Pathology Core Scoring Parameters and Reproducibility in the CureGN Study
Bibliographic record
Abstract
Background: CureGN is an NIH-funded multi-center, prospective, observational cohort study of patients with minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), or IgA nephropathy from 66 international sites with 2500 enrolled participants. The large scale of CureGN requires a practical systematic approach to pathologic scoring that can be applied consistently across a large number of cases and multiple scoring pathologists. The method reflects common pathology practices, generating data for assignment to currently used disease classifications and use in future studies utilizing conventional parameters. The objective of this analysis was to determine and evaluate the pathology scoring reproducibility. Methods: The CureGN Core Scoring Workgroup established definitions of multiple glomerular, tubular, interstitial and vascular lesions evaluated semi-quantitatively, as observed by light, immunofluorescence, and electron microscopy (EM). All cases with complete pathology data as of April 2019 were randomly assigned for scoring of whole slide and EM images to one of eleven pathologists; a random subset of >10% were scored by a second pathologist. Reproducibility was assessed using Gwet's AC1 statistic. Results: Of 797 biopsy specimens (141 MCD, 186 FSGS, 205 MN, 265 IgA) scored by at least one pathologist, 94 were scored twice (12%). Of 60 pathology features, 46 (77%) demonstrated excellent reproducibility (Gwet's AC1>0.8), and 12 (20%) had good reproducibility (Gwet's AC1>0.6). Mesangial hypercellularity scored as absent, focal or diffuse had moderate reproducibility (AC1=0.58), but scored as absent vs present had AC1=0.71. The percent glomeruli scored as having no lesions had fair reproducibility (AC1=0.34). Conclusions: The majority of pathologic features scored showed excellent reproducibility, supporting the hypothesis that these features can be scored consistently by multiple pathologists. Future studies will include correlation of these histopathologic features with clinical and demographic characteristics at the time of biopsy and eventually disease biomarkers and clinical outcomes. Funding: NIDDK Support
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.067 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".