Evidence map›Paper›PMID 39299605›Full record

ArticleJournal of advanced research2025

A novel prognostic scoring system for AML patients undergoing allogeneic hematopoietic stem cell transplantation with real world validation.

Qing Ya Wang, Yi Fan Han, Yu Han Li, Qing Yun Wang, Jin Ye Zhu, Yu Jun Dong, Wei Liu, Na Han, Han Yun Ren, Yuan Li

Abstract readValidation Study
In one paragraph

Article in Journal of advanced research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

10 authors.

Qing Ya WangDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Yi Fan HanDepartment of Gastroenterology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Yu Han LiDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Qing Yun WangDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Jin Ye ZhuDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Yu Jun DongDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Wei LiuDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Na HanDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Han Yun RenDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China.
Yuan LiDepartment of Hematology, Peking University First Hospital, Peking University, No.8 Xi Shi Ku Street, Xi Cheng District, Beijing, China. Electronic address: drliyuan75@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aims to develop a robust predictive model for survival in AML patients undergoing allo-HSCT.

methodsIt was performed a retrospective analysis of 336 AML patients who underwent allo-HSCT at Peking University First Hospital between September 2003 and March 2023. Univariable and multivariable Cox regression analyses were conducted to determine hazard ratios (HR) for overall survival. A predictive model was developed based on multivariable analysis results. Internal validation was carried out through bootstrap resampling, and the model's performance was assessed using the Concordance Index (C-index), Receiver Operating Characteristics (ROC) curve, calibration plots, and Decision Curve Analysis (DCA).

resultsOur prognostic model, which includes age, disease stage, donor/recipient gender, mononuclear cell counts, and the Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI), effectively stratified patients into low-risk and high-risk groups. The two groups showed significant differences in overall survival (P<0.0001), disease-free survival (P<0.0001), non-relapse mortality (NRM) (P<0.0001), and relapse rates (P=0.08). The model achieved a C-index of 0.71. Calibration plots and DCA confirmed strong alignment between predicted and observed outcomes. Subgroup analysis revealed that overall survival was significantly lower in the high-risk group compared to the low-risk group in both measurable residual disease (MRD) negative and MRD positive subgroups (P=0.015 for both).

conclusionThe developed prognostic model, which integrates comprehensive disease and patient characteristics, enhances risk stratification for AML patients undergoing allo-HSCT. This model effectively stratifies risk in both MRD-negative and MRD-positive subgroups and may facilitate more informed MRD-based treatment decisions.

Indexed as

Hematopoietic Stem Cell TransplantationLeukemia, Myeloid, AcuteAdolescentAdultAgedFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentTransplantation, HomologousYoung AdultAcute myeloid leukemiaAllogeneic hematopoietic stem cell transplantationPrognostic modelSurvival prediction

Identifiers

PMID39299605
PMCPMC12225890

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.