CNS relapse in high-grade B-cell lymphoma with <i>MYC</i> and <i>BCL2</i> rearrangements and dark-zone signature–expressing DLBCL
Bibliographic record
Abstract
ABSTRACT: High-grade B-cell lymphoma with MYC and BCL2 rearrangements (HGBCL-DH-BCL2), or "double-hit lymphoma," has been associated with a high risk of central nervous system (CNS) relapse. However, historic estimates are impacted by selection bias. We report CNS relapse rates associated with HGBCL-DH-BCL2 from a population-based cohort with complete fluorescence in situ hybridization testing, as well as diffuse large B-cell lymphoma morphology (DLBCL) tumors expressing the dark-zone gene expression signature (DZsig), which was originally derived from HGBCL-DH-BCL2. The 2-year CNS relapse risk in HGBCL-DH-BCL2 was 6.8%. CNS relapses were early, predominantly leptomeningeal (73%), and co-occurred with systemic relapse (64%). High-risk CNS International Prognostic Index (CNS-IPI) and concordant bone marrow involvement were associated with an elevated CNS relapse risk in HGBCL-DH-BCL2. The "refined cell-of-origin" classification assigned 20% of DLBCL morphology tumors with germinal center B-cell-like phenotype (GCB-DLBCL) into a distinct subgroup based on DZsig expression (DZsig+). CNS relapse risk in DZsig+ (2 year: 6.4%) was independent of HGBCL-DH-BCL2 status and was further stratified by the CNS-IPI. CNS relapse in DZsig-negative GCB-DLBCL was rare (2-year risk, 1.4%; P = .04 vs DZsig+) and exclusively parenchymal. Altogether, the CNS relapse risk in HGBCL-DH-BCL2 is lower than previously reported, and DZsig refines risk stratification in GCB-DLBCL.
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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".