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Record W4406772134 · doi:10.1002/pbc.31516

Access to CARe: A Narrative of Real‐World Medical Decision‐Making to Access Chimeric Antigen Receptor (CAR) T‐Cell Therapy in Children, Adolescents, and Young Adults

2025· review· en· W4406772134 on OpenAlexaff
Angela Steineck, Karen Chao, Anurekha G. Hall, Elad Jacoby, Allison Barz Leahy, John A. Ligon, Katia Luciani, Liora M. Schultz, Corinne Summers, Lisa Wård, Lena E. Winestone, Nirali N. Shah

Bibliographic record

VenuePediatric Blood & Cancer · 2025
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of Ottawa
FundersNational Cancer InstituteIntramural Research ProgramNIH Clinical CenterNational Institutes of Health
KeywordsChimeric antigen receptorMedicineNarrative reviewRefractory (planetary science)Clinical trialOncologyPediatricsImmunotherapyIntensive care medicineInternal medicineCancer

Abstract

fetched live from OpenAlex

Chimeric antigen receptor (CAR) T-cell therapy is a potentially life-saving treatment for children with relapsed/refractory B-cell hematologic malignancies, and remains an important investigational therapy for other childhood cancers. Yet, access to this class of therapies remains suboptimal through both commercial use and clinical trials, especially in children, adolescents, and young adults. Using a series of case-based discussions, we outline guidance on real-world medical decision-making, and offer potential solutions to enhancing access to CAR T-cell therapy as a treatment modality.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.405
Teacher spread0.376 · 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 designQualitative
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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