Clinical Practice Recommendations for Hematopoietic Cell Transplantation and Cellular Therapies in Follicular Lymphoma: A Collaborative Effort on Behalf of the American Society for Transplantation and Cellular Therapy and the European Society for Blood and Marrow Transplantation
Bibliographic record
Abstract
Follicular lymphoma (FL) is the most common indolent B-cell non-Hodgkin lymphoma (NHL), accounting for nearly one-third of all NHL. The therapeutic landscape for patients with FL has significantly expanded over the past decade, but the disease continues to be considered incurable. Hematopoietic cell transplantation (HCT) is potentially curative in some cases. Recently, the emergence of chimeric antigen receptor T-cell therapy (CAR-T) for patients with relapsed/refractory (R/R) FL has yielded impressive response rates and long-term remissions, but definitive statement on the curative potential of CAR-T is currently not possible due to limited patient numbers and relatively short follow up. A consensus on the contemporary role, optimal timing, and sequencing of HCT (autologous or allogeneic) and cellular therapies in FL is needed. As a result, the American Society of Transplantation and Cellular Therapy (ASTCT) Committee on Practice Guidelines endorsed this effort to formulate consensus recommendations to address this unmet need. The RAND-modified Delphi method was used to generate 15 consensus statements/recommendations. These clinical practice recommendations will help guide clinicians managing patients with FL. Of note, the use of bispecific antibodies in R/R FL was not in the scope of this project.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.084 | 0.195 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".