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Record W3019605854 · doi:10.1200/edbk_278171

Cutting to the Front of the Line: Immunotherapy for Childhood Acute Lymphoblastic Leukemia

2020· review· en· W3019605854 on OpenAlexaff
Jennifer L. McNeer, Rachel E. Rau, Sumit Gupta, Shannon L. Maude, Maureen M. O’Brien

Bibliographic record

VenueAmerican Society of Clinical Oncology Educational Book · 2020
Typereview
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBlinatumomabMedicineOncologyChemotherapyCD22ImmunotherapyInternal medicineClinical trialMitoxantroneRefractory (planetary science)DiseaseLymphoblastic LeukemiaCalicheamicinImmunologyLeukemiaImmune systemLymphomaMyeloid leukemiaCD20

Abstract

fetched live from OpenAlex

Although many children and young adults with B-cell acute lymphoblastic leukemia (B-ALL) are cured with modern, risk-adapted chemotherapy regimens, 10% to 15% of patients will experience relapse or have refractory disease. Recent efforts to further intensify cytotoxic chemotherapy regimens in the frontline setting have failed as a result of excessive toxicity or lack of improvement in efficacy. As a result, novel approaches will be required to achieve cures in more newly diagnosed patients. Multiple immune-based therapies have demonstrated considerable efficacy in the setting of relapsed or refractory (R/R) disease, including CD19 targeting with blinatumomab and tisagenlecleucel and CD22 targeting with inotuzumab ozogamicin. These agents are now under investigation by the Children's Oncology Group (COG) in clinical trials for newly diagnosed B-ALL, with integration into standard chemotherapy regimens based on clinically and biology-based risk stratification as well as disease response.

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 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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.464
Teacher spread0.398 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations41
Published2020
Admission routes1
Has abstractyes

Explore more

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