Diffuse large B‐cell lymphoma
Bibliographic record
Abstract
Large B-cell lymphoma, the prototype of aggressive non-Hodgkin lymphomas, is both the most common lymphoma and accounts for the highest global burden of lymphoma-related deaths. For nearly 4 decades, the goal of treatment has been "cure", first based on CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone), and subsequently with rituximab plus CHOP. However, there is significant clinical, pathologic, and biologic heterogeneity, and not all patients are cured. Understanding and incorporating this biologic heterogeneity into treatment decisions unfortunately is not yet standard of care. Despite this gap, we now have significant advances in frontline, relapsed, and refractory settings. The POLARIX trial shows, for the first time, improved progression-free survival in a prospective randomized phase 3 setting. In the relapsed and refractory settings, there are now many approved agents/regimens, and several bispecific antibodies poised to join the arsenal of options. While chimeric antigen receptor T-cell therapy is discussed in detail elsewhere, it has quickly become an excellent option in the second-line setting and beyond. Unfortunately, special populations such as older adults continue to have poor outcomes and be underrepresented in trials, although a new generation of trials aim to address this disparity. This brief review will highlight the key issues and advances that offer improved outcomes to an increasing portion of patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.012 |
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; both teacher heads agree on what is shown here.
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".