Biomarkers of potential prognostic significance in diffuse large B‐cell lymphoma
Bibliographic record
Abstract
Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous disease for which the current approach to treatment is only successful for 50% of patients. The prognostic value of various clinical and biological factors in predicting treatment outcome is discussed in this paper. A review of the English literature was performed including original articles and relevant reviews from MEDLINE that addressed the topics of DLBCL biology and potential prognostic factors. The International Prognostic Index is, to date, the most successful clinical model for predicting outcome. In addition, a rapidly expanding list of molecules has been identified by conventional and newer diagnostic methods that may be of significant prognostic value. Gene expression profiling has led to the discovery of new biological subtypes of DLBCL based on patterns of gene expression, and a host of new genes that may play important roles in this disease. Various derangements in apoptosis, cell-cycle regulation, differentiation, and signal transduction have been noted, while the host environment and immune response also appear to modify clinical outcome. Although to our knowledge, the fundamental abnormalities underlying DLBCL remain elusive, progress is being continuously made to further the understanding of the biological heterogeneity of this disease and the use of various clinical and biological variables to predict treatment outcome. The goal is to be able to identify subgroups of patients at high risk of treatment failure and develop more effective treatment based on specific biological defects that may represent new rational therapeutic targets.
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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) | 0.002 | 0.001 |
| 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".