Comparison of 2-year outcomes with CAR T cells (ZUMA-1) vs salvage chemotherapy in refractory large B-cell lymphoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The SCHOLAR-1 international retrospective study highlighted poor clinical outcomes and survival among patients with refractory large B-cell lymphoma (LBCL) treated with conventional chemotherapy. Axicabtagene ciloleucel (axi-cel), an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy, demonstrated durable responses in patients with refractory LBCL in the pivotal phase 1/2 ZUMA-1 study (NCT02348216). Here, we compared SCHOLAR-1 with the 2-year outcomes of ZUMA-1. Prior to comparison of clinical outcomes, propensity scoring (based on a broad set of prognostic covariates) was used to create balance between ZUMA-1 and SCHOLAR-1 patients. In the pivotal phase 2 portion of ZUMA-1, 101 patients received axi-cel and were evaluable for response and survival. In SCHOLAR-1, 434 and 424 patients were evaluable for response and survival, respectively. ZUMA-1 patients were more heavily pretreated than were SCHOLAR-1 patients. The median follow-up was 27.1 months in ZUMA-1. The objective response rate (ORR) and complete response rate were 83% and 54% in ZUMA-1 vs 34% and 12% in SCHOLAR-1, respectively. The 2-year survival rate was 54% in ZUMA-1 and 20% in SCHOLAR-1, and a 73% reduction in the risk of death was observed in ZUMA-1 vs SCHOLAR-1. These results were consistent with those of an additional standardization analysis in which strata were limited to 2 prognostic factors (refractory categorization and presence/absence of stem cell transplant after refractoriness to chemotherapy) to conserve sample size. Despite the limitations of a nonrandomized analysis, these results indicate that axi-cel produces durable responses and a substantial survival benefit vs non-CAR T-cell salvage regimens for patients with refractory LBCL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it