Preliminary results of earlier steroid use with axicabtagene ciloleucel (axi-cel) in patients with relapsed/refractory large B-cell lymphoma (R/R LBCL).
Bibliographic record
Abstract
7558 Background: Axi-cel is an autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy approved in the EU and US for patients (pts) with R/R LBCL with ≥ 2 prior systemic therapies. In the 2-y follow-up of ZUMA-1, the objective response rate (ORR) was 83% with a complete response (CR) rate of 58%. Grade ≥ 3 cytokine release syndrome (CRS) and neurologic events (NE) occurred in 11% and 32% of pts, respectively; 26% of pts received steroids, and 43% received tocilizumab (Locke et al. Lancet Oncol. 2019). A safety expansion cohort was added to evaluate the effect of earlier steroid use on the rates of these adverse events (AEs). Methods: Eligible pts with R/R LBCL were leukapheresed and received conditioning chemotherapy followed by a target dose of 2 × 106 anti-CD19 CAR T cells/kg. Pts in this cohort received early steroid intervention starting at Grade 1 NE and at Grade 1 CRS when no improvement was observed after 3 days of supportive care. The primary endpoint for this cohort was incidence and severity of CRS and NE. Results: As of 9/14/2018, 21 of 40 planned pts received axi-cel with a minimum follow-up of 1 mo (median, 2.6 mo). The median age was 63 y (range, 36 – 73), 67% were male, 81% had disease stage III-IV, 76% were R/R to ≥ second-line therapy, and 10% had relapsed post-autologous stem cell transplantation. Seventy-six percent of pts received steroids and 81% received tocilizumab. Most pts (81%) had Grade ≥ 3 AEs, most commonly neutrophil count decreased (33%), anemia (29%), and pyrexia (24%). Grade ≥ 3 NE occurred in 10% of pts; the most common symptoms were somnolence (10%) and confusional state (10%). Grade 1 and 2 NE occurred in 38% and 5% of pts, respectively. No pt had Grade ≥ 3 CRS; 33% of pts had Grade 1 CRS and 67% had Grade 2. There were no deaths due to AEs; 1 pt died due to disease progression. The ORR per investigator assessment was 76% with 48% of pts achieving a CR. Pharmacokinetic data will be presented. Conclusions: Early use of steroids may help in managing severe CRS and NE by potentially reducing their incidence in pts treated with CAR T cell therapy without affecting response rates. Optimizing AE management may help to further improve the benefit:risk profile of CAR T cell therapy. Clinical trial information: NCT02348216.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".