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Record W3213936100 · doi:10.3389/fped.2021.777108

Minimal Residual Disease Prior to and After Haematopoietic Stem Cell Transplantation in Children and Adolescents With Acute Lymphoblastic Leukaemia: What Level of Negativity Is Relevant?

2021· review· en· W3213936100 on OpenAlexaff
Pietro Merli, Marianne Ifversen, Tony H. Truong, Hanne Vibeke Marquart, Jochen Buechner, Matthias Wölfl, Peter Bader

Bibliographic record

VenueFrontiers in Pediatrics · 2021
Typereview
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineTransplantationNegativity effectMinimal residual diseaseHaematopoiesisStem cellDiseaseHematopoietic stem cell transplantationLymphoblastic LeukemiaImmunologyOncologyPediatricsInternal medicineLeukemiaDevelopmental psychologyGeneticsPsychology

Abstract

fetched live from OpenAlex

Minimal residual disease (MRD) assessment plays a central role in risk stratification and treatment guidance in paediatric patients with acute lymphoblastic leukaemia (ALL). As such, MRD prior to haematopoietic stem cell transplantation (HSCT) is a major factor that is independently correlated with outcome. High burden of MRD is negatively correlated with post-transplant survival, as both the risk of leukaemia recurrence and non-relapse mortality increase with greater levels of MRD. Despite growing evidence supporting these findings, controversies still exist. In particular, it is still not clear whether multiparameter flow cytometry and real-time quantitative polymerase chain reaction, which is used to recognise immunoglobulin and T-cell receptor gene rearrangements, can be employed interchangeably. Moreover, the higher sensitivity in MRD quantification offered by next-generation sequencing techniques may further refine the ability to stratify transplant-associated risks. While MRD quantification from bone marrow prior to HSCT remains the state of the art, heavily pre-treated patients may benefit from additional staging, such as using 18 F-fluorodeoxyglucose positron emission tomography/computed tomography to detect focal residues of disease. Additionally, the timing of MRD detection (i.e., immediately before administration of the conditioning regimen or weeks before) is a matter of debate. Pre-transplant MRD negativity has previously been associated with superior outcomes; however, in the recent For Omitting Radiation Under Majority age (FORUM) study, pre-HSCT MRD positivity was associated with neither relapse risk nor survival. In this review, we discuss the level of MRD that may require pre-transplant therapy intensification, risking time delay and complications (as well as losing the window for HSCT if disease progression occurs), as opposed to an adapted post-transplant strategy to achieve long-term remission. Indeed, MRD monitoring may be a valuable tool to guide individualised treatment decisions, including tapering of immunosuppression, cellular therapies (such as donor lymphocyte infusions) or additional immunotherapy (such as bispecific T-cell engagers or chimeric antigen receptor T-cell 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)0.002
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.276
Teacher spread0.259 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

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