Bibliographic record
Abstract
Folicular lymphoma (FL), the second most common subtype of non-Hodgkin lymphoma, shows considerable heterogeneity in its clinical behavior, representative of a biology that appears increasingly complex and diverse. As our knowledge of the molecular basis of FL increases, we strive for an integration between the bench and clinic that yields treatments based on our scientific understanding and biomarkers that allow us to prescribe treatment rationally. In Section I, Dr. Randy Gascoyne describes the histologic, cytogenetic and biologic features of FL that underlie its clinical variability. Key aspects of the pathologic diagnosis of FL that have particular relevance to the clinician are highlighted. A proposed model for follicular lymphomagenesis and diffuse large B cell lymphoma transformation has emerged and continues to evolve as the molecular story unfolds. A biologic basis for clinical outcome in FL also appears to be forthcoming. In Section II, Dr. Jane Winter addresses the complex process of selecting among the many treatment options for patients with FL. Previously a simple matter of deciding between oral or intravenous alkylators, clinicians and patients must now struggle to choose among vastly different approaches ranging from "watch and wait" to stem cell transplantation. The introduction of rituximab and radioimmunoconjugates is changing the treatment paradigm, but the optimal approach to integrating these and other new agents remains to be determined. At every decision point, the best approach is always a clinical trial. In Section III, Dr. Koen Van Besien provides a well-documented update on outcomes associated with autologous and allogeneic stem cell transplantation for FL. The results of trials of autologous stem cell transplantation in first remission and recent data supporting a role for graft purging are discussed. Based on the premise that a graft-versus-lymphoma effect is operative in FL, reduced-intensity allogeneic transplantation is the preferred approach in many cases, and recently reported results are summarized. Criteria for patient selection and the optimal role of transplantation in the overall therapeutic plan for the patient with FL are presented.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.019 |
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".