Real-World Outcomes of Patients With Advanced Non-small Cell Lung Cancer Treated With Anti-PD1 Therapy on the Basis of PD-L1 Results in EBUS-TBNA vs Histological Specimens
Bibliographic record
Abstract
BACKGROUND: Programmed death-ligand 1 (PD-L1) testing is feasible in most specimens acquired using endobronchial ultrasound-guided needle aspiration (EBUS-TBNA). RESEARCH QUESTION: Are the outcomes of patients with advanced non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICI) on the basis of PD-L1 expression in EBUS-TBNA samples significantly different from those of patients who are treated on the basis of PD-L1 expression in histological samples? STUDY DESIGN AND METHODS: Patients treated with pembrolizumab or nivolumab between June 2016 and 2019 were included. Patient characteristics, PD-L1 expression, line of treatment, response (Response Evaluation Criteria in Solid Tumors [RECIST] criteria), and vital status (May 14, 2020) were recorded. Progression-free survival (PFS) and overall survival (OS) were assessed, and hazard ratios (HR) estimated. RESULTS: A total of 145 patients were treated with pembrolizumab or nivolumab on the basis of PD-L1 expression in EBUS-TBNA (31.7%) or histological (68.3%) samples. Most had metastatic disease, with a predominance of adenocarcinomas (64.1%). First-line pembrolizumab was administered to 61 patients with tumor proportion score ≥50% in EBUS-TBNA (n = 16) or histology samples (n = 45). Median OS and PFS of patients who received first-line pembrolizumab on the basis of PD-L1 results in EBUS-TBNA vs histology samples were not significantly different (OS 25.8 months vs not reached, respectively; HR, 0.82 [95% CI, 0.34-1.95], P = .651). Similarly, the median OS and PFS of patients who received subsequent lines of treatment on the basis of PD-L1 results in EBUS-TBNA vs histological samples were not significantly different (including after adjustment for PD-L1 expression). INTERPRETATION: These findings suggest that PD-L1 results in EBUS-TBNA samples can guide ICI therapy, with treatment outcomes being comparable to those of patients in whom PD-L1 expression was assessed in histological specimens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".