Granulomatous Inflammation—An Underestimated Cause of False-Positive Diagnoses in Lung Fine-Needle Aspirates: Observations From the College of American Pathologists Nongynecologic Cytopathology Interlaboratory Comparison Program
Bibliographic record
Abstract
CONTEXT: The false-positive rate for fine-needle aspirates of the lung has been cited as less than 1% for granulomatous inflammation, comprising one of the known causes of false-positive diagnoses. OBJECTIVE: To determine the rate of false-positive diagnoses of granulomatous inflammation for lung fine-needle aspirates by assessing the false-positive response rate in the context of the College of American Pathologists Nongynecologic Cytopathology Interlaboratory Comparison Program. DESIGN: We performed a retrospective review of 1092 participant responses for lung fine-needle aspirate challenges with the reference diagnosis of specific infections/granulomatous inflammation from 1998 to 2008 from the College of American Pathologists Nongynecologic Cytopathology Interlaboratory Comparison Program. False-positive rates by participant type (pathologist versus cytotechnologist), general diagnosis category, reference diagnosis, and preparation type were analyzed for the pathologists' responses. RESULTS: Of the 502 general category responses for pathologists, 428 (85.3%) were benign, 55 (11%) were malignant, and 19 (3.8%) were suspicious. There was no difference in the false-positive rate between preparations (P = .76) or participants (P = .39). Of those responses by pathologists that were benign, only 68.7% (292 of 425) were an exact match to granulomatous inflammation. Non-small cell carcinoma, adenocarcinoma, and squamous carcinoma represented 64% of false-positive/suspicious responses, while small cell carcinoma and carcinoid comprised 13%. CONCLUSION: In an interlaboratory comparison program, granulomatous inflammation represents an important cause of false-positive/suspicious responses in lung fine-needle aspirates (14.8%) and is much higher than false-positive rates reported historically in clinical studies. These results highlight the importance of granulomatous inflammation as a mimic of carcinoma.
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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 | 0.015 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".