P27 and MIB-1 Expression Is Related to Malignancy Recurrence in Laryngeal Carcinoma Treated with Partial Laryngectomy: Preliminary Results
Bibliographic record
Abstract
OBJECTIVE: Considerable evidence has confirmed that p27 protein plays a negative role in cell-cycle progression from the G1 to the S phase and is considered a tumour suppressor. p27 down-regulation was demonstrated in several malignancies. Only a few studies investigated p27's potential prognostic role in laryngeal squamous cell carcinoma (SCC). The aim of the present study was to determine the prognostic relevance of p27 expression in a cohort of laryngeal SCCs that were very homogeneous from a treatment viewpoint to avoid possible influences of treatment modalities on results; all patients underwent only partial laryngectomy on the primary lesion. We simultaneously investigated monoclonal antibody against a proliferating cell associated epitope MIB-1 expression. DESIGN AND METHODS: Twenty-two cases of laryngeal SCC that had undergone exclusive supracricoid or supraglottic laryngectomies with or without neck dissection at the Department of Otolaryngology of Padova University were evaluated. Primary laryngeal SCC p27 reactivity and MIB-1 reactivity were immunohistochemically tested and evaluated by a workstation image analysis system. MAIN OUTCOME MEASURES: A lesion was considered p27 positive when more than 18.56% of the tumour cells showed diffuse strong staining. Samples with > 20.24% of stained cells were considered MIB-1 positive. RESULTS: The mean p27 expression was 17% and 22% in patients with and without disease recurrence, respectively. Low p27 expression was statistically associated with disease recurrence (p = .045); on the other hand, high MIB-1 values were associated with SCC recurrence after treatment (p = .045). CONCLUSIONS: The intervals of confidence analysis showed a stronger relationship of MIB-1 versus p27 in predicting disease recurrence in our cohort of patients treated only with partial laryngectomies.
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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 | 0.000 | 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) | 0.001 | 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".