ReviewClinical transplantation and research2025
Donor-derived cell-free DNA in solid organ transplantation: analytical considerations, diagnostic performance, and clinical interpretation.
Review in Clinical transplantation and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Soluble Immune Checkpoints and Anti-HLA Antibodies in Kidney Transplant Recipients: Associations With Kidney Function.Immunology · 2026Article
- First-Trimester Down Syndrome Screening in Renal-Transplanted Pregnant Women: Blood Creatinine Levels Impact False-Positive Rate.Prenatal diagnosis · 2026Article
- Rejection-Focused Precision Medicine in Kidney Transplantation: Biology, Biomarkers, and Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Variability and longitudinal dynamics of donor-derived cell-free DNA in kidney and liver recipients: a comparison of absolute and relative quantities in plasma and urine.Frontiers in transplantation · 2026Article
- Advances in donor-derived cell-free DNA monitoring for solid organ transplantation.Frontiers in immunology · 2026Review
- Donor-Derived Cell-Free DNA in Allograft Transplantation: Exaggerated Hope or Cautious Reality?Biomedicines · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Donor-derived cell-free DNA (dd-cfDNA) has emerged as a valuable noninvasive biomarker for detecting allograft injury in solid organ transplantation. It is released into the bloodstream from the transplanted organ as a result of cell injury and immune activation, with baseline levels influenced by organ type, tissue turnover, and posttransplant physiological changes. Several analytical platforms are available, including quantitative polymerase chain reaction (PCR), digital droplet PCR, and next-generation sequencing, each differing in sensitivity, throughput, and reporting format. Commercial assays have been clinically validated across multiple organs. dd-cfDNA can be quantified as a percentage of total cell-free DNA or as an absolute concentration, with diagnostic thresholds varying by platform and organ type. Although dd-cfDNA demonstrates high negative predictive value and can reduce the need for unnecessary biopsies, it is not specific to rejection and may be elevated in the setting of infection, ischemia, or inflammation. Preanalytical and technical factors can also affect test performance. Therefore, dd-cfDNA should be interpreted with careful consideration of biological variation, assay characteristics, and the patient's clinical context. Future efforts should focus on defining organ-specific thresholds, improving interlaboratory standardization, expanding validation in underrepresented graft types, and assessing cost-effectiveness and clinical impact to support broader clinical adoption.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.