Reproducibility of the Banff classification in subclinical kidney transplant rejection
Bibliographic record
Abstract
The Banff classification for kidney allograft pathology has proved to be reproducible, but its inter and intraobserver agreement can vary substantially among centres. The aim of this study was to evaluate Banff reproducibility of surveillance renal allograft biopsies among renal pathologists from different transplant centres. This study included 32 renal transplant patients with stable graft function. Biopsies were performed 2 and 12 months post-transplant. Histology was interpreted according to the Banff schema by three renal pathologists, and inter and intraobserver agreement were measured. The best reproducibility was obtained for the presence or absence of acute rejection (AR), with kappa values ranging from moderate (kappa = 0.47; p = 0.006) to good (kappa = 0.72; p = 0.0001). However, the agreement for 'suspicious for AR' category was poor between all observers. For scoring and grading interstitial inflammation and intimal arteritis the agreement were poor and moderate, respectively. Reproducibility for the presence or absence of chronic allograft nephropathy (CAN) was heterogeneous, ranging from poor (kappa = 0.13; p = NS) to moderate (kappa = 0.56; p = 0.007). Scoring chronic changes such as fibrous intimal thickening gave a reasonable interobserver agreement. Intraobserver reproducibility was good for presence or absence of AR, but was poor for the diagnosis of CAN. In conclusion, histologic analysis of stable renal allografts based on Banff criteria showed a good agreement for the diagnosis of AR and a reasonable kappa for CAN, but reproducibility for scoring and grading showed a substantial interobserver variation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".