Inferior survival in double refractory large B-cell lymphoma eligible for third-line CD19 CAR T-cell therapy
Bibliographic record
Abstract
Outcomes following CD19 chimeric antigen receptor (CAR) T-cell therapy in third-line treatment and beyond for patients with large B-cell lymphoma (LBCL) refractory to both an anthracycline during initial and platinum-based salvage therapy, referred to as double refractory (DR), are not well-described. It is also unclear if these patients may be less likely to proceed to CAR T-cell infusion. Our objectives were to assess third-line CAR T-cell survival outcomes in DR- and non-DR (NDR)-LBCL cohorts including the failure rates to proceed to cell infusion. Review of 199 patients with LBCL referred for CAR T-cell treatment at our center, demonstrates that the DR-LBCL patients (n = 68) have an inferior 12-month (overall survival [OS], 47.1% vs 66.7%, respectively;) when compared to the patients with NDR-LBCL (n = 131). This OS difference is driven by a higher failure rate to proceed to CAR T-cell infusion (32% vs 18%). For patients unable to proceed to CAR T-cell infusion median OS was 2.56 months; DR-LBCL 1.94 months vs NDR-LBCL 3.42 months. The 12-month OS (65% vs 72.3%) and 6-month progression-free survival (46.5% vs 57.2%) of patients with DR- and NDR-LBCL proceeding to CAR T-cell infusion, appears similar. Our study highlights a high-risk subgroup characterized by inferior OS with challenges in getting to CAR T-cell infusion and could benefit from different management approaches such as novel bridging or "off-the-shelf" strategies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".