Interobserver and Intraobserver Variability Using the Fuhrman Grading System for Renal Cell Carcinoma
Bibliographic record
Abstract
CONTEXT: Histologic grading of renal cell carcinoma has been shown to be second to staging in prognostic significance. A 4-tier grading scheme proposed by Fuhrman et al and based on nuclear features is the system used most frequently in North America. There are, however, very few studies in the literature assessing the interobserver variability for this system, and to our knowledge, none addressing intraobserver variability. OBJECTIVE: To assess the interobserver and intraobserver agreement among 4 pathologists using the Fuhrman nuclear grading scheme for renal cell carcinoma. DESIGN: Representative hematoxylin-eosin-stained slides of 99 consecutive primary renal cell carcinoma cases diagnosed between 1994 and 1999 at St Joseph's Hospital, Hamilton, Ontario, were independently graded by 4 pathologists on 2 occasions with a minimum period of 3 months separating the 2 readings. RESULTS: Intraobserver kappa values ranged from 0.29 to 0.62 (mean = 0.45), and interobserver kappa values ranged from 0.19 to 0.38 and from 0.09 to 0.44 for the first and second rounds, respectively (combined mean kappa value = 0.29). When combining Fuhrman grades 1 and 2 as low-grade tumors and grades 3 and 4 as high-grade tumors, the intraobserver kappa values ranged from 0.4 to 0.64 (mean = 0.53) and interobserver kappa values ranged from 0.28 to 0.59 and from 0.26 to 0.58 for the first and second rounds, respectively (combined mean kappa value = 0.45). The admixture of 2 grades in the same tumor was observed in 53% of cases. CONCLUSIONS: We found only moderate intraobserver and interobserver agreement using the 4-grade Fuhrman scheme. After collapsing the diagnostic grades to 2, the intraobserver agreement changed from moderate to substantial. The collapsing of the 4-category Fuhrman grades into 2 categories is useful in improving intraobserver agreement.
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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 | 0.042 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".