A bioclinical prognostic model using MYC and BCL2 predicts outcome in relapsed/refractory diffuse large B-cell lymphoma
Bibliographic record
Abstract
The objective of this study was to create a bioclinical model, based on clinical and molecular predictors of event-free and overall survival for relapsed/refractory diffuse large B-cell lymphoma patients treated on the Canadian Cancer Trials Group (CCTG) LY12 prospective study. In 91 cases, sufficient histologic material was available to create tissue microarrays and perform immunohistochemistry staining for CD10, BCL6, MUM1/IRF4, FOXP1, LMO2, BCL2, MYC, P53 and phosphoSTAT3 (pySTAT3) expression. Sixty-seven cases had material sufficient for fluorescent in situ hybridization (FISH) for MYC and BCL2. In addition, 97 formalin-fixed, paraffin-embedded tissue samples underwent digital gene expression profiling (GEP) to evaluate BCL2, MYC, P53, and STAT3 expression, and to determine cell-of-origin (COO) using the Lymph2Cx assay. No method of determining COO predicted event-free survival (EFS) or overall survival (OS). Factors independently associated with survival outcomes in multivariate analysis included primary refractory disease, elevated serum lactate dehydrogenase (LDH) at relapse, and MYC or BCL2 protein or gene expression. A bioclinical score using these four factors predicted outcome with 3-year EFS for cases with 0–1 vs. 2–4 factors of 55% vs. 16% (P
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".