Tumor stroma ratio as a parameter for prognosis and clinicopathological behavior of oral squamous cell carcinoma: A retrospective cohort study
Bibliographic record
Abstract
Background and aim: Tumor-stroma ratio (TSR) is the proportion of tumor cells to surrounding stroma. TSR was reported in many carcinomas as an independent strong, prognostic parameter, and could be applied routinely in diagnostic pathology. This study aimed to clarify the association between prognosis and TSR of oral squamous cell carcinoma (OSCC) and to evaluate its correlations with the clinical stages and histological grades of the studied cases.Materials and Methods: One hundred thirty-nine anti-vimentin stained slides were digitized and analyzed for TSR scoring. TSR was classified as stroma rich (< 50%) and stroma poor (≥ 50%). Correlations between clinicopathological variables and TSR were assessed.Results: Microscopical examination of the studied cases revealed that 67 (48.2%) were stroma-rich and 72 (51.8%) were stroma-poor. Overall findings explained that stroma rich group had larger size, higher clinical stage, higher recurrence rate with a low disease free survival (DFS) and worse overall survival (OS) than the stroma poor.Conclusion: The clinical outcomes of stroma rich OSCC is poor as it is associated with decreased OS and DFS of patients. Hence, TSR may be used as a prognostic independent factor for OSCC and thus, TSR can be considered as an important, low cost and valuable parameter that could be used in addition to the TNM status. Moreover, TSR might be helpful for the judgment of prognosis and for the determination of OSCC high-risk patients to treat them individually.
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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 | 0.001 |
| 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".