Rituximab-Based Therapy in Newly Diagnosed Diffuse Large B-Cell Lymphoma Patients: Individualized Risk-Adapted Therapy Approach Using Molecular Subtypes
Bibliographic record
Abstract
Rituximab (R) with cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) is the current standard of care as first-line treatment for diffuse large B-cell lymphoma (DLBCL), the most common lymphoma subtype. Patients who fail R-CHOP have a poor outcome with relapse or refractory disease resulting in fatality in majority of patients. This review focuses on novel therapies which are currently being assessed as first-line treatment in combination with R-CHOP in patients with DLBCL. Targeted drug development is a possibility with recent developments like gene expression profiling, RNA interference screening, DNA sequencing, identification of new biomarkers and signaling pathways. Newer drugs such as bortezomib, lenalidomide, and ibrutinib are being investigated as first-line therapy in combination with R-CHOP (XR-CHOP) in the activated B-cell (ABC) subtype of DLBCL. Additionally, inhibitors of BCL6, EZH2, and PI3K/Akt/mTOR are being considered for treatment of germinal center B-cell (GCB) subtype of DLBCL in patients with probable survival of less than 5 years. Double- or triple-hit lymphomas and double-expressor lymphomas also have poor prognosis and research to identify effective first-line therapy in these patients remains an unmet need. Presently, individualized approach that includes effective therapeutic combinations with acceptable safety profiles for use in routine practice, especially in patients likely to have poor outcomes such as relapsed/refractory DLBCL remains a distant possibility. Current evidence shows that untreated high risk patients do not have the greater benefit with use of newer drugs compared with R-CHOP. Therefore, R-CHOP remains the first-line treatment for newly diagnosed 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".