Prognostic and clinicopathological significance of tumor-stroma ratio in head and neck squamous cell carcinoma: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Analysis of the tumor microenvironment has been proposed as a strategy for the treatment and prognosis of different neoplastic processes. A grading system based on the tumor-stroma ratio (TSR), which evaluates the proportion of stroma in relation to neoplastic parenchyma at the invasion front, has shown a strong prognostic value in different neoplastic processes. The aim of the present systematic review was to understand the role of the TSR in head and neck squamous cell carcinoma (HNSCC), evaluating its correlation with clinical and prognostic parameters. MATERIAL AND METHODS: An electronic search was performed in PubMed/Medline, Web of Science, Science Direct, Scopus, Embase, and the Cochrane Collaboration Library. Publications assessing the relationship between TSR and prognosis in cases of HNSCC were eligible. The quality of the studies was assessed independently by four evaluators using the Newcastle-Ottawa scale. RESULTS: After application of the previously es+lished inclusion/exclusion criteria, nine articles were included in the qualitative synthesis. With regards to quality on the Newcastle-Ottawa scale, an overall value of 4.55 was obtained. This systematic review demonstrated a strong association between TSR and prognosis in esophageal and oral squamous cell carcinomas. CONCLUSIONS: Histopathological analysis of the TSR can optimize the analysis of the prognosis of cases diagnosed with HNSSC. In addition, the TSR is a reliable and simple parameter that can be evaluated in hematoxylin/eosin-stained slides during routine laboratory examinations, showing high inter- and intraobserver agreement.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it