{
  "abstract": "Donor-derived cell-free DNA (dd-cfDNA) is increasingly used for post transplantation non-invasive surveillance; however, its clinical interpretation remains inconsistent, with widely ranging thresholds and is typically applied as a single binary cutoff in literature. The optimal decision framework for rule-out and rule-in decisions, and whether a single threshold remains clinically meaningful, are currently uncertain. We performed a Bayesian hierarchical summary receiver operating characteristic (HSROC) meta-analysis of 14 studies (1,763 patients) evaluating dd-cfDNA against endomyocardial biopsy. To account for serial testing within individuals, we applied a cluster-corrected design effect, reducing 6,103 observations to 2,518 effective tests. Threshold-dependent sensitivity and specificity were modelled continuously. We compared a conventional single-threshold approach with a data-driven adaptive framework defining rule-out and rule-in thresholds and evaluated clinical utility by decision-curve analysis across rejection prevalences from 1% to 50%, incorporating repeat-testing strategies. The pooled area under the HSROC curve was 0.78 (95% CrI, 0.67-0.84). The Youden-optimal threshold (0.20%) yielded balanced sensitivity (0.77) and specificity (0.77) but failed to support clinical objectives of diagnosis. An adaptive framework identified a rule-out threshold of 0.16% (sensitivity 0.80) and a rule-in threshold of 0.48% (specificity 0.90), defining a indeterminate / grey zone. The residual one-in-five false-negative rate at the rule-out anchor reflects low-grade, non-cytolytic rejection, the imperfect histological reference standard and fractional suppression of the donor signal, rather than the statistical model; a result above the rule-in anchor carries a positive predictive value of approximately 38% at 10% prevalence and denotes an indication for tissue diagnosis and multimodal investigation, not for empiric treatment. Across low-to-intermediate prevalence, dd-cfDNA-guided strategies exceeded both the biopsy-all and monitor-all reference strategies; among testing strategies, repeat-if-borderline achieved the highest net benefit across the majority of the prevalence-threshold space and sustained positive net benefit over the widest operating range of any strategy, reducing false-positive biopsies without materially compromising detection. At high prevalence, where a first elevated result is usually true, biopsy-all became competitive. A single threshold is therefore clinically inadequate for post-transplant surveillance. Our tri-state, prevalence-aware framework integrating rule-out, indeterminate, and rule-in zones with selective repeat testing, more accurately reflects biomarker behavior and yields greater net benefit than any single cutoff because these anchors are pooled, population-level estimates rather than universal constants, programs should adopt this architecture and calibrate their own high-sensitivity rule-out and high-specificity rule-in thresholds to their local assay and population.",
  "abstract_shown": true,
  "affiliations": [
    "Malla Reddy Institute of Medical Sciences"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "J. D. John"
    },
    {
      "name": "F. Henna"
    },
    {
      "name": "F. Waseem"
    },
    {
      "name": "M. A. Hassan"
    },
    {
      "name": "Z. Bacha"
    },
    {
      "name": "M. Mukhlis"
    },
    {
      "name": "B. K. Mohammed"
    },
    {
      "name": "S. Cheema"
    },
    {
      "name": "K. Shah"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9zf6qv44rbhak.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.05.15.26353184",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.05.15.26353184v4.full",
  "id": "9zf6qv44rbhak",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.05.15.26353184v4",
  "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": [
    [
      "medrxiv",
      "cardiovascular medicine"
    ],
    [
      "openalex",
      "2746|Transplantation: Methods and Outcomes"
    ]
  ],
  "openalex": "W7162096646",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.05.15.26353184v4.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-05-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9zf6qv44rbhak.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:52Z",
      "native_id": "10.64898/2026.05.15.26353184",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.05.15.26353184v4"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:cardiovascular medicine",
      "subfield": "cardiovascular"
    }
  ],
  "title": "Redefining Non Invasive Post Transplant Surveillance: A Bayesian Meta Analysis and Decision Curve Framework for Donor Derived Cell Free DNA in Heart Transplantation",
  "title_text": "Redefining Non Invasive Post Transplant Surveillance: A Bayesian Meta Analysis and Decision Curve Framework for Donor Derived Cell Free DNA in Heart Transplantation",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:52Z",
  "url": "https://research.draconitic.com/paper/9zf6qv44rbhak",
  "venue": "medRxiv",
  "versions": []
}