Evidence map›Paper›PMID 40731268›Full record

ArticleBMC cancer2025

Risk factor analysis and predictive model development for secondary failure of platelet recovery following allogeneic hematopoietic stem cell transplantation.

Xiru Peng, Juan Cheng

Abstract read
In one paragraph

Article in BMC cancer, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Xiru PengThe First Clinical Medical College of Lanzhou University, Lanzhou, China.
Juan ChengThe First Clinical Medical College of Lanzhou University, Lanzhou, China. Chenggu029@163.com.

Funding

Analysis of the Efficacy and Safety of Azacitidine in Maintenance Therapy for Acute Myeloid Leukemia (23)0379
6 · The paper itself

Abstract

Secondary failure of platelet recovery (SFPR) is a common complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), occurring in approximately 20% of cases, and is closely associated with poor patient prognosis. The purpose of this study is to analyze the risk factors associated with SFPR following allo-HSCT, develop a nomogram-based predictive model for SFPR, and validate its accuracy. Clinical data of patients who underwent allo-HSCT in the Department of Hematology at the First Hospital of Lanzhou University from January 2016 to December 2023 were collected. Variables with P < 0.05 in univariate analysis were included in a logistic multivariate stepwise regression to identify the final variables for the model. An SFPR nomogram prediction model was developed using R software and internally validated using the Bootstrap method. The accuracy of the prediction model was assessed through receiver operating characteristic(ROC) and calibration curves, while decision curve analysis evaluated its clinical predictive performance. Based on the body mass index(BMI), chromosome karyotype, transplant type, acute graft-versus-host disease(aGVHD) and post-transplant Interleukin-6(IL-6) and Procalcitonin(PCT), the predicted area under the ROC curve of SFPR is 0.778 (95% CI 0.697-0.858). The absolute error between the predicted risk of SFPR and the actual risk is 0.019. The SFPR nomogram prediction model developed in this study exhibits high accuracy and excellent predictive efficiency, thereby possessing significant clinical guidance value.

Indexed as

Blood PlateletsGraft vs Host DiseaseHematopoietic Stem Cell TransplantationAdolescentAdultFemaleHumansInterleukin-6MaleMiddle AgedNomogramsPrognosisRetrospective StudiesRisk FactorsROC CurveTransplantation, HomologousInterleukin-6Allogeneic hematopoietic stem cell transplantationNomogramPrediction modelRisk factorsSecondary failure of platelet recovery

Identifiers

PMID40731268
PMCPMC12309133

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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 OpenQuestion graph.