A Review on Splenic Diffuse Red Pulp Small B-Cell Lymphoma
Bibliographic record
Abstract
Splenic diffuse red pulp small B-cell lymphoma (SDRPL) is a rare disease, representing <1% of all non-Hodgkin lymphomas (NHL). The most common clinical manifestations include splenomegaly, lymphocytosis, and hemocytopenia. A diagnosis of SDRPL can be challenging, as it shares multiple clinical and laboratory features with splenic marginal zone lymphoma (SMZL), hairy cell leukemia (HCL), and HCL variant (HCL-v). Obtaining splenic tissue remains the gold standard for diagnosis. In the cases where splenic tissue is not available, diagnosis can be established by a review of peripheral blood and bone marrow studies. SDRPL is characterized by a diffuse involvement of the splenic red pulp by monomorphous small-to-medium sized mature B lymphocytes effacing the white pulp. The characteristic immunophenotype is positive for CD20, DBA.44 (20 to 90%), and IgG, and typically negative for CD5, CD10, CD23, cyclin D1, CD43, annexin A1, CD11c, CD25, CD123, and CD138. The Ki-67 proliferative index is characteristically low. Cyclin D3 is expressed in the majority of SDRPL in contrast with other types of small B-cell lymphomas, thus facilitating the recognition of this disease. There is no standard treatment regimen for SDRPL. Initial treatment options include splenectomy, rituximab monotherapy, or a combination of both. Chemoimmunotherapy should be considered in patients with advanced disease at baseline or progression.
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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 | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".