International consensus statement on diagnosis, evaluation, and research of Richter transformation: the ERIC recommendations
Bibliographic record
Abstract
ABSTRACT: Richter transformation (RT) is defined as an aggressive lymphoma emerging in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). Despite novel therapeutics developed in CLL, RT is associated with poor outcomes. In light of recent progress regarding the diagnostic procedures and therapeutic concepts of RT, an international group of experts, under the coordination of the European Research Initiative on CLL, has developed consensus recommendations for clinical procedures and future research on this disease. Patients with RT typically present with a rapid clinical decline, worsening B-symptoms, elevated lactate dehydrogenase, and/or rapidly enlarging lymphadenopathy. Workup should include a positron emission tomography-computed tomography scan for patients with suspected RT. An excisional biopsy should be taken from an accessible lesion, preferably with the highest fluorodeoxyglucose avidity, and analyzed for the presence of aggressive lymphoma. The molecular relationship to the original CLL clone(s) should be defined. Because no effective standard treatment for RT exists, patients should be treated in a clinical trial. Response of both RT and CLL should be assessed at an early time point, and survival end points should be prioritized in trial design. We hope that these recommendations can help to harmonize clinical and translational research and improve outcomes for patients with RT.
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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 | 0.158 | 0.229 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.013 | 0.009 |
| Research integrity | 0.025 | 0.024 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".