Real-world data for tisagenlecleucel in patients with R/R B-ALL: subgroup analyses from the CIBMTR registry
Bibliographic record
Abstract
ABSTRACT: Since the first approval of tisagenlecleucel in 2017, pediatric and young adult patients with relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL) may receive this CD19-directed chimeric antigen receptor T-cell therapy. We report real-world data from the Center for International Blood and Marrow Transplant Research (>2.5 years of follow-up). As of 4 May 2022, 768 patients with B-ALL had received tisagenlecleucel. Patients aged ≥18 and <18 years of age (including those <3 years) were treated during first relapse (26.6% and 26.7% [<3 years, 44.8%], respectively) or primary refractory disease (12.4% and 12.1% [<3 years, 15.5%], respectively) with 17.6% and 11.6% (<3 years, 13.8%), respectively, having high disease burden (≥50% bone marrow [BM] blasts) and 20.2% and 20.2% (<3 years, 13.8%), respectively, having low disease burden (>0 to <5% BM blasts). Among patients with ≥12 months postinfusion follow-up (n = 578; median follow-up, 32.1 months), the best overall response of complete remission/complete remission with incomplete blood count recovery was 86.0%. The 12-month relapse-free survival (RFS) and overall survival (OS) were 61.8% and 79.4%, respectively, whereas the 24-month RFS and OS were 50.3% and 63.8%, respectively. Age (<18 years) and disease burden (<50% BM blasts) were associated with better outcomes. Previous inotuzumab therapy and KMT2A rearrangement were associated with worse outcomes. Older patients (≥18 years) experienced a higher rate of any-grade cytokine release syndrome (CRS) associated with higher disease burden before infusion. Any-grade CRS and neurotoxicity were lower in patients aged <3 years. Extended follow-up continues to demonstrate high rates of RFS and favorable safety in this population.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".