{
  "abstract": "Background: Mathematical coupling and comparator selection are established concerns when a transcriptome response is defined as follow-up minus baseline. We assessed whether apparent within-cohort improvement survives matched constant-follow-up and scalar-shrinkage controls, and whether specified evaluation faults are detectable in an auditable vascular transcriptome benchmark. Results: Using eight frozen modules, 72 rosuvastatin pairs, 14 peripheral artery disease pairs, 20 repeated subject-held-out five-fold partitions, and 5,000 subject bootstrap draws of fixed losses, we compared 15 explicit specifications. Supporting post hoc analyses included 800 known-truth training/test simulations, annotation and input-ablation sensitivities, complete-tuning integrity checks, and an independent-source cross-sectional artery description. In GSE86216, nested follow-up ridge had lower observed repeated-CV mean absolute error than mean follow-up, 0.3280 versus 0.3405 (difference 0.0126; descriptive central 95% percentile range 0.0033-0.0224), while scalar shrinkage had lower observed error (0.3256). These ranges have no validated coverage guarantee. No full-matrix advantage was established; equivalence was not tested. In peripheral artery disease, nested ridge (0.3449) had slightly higher observed MAE than the median follow-up comparator (0.3409), and no advantage was established. Simulations illustrated how mean follow-up can outperform mean change without temporal signal, while the GSE281841 histological stenosis-grade description remained limited by anatomical imbalance, unconfirmed participant identity and an unresolved sample-count discrepancy. Conclusions: These retrospective, nonconfirmatory comparisons show modestly lower observed within-cohort error than constant-follow-up controls in one cohort, without established full-matrix advantage. They do not partition prediction into mathematical, technical and biological components. Independent longitudinal validation and clinical utility remain unestablished.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai 200032, China."
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "L. You"
    },
    {
      "name": "Z. Peng"
    },
    {
      "name": "Y. Guo"
    },
    {
      "name": "L. Shen"
    },
    {
      "affs": [
        0
      ],
      "name": "J. Ge"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bzshpx5bf0a7x.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.25.26366405",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.10.25.26366405v1.full",
  "id": "bzshpx5bf0a7x",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.10.25.26366405v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "health informatics"
    ],
    [
      "openalex",
      "1312|Gene expression and cancer classification"
    ]
  ],
  "openalex": "W7224136171",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.10.25.26366405v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bzshpx5bf0a7x.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:58Z",
      "native_id": "10.64898/2026.10.25.26366405",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.10.25.26366405v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:health informatics",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "VascFlux-GEO: Comparator selection and auditability in vascular transcriptome module prediction",
  "title_text": "VascFlux-GEO: Comparator selection and auditability in vascular transcriptome module prediction",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:58Z",
  "url": "https://research.draconitic.com/paper/bzshpx5bf0a7x",
  "venue": "medRxiv",
  "versions": []
}