Expansion of PD1-positive T Cells in Nodal Marginal Zone Lymphoma
Bibliographic record
Abstract
The diagnosis of nodal marginal zone lymphoma (NMZL) can be challenging, with the differential diagnosis including other low-grade B-cell lymphomas, reactive hyperplasia, and even some cases of peripheral T-cell lymphoma (PTCL). PTCL may have a perifollicular growth pattern mimicking NMZL. We and others have noted an atypical distribution of T-follicular helper (TFH) cells in some cases of NMZL. This study was prompted by the diagnosis of NMZL in several cases in which a marked increase of TFH cells, as determined by staining for programmed death-1 (PD1), had prompted suspicion for a diagnosis of PTCL. We analyzed PD1 staining in 48 cases of NMZL to characterize the extent and pattern of the PD1-positive infiltrate. Three main patterns of PD1 staining were identified: follicular pattern (peripheral, n=16; central, n=9; mixed, n=3), diffuse pattern (n=4), and a reduced or normal staining pattern in residual follicles (n=16). A comprehensive analysis of other TFH markers was undertaken in 14 cases with a high content of PD1-positive cells that were confirmed as B-cell lymphoma by clonality analysis. We describe in detail 5 of these cases in which PTCL was an initial consideration. This study illuminates the diverse immunohistochemical patterns encountered in NMZL and highlights a diagnostic pitfall important for diagnostic accuracy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".