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Evolution of tisagenlecleucel use for the treatment of pediatric and young adult relapsed/refractory (r/r) B-cell acute lymphoblastic leukemia (B-ALL): Center for International Blood & Marrow Transplant Research (CIBMTR) registry results.

2024· article· en· W4399281392 on OpenAlexaboutno aff
Rayne H. Rouce, Susanne H.C. Baumeister, Kevin J. Curran, Vanessa A. Fabrizio, Erin Hall, Emily M. Hsieh, Nicole Karras, Amy K. Keating, Amy Moskop, Marcelo C. Pasquini, Christine L. Phillips, Michael A. Pulsipher, Marja Nuortti, Jennifer Willert, Roberto Ramos, Samuel John, Stephan A. Grupp

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRefractory (planetary science)Lymphoblastic LeukemiaBlinatumomabBone marrow transplantHematopoietic cellAcute lymphocytic leukemiaBone marrowOncologyBone transplantationPediatricsLeukemiaInternal medicineBone marrow transplantationStem cellSurgeryHaematopoiesis

Abstract

fetched live from OpenAlex

10016 Background: Tisagenlecleucel is an autologous CD19-directed chimeric antigen receptor (CAR) T-cell immunotherapy indicated for patients (pts) up to 25 y of age with B-ALL that is refractory or in second or later relapse. Since the pivotal ELIANA trial, pt characteristics now include pts < 3 y, pts with isolated central nervous system relapse, and pts with leukemia burden < 5%. Here we examine the impact of tisagenlecleucel on the pt treatment journey since FDA approval in 2017. Methods: Data were collected as a part of a noninterventional, prospective, longitudinal study using the CIBMTR registry. Pts were treated in the United States, Canada, Korea, or Taiwan. Results: As of May 4, 2023, 974 pts received tisagenlecleucel. Primary disease history has evolved since 2017. Notably, disease burden prior to infusion has decreased (≥50% blasts: 18% in 2018, 4% in 2022) and a higher proportion of pts received tisagenlecleucel while in morphological complete remission (34% in 2018, 51% in 2022). Between 2018 and 2022, the proportion of pts who were in third or greater relapse decreased (14% vs 2%, respectively). Pts ≥18 y had more prior exposure to blinatumomab and inotuzumab compared with pts < 18 y: 27% vs 16% and 17% vs 7%, respectively. The proportion of pts undergoing ≥1 hematopoietic stem cell transplantation (HSCT) before tisagenlecleucel infusion decreased (37% in 2018, 15% in 2022), coinciding with the use of tisagenlecleucel in earlier lines of therapy. Reporting of B-cell recovery was suboptimal. In total, 34.5% (314/911) of pts received postinfusion HSCT (reasons for HSCT were not captured for most pts); 8.5% (77/911) of pts received postinfusion HSCT to treat relapse, persistent/progressive disease, or positive minimal residual disease. Although the overall rate of postinfusion HSCT did not change, pts with high-risk cytogenetics showed a decrease in HSCT frequency. Previously, most pts < 3 y with KMT2A rearrangement received a HSCT. Since 2017, only 16% (12/75) of pts < 3 y received a prior HSCT despite 72% (54/75) having a KMT2A rearrangement. Furthermore, of the pts with rearrangement, only 43% (23/53) received a HSCT postinfusion. With censoring for HSCT, median RFS improved: 18 mo in 2018, 27 mo in 2020, and not estimable in 2021. OS was not substantially affected by HSCT censoring; 36-mo probabilities (95% CI) with and without censoring were 66 (61-71) and 62 (57-66), respectively. Conclusions: Pediatric and young adult pts with r/r B-ALL are receiving tisagenlecleucel earlier in the course of their disease treatment, reducing the use of HSCT for r/r disease, and prolonging RFS. As both real-world and clinical trial data supporting the curative potential of tisagenlecleucel grow, the use of HSCT in pts with remission after CAR-T should be carefully evaluated.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.146
GPT teacher head0.460
Teacher spread0.314 · 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 designObservational
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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Citations4
Published2024
Admission routes1
Has abstractyes

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