Management of Canadian patients with refractory or relapsed diffuse large B-cell lymphoma in the real world: a subanalysis of the RE-MIND2 study
Bibliographic record
Abstract
BACKGROUND: In the current Canadian treatment landscape for relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL), eligibility for autologous stem cell transplantation (ASCT) guides the choice of salvage treatment. CD19 chimeric antigen receptor T-cell (CAR-T) therapies have improved outcomes in patients with chemorefractory DLBCL, but access is limited to eligible patients. This subanalysis of the RE-MIND2 observational retrospective cohort study investigated treatment patterns for R/R DLBCL in Canada. PATIENTS AND METHODS: Data from patients enrolled in RE-MIND2 treated between 2010 and 2020 at 2 Canadian centers were retrospectively collected from health records. Descriptive statistics were used to analyze baseline characteristics, treatment initiated, and duration of treatment by line of therapy. RESULTS: One hundred and nine patients were included; 74.2% of patients were eligible for ASCT as 2L therapy, and 45.4% received transplants. ASCT eligibility for third- (3L) and fourth-line (4L) therapy declined to 17.1% and 5.9%, respectively. Patients received a wide variety of treatments in 3 and 4L. CAR-T therapy became available in 3 and 4L by the end of 2019. Median durations of treatment were <2.6 months in all lines of therapy; median time to next treatment ranged from 3.4 months in 4L to 5.3 months in 2L. CONCLUSION: Results of our study support that ASCT-ineligible patients have a poor prognosis with conventional salvage chemotherapy. Before the availability of novel immunotherapies, no apparent standard of care was observed for Canadian patients with R/R DLBCL who were ineligible for or did not receive ASCT, especially after 2L treatment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".