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Record W2793382697 · doi:10.1111/petr.13142

Principles of alemtuzumab immunoablation in hematopoietic cell transplantation for non‐malignant diseases in children: A review

2018· review· en· W2793382697 on OpenAlexaff
Gregory M.T. Guilcher, Ravi Shah, Shalini Shenoy

Bibliographic record

VenuePediatric Transplantation · 2018
Typereview
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAlemtuzumabMedicineDosingTransplantationOncologyHematopoietic cellImmunologyImmune systemCD52ImmunotherapyInternal medicineHaematopoiesisStem cell

Abstract

fetched live from OpenAlex

Alemtuzumab is a humanized mAb targeted to CD52. Alemtuzumab is highly immunosuppressive with the ability to deplete T and B cells (in addition to other immune cell lines). A growing understanding of the PKs, dosing, and timing of administration of alemtuzumab has allowed for the study of its use as a conditioning agent for allogeneic HCT. The highly immunosuppressive properties of the drug are particularly appealing in the setting of non-malignant HCT, where GVHD provides no clinical benefit and relapse of malignancy is not applicable. In addition, the degree of immune suppression achieved with alemtuzumab has allowed for a reduction in the intensity of myeloablative cytotoxic agents included in some HCT conditioning regimens, allowing for fewer acute and late toxicities. This review paper will provide a comprehensive summary of the mechanism of action, PKs, dosing, and timing of alemtuzumab, a brief description of its use in various allogeneic HCT protocols for non-malignant conditions and a summary of the data regarding its use for GVHD therapy. The goal of this review was to provide an understanding as to how alemtuzumab might be safely incorporated into HCT conditioning regimens for children with non-malignant disease, allowing for expanded access to curative HCT 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 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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.354
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.026
GPT teacher head0.305
Teacher spread0.279 · 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 designSystematic review
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

Citations13
Published2018
Admission routes1
Has abstractyes

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