Evidence map›Paper›PMID 40144893›Full record

ReviewBlood science (Baltimore, Md.)2025

Stem cell transplantation indications for patients with acute leukemia determined by measurable residual disease: what we know and what we do not know.

Xiao-Su Zhao, Xiao-Tong Chen, Ying-Jun Chang

Abstract readReview
In one paragraph

Review in Blood science (Baltimore, Md.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Advancements in diagnosis and treatments of acute leukemia.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiao-Su ZhaoPeking University People's Hospital & Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, No. 11 South Street of Xizhimen, Xicheng District, Beijing 100044, China.
Xiao-Tong ChenPeking University People's Hospital & Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, No. 11 South Street of Xizhimen, Xicheng District, Beijing 100044, China.
Ying-Jun ChangPeking University People's Hospital & Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, No. 11 South Street of Xizhimen, Xicheng District, Beijing 100044, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute leukemia (AL), which includes acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL), is a hematological malignancy characterized by the uncontrolled proliferation of immature myeloid or lymphoid cells. Allogeneic stem cell transplantation (ASCT) remains a therapeutic option for patients with AL. Determination of transplantation indications is a key step in successful ASCT and in curing patients. Currently, the measurable residual disease (MRD) is used as a biomarker for response evaluation, relapse prediction, preemptive therapy, and post-remission treatment selection. In this review, we discuss the advantages and disadvantages of these techniques for MRD detection. We focused mainly on the residual disease-directed selection of transplant indications for patients with either AML or ALL and provided expert opinions in these settings. We also discuss the challenges associated with transplantation indications and propose expert opinions and future directions for the selection of indications for transplantation.

Indexed as

Acute leukemiaAllogeneic stem cell transplantationIndicationMeasurable residual disease

Identifiers

PMID40144893
PMCPMC11939945

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.