Practical Guidance for the Expanded Implementation and Provision of Bispecific Antibodies for Diffuse Large B-Cell Lymphoma (DLBCL) Across Canada
Bibliographic record
Abstract
(1) Background: Bispecific antibodies (BsAbs) for the treatment of relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL) can be delivered in ambulatory healthcare settings; however, the safe and effective management of potential side effects, such as cytokine release syndrome (CRS), requires protocolized monitoring and management. (2) Methods: An Expert Working Group (EWG) of nine hematologists from across Canada, with experience in leading BsAb program implementation, combined a review of published literature, a comparison of national/provincial/regional guidance documents and protocols, and their professional experiences to produce an informed framework for BsAb program implementation in various healthcare settings. (3) Results: The EWG supports and recommends the progression of BsAb provision from predominantly inpatient hospital settings to community/ambulatory care settings closer to the patient's home. A seven-step implementation process is outlined to support the safe and effective establishment of such programs, from establishing leadership, through customization of protocols, to education and execution. Strategies and considerations are offered to overcome potential barriers and empower healthcare professionals who are working to establish or improve BsAb programs across Canada. (4) Conclusions: For patients with R/R DLBCL, the safe and effective provision of BsAbs closer to home is both feasible and preferred. This guidance is intended to support the efficient and effective setup or enhancement of BsAb programs in lymphoma.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".