Testing for BAP1 loss and <i>CDKN2A/p16</i> homozygous deletion improves the accurate diagnosis of mesothelial proliferations in effusion cytology
Bibliographic record
Abstract
BACKGROUND: A number of ancillary tests have been developed that aid in the diagnosis of mesothelioma in cytology specimens. The aim of this retrospective study was to determine whether testing for BAP1 and CDKN2A/p16 status in effusion specimens preceding the tissue diagnosis of mesothelioma would improve diagnostic accuracy and allow an earlier diagnosis of malignancy. METHODS: The study cohort included 99 matched cytology fluid specimens from 74 patients with a surgical specimen diagnosis of malignant mesothelioma (67 epithelioid, 7 biphasic, 55 pleural, and 19 peritoneal). BAP1 immunohistochemistry and p16 fluorescence in situ hybridization (FISH) were performed retrospectively. RESULTS: BAP1 or p16 FISH testing revealed a loss in 7 of 18 (39%) samples originally categorized as benign/reactive, 20 of 33 (61%) interpretable samples categorized as atypical, and 10 of 14 (71%) cases suspicious for mesothelioma. In some cases, the diagnosis of mesothelioma could have been made up to 9 months before biopsy. Similarly, loss of BAP1 or p16 was found in 28 of 30 (93%) samples categorized as malignant, with some cases diagnosable up to 6 months before biopsy. Overall, loss of BAP1 and/or CDKN2A/p16 homozygous deletion would change the diagnostic interpretation in 37 of 60 (62%) (P = .07) effusion specimens, particularly in pleural effusions (32 of 48 samples) (P = .002). The sensitivity of morphologic interpretation alone was 30.3%; however, adding testing for BAP1 and p16 resulted in an increase in sensitivity to 68.7%. (P < .0001). CONCLUSION: These findings suggest that routine use of BAP1 immunochemistry and p16 FISH as adjunctive tests improves the diagnostic accuracy of cytology specimens and potentially allows an earlier diagnosis of malignant mesothelioma.
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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 | 0.002 | 0.005 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".