Limited-stage diffuse large B-cell lymphoma
Bibliographic record
Abstract
Diffuse large B-cell lymphoma (DLBCL), the most common lymphoma subtype, is localized in 25% to 30% of patients. Prognosis in patients with limited-stage DLBCL (LS-DLBCL) is excellent with 10-year overall survival of at least 70% to 80%. Improved insights into the disease biology, the availability of positron-emission tomography (PET) scans, and recent dedicated clinical trials within this unique population have led to evolving treatment paradigms. However, no standard definition of LS-DLBCL exists, and although generally defined as Ann Arbor stages I to II disease with largest mass size <10 cm in diameter, variations across studies cause challenges in interpretation. Similar to advanced-stage disease, rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP) immunochemotherapy forms the basis of treatment, with combined modality therapy including 3 cycles of systemic treatment and involved-site radiation therapy being a predominant historical standard. Yet the well-described continuous risk of relapse beyond 5 years and established late complications of radiotherapy have challenged previous strategies. More rigorous baseline staging and response assessment with PET may improve decision making. Recent clinical studies have focused on minimizing toxicities while maximizing disease outcomes using strategies such as abbreviated immunochemotherapy alone and PET-adapted radiotherapy delivery. This comprehensive review provides an update of recent literature with recommendations for integration into clinical practice for LS-DLBCL patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".