ClinicalTrials.gov
public full text
Public Domain
Leukemia Stem Cell-based Assay to Predict Relapse and Survival in Patients With Acute Myeloid Leukemia
The goal of this observational study is to learn about the predict value of leukemia stem cell for acute myeloid leukemia patients with MLL-rearrangement. The main question it aims to answer is: • Could be leukemia stem cell used for relapse prediction in acute myeloid leukemia patients with MLL-rearrangement? Leukemia stem cell will be detected at the same time for participants who detected minimal residual disease using bone marrow as part of their regular medical care to answer the question.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Unravelling a clinical role of peripheral blood leukemia stem cells at diagnosis in chronic myeloid leukemia patients: Final results of prospective FLOWERS study#185588
- Immediate Allogeneic Hematopoietic Stem Cell Transplantation Versus Re-treatment for Patients With High-Risk Acute Myeloid Leukemia#1009001
- LILRB4 STAR-T Cells in the Treatment of R/R AML/CMML#805504
- Comprehensive mutational profiling and clinical outcome of adult acute myeloid leukemia patients with NUP98 rearrangement#1107236
- Cancer Stem Cells in Acute Leukemia#870253
Record · ID 906153
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive