Prognostic significance of immunohistochemical biomarkers in diffuse large B-cell lymphoma: a study from the Lunenburg Lymphoma Biomarker Consortium
Bibliographic record
Abstract
The Lunenburg Lymphoma Biomarker Consortium (LLBC) evaluated the prognostic value of IHC biomarkers in a large series of patients with diffuse large B-cell lymphoma (DLBCL). Clinical data and tumor samples were retrieved from 12 studies from Europe and North America, with patients treated before or after the rituximab era. Using tissue microarrays from 1514 patients, IHC for BCL2, BCL6, CD5, CD10, MUM1, Ki67, and HLA-DR was performed and scored according to previously validated protocols. Optimal cut points predicting overall survival of patients treated in the rituximab era could only be determined for CD5 (P = .003) and Ki67 (P = .02), whereas such cut points for BCL2, BCL6, HLA-DR, and MUM1 could only be defined in patients not receiving rituximab. A prognostic model for patients treated in the rituximab era identified 4 risk groups using BCL2, Ki67, and International Prognostic Index (IPI) with improved discrimination of low-risk patients. Newly recognized correlations between specific biomarkers and IPI highlight the importance of carefully controlling for clinical and biologic factors in prognostic models. These data demonstrate that the IPI remains the best available index in patients with DLBCL treated with rituximab and chemotherapy.
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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) | 0.001 | 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".