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262.6: Absolute dd-cfDNA monitoring reduces time to ABMR diagnosis in kidney transplant recipients with de novo DSA: a diagnostic randomized clinical trial.

2024· article· en· W4402798062 on OpenAlexaff
Aylin Akifova, Klemens Budde, Mira Choi, Michael Oellerich, Julia Beck, Kirsten Bornemann-Kolatzki, Ekkehard Schütz, Nils Lachmann, Philip F. Halloran, Bilgin Osmanodja

Bibliographic record

VenueTransplantation · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineRandomized controlled trialKidney transplantKidney transplantationInternal medicineUrologyKidney

Abstract

fetched live from OpenAlex

Introduction: Donor-derived cell-free DNA (dd-cfDNA) is an emerging biomarker in transplantation that non-invasively detects graft pathologies with increased cellular damage, such as allograft rejection. Recent studies demonstrated its excellent diagnostic performance in detecting antibody-mediated rejection (ABMR) in kidney transplant recipients (KTR). However, the clinical benefits of routine dd-cfDNA monitoring still need to be established. Methods: In this diagnostic, single-center, open-label, randomized clinical trial, we assigned 40 KTR with prevalent de novo DSA (dnDSA) with mean fluoerscence intensity (MFI) >1000 and estimated glomerular filtration rate ≥20 mL/min/1.73m2, but without biopsy-proven ABMR, to either dd-cfDNA-guided biopsy (intervention group) or clinician-guided biopsy (control group) over a 12-months period. In both groups, dd-cfDNA was assessed at inclusion and 1, 3, 6, 9, and 12 months. In the intervention group, dd-cfDNA >50cp/mL indicated a diagnostic biopsy. Biopsies for clinical indication could be performed at any point during the study period in both groups. A protocol biopsy was scheduled after 12 months for patients without dd-cfDNA-guided biopsy or clinical indication biopsy until study completion. Along with conventional histopathological examination, additional analysis with the Molecular MicroscopeⓇ Diagnostic System (MMDx) was available to assess the correlation with dd-cfDNA. The primary endpoint was time from study inclusion to diagnosis of active or chronic active ABMR. Results: 39/40 patients had functioning grafts at study completion. From these, 26 patients underwent biopsy, 13 in each group. ABMR was diagnosed earlier in the intervention group than in the control group (median 2.8 months, IQR 1.7-5.3 vs. median 14.5 months, IQR 13.3-16.7, p=0.003). Longitudinal dd-cfDNA monitoring with an absolute cutoff of 50 copies/mL had following test metrics for the detection of ABMR in DSA+ patients: AUC, 0.92; sensitivity, 0.83; specificity, 0.79; PPV, 0.77; NPV, 0.85, and was superior to routine biomarkers such as serum creatinine, urine albumin and dnDSA-MFI for distinguishing ABMR. Furthermore, absolute dd-cfDNA levels showed strong correlation (R=0.8, p<0.001) with the molecular ABMR score in MMDx and moderate correlation (R=0.64, p<0.001) with ABMR features, such as microvascular inflammation (g+ptc), in conventional histopathology. Conclusion: We conclude that dd-cfDNA-guided biopsy in KTR with prevalent dnDSA can reduce the time to ABMR diagnosis and hereby expedite therapy initiation.Laboratory testing was sponsored by Oncocyte.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.360
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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