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Completed

NCT Number: NCT07004660

Performances of Large Language Models in Kidney Allograft Diagnostics

Kidney allograft rejection diagnosis relies on the complex Banff classification, but its application is limited by variability and workload. Our group previously built a scripted automation system, though it required major expert input. This study assesses whether modern LLMs can achieve similar diagnostic performance using Banff-based prompts, without extensive manual engineering.

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Key information

Conditions

Kidney Transplantation Disease Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

0 year–100 year

Sex eligibility

All sexes

Study type

Observational

About this study

Kidney allograft rejection remains a leading cause of allograft failure. Histological diagnosis relies on the Banff classification, a complex and evolving rule based framework. While successive Banff working groups refined the guidelines over time, daily interpretation is still hampered by inter and intra pathologist variability and growing demands on renal pathologists. This is why our group previously built a fully scripted Banff automation system. However, this system demanded years of expert curation and bespoke code before reaching acceptable accuracy. Whether modern LLMs, which show high capabilities to generate consistent and transparent reasoning at scale, can match expert pathologists without such resource intensive engineering remains unknown. The present study was therefore designed to benchmark state of the art LLMs against consensus diagnoses from senior renal pathologists on a representative series of kidney allograft biopsies, and to explore whether properly engineered prompts can translate Banff rules into reliable, reproducible diagnostic output.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Kidney recipients

Exclusion criteria

  • Combined transplant

Treatment and study plan

Primary outcomes

  1. Biopsy diagnosis

    Time frame: The biopsy will be protocol biopsies performed at 3 months and 1 year post transplant, or for-cause biopsies performed at any time post transplant.

    The diagnosis of the biopsy will be based on the latest Banff classification (2022). The diagnoses will include i) biopsies with nonspecific lesions or clean (n=40), ii) biopsies with antibody-mediated rejection (AMR) (n=40) among which 14 had acute AMR, 13 chronic active AMR and 13 chronic inactive AMR, iii) biopsies with T cell-mediated rejection (TCMR) (n=40), among which 20 had acute TCMR and 20 had chronic active TCMR, iv) biopsies with borderline for acute TCMR (n=40), v) biopsies with mixed rejection (n=40), and vi) biopsies with microvascular inflammation (MVI) (n=40) among which 20 had probable AMR and 20 had MVI without DSA and without C4d.

Sponsors and collaborators

Lead sponsor

Paris Translational Research Center for Organ Transplantation

Other

Registry information

Important dates

Study start
2004
Primary completion
2023
Study completion
2023
First posted
Jun 4, 2025
Registry last updated
Jun 4, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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