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Record W4214859401 · doi:10.1182/blood.2022015789

CAR T cells as a second-line therapy for large B-cell lymphoma: a paradigm shift?

2022· review· en· W4214859401 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood · 2022
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsSpinal Cord Injury BCUniversity of British Columbia
Fundersnot available
KeywordsMedicineChimeric antigen receptorOncologyLymphomaInternal medicineChemotherapyAutologous stem-cell transplantationTransplantationRefractory (planetary science)Cell therapySurgeryStem cellImmunotherapyCancerBiology

Abstract

fetched live from OpenAlex

The standard of care treatment strategy for patients with relapsed or refractory large B-cell lymphoma (LBCL) has been high-dose chemotherapy followed by autologous stem cell transplantation (ASCT) if chemotherapy sensitive in suitable patients. Because of treatment intensity, this approach has only been feasible in half of patients and because of chemotherapy resistance has only been successful in a quarter of transplant-eligible patients. Chimeric antigen receptor (CAR) T-cell therapy, using genetically modified autologous T cells targeting CD19, has been approved for third-line therapy of LBCL and has been associated with durable remissions in a proportion of patients. In this review, we interpret the design and results of 3 randomized phase 3 trials comparing CAR T-cell therapy and ASCT and their implications for CAR T-cell therapy as a potential new standard of care for second-line treatment in appropriate patients with refractory or early relapsing 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.000

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 head0.059
GPT teacher head0.353
Teacher spread0.295 · 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