Tumor-Stroma Ratio and Programmed Cell Death Ligand 1 Expression in Preoperative Biopsy and Matched Laryngeal Carcinoma Surgical Specimen
Bibliographic record
Abstract
Programmed cell death ligand 1 (PD-L1) seems to rely on close relations between neoplastic and immune cells in the tumor microenvironment. Tumor to stroma ratio (TSR) has been associated with prognosis in different malignancies. The aims of this exploratory investigation were to analyze for the first time the: (i) association between TSR, PD-L1 expression and other clinical−pathological features in laryngeal squamous cell carcinoma (LSCC) biopsies and paired surgical specimens; (ii) prognostic and predictive role of TSR and PD-L1. TSR, PD-L1 expression (in terms of combined positive score [CPS]), and other clinical−pathological features were analyzed in biopsies and surgical specimens of 43 consecutive LSCC cases. A CPS < 1 evaluated on surgical specimens was associated with a low TSR (stroma rich) on both biopsies and surgical specimens (p = 0.0143 and p = 0.0063). Low TSR showed a significant negative prognostic value when evaluated on both biopsies and surgical specimens (HR = 8.808, p = 0.0003 and HR = 11.207, p = 0.0002). CPS ≥ 1 appeared to be a favorable prognostic factor (HR = 0.100, p = 0.0265). The association between bioptic and surgical specimen TSR and PD-L1 expression should be further investigated for a potential impact on targeted treatments, also with regard to immunotherapeutic protocols.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".