A Comparison of Two-Year Outcomes in ZUMA-1 (Axicabtagene Ciloleucel) and SCHOLAR-1 in Patients with Refractory Large B Cell Lymphoma
Bibliographic record
Abstract
Background: In the SCHOLAR-1 study, the largest published retrospective analysis of outcomes in patients with refractory large B-cell lymphoma (LBCL), the objective response rate (ORR) was 26% and complete response (CR) rate was 7% with available salvage therapies in the pre-chimeric antigen receptor (CAR) T cell therapy era (Crump et al. Blood. 2017). These results served as a benchmark for assessing novel therapies. ZUMA-1 (NCT02348216) is the pivotal, multicenter, single-arm Phase 1/2 study evaluating axicabtagene ciloleucel (axi-cel), an autologous anti-CD19 CAR T cell therapy, in patients with refractory LBCL that supported the approval of axi-cel in the United States and Europe. At a median follow-up of 27.1 months, the ORR in ZUMA-1 was 83% and the CR rate was 58% (Locke et al. Lancet Oncol. 2019). Here, we describe comparative analyses of outcomes in ZUMA-1 and SCHOLAR-1 after adjusting for potential imbalances in refractory status between the 2 studies. Methods: Patients in both studies had refractory LBCL defined as stable disease of ≤ 6 months with ≥ 4 cycles of frontline or ≥ 2 cycles of later-line therapy, progressive disease as best response, or relapse ≤ 12 months post autologous stem cell transplant (SCT). To address potential imbalances between studies in refractory status which could affect response and survival outcomes, standardized analyses were performed which equally weighted the proportions of patients by refractory categorization (primary refractory, refractory to ≥ second-line therapy, or relapse after SCT) and presence of post-refractory SCT in each study. Stratified Cochran-Mantel-Haenszel (CMH) tests and Cox models were used to compare the odds ratio for response and hazard ratio (HR) for survival between ZUMA-1 and SCHOLAR-1. P values were descriptive and were not adjusted for multiplicity. Results: Axi-cel was administered to 101 patients in the pivotal Phase 2 portion of ZUMA-1. In the SCHOLAR-1 analysis, 508 patients were evaluable for response and 497 were evaluable for survival. The median follow-up in ZUMA-1 was 2.3 years, and the median follow-up from the overall SCHOLAR-1 study ranged from 7.6 to 14.8 years across different cohorts. In general, ZUMA-1 patients were more heavily pretreated with more patients receiving ≥ 3 lines of therapy as compared with SCHOLAR-1 (69% vs 23%). ZUMA-1 also had more patients who were refractory to second- or later-line therapy compared with SCHOLAR-1 (76% vs 62%). Fewer patients in ZUMA-1, however, were classified as primary refractory vs those in SCHOLAR-1 (26% vs 45%), and a similar proportion of patients between studies relapsed within 1 year of SCT (21% vs 18%). After standardization, the ORR and CR rate in ZUMA-1 vs SCHOLAR-1 were 72% and 54% vs 22% and 7%, respectively. The odds ratios for ORR and CR rate were 7.2-fold and 11.5-fold higher, respectively in ZUMA-1 vs SCHOLAR-1 (CMH test; P < .0001 for both ORR and CR rate). The 2-year survival rate after standardization was 50% (95% CI, 40% - 59%) in ZUMA-1 and 12% (95% CI, 9% - 15%) in SCHOLAR-1, which translated to a 73% reduction in the risk of death in ZUMA-1 relative to SCHOLAR-1 (HR, 0.27; P < .0001). Conclusions: This standardized analysis of the ZUMA-1 and SCHOLAR-1 studies indicates that treatment with axi-cel in this selected population results in 11.5-fold higher odds of CR and a 73% reduction in the risk of death compared with standard salvage regimens in an unselected population. Although limited by retrospective evaluation and cross-study comparisons, these results support the previous literature indicating that axi-cel is a highly effective treatment option for patients with refractory LBCL. Disclosures Neelapu: Pfizer: Consultancy; BMS: Research Funding; Cellectis: Research Funding; Precision Biosciences: Consultancy; Allogene: Consultancy; Acerta: Research Funding; Cell Medica: Consultancy; Celgene: Consultancy, Research Funding; Karus: Research Funding; Novartis: Consultancy; Poseida: Research Funding; Unum Therapeutics: Consultancy, Research Funding; Incyte: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; Merck: Consultancy, Research Funding. Locke:Novartis: Other: Scientific Advisor; Kite: Other: Scientific Advisor; Cellular BioMedicine Group Inc.: Consultancy. Bartlett:Genentech, Inc.: Research Funding; Gilead: Research Funding; Autolus: Research Funding; ADC Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Forty Seven: Research Funding; Affimed: Research Funding; Immune Design: Research Funding; Incyte: Research Funding; Janssen: Research Funding; Kite Pharma: Research Funding; Merck: Research Funding; Millennium: Research Funding; Pfizer: Research Funding; Pharmacyclics: Research Funding. Reagan:Kite, A Gilead Company: Consultancy; Curis: Consultancy; Seattle Genetics: Research Funding. Miklos:Celgene-Juno: Consultancy; Novartis: Consultancy; Adaptive Biotechnologies: Consultancy, Research Funding; Janssen: Consultancy; Miltenyi: Consultancy, Research Funding; AlloGene: Consultancy; Kite, A Gilead Company: Consultancy, Research Funding; Pharmacyclics: Consultancy, Patents & Royalties, Research Funding; Becton Dickinson: Consultancy; Precision Bioscience: Consultancy. Jacobson:Pfizer: Research Funding; Celgene: Consultancy, Other: travel support; Humanigen: Consultancy, Other: travel support; Precision Biosciences: Consultancy, Other: travel support; Bayer: Consultancy, Other: travel support; Novartis: Consultancy, Honoraria, Other: travel support; Kite, a Gilead Company: Consultancy, Honoraria, Other: travel support. Oluwole:Pfizer: Consultancy; Spectrum: Consultancy; Gilead Sciences: Consultancy; Bayer: Consultancy. Siddiqi:BeiGene: Research Funding; Celgene: Research Funding; TG Therapeutics: Research Funding; Kite, A Gilead Company: Research Funding; Seattle Genetics: Speakers Bureau; Janssen: Speakers Bureau; Juno Therapeutics: Consultancy, Other: travel support, Research Funding; PCYC: Consultancy, Research Funding, Speakers Bureau; AstraZeneca: Consultancy, Research Funding, Speakers Bureau. Crump:Kite/Gilead: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Servier: Consultancy. Kuruvilla:Seattle Genetics: Honoraria; Roche: Honoraria; Novartis: Honoraria; Merck: Honoraria; Karyopharm: Honoraria; Janssen: Honoraria; Gilead: Honoraria; Celgene: Honoraria; BMS: Honoraria; Astra Zeneca: Honoraria; Amgen: Honoraria; Seattle Genetics: Consultancy; Roche: Consultancy; Merck: Consultancy; Karyopharm: Consultancy; Gilead: Consultancy; Abbvie: Consultancy; BMS: Consultancy; Janssen: Research Funding; Roche: Research Funding. Van Den Neste:Gilead: Other: travel support. Farooq:Celgene: Honoraria; Kite Pharma: Research Funding. Navale:Kite, A Gilead Company: Employment, Equity Ownership; Gilead: Equity Ownership; Allogene: Equity Ownership; Cellectis: Equity Ownership; Bluebird Bio: Equity Ownership; Amgen: Equity Ownership; Organesis: Equity Ownership; Jounce: Equity Ownership; Editas: Equity Ownership; Intellia: Equity Ownership. DePuy:Kite, A Gilead Company: Consultancy, Other: travel support. Kim:Kite, A Gilead Company: Employment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".