Programmed Death Ligand 1 Testing of Endobronchial Ultrasound–guided Transbronchial Needle Aspiration Samples Acquired For the Diagnosis and Staging of Non–Small Cell Lung Cancer
Bibliographic record
Abstract
RATIONALE: Immunotherapy has become an integral part of management in patients with advanced non-small cell lung cancer (NSCLC). Programmed death ligand 1 (PD-L1) expression in at least 50% of tumor cells on histologic samples has been correlated with improved efficacy of the immune checkpoint inhibitor pembrolizumab. A limited number of studies have examined the suitability of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) specimens for assessment of PD-L1 status. OBJECTIVE: We sought to examine the feasibility and results of PD-L1 testing performed on EBUS-TBNA samples acquired for the diagnosis and staging of NSCLC. MATERIALS AND METHODS: Patients were identified from a prospectively maintained pathology database. Baseline characteristics were tabulated. Hematoxylin and eosin slides were reviewed to categorize cellularity between <100, 100 to 500, and >500 viable tumor cells. Samples were tested using Dako's PD-L1 IHC 22C3 pharmDx kit, with a minimum of 100 viable tumor cells. For patients in whom additional tissue samples were available, the results of PD-L1 testing were compared. RESULTS: PD-L1 testing was attempted on 120 EBUS-TBNA samples. The most common NSCLC subtype was adenocarcinoma (78%). Seventy-six specimens (63%) had a cellularity >500 tumor cells. Among 110 of 120 (92%) patients with an adequate endobronchial ultrasound (EBUS) sample, 53 of 110 (48.2%) had high PD-L1 expression, defined as a Tumor Proportion Score ≥50%. EBUS PD-L1 results were concordant with an available histologic sample in 14 of 18 patients (78%), with no false-negative results. CONCLUSION: PD-L1 testing was feasible in the majority of EBUS-TBNA samples acquired for the diagnosis and staging of NSCLC. Comparison of EBUS results with histologic samples revealed moderate concordance, with no false-negative results.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".