Evidence map›Paper›PMID 41835623›Full record

ArticleFrontiers in oncology2025

Nomogram to predict hemorrhage risk related to anti-tumor therapy in patients with acute leukemia.

Xinxin Hu, Ying He, Yinghua Xie, Li Zhao, Ruijuan Wang, Lijuan Duan, Peipei Mao, Xiyao Han, Yihan Liu, Chao Li

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Xinxin HuDepartment of Hematology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Ying HeDepartment of Hematology, Nanyang Municipal Central Hospital, Nanyang, Henan, China.
Yinghua XieDepartment of Hematology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Li ZhaoClinical Molecular Cytogenetics and Immunology Laboratory, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Ruijuan WangDepartment of Hematology, Nanyang Municipal Central Hospital, Nanyang, Henan, China.
Lijuan DuanDepartment of Hematology, Nanyang Municipal Central Hospital, Nanyang, Henan, China.
Peipei MaoDepartment of Hematology, Nanyang Municipal Central Hospital, Nanyang, Henan, China.
Xiyao HanDepartment of Hematology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Yihan LiuDepartment of Hematology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Chao LiDepartment of Hematology, Nanyang Municipal Central Hospital, Nanyang, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aimed to identify clinical characteristics associated with hemorrhagic events in acute leukemia patients who received anti-tumor therapies and to develop and evaluate a prediction nomogram for hemorrhagic events based on those characteristics. Method: This retrospective cohort study included 468 acute leukemia patients, excluding those with acute promyelocytic leukemia, treated at The Shanghai Fifth People's Hospital and Nanyang Municipal Central Hospital between January 2013 and December 2023. The primary endpoint was World Health Organization (WHO) grade 2 or higher hemorrhagic events related to anti-tumor therapy. Patients were randomly divided into training and test groups at a ratio of 7:3. In the training group, univariable logistic analysis and least absolute shrinkage and selection operator (LASSO) regression were performed to identify significant predictors, which were then used to construct a prediction nomogram for hemorrhage risk. Nomogram performance was evaluated by receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis (DCA). The following five independent variables were identified as predictors of anti-tumor therapy-related hemorrhagic events in acute leukemia patients and used to develop a prediction nomogram: infection status, types of different hemorrhage prevention drugs and blood products administered, platelet (PLT) transfusion, hematocrit, and PLT count. Result: On ROC curve analysis, the nomogram exhibited satisfactory performance in both the training group [area under the ROC curve (AUC)=0.741] and test group (AUC=0.718). Calibration plots showed a high degree of consistency between the actual and nomogram-predicted survival rates in both groups, and the nomogram showed good clinical utility on DCA. We successfully developed and validated a nomogram for predicting the risk of anti-tumor therapy-related hemorrhage of WHO grade 2 or higher among patients with acute leukemia. Conclusion: This nomogram may provide a practical and user-friendly tool for clinical practice once further validated in perspective large cohort or trials.

Indexed as

acute leukemiaanti-tumor therapyhemorrhagenomogrampredictive model

Identifiers

PMID41835623
PMCPMC12979094

What Socratic holds

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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.