Impact of vein-to-vein time in patients with R/R LBCL treated with axicabtagene ciloleucel
Bibliographic record
Abstract
ABSTRACT: Chimeric antigen receptor (CAR) T-cell products axicabtagene ciloleucel (axi-cel), tisagenlecleucel (tisa-cel), and lisocabtagene maraleucel (liso-cel) are approved for relapsed/refractory (R/R) large B-cell lymphoma (LBCL). Emerging evidence indicates that delayed CAR T-cell infusion, including prolonged time from leukapheresis to infusion, known as vein-to-vein time (V2Vt), may adversely impact clinical outcomes. We conducted a systematic literature review (SLR) and meta-analysis to identify differences in V2Vt in patients with R/R LBCL treated with axi-cel, tisa-cel, or liso-cel. The impact of V2Vt (<28 days vs ≥28 to <40 days vs ≥40 days) on effectiveness and safety outcomes was evaluated in patients treated with axi-cel enrolled in a post-authorization safety study using the Center for International Blood and Marrow Transplant Research data. SLR and meta-analysis showed that patients treated with axi-cel had the shortest median V2Vt (30.6 days) compared with tisa-cel (48.4 days) or liso-cel (35.9 days). Real-world analysis of patients treated with axi-cel demonstrated that V2Vt ≥40 days was associated with significantly lower complete response rate than V2Vt <28 days (odds ratio [OR], 0.61) or ≥28 to <40 days (OR, 0.66) and significantly worse overall survival than V2Vt <28 days (hazard ratio [HR], 1.33) or ≥28 to <40 days (HR, 1.36). Higher prolonged thrombocytopenia rates were observed in patients with axi-cel V2Vt ≥28 to <40 days or ≥40 days compared with <28 days (OR, 1.44 or 1.95, respectively). Together, these results show the impact of V2Vt on patient outcomes with axi-cel therapy and that earlier infusion with CD19-CAR therapies may be beneficial.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.012 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".