Vascularization predicts overall survival and risk of transformation in follicular lymphoma
Bibliographic record
Abstract
Follicular lymphoma patients display heterogeneous overall survival and variable risk of transformation. Recent studies have highlighted the role of the microenvironment. The contribution of microvessel density to follicular lymphoma survival remains controversial. We used a quantitative tumor mapping approach to determine whether the degree of vascularization correlated with outcome in a uniformly treated cohort. Whole-tissue sections of diagnostic biopsies from 84 cases were stained for CD34 and tumor-to-vessel-distance that encompassed 90% of the tumor (TVD(90)) was determined using image analysis. Twenty-one cases with lower TVD(90) showed inferior overall survival (P=0.0001) and high risk of transformation (P=0.01). These cases significantly correlated with increased Lymphoma-Associated Macrophages (χ(2)=0.025). In multivariate analysis macrophages content, IPI and TVD(90) were independent predictors of overall survival (P=0.05, P=0.001 and P=0.01, respectively) and IPI and TVD(90) predicted risk of transformation (P=0.008 and P=0.08, respectively). Increased angiogenesis is an independent marker of inferior survival and may promote transformation.
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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".