ArticleCell reports. Medicine2024
A simplified and robust risk stratification model for stem cell transplantation in pediatric acute myeloid leukemia.
Article in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A parallel-risk framework accurately predicts hematopoietic stem cell transplantation outcomes and identifies benefiting patients in pediatric AML.Genes & diseases · 2026Article
- Unmasking hidden high risk inInnovation (Cambridge (Mass.)) · 2026Article
- Early detection and better outcomes: molecular approaches in pediatric hematologic malignancies - a review.Annals of medicine and surgery (2012) · 2025Review
- Stem cell transplantation indications for patients with acute leukemia determined by measurable residual disease: what we know and what we do not know.Blood science (Baltimore, Md.) · 2025Review
- Identification and validation of mitochondrial and programmed cell death-related prognostic markers in pediatric acute myeloid leukemia.Frontiers in immunology · 2025Article
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Authors and funding
13 authors.
Funding
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Abstract
The efficacy of stem cell transplantation (SCT) in pediatric acute myeloid leukemia (pAML) remains unsatisfactory due to the limitations of existing prognostic models in predicting efficacy and selecting suitable candidates. This study aims to develop a cytomolecular risk stratification-independent prognostic model for SCT in pAML patients at CR1 stage. The pAML SCT model, based on age, KMT2A rearrangement (KMT2A-r), and minimal residual disease at end of course 1 (MRD1), effectively classifies patients into low-, intermediate-, and high-risk groups. We validate the effectiveness in an internal validation cohort and in four external validation cohorts, consisting of different graft sources and donors. Moreover, by incorporating the FMS-like tyrosine kinase 3/internal tandem duplication (FLT3/ITD) allelic ratio, the pAML SCT model is refined, enhancing its ability to effectively select suitable candidates. We develop a simple and robust risk stratification model for pAML patients undergoing SCT, to aid in risk stratification and inform pretransplant decision-making at CR1 stage.
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Registered trials
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