Analysis of multiple biomarkers shows that lymphoma-associated macrophage (LAM) content is an independent predictor of survival in follicular lymphoma (FL)
Bibliographic record
Abstract
We studied the role of multiple biomarkers in determining outcome in follicular lymphoma (FL), concentrating in particular on the role of benign macrophages. The study group consisted of uniformly staged and treated patients with FL enrolled in a phase 2 trial between 1987 and 1993. All patients were younger than 61 years of age, had advanced-stage FL, and were treated with a multiagent chemotherapy regimen, BP-VACOP (bleomycin, cisplatin, etoposide, doxorubicin, cyclophosphamide, vincristine, and prednisone), followed by involved region radiation. The median follow-up of living patients was 12.5 years, and the median survival was 16.3 years. The International Prognostic Index (IPI) was predictive of overall survival (OS) (P = .003). Biopsy specimens from all cases were stained with an anti-CD68 antibody. Of the 99 evaluable patients with FL, 87 had less than 15 CD68+ macrophages/high-power field (hpf) (median, 7; range, 1-14) and 12 had more than 15 CD68+ macrophages/hpf (median, 20; range, 16-25) with a median OS of 16.3 vs 5.0 years, respectively (P < .001). A multivariate Cox model that included the IPI score, the histologic grade, and the lymphoma-associated macrophage (LAM) score, showed IPI and LAM to be independent predictors of OS (P = .009 and P = .004, respectively). The LAM content of FL predicts survival, and these data support a prominent role for nonneoplastic immune cells in the biology of FL.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".