{
  "abstract": "Cross-cohort evaluation of multi-omics prognostic models can fail because molecular features are not assayable, fitted models do not transport, feature selection is unstable, or molecular data add little beyond clinical predictors. We used a dual-track evaluation design with TCGA-BRCA as the source cohort and METABRIC as the independent target cohort. Track A tested outcome-blind transport of fixed historical RNA and copy-number models without target-cohort refitting, whereas Track B reconstructed the dependency-aware selection procedure within METABRIC using leakage-controlled repeated cross-validation. Literal transport provided little or negative incremental overall-survival discrimination: RNA reduced Harrell's C-index relative to clinical prediction (Delta C = -0.0136), while copy number was essentially neutral. Track B showed no reliable overall-survival gain for RNA, copy number, or mutation; methylation and the reconstructed multimodal model performed worse than matched clinical comparators. In a protocol-locked post-hoc extension, the same fixed features were retained but model parameters were re-estimated within METABRIC. Incremental C-index increased by 0.0162 for RNA, 0.0091 for copy number, and 0.0201 for the combined panel. Random-panel benchmarks showed that the RNA gain was common among alternative panels, whereas the historical copy-number panel ranked above all 200 panels sampled from its recovered assayable candidate space. The recurrence-free-survival sensitivity analysis showed a positive RNA contrast (Delta C = 0.0146). These results separate failure of fixed-model transport from loss of information in the underlying feature set and show that successful local redevelopment does not by itself establish feature-set specificity.",
  "abstract_shown": true,
  "affiliations": [
    "Lakehead University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "E. Krikun"
    },
    {
      "name": "A. Alkhateeb"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/crevn7e1b35fk.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.18.752709",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752709v1.full",
  "id": "crevn7e1b35fk",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752709v1",
  "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": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1306|Breast Cancer Treatment Studies"
    ]
  ],
  "openalex": "W7214205757",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752709v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/crevn7e1b35fk.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:27Z",
      "native_id": "10.64898/2026.09.18.752709",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752709v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "External Evaluation of Multi-Omics Prognostic Models Across TCGA-BRCA and METABRIC: Transportability, Stability, and Incremental Performance",
  "title_text": "External Evaluation of Multi-Omics Prognostic Models Across TCGA-BRCA and METABRIC: Transportability, Stability, and Incremental Performance",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:27Z",
  "url": "https://research.draconitic.com/paper/crevn7e1b35fk",
  "venue": "bioRxiv",
  "versions": []
}