ASTCT Clinical Practice Recommendations for Transplantation and Cellular Therapies in Diffuse Large B Cell Lymphoma
Bibliographic record
Abstract
Autologous hematopoietic cell transplantation (auto-HCT) has long been the standard approach for patients with relapsed/refractory (R/R) chemosensitive diffuse large B cell lymphoma (DLBCL). However, the advent of chimeric antigen receptor (CAR) T cell therapy has caused a paradigm shift in the management of R/R DLBCL patients, especially with the recent approval of CD19-directed CAR-T therapy in the second-line setting in high-risk groups (primary refractory and early relapse [≤12 months]). Consensus on the contemporary role, optimal timing, and sequencing of HCT and cellular therapies in DLBCL is lacking; therefore, the American Society of Transplantation and Cellular Therapy (ASTCT) Committee on Practice Guidelines undertook this project to formulate consensus recommendations to address this unmet need. The RAND-modified Delphi method was used to generate 20 consensus statements with a few key statements as follows: (1) in the first-line setting, there is no role for auto-HCT consolidation for patients achieving complete remission (CR) following R-CHOP (rituximab, cyclophosphamide, adriamycin, vincristine, and prednisone) or similar therapy in non-double-hit/triple-hit cases (DHL/THL) and in DHL/THL cases receiving intensive induction therapies, but auto-HCT may be considered in eligible patients receiving R-CHOP or similar therapies in DHL/THL cases; (2) auto-HCT consolidation with thiotepa-based conditioning is standard of care for eligible patients with primary central nervous system lymphoma achieving CR with first-line therapy; and (3) in the primary refractory and early relapse setting, the preferred option is CAR-T therapy, whereas in late relapse (>12 months), consolidation with auto-HCT is recommended for patients achieving chemosensitivity to salvage therapy (complete or partial response), and CAR-T therapy is recommended for those not achieving remission. These clinical practice recommendations will serve as a tool to guide clinicians managing patients with newly diagnosed and R/R DLBCL.
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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 | 0.116 | 0.160 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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".