Impact of dual expression of MYC and BCL2 by immunohistochemistry on the risk of CNS relapse in DLBCL
Bibliographic record
Abstract
Dual expression of MYC and BCL2 by immunohistochemistry (IHC) is associated with poor outcome in diffuse large B-cell lymphoma (DLBCL). Dual translocation of MYC and BCL2, so-called "double-hit lymphoma," has been associated with a high risk of central nervous system (CNS) relapse; however, the impact of dual expression of MYC and BCL2 (dual expressers) on the risk of CNS relapse remains unknown. Pretreatment formalin-fixed paraffin-embedded DLBCL biopsies derived from patients subsequently treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) were assembled on tissue microarrays from 2 studies and were evaluated for expression of MYC and BCL2 by IHC. In addition, cell of origin was determined by IHC and the Lymph2Cx gene expression assay in a subset of patients. We identified 428 patients who met the inclusion criteria. By the recently described CNS risk score (CNS-International Prognostic Index [CNS-IPI]), 34% were low risk (0 to 1), 45% were intermediate risk (2 to 3), and 21% were high risk (4 or greater). With a median follow-up of 6.8 years, the risk of CNS relapse was higher in dual expressers compared with non-dual expressers (2-year risk, 9.7% vs 2.2%; P = .001). Patients with activated B-cell or non-germinal center B-cell type DLBCL also had an increased risk of CNS relapse. However, in multivariate analysis, only dual expresser status and CNS-IPI were associated with CNS relapse. Dual expresser MYC(+) BCL2(+) DLBCL defines a group at high risk of CNS relapse, independent of CNS-IPI score and cell of origin. Dual expresser status may help to identify a high-risk group who should undergo CNS-directed evaluation and consideration of prophylactic strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".