    {
      "name": "Georgia Bullock"
    },
    {
      "name": "Graham Robinson"
    },
    {
      "name": "Gulistan Keskinbicak"
    },
    {
      "name": "Gulten Geneci"
    },
    {
      "name": "Harriet Sorrell"
    },
    {
      "name": "Hasti Robbie"
    },
    {
      "name": "Helen Kiconco"
    },
    {
      "name": "Helen Victoria Bowyer"
    },
    {
      "name": "Henna Makwana"
    },
    {
      "name": "Hina Pervez"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8nwcm2cm04byd.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-75832-2",
  "fulltext_url": null,
  "id": "8nwcm2cm04byd",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-75832-2",
  "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",
      "2740|Lung Cancer Diagnosis and Treatment"
    ]
  ],
  "openalex": "W7202148274",
  "pdf_url": "https://www.nature.com/articles/s41598-026-75832-2_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/8nwcm2cm04byd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:28Z",
      "native_id": "10.1038/s41598-026-75832-2",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-75832-2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2740|Lung Cancer Diagnosis and Treatment",
      "subfield": "general"
    }
  ],
  "title": "Imaging-based biological age estimation predicts competing mortality risk in lung cancer screening",
  "title_text": "Imaging-based biological age estimation predicts competing mortality risk in lung cancer screening",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:28Z",
  "url": "https://research.draconitic.com/paper/8nwcm2cm04byd",
  "venue": "Scientific Reports",
  "versions": []
}