Prevalence of Thyroid Transcription Factor-1 (TTF-1)-Negative Small Cell Carcinoma and Napsin A Positivity in Small Cell Carcinoma in a Cross-Sectional Study of Lung Core Biopsies
Bibliographic record
Abstract
Background The prevalence of thyroid transcription factor-1 (TTF-1) and napsin A expression are poorly characterized in lung core biopsies of small cell carcinoma. Locally, the TTF-1 clone is 8G7G3/1 (Agilent/Dako), and the napsin A clone is IP64 (Leica Biosystems). Methods All in-house lung core biopsy reports for cases accessioned at a regional laboratory from January 2011 to December 2020 were retrieved and analyzed using a validated hierarchical free-text string matching algorithm (HFTSMA) to establish the diagnosis. TTF-1 and napsin A were manually coded with the assistance of a logical text parsing tool. All TTF-1-negative small cell lung carcinoma (SCLC) cases had a full report review by pathologists. Results The cohort had 5,867 lung core biopsies, and 232 cases were confirmed as small cell carcinoma on pathologist review. TTF-1 immunostain results were available in 173 SCLC cases, and 16 cases of TTF-1-negative SCLC were confirmed on full report review. These 16 cases had at least one positive neuroendocrine (NE) marker and positive keratin staining; cases with mixed histology or positive CK5/6 staining were excluded. Ki-67 was done in 10/16 cases; the average Ki-67 was 75%. Napsin A was negative in 50/51 small cell carcinomas, and 0/3 TTF-1-negative SCLC had napsin A positivity. Conclusions Standardized immunostain reporting would simplify such analyses. Based on the cohort, approximately 9% (16/173) of SCLC is TTF-1 negative. Napsin A positivity in suspected small cell carcinoma should prompt consideration of an alternate diagnosis or explanation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".