biostudies-literatureLiu FQKey Technologies Research and Development ProgramNatural Science Foundation of Beijing MunicipalityDepartment of Human Resources and Social Security of Jiangsu ProvincePeking University MedicineChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaCapital Health Research and Development of Special Funde2410417https://www.ebi.ac.uk/biostudies/studies/S-EPMC12165022biostudies-literatureUnknown12(22)Corticosteroids (CSs) are the initial therapy for immune thrombocytopenia (ITP); however, their efficacy is not adequately predicted. As a novel biomarker, the composition of the gut microbiota is non-invasively tested and altered in patients with ITP. This study aims to develop a predictive model that leverages gut microbiome data to predict the CS response in patients with ITP within the initial four weeks of treatment. Metagenomic sequencing is performed on fecal samples from 212 patients with ITP, 152 of whom underwent CS treatment and follow-up. Predictive models are trained using six machine-learning algorithms, integrating clinical indices and gut microbiome data. The support vector machine (SVM) algorithm-based model has the highest accuracy (AUC = 0.80). This model utilized a compAdvanced science (Weinheim, Baden-Wurttemberg, Germany)Correlation Between Fecal Microbiota and Corticosteroid Responsiveness in Primary Immune Thrombocytopenia: an Exploratory Study.PMC121650222024M761208823500042022-1-40822023YFC25078032023ZB182824300068230014971003Y3035821300087232188724215482230004Zhou JYYu LHuang QSYu FWu YJGao DZhang BSCooperative ITP Working GroupLiu YCui LJZhu XYCheng YFWang XZhou HBWang LLLi YYLi MLLiu FQChen QChen YXJiang ZXRen JHLi YHQu QYLi WFu HXZhang XHHuang RBQiao JLZang MTWang QFAn ZYFeng JHuang XJXiao MYLiu ZGJing HMHu DHFeng RfalseCorrelation Between Fecal Microbiota and Corticosteroid Responsiveness in Primary Immune Thrombocytopenia: an Exploratory Study.Corticosteroids (CSs) are the initial therapy for immune thrombocytopenia (ITP); however, their efficacy is not adequately predicted. As a novel biomarker, the composition of the gut microbiota is non-invasively tested and altered in patients with ITP. This study aims to develop a predictive model that leverages gut microbiome data to predict the CS response in patients with ITP within the initial four weeks of treatment. Metagenomic sequencing is performed on fecal samples from 212 patients with ITP, 152 of whom underwent CS treatment and follow-up. Predictive models are trained using six machine-learning algorithms, integrating clinical indices and gut microbiome data. The support vector machine (SVM) algorithm-based model has the highest accuracy (AUC = 0.80). This model utilized a comp2025-01-01T00:00:00Z2025 Jun2026-06-01T23:20:22.105Z2026-05-23T03:08:09.083ZS-EPMC121650224004060910.1002/advs.202410417