Prognostic utility of basaloid differentiation in oropharyngeal cancer
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus (HPV) is recognized as the key risk factor for a distinct subset of oropharyngeal squamous cell carcinoma. P16 is a reliable, sensitive surrogate marker for HPV and confers a positive prognostic advantage. Basaloid differentiation on hematoxylin and eosin (H&E) staining is anecdotally noted by some pathologists to be associated with p16 positivity. This association, however, has not been adequately quantified in the literature, nor has the prognostic implications of basaloid differentiation been described. OBJECTIVES: 1) To correlate the H&E staining feature of basaloid differentiation with p16 positivity in oropharyngeal cancer. 2) To investigate the prognostic utility of basaloid differentiation in oropharyngeal cancer survival. METHODS: Retrospective cross-sectional study of all patients diagnosed with and treated for oropharyngeal cancer at a single tertiary cancer center from 2002 to 2009. Tissue microarrays (TMAs) were generated from 208 oropharyngeal tumor specimens stained with H&E and immunohistochemical markers. These oropharyngeal TMAs were utilized in several previous publications. Samples were scored for basaloid differentiation by a pathologist blinded to the p16 result. A multivariate survival analysis with Cox-regression and Kaplan-Meier survival analysis was performed. RESULTS: In the 208 samples, basaloid differentiation correlated with p16 positivity (Spearman's rho 0.435). Basaloid differentiation and p16 positivity were both independent predictors of improved survival. The 5 year disease specific survival (DSS) was 73% for p16 positive tumors and 35% for p16 negative tumors (p < 0.001). Similarly, the 5 year DSS of basaloid differentiated tumors was 74% compared to 41% for non-basaloid tumors (p = 0.001). Patients with p16 positive and basaloid differentiated tumors had the best survival outcomes with a 5 year DSS of 80%. CONCLUSIONS: Basaloid differentiation is a feature on H&E which correlates with p16 positivity and is a simple, inexpensive, independent, positive prognostic indicator of comparable magnitude to p16 status. Due to the added prognostic value of basaloid differentiation, this feature should be routinely reported by qualified pathologists.
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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".