Matching-Adjusted Indirect Comparison (MAIC) of Lisocabtagene Maraleucel (liso-cel) Versus Axicabtagene Ciloleucel (axi-cel) for Second-Line (2L) Treatment of Patients (pts) with Refractory/Early Relapsed (R/R) Large B-Cell Lymphoma (LBCL): Update with 34 Months of Liso-Cel Follow-up
Bibliographic record
Abstract
Background: Two CAR T cell therapies, liso-cel and axi-cel, demonstrated superior efficacy over salvage chemotherapy and autologous transplant as 2L therapy in transplant-intended pts with high-risk R/R LBCL, yet no head-to-head comparisons have been performed. A previous MAIC in the 2L setting with a median follow-up of 17.5 mo for liso-cel and 24.9 mo for axi-cel showed comparable efficacy and more favorable safety outcomes for liso-cel with lower rates of all-grade and grade ≥ 3 cytokine release syndrome (CRS) and neurological events (NEs) (Abramson JS, et al. Blood 2022). Here, we present updated results with long-term follow-up for liso-cel and axi-cel. Methods: MAICs were used to estimate population-adjusted relative treatment effects associated with liso-cel for event-free survival (EFS), PFS, ORR, and CR rate (TRANSFORM; NCT03575351; N = 184; data cutoff date: October 2023) vs axi-cel (ZUMA-7; NCT03391466; N = 359; data cutoff date: January 2023) and safety (TRANSFORM, n = 183; ZUMA-7, n = 338). Pts were excluded from the TRANSFORM data set if they did not meet ZUMA-7 eligibility criteria (ie, matching). Individual pt data (IPD) for pts remaining in the TRANSFORM data set were weighted using a method-of-moments propensity score model to match the marginal distribution (ie, mean, variance) of clinical factors among pts from ZUMA-7 (ie, adjustment). Baseline characteristics and outcome measures were revised to align with those defined in ZUMA-7. Efficacy comparisons were anchored through the common comparator, standard of care (SOC; with similar protocol-defined salvage chemotherapy regimens in both trials, followed by high-dose chemotherapy and autologous transplant in responders). Hazard ratios (HRs) were used to compare time-to-event outcomes (EFS, PFS), and odds ratios were used to compare binary outcomes (ORR, CR rate, safety). Selection and rank ordering of the treatment effect modifiers were guided by analysis of the TRANSFORM IPD and clinical experts. Factors to match (ie, pts from TRANSFORM were removed) and adjust (ie, pts from TRANSFORM were reweighted) for efficacy and safety comparisons were reported previously (Abramson JS, et al. Blood 2022). Safety comparisons were unanchored due to the absence of CAR T cell-associated toxicities in the SOC arms. Bridging chemotherapy was allowed in TRANSFORM but not in ZUMA-7; it was not possible to adjust for this factor given sample size constraints. Results: Median study follow-up time was 33.9 mo for liso-cel and 47.2 mo for axi-cel. Efficacy outcomes were comparable between therapies in the unmatched/unadjusted comparison. For liso-cel vs axi-cel, respectively, median (95% CI) EFS was 29.5 mo (9.5‒not reached [NR]) vs 8.3 mo (4.5‒15.8) with HR (95% CI) of 0.94 (0.60‒1.46), and median (95% CI) PFS was 29.5 mo (10.3‒NR) vs 14.7 mo (5.4‒43.5) with HR of 0.90 (95% CI, 0.56‒1.47). Median ORR was 87% vs 83% with odds ratio (95% CI) of 1.41 (0.58‒3.40), and CR rate was 74% vs 65% with odds ratio (95% CI) of 0.95 (0.44‒2.03). After matching with ZUMA-7 for pt eligibility, the TRANSFORM sample size was 158; matching and adjusting for the selected effect modifiers resulted in an effective sample size of 80 for the primary efficacy scenario comparisons (sample size for ZUMA-7 and median efficacy values for axi-cel were unchanged). After matching and adjustment, efficacy outcomes remained comparable between therapies. Median (95% CI) EFS for liso-cel was NR (6.21‒NR) with HR (95% CI) of 0.75 (0.43‒1.33), and median (95% CI) PFS was NR (9.4-NR) with HR (95% CI) of 0.68 (0.37‒1.23). ORR was 85% with odds ratio (95% CI) of 1.63 (0.60‒4.44), and CR rate was 68% with odds ratio (95% CI) of 0.94 (0.40‒2.22). For safety, MAIC results demonstrated lower odds ratios (95% CI) of grade ≥ 3 serious treatment-emergent adverse events (TEAEs; 0.49 [0.27‒0.90]), CRS (any grade, 0.09 [0.04‒0.18]; grade ≥ 3, 0.09 [0.01‒0.75]), and NEs (any grade, 0.08 [0.03‒0.18]; grade ≥ 3, 0.21 [0.06‒0.68]) for liso-cel vs axi-cel. Conclusions: Results from this updated MAIC of liso-cel and axi-cel for the 2L treatment of R/R LBCL showed comparable efficacy, with more favorable safety outcomes for liso-cel. Liso-cel demonstrated a better safety profile with lower rates of grade ≥ 3 serious TEAEs and lower rates of all-grade and grade ≥ 3 CRS and NEs compared with axi-cel.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".