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Matching-adjusted indirect comparison (MAIC) of lisocabtagene maraleucel (liso-cel) versus axicabtagene ciloleucel (axi-cel) and tisagenlecleucel (tisa-cel) for treatment of third-line or later (3L+) R/R follicular lymphoma (FL): Update with 24 months of liso-cel follow-up (FU).

2025· article· en· W4410822970 on OpenAlexaff
Alexander P. Boardman, Juan Luis Reguera, Pearl Wang, Jenna Ellis, Merav Bar, Jinender Kumar, Thalia A. Farazi, Alejandro Martı́n, Koji Izutsu

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsEVERSANA (Canada)
Fundersnot available
KeywordsMedicineFollicular lymphomaInternal medicineSecond lineOncologyLymphomaFirst line

Abstract

fetched live from OpenAlex

e19049 Background: Liso-cel, axi-cel, and tisa-cel are FDA-approved chimeric antigen receptor T cell therapies for 3L+ R/R FL, but no head-to-head comparisons have been conducted. A previous MAIC (Boardman AP, et al. Blood 2024) with median FUs of 19.3 mo for liso-cel, 24.4 mo for axi-cel, and 16.85 mo for tisa-cel found liso-cel had a higher CR rate and similar ORR, PFS, and duration of response (DOR) versus axi-cel and tisa-cel. Here, we present updated results with longer FU for all 3 therapies, including additional comparisons of OS and time to next treatment (TTNT). Methods: MAICs estimated population-adjusted relative treatment effects for liso-cel (TRANSCEND FL; data cutoff for independent review committee [IRC]–assessed and investigator [INV]-assessed outcomes and safety was 10 Jan 2024; median FU, 30.0 mo) versus axi-cel (ZUMA-5; data cutoffs were 14 Sep 2020 [IRC-assessed outcomes and safety] and 31 Mar 2022 [INV-assessed outcomes]; median FU, 24.4 mo and 41.7 mo, respectively) and tisa-cel (ELARA; data cutoffs were 29 Mar 2021 [safety] and 29 Mar 2022 [IRC-assessed outcomes]; median FU, 16.6 and 28.9 mo, respectively). Baseline characteristics and outcomes in TRANSCEND FL were redefined to align with ZUMA-5 and ELARA. TRANSCEND FL data were weighted by a method-of-moments propensity score model. Response ratios (RR) or HRs with corresponding 95% CIs were used to compare response, time-to-event, and safety outcomes. Results: Comparing IRC-assessed outcomes with axi-cel, liso-cel showed a higher CR rate (RR, 1.26; 95% CI, 1.09–1.45) and a similar ORR (RR, 1.06; 95% CI, 1.00–1.12). Liso-cel also exhibited comparable DOR (HR, 1.21; 95% CI, 0.54–2.75), PFS (HR, 1.13; 95% CI, 0.50–2.53), and OS (HR, 0.51; 95% CI, 0.13–2.00). INV-assessed outcomes demonstrated a higher CR rate for liso-cel and similar ORR. Further, liso-cel showed numerically favorable DOR (HR, 0.83; 95% CI, 0.41–1.67), PFS (HR, 0.76; 95% CI, 0.38–1.54), OS (HR, 0.63; 95% CI, 0.20–1.97), and TTNT (HR, 0.51; 95% CI, 0.22–1.19). Comparing liso-cel with tisa-cel based on IRC-assessed outcomes, liso-cel had a higher CR rate (RR, 1.37; 95% CI, 1.08–1.72) and a comparable ORR (RR, 1.10; 95% CI, 0.96–1.25), DOR (HR, 0.95; 95% CI, 0.38–2.38), PFS (HR, 0.86; 95% CI, 0.38–1.95), OS (HR, 0.81; 95% CI, 0.20–3.28), and TTNT (HR, 0.88; 95% CI, 0.31–2.46). Safety analysis results were consistent with the previously reported MAIC publication. Conclusions: After incorporating longer FU data and adjusting for population differences, liso-cel had a higher CR rate versus axi-cel and tisa-cel, and comparable or numerically favorable ORR, DOR, PFS, OS, and TTNT. Liso-cel had a more favorable safety profile versus axi-cel and a similar safety profile compared with tisa-cel. Clinical trial information: NCT04245839 , NCT03105336 , NCT03568461 .

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.009
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.148
GPT teacher head0.446
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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