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Record W4317395238 · doi:10.3389/fonc.2022.1105779

The role of allogeneic hematopoietic cell transplantation for chronic lymphocytic leukemia: A review

2023· review· en· W4317395238 on OpenAlexaff
Robert Puckrin, Mona Shafey, Jan Storek

Bibliographic record

VenueFrontiers in Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsOccupational Cancer Research CentreUniversity of Calgary
Fundersnot available
KeywordsMedicineChronic lymphocytic leukemiaHematopoietic cellTransplantationLeukemiaHematopoietic stem cell transplantationOncologyDiseaseImmunologyGraft-versus-host diseaseHaematopoiesisInternal medicineStem cellBiology

Abstract

fetched live from OpenAlex

Although the use of allogeneic hematopoietic cell transplantation (HCT) for chronic lymphocytic leukemia (CLL) has declined with the development of novel targeted agents, it continues to play an important role for eligible patients with high-risk or heavily pretreated CLL who lack other treatment options. CLL is susceptible to a potent graft-versus-leukemia (GVL) effect which produces long-lasting remissions in 30-50% of transplanted patients. While allogeneic HCT is associated with significant risks of graft-versus-host disease (GVHD), infection, and non-relapse mortality (NRM), improvements in patient and donor selection, reduced intensity conditioning (RIC), GVHD prophylaxis, and supportive care have rendered this an increasingly safe and effective procedure in the current era. In this review, we discuss recent advances in allogeneic HCT for CLL, with a focus on the optimal evidence-based strategies to maximize benefit and minimize toxicity of this potentially curative cellular therapy.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.375
Teacher spread0.339 · 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 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

Citations10
Published2023
Admission routes1
Has abstractyes

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